Jun Li

Xiaojing Zha

Dongsheng Wu

The theoretical analysis of test result's errors for the roller type automobile brake tester

Keywords: Roller brake tester, Mathematical model, Adhesion coefficient, Braking force, Error

The main testing parameter of the roller brake tester is the braking force. Actually, there are some differences in results even if the same vehicle is tested on the same tester. So it will bring trouble to evaluate the braking performance accurately. Based on force analysis, the mathematical model of the roller opposite force type automobile brake tester is built in this article. And then the factors of influencing braking force value will be analyzed by theoretical calculations Taking the instance of the Jianghuai light truck and using the mathematical model analyze influencing factors for testing results and calculate error value.The results showed that adhesion cofficients of between testing wheels and rollers and between non-testing wheels and floor, structure of the roller brake testor have an influece on testing results of braking force and structure of the roller brake testor is the least. The theoretical analysis provide references for comparison test among testing equipments of the braking performance.

Introduction

Automobile braking performance is one of the most important factors in vehicle safety performances [START_REF] Zhou Deguang | The Establishing and Analysis of Stress Model about the Roller Brake Tester and the Flat Brake Tester[END_REF] [START_REF] Yonghong | The analysis of advantage and disadvantage between the roller brake tester and the platform brake tester[END_REF] .It is also a key indicator and an essential inspection item of vehicle safety performance test. Currently, the automobile braking performance is tested mostly through the roller opposite force type brake tester according to GB7258-2004 named "Safety specifications for power-driven vehicles operating on roads" However, the same car in different tester for the braking performance test, the results often not consistent, even contrary. So that, it can't evaluate the vehicle's braking performance whether reached the national standards.

Based on the above situation, it is necessary to approach the influencing factors of testing results for the parameters of the testers, and establish its mathematical model of automobile testing on the roller brake tester. Thus, it can analyze the relationship of the vehicle testing results from different testers, and it can obtained more consistent evaluations of the vehicle's braking performance.

According to the braking test of automobile on the roller tester, the force analysis is processed in two ways: force analysis of front wheels test and rears wheel test. So the mathematics theoretical models are built individually. When analyzing, it is assumed that the center of front and rear wheels is located in the same level. And the influences caused by rolling resistance and resilient wheels on force-measuring system are ignored. [START_REF] Guochang | Contrastive Analysis of Static Inspection and Dynamic Inspection of Automobile Brake Performance[END_REF] When the automobile's front wheels brake, the force analysis of the roller brake tester is as shown in Figure 1.

Mathematical model of front wheels braking test

D----wheel diameter(mm); d----roller diameter(mm); α----formed angle;

G 1 , G 2 ----load of the front wheels and rear wheels(N); N 1 、N 2 ----normal force of the front and rear rollers to front wheels(N); F b1 、F b2 ----tangential force of the front and rear rollers to front wheels(N); φ 1 ----adhesion coefficient between testing wheels and rollers; φ 2 ----adhesion coefficient between non-testing wheels and floor; X b2 ----horizontal reaction force of floor to rear wheels(N) Fig. 1 The force analysis of front wheels braking test on the roller tester According to the principle of mechanical equilibrium, relations can be built as below:

0 X F ∑ = 1 2 1 2 0 cos cos sin sin 0 b b F F N N F α α α α + + - -= = (1) 0 Y F ∑ = (2) 1 2 1 2 1 sin sin cos cos 0 b b F F N N G α α α α - + + + -
With the increasing of F b1 when the front wheels brake force is being tested, if the front wheels don't slip backwards, the maximum value of F b1 and F b2 will be: 1max

1 1 b F N ϕ = ⋅ and 2max 2 1 b F N ϕ = ⋅ . Meanwhile, 0 2 m a x 2 b F X G 2 ϕ = = ⋅ . So
Eq.1 and Eq.2 can be written as:

2 2 1 1 1 1 2 1 ( sin cos ) ( cos sin ) (1 ) sin 2 G G N ϕ ϕ α α ϕ α α ϕ α + - - = + (3) 2 2 1 1 1 2 2 1 ( sin cos ) ( cos sin ) (1 ) sin 2 G G N ϕ ϕ α α ϕ α α ϕ α - + + = + (4)
Under the premise of no moving backwards, the vehicle's front wheels maximum brake force should be:

2 2 1 2 1 1 max 1max 2 max 1 2 1 2 1 ( ) (1 ) cos bf b b G G F F F N N ϕ ϕ ϕ ϕ ϕ α + = + = + = + (5)
According to Eq.3, if

1 1 2 2 1 ( cos sin ) ( sin cos ) G G ϕ α α ϕ ϕ α α - = + then
, the tested wheels will leave the 1 0 N = roller and move backwards. Meanwhile we can get:

1 2 1 sin cos G N ϕ α α = + (6)
If the tested wheels are locked after leaving the roller tester, the maximum brake force of the front wheels is:

1 1 max 2 1 1 sin cos bf G F N ϕ ϕ ϕ α α ′ = ⋅ = + (7)

Mathematical model of rear wheel braking test

When the vehicle's rear wheels brake force is tested, the force analysis of the roller brake tester is as shown in Fig. 2.

Fig. 2 The force analysis of rear wheel braking test on the roller brake tester

Similarly, according to the principle of mechanical equilibrium, relations can be built as below:

0 X F ∑ = (8) 1 1 2 0 2 sin cos cos sin 0 b b N F F F N α α α α + + -- = = 0 Y F ∑ = (9) 1 2 2 1 2 cos cos sin sin 0 b b N N F F G α α α α + + - -
If the rear wheels don't slip backwards, have

1 1 max 1 ϕ ⋅ = N F b , 1 2 max 2 ϕ ⋅ = N F b and 2 1 max 0 ϕ ⋅ = = G X F b
. So it can be gotten that:

1 2 1 2 1 1 2 1 ( sin cos ) ( cos sin ) (1 ) sin 2 G G N ϕ ϕ α α ϕ α α ϕ α + - - = + (10) 1 2 1 2 1 2 2 1 ( sin cos ) ( cos sin ) (1 ) sin 2 G G N ϕ ϕ α α ϕ α α ϕ α - + + = + (11)
The maximum brake force of the rear wheels is

2 1 1 2 2 1 max 2 1 (1 ) cos br G G F ϕ ϕ ϕ ϕ α + = + (12)
According to Eq.10, it can be known that when

1 0 N = 2 1 2 1 1 ( cos sin ) ( sin cos ) G G ϕ α α ϕ ϕ α α - = + , then 2 2 1 sin cos G N ϕ α α = + (13)
If the tested wheels locked after leaving the roller tester, the maximum brake force of the rear wheels is:

2 1 max 2 1 1 sin cos br G F N ϕ ϕ ϕ α α ′ = ⋅ = + (14)
3 Analysis on influencing factors of testing results [START_REF] Zhisheng | Automobile Theory[END_REF] [5]

The adhesion coefficient between testing wheels and rollers

According to GB/T13564-2005 "the roller opposite force type automobile brake tester", if vehicle is lighter than 3 tons, the roller tester's diameter should be 245 mm and the center distance should be 430 Because the rollers may be worn more or less after a long use, the value of φ 1 will decrease. Regarding the front and rear brake force when It can be concluded that with the increase of adhesion coefficient between wheels and rollers, the braking force test capability of front and rear wheels will significantly increase as well. Hence, a good value of φ 1 which must be ensured through a number of ways is a basic premise for braking force test.

The adhesion coefficient between non-testing wheels and floor

Similarly, taking the light truck and the same tester as an example, the front and rear braking force will be calculated. According to GB7258-2004, the value of φ 1 should not be less than 0.75. So it is taken as 0.75 on the calculation. Considering the actual testing situation, φ 2 is taken between 0.4 and 0.8. The results are calculated and shown in Fig. 4. The relationship between the value of φ 2 and front and rear brake force front F bf rear F br Fig. 4 The relation of the front and rear brake force with the increase of φ 2

From Fig. 4, we can tell that the test result differs when we take different values of the adhesion coefficient between non-testing wheels and floor. Furthermore there is a proportional relationship between the value of φ 2 and braking force. The difference of braking forces between .4 0 2 = ϕ and .8 0 2 = ϕ is up to about 2000 N, which has a great impact on the evaluation of braking performance. In test stations, if the ground cannot be cleaned up or maintained in time, it will lead to the decrease of adhesion coefficient, and then affect the evaluation on braking performance. For example, the adhesion coefficient of terrazzo floor is less than 0.6. Regarding the front and rear brake force when By the Eq.6, Eq.7, Eq.13 and Eq.14, it is known that when the φ 2 takes a particular data ( ) the testing braking force is minimum. It means the vehicle is slipping on the tester. That may be one reason why the vehicle with good brake performance cannot pass the test. So in the actual test, it is specified that the adhesion coefficient between non-test wheels and ground cannot be less than 0.7. 1 0 N =

Structural factors of the roller brake tester

After investigation we found that the sizes of testers which are being used in different test institutions have differences, although GB/T13564-2005 has made provisions for the standard of tester.

According to the force analysis in Fig. 1 and Fig. 2, it can be known that the formed angle α is related to the wheel diameter D, the roller diameter d and the roller center distance L. Supposing that D is a constant value (taking the light truck as an example), we can discuss the relationship between the formed angle α and braking force through combining with the actual parameters of different testers.

The formed angle α is proportional to the front and rear braking force, as shown in Fig. 5. The relationship between the value of α and front and rear brake force front F bf rear F br Fig. 5 The braking force of front and rear wheels with the change of the formed angle α Also taking the light truck as an example, applying relevant parameters of three different testers and combining Eq.5 with Eq.12, the braking force of front and rear wheels are shown as below: From Fig. 5 and Tab.3, the conclusion is made: when the same vehicle is tested in different testers, the formed angles are different due to the different structures. It causes the errors in test results.

Therefore, the structure of the brake tester can be an impact for the braking force test as well.

Conclusions

By taking a light truck as an example, the mathematical model is established through force analysis.

Combining the specific parameters of tester, the test results of braking force can be theoretically analyzed and calculated by the model. The conclusions can be made as below:

1. The testing results are affected by the adhesion coefficient between the tested wheels and rollers, by the adhesion coefficient between non-tested wheels and ground, and by the structure of the brake roller tester. Among them, the structure of brake tester contributes relatively less affection to the braking force.

2. Due to the difference of the structure of testers in different places, it makes some differences in braking force test results. They belong to structural errors and are unavoidable in the testing process.

From Tab.3 and Fig. 5 we can see that the formed angle has less influence in test results. It indicates that doing comparative tests of different test devices is feasible and the test results are comparable.

3. To reduce the test errors resulting from the structure of the testing equipment, the formed angles α can be modified through the mathematical model if they are too large or too small.

.Fig. 3 1 From Fig. 3 ,

 313 Fig.3The relation curves of the front and rear wheel braking forces with the increase of φ 1

1

 1 The comparison of the front and rear brake force between and

Table 3

 3 The front and rear brake force of JAC light truck on the different testers In Tab.3 the data of Type 3 is the ruled data in GB/T13564-2005. If taking them as reference values, the relative errors are -1.43% in Type 1 and 4.01% in Type 2.

	Type	d(mm)	L(mm)	α(°)	F bf (N)	F br (N)
	1	200	390	29.6	13293.9	12512.7
	2	240	470	34.5	14027.5	13203.2
	3	245	430	31.0	13487.0	12694.4

Acknowledgement

The work is supported by the Department of Transportation of Jiangxi Province (2009T0053).


Zhigang Huang

Xuecheng Ping

Pingan Liu

Stress Analysis near the Welding Interface Edges of a QFP Structure under Thermal Loading

Keywords: Electronic packaging, QFP structure, Interfacial thermal stresses, Stress concentration

The purpose of this paper was to investigate the reason why the interface delaminations occurred in the QFP structure. The stress concentration was the key factor responsible for the microcrack occurrence. In order to figure out which factors affect the stress distribution, the material's attributes and the structure's dimension were considered. The finite element program ABAQUS6.9 together with the analytical solutions of singular stress fields was used to calculate the stresses near the interface edges. In conclusion, it appeared that strong mismatches of the thermal expansion coefficients and material elastic constants of the chip and PCB would lead to serious singular stresses at the interface edges. Stress intensity factor K and stress singularity order  were given, based on which failure criterions could be established to predict the potential interface delamination. It is suggested that the good design of packaging structure depends on proper material selection and dimension determination.

Introduction

Nowadays, quad flat packages(QFPs) are widely used in electronics engineering. A QFP structure often consists of metal pins, solder and PCBs. This kind of structure has two common features such as interfaces and corners. The solder layer plays an important role in the mechanical and electric connections. The require-ments of highdensity,cost-effective performance for package have resulted in very high IO count in smaller dimensions in the chip design(A.Q. Xu et al.2000) [START_REF] Xu | Finite Element Analysis of Stress Singularities in Attached Flip Chip Packages[END_REF]. Due to the mismatch of thermal and mechanical properties in the dissimilar material structures as well as the change in working or environment temperature, high stress singularity will appear at the interface edges. Since the solder interlayers tend to be weak mechanically, in which microcracking or delamination are more easy to occur, the strength and service life of the whole structure will be directly reduced (Yi lan Kang 1996) [START_REF] Kang | the thermal stress analysis of the interfacial edge in dissimilar structure and the effects of geometric shape[END_REF]. Therefore, the awareness of the stress state near the interface edges is very essential to the strength evaluation and life prediction.

Many researchers have studied these problems and have brought some methods to relax singular stresses at the interface edges. Failure criterions have also been discussed by some scientists. The stress singularity problems at the free edges of bonded dissimilar materials were analyzed previously(Shuir 1989 and Munz and Yang 1992) [START_REF] Suhir | Thermally induced interfacial stresses in elongated bimaterial plates[END_REF][START_REF] Munz | Stress singularities at the interface in bonded dissimilar materials under mechanical and thermal loading[END_REF]. The stress singularity problems of the edge of bonded bimaterial beams were discussed by some scholars [START_REF] Kang | Experimental analysis for bonded bimaterial beam under bending load[END_REF] [START_REF] Kang | Experimental analysis for bonded bimaterial beam under bending load[END_REF]. The stress singularities in an anisotropic wedge was analyzed (Chue et al.2001) [START_REF] Chue | A general solution on stress singularities in an anisotropic wedge[END_REF]. The failure models and strength criterions were studied experimentally [START_REF] Basaran | Failure Modes of Flip Chip Solder Joints Under High Electric Current Density[END_REF] [START_REF] Chang-Shun | Interfacial Thermal Stress Analysis in Packaging[END_REF][START_REF] Cho | Study on the Behavior Characteristics of Solder Balls for FCBGA Package[END_REF].

The failure usually initiates at the singular stress point, and the knowledge of interfacial fracture mechanics is important to understand the failure mechanisms and to achieve better structure design. Although some jobs have been done by some scholars in this area (Seiji Ioka,and Keiji Masuda, et al.1999) [START_REF] Ioka | Singular stress field near the edge of interface of bonded dissimilar materials with an electronic packaging[END_REF], there were relatively few papers to discuss the singular thermal stresses near the interface edges. It should be pointed out that, 1) the thermal stress is singular near the sharp corner of the electronic packages, it is difficult to calculate the singular stress fields by the conventional finite element method(J.M. Hu 1995) [START_REF] Hu | Interfacial stress singularity analysis: A case study for plastic encapsulated IC packages[END_REF]; 2) the effects of solder thicknesses for a pin/PCB joint on the singular thermal stresses were not systematically studied. In this paper, the above two problems are going to be researched.

Theoretical Background

If two materials with different elastic properties are bonded together, stress singularities often occur at free edges of the interface under mechanical or thermal loading. A general configuration of a joint between two rectangular plates is shown in Fig. 1. The stress states near the free edge of the interface (point o) is given by the following equation:

 . ) ( ) / ( ) , ( 0       ij ij ij f L r K r   (1)
) ( 0   ij
is the constant stress term under the thermal loading. In order to determine its value, we can use the following formulas(Suga and Lancu 1989):

 . 2 cos 1 2 0 0       (2) if 0   , 0 0     .Where 0  is defined by: . 0 T E         (3) with    . 1 1 2 2 1 1 v v         (4) 1 2 1 1 1             E E E (5)   . 1 v v E E    (6)
where, T =T-T 0 is the temperature difference, T is the working temperature, and T 0 is the initial temperature. E is the Young modulus, and  E is the effective modulus. is the thermal expansion coefficient.

Analysis of the QFP Welded Joints

The welded pin joint in a QFP structure is shown in Fig. 2. The upper layer is the pin, the bottom layer is the PCB, and the medium layer is the solder. The detailed dimension of these components is shown in Fig. 2. The material properties for the pin, PCB and solder are listed in Table .1.The finite element model of the welded joint is given in Fig. 3. In order to guarantee the calculation accuracy, the meshes near the interface edges are refined systematically. During the compu-tation and analysis, the finite element model must be based on the following assumptions(Jamil Wakil,and Paul S Ho 2007) [START_REF] Wakil | Effect of non-uniform temperature on thermal modeling and strain distribution in Interlayer[END_REF]: 1)Temperature for the thermal analysis dropped from 183C to an ambient environmental temperature of 20C, since the QFP package is in a stress free state over 183C-the melting point temperature of the solder. Simplifications are made to facilitate prediction of junction temperatures and therm-mechanical stresses.

2)Thermal cycling was not considered, and the temperature dropped from 183C to 20C in 90 minutes.

3)The temperature condition was applied simul-taneously to the entire package. 4)A horizontal line on the bottom substrate surface was fixed along the Y-direction to constrain free body motion. The upper horizontal line of the pin was constrained using the same pattern. These were the boundary conditions of the analysis model.

5)All component interfaces were assumed to adhere perfectly and the material properties do not change with the temperature. Once the peeling stress y  and the constant stress term 0  are obtained, according to Eq. ( 1), the  and K can be obtained from the following plots:

  . ) / lg( lg lg 0 L r K FE        (7)
where

FE 
 is the stress value calculated by the finite element method. Fig. 5 shows an example of these plots. It was found that the slope of the straight line through the data points in the range -4<lg(r/L)<-3.2 was in good agreement with the analytically calculated  in Munz and Yang [START_REF] Munz | Stress singularities at the interface in bonded dissimilar materials under mechanical and thermal loading[END_REF]. The y-intercept of the fitting curve represents the lgK and the slope of the fitting curve represents the -.

Fig. 6 shows the effect of  2 on the stress singularity order . It was found that the stress singularity order  was decreased with the increasing of  2 . Fig. 7 shows the effect of  2 on K1/T. It can be seen that the K1/T increases with the increasing of 2. The stress intensity factor K1 is a very important parameter for crack initiation, i.e., when the K1 reaches an ultimate value, the interface failure will occur. Fig. 8 showed the effect of changing 2 on the K1/ 0 . The result was that larger  2 leads to larger K1/ 0 . Fig. 9 showed the effect of the poisson's ratio on the term K1/T including the stress intensity factor. In order to study the effect of the mismatch of thermal and mechanical properties of the bonded materials on the stress distribution, the FE plot of  y /T versus k(=

    2 1 * 2 * 1 E E E E
) was given in Fig. 10. It can be seen that  y /T decreases with the decreasing of k. In some cases (e.g. k<0.2), the compressive stresses will appear. In Fig. 11, the effect of thickness of the solder layer on the peeling stress y/T was considered. In the analysis, the thermal and mechanical properties of the materials were constants. It was easy to see that the peeling stress y/T will increase with the increasing of the solder layer's thickness. Therefore, thinner solder layer is recommended on the premise of enough bonding strength.

CONCLUSIONS

The thermal stress distribution at the interface between the chip and PCB was affected by the material's properties and the structure's dimension. The peeling stress's distribution is also dependent on the solder layer's thickness. The effects of  2 on K1 and  are different, and the stress intensity factor K1 is very important to predict the interface failure occurrence. The peeling stresses are directly proportional to the r - and the stress values near the free edges (when r approaches to zero) are very rigorous theoretically. It is in accordance with the results of the finite element analysis. The analysis of thermal stresses along the interface is very important for guiding the good design of packaging structures.

Fig. 1 .K

 1 Fig.1. A configuration of the interface edges where r and  are the polar coordinates of the specified point o and L is a characteristic length of the configuration.  is the stress singularity order, ) (

Fig. 2 .

 2 Fig.2. Section of the Package Components

Fig. 3 .

 3 Fig.3. Finite element model of the QFP

Fig. 4 .

 4 Fig. 4. Distribution of the peeling stress along the interface

Fig. 5 .Fig. 6 . 2 Fig 7 .

 5627 Fig. 5. Relation between lg( y - 0 ) and lg(r/L)

Fig. 8 . 2 Fig. 9 . 2 Fig. 10 .

 829210 Fig.8. -K1/ 0 varied against different  2

Fig. 11 .

 11 Fig.11. y/T varied against different solder thickness

Table 1 .

 1 Thermodynamics parameters of the materials in the model

	Material	E (Mpa)				c
	Cu	120658	0.345	8900	17e-5 385
	Pb40Sn60	34590	0.38	8400	21e-5 176
	FR4	22000	0.28	1800	18e-5 930

Acknowledgements

.The authors acknowledge the support of National Natural Science Foundation of China through grant No.10362002 and No.10662004, the Jiangxi Provincial Natural Science Foundation of China through grant No. 2007GZW0862 and the Scientific Research Project of Jiangxi Provincial Department of Education grant NO. GJJ10444.


Yande Liu

Tao Liu

Determination of Pesticide Residues on the Surface of Fruits Using Micro-Raman Spectroscopy

Keywords: micro-Raman spectroscopy, fruit, pesticide residue

A simple, rapid and environmentally friendly method was developed for micro-Raman spectroscopy determination of pesticide residues on the surface of fruits. Raman spectra of fruits, pesticides and pericarps sprayed by pesticide solutions were acquired using a laser power of 14 mW at excitation wavelength of 780 nm. From the Raman spectra, the residual pesticides could be distinguished and determined through the characteristic Raman peaks. The overall results indicted that micro-Raman spectroscopy is a potential tool to determine the pesticide residues on the surface of fruits for fruit quality and safety control.

Introduction

Pesticides are defined by the United Nations Food and Agricultural Organization (FAO) as substances or mixtures intended to prevent, destroy, repel or mitigate any pest, including insects, rodents and weeds [START_REF]UN Food and Agricultural Organization: International Code of Conduct on the Distribution and Use of Pesticides[END_REF]. Currently, pesticides play a critical role in protecting fruit crops. However, large amount of pesticides are used in fruits production making it unsafe and endangering humans and animals. One of the most common used pesticides are the organophosphates, which kill insects and mites by attacking the central nervous system, and consequently pose a threat to human beings and animal lives [START_REF] Tuormaa | Adverse Effects of Agrochemicals on Reproduction and Health: a Brief Review from the Literature[END_REF]. Nowadays, fruit safety and quality has been attracted more and more attention. In many countries, strict tolerance levels are set up to ensure public safety.

The current analysis methods for determining the residual pesticides in fresh fruits are based on chemical analysis, such as liquid chromatography-mass spectrometry (LC-MS) [START_REF] Picó | Pesticide Residue Determination in Fruit and Vegetables by Liquid Chromatography-mass Spectrometry[END_REF], liquid chromatography-tandem mass spectrometry (LC-MS/MS) [START_REF] Jansson | A New Multi-residue Method for Analysis of Pesticide Residues in Fruit and Vegetables Using Liquid Chromatography with Tandem Mass Spectrometric Detection[END_REF][START_REF] Frenich | Monitoring Multi-class Pesticide Residues in Fresh Fruits and Vegetables by Liquid Chromatography with Tandem Mass Spectrometry[END_REF], gas chromatography-mass spectrometry (GC-MS) [START_REF] Guan | Disposable Pipette Extraction for the Analysis of Pesticides in Fruit and Vegetables Using Gas Chromatography/Mass Spectrometry[END_REF], capillary electrophoresis-mass spectrometry (CE-MS) [START_REF] Juan-García | Pressurised Liquid Extraction and Capillary Electrophoresis-mass Spectrometry for the Analysis of Pesticide Residues in Fruits from Valencian Markets[END_REF] and ultra-high-performance liquid chromatography (UHPLC) [START_REF] Lacina | Identification/Quantification of Multiple Pesticide Residues in Food Plants by Ultra-high-performance Liquid Chromatography-time-of-flight Mass Spectrometry[END_REF], etc. However, all of the methods mentioned above are time-consuming, not environmentally friendly and inconvenient enough for the process of sample preparation. Hence, it was very necessary to develop a simple, rapid and low cost method for the determination of pesticide residuals in fruits.

Raman spectroscopy is a fast technique compared to classical chromatography. It is a powerful analytical tool that provides wonderful advantages including non-destructive, low cost and ultrasensitive characterization down to single molecular level [START_REF] Armenta | Mid-infrared and Raman Spectrometry for Quality Control of Pesticide Formulations[END_REF]. Shende et al. [START_REF] Shende | Analysis of Pesticides on or in Fruit by Surface-enhanced Raman Spectroscopy[END_REF] used surface-enhanced Raman spectroscopy (SERS) to analyze pesticides on fruit surfaces. Zhou et al. [START_REF] Zhou | Raman Spectra of Pesticides on the Surface of Fruits[END_REF] recorded several spectra of fruits with pesticides using near infrared Fourier transform Raman spectroscopy (FT-Raman). Several Raman spectra of some fruits and pesticides on the surface of fruits were acquired and compared with at two excitation wavelengths of 514.5 and 1064 nm by Zhang et al. [START_REF] Zhang | Raman Spectra from Pesticides on the Surface of Fruits[END_REF].

Micro-Raman has its unique characters compared to other Raman techniques, since it allows analysis of materials with a spatial resolution of several microns focused by an optical microscope. It has been developed for a rapid, environmentally friendly and low cost generation procedure, and has been applied in many fields, such as gems [START_REF] Sudheer | Characterization of Laser Processing of Single-crystal Natural Diamonds Using Micro-Raman Spectroscopic Investigations[END_REF][START_REF] Palanza | Micro-Raman Spectroscopy Applied to the Study of Inclusions within Sapphire[END_REF], fibers [START_REF] Doherty | Micro-Raman Spectroscopic Study of Artificially Aged Natural and Dyed Wool[END_REF][START_REF] Colomban | Nanomechanics of Single Silkworm and Spider Fibres: a Raman and Micro-mechanical in Situ Study of the Conformation Change with Stress[END_REF] and geology [START_REF] Rull | Comparative Micro-Raman Study of the Nakhla and Vaca Muerta Meteorites[END_REF][START_REF] Łodziński | Micro-Raman Spectroscopy Studies of Some Accessory Minerals from Pegmatites of the Sowie Mts and Strzegom-Sobótka Massif, Lower Silesia, Poland[END_REF], etc. In this paper, a new attempt to determine the residual pesticides on the surface of fruits using micro-Raman spectroscopy was reported. The objective was to record the Raman spectra of fruits and pesticides in order to study the feasibility of using micro-Raman spectroscopy to determine the residual pesticides on the surface of fruits.

Materials and methods

Apparatus

A Nicolet DXR Raman Microscope (Thermo Fisher Scientific Corp., Madison, WI, USA), equipped with a liquid nitrogen cooled CCD detector and a 14 mW maximum power diode laser, that emits at 780 nm, was employed for confocal micro-Raman spectra acquisition using 2 ml standard glass chromatographic vials (12 mm×32 mm) as sample cells. The laser was focused within the sample using an inverted microscope setup equipped with a 10× ultra long working distance objective. The scattered signal was then recorded at a 180° backscattering geometry and dispersed by a single monochromator using a 400 grooves/mm diffraction grating and a laser line filter used as a beam splitter to lead the laser beam into the microscope assembly and also to reject the Rayleigh scattered light on the returning path. Spectrometer was controlled with OMINIC software (Thermo Nicolet Corp., Madison, WI, USA).

Sample preparation and chemicals

The samples, including apples, pears and oranges fruits in the experiment, were purchased directly from the Nanchang fruit market. Before recording the micro-Raman spectra, all the fruits were cleaned carefully. Firstly, fruits were flushed several times with fresh water to get rid of the dirt left on the surface, and then wiped with cotton and alcohol. After that, small pieces of pericarps from the cleaned fruits were taken off, and then sprayed by a little amount of pesticide formulations. At last, filter papers were used to wipe off any left over pesticides from the pericarps, and let the samples dry naturally.

Micro-Raman procedure

When it was time to record the micro-Raman spectra, the resolution and accumulating time were fixed at 1.93 cm -1 and 100 scans per spectrum. The micro-Raman spectra of clean pericarps of apples, pears, oranges and four standard pesticides were collected, firstly. These spectra were used as standards in the comparison database. Then the spectra of pericarps sprayed by the pesticide formulations were collected and compared with those in the database to identify the trace amount of pesticides on the surface of fruits. All the spectra mentioned above were carried out in chromatographic glass vials from 3390 to 110 cm -1 with the diode laser power employed fixed at 14 mW.

Results and discussion

Raman spectra of fruits

Based on the measuring conditions mentioned above, the micro-Raman spectra of clean pericarps of apple, pear and orange fruits are shown in Fig. 1. Each of fruits has its characteristic peaks. Oranges mainly have the Raman peaks at 1530, 1155 and 1005 cm -1 attributed to C=C stretching, C-C stretching and C-CH 3 bending of carotene [START_REF] El-Abassy | Rapid Determination of Free Fatty Acid in Extra Virgin Olive Oil by Raman Spectroscopy and Multivariate Analysis[END_REF]. However, both apple and pear fruits have combined peaks around 1600, 1439, 1136 and 850 cm -1 . It is estimated that these peaks are due to the combination of Raman scattering peaks by nourishment compositions of apple and pear. Because each of them contains very complicated compositions as there are usually different amount of water, sugar, vitamin, fat, protein, amino acid, as well as other components and elements such as calcium, iron and zinc, etc. At present, these fruits still can not be identified from the Raman peaks, but it has differences in the peaks attributed to the different compositions.

Raman spectra of pesticides

Raman spectra of three standard pesticides, including dimethoate, chlorpyrifos and malathion, are shown from Fig. 2 to Fig. 4 in the 3390-110 cm -1 region. All pesticides have the same structure with P=S bonds, which display a strong band in the 600-700 cm -1 region. This band is clearly distinguishable for compounds without benzene rings, but several of the vibrations due to the benzene ring overshadow it as in chlorpyrifos spectrum, where two overlapping bands appear at 630 and 676 cm -1 in Fig.

2 [START_REF] Skoulika | FT-Raman Spectroscopy-Analytical Tool for Routine Analysis of Diazinon Pesticide Formulations[END_REF].

The most intense bands in the chlorpyrifos Raman spectrum are those present at 340 and 630 cm -1 due to N-cyclopropyl bending and ring deformation, respectively. Other less intense bands located at 158, 676, 1276 and 1569 cm -1 are due to P-O vibration, ring breathing, C-H bending and C=C stretching. C-H stretching modes are observed from 2800 to 3100 cm -1 . In Fig. 3 of dimethoate Raman spectrum, P=S bond displays a strong band at 696 cm -1 . The most intense band in the spectrum is located at 575 cm -1 due to C-S vibration. Other less intense bands located at 171, 494, 768, 903, 1156, 1330 and 1640 cm -1 are due to P-O vibration, P-S vibration, S-P-O backbone mode, C-C backbone stretching, C-C stretching, N-H in-plane bending and symmetric C=O stretching. The intense bands appearing around 2936 cm -1 are due to CH 2 and CH 3 deformation. In Fig. 4 of malathion spectrum, P=S bond displays a strong band at 652 cm -1 . The bands located at 159, 496, 859, 1022, 1110 and 1733 cm -1 are due to P-O vibration, P-S vibration, C-O-C stretching, C-H in-plane deformation, C-C stretching and C=O stretching [START_REF] Quintás | FT-Raman Spectrometry Determination of Malathion in Pesticide Formulations[END_REF]. The intense bands appearing in 1451 and 2800 to 3100 cm -1 are due to CH 2 and CH 3 deformation and C-H stretching. From the three figures mentioned above, each of pesticides could be distinguished using their characteristic peaks shown in Table 1. These bands could be employed for determining pesticide residues on the surface of fruits.

Raman spectra of pesticide residues on the surface of fruits

Acquirements of Raman spectra of fruits with pesticides were performed with the same measuring conditions as before. Fig. 5 and Fig. 6 show the Raman spectra of chlorpyrifos and malathion formulations residues on the surface of oranges. From Fig. 5, it can be obviously seen that the spectrum of chlorpyrifos residue on the surface of orange not only contains the strong peaks of orange itself, but also contains the characteristic modes of chlorpyrifos which located at 676, 630 and 340 cm -1 . Similarly, in Fig. 6, the characteristic modes of malathion at 1451, 859, 652 and 496 cm -1 can be seen in the spectrum of its residue on the surface of orange. Based on the results, it was concluded that the method of using micro-Raman spectroscopy could be utilized for automatic and intelligent determination of the pesticide residues on the surface of fruits.

Conclusions

The micro-Raman spectra of apples, pears, oranges, several pesticides and pesticide residues on the surface of oranges were successfully recorded using a micro-Raman spectrometer. The characteristic peaks of pesticides can be seen from the spectra of pesticides left on the surface of fruits. Micro-Raman spectroscopy is a potential tool to determine the pesticide residues for fruit quality and safety control with rapid, non-destructive, low cost and environmentally friendly advantages.

Fig. 1 .

 1 Fig. 1. Raman spectra of orange, pear and apple fruits.

Fig. 2 .

 2 Fig. 2. Raman spectrum and molecular structure of chlorpyrifos.

Fig. 3 .

 3 Fig. 3. Raman spectrum and molecular structure of dimethoate.

Fig. 4 .

 4 Fig. 4. Raman spectrum and molecular structure of malathion.

Fig. 5 .

 5 Fig. 5. Raman spectra of (a) orange's pericarp, (b) chlorpyrifos formulation (40% w/w) left on the surface of orange and (c) standard chlorpyrifos solid.

Fig. 6 .

 6 Fig. 6. Raman spectra of (a) orange's pericarp, (b) malathion formulation (40% w/w) left on the surface of orange and (c) standard malathion solution.

Table 1 .

 1 Characteristic peaks of chlorpyrifos, dimethoate and malathion.

	Pesticide	Characteristic peaks (cm -1 )
	Chlorpyrifos	1569, 1276, 676, 630, 340
	Dimethoate	1640, 651, 494
	Malathion	1733, 1451, 652

Acknowledgements

The authors gratefully acknowledge the financial support provided by National Science and Technology Support Program (2008BAD96B04), Natural Science Foundation of Jiangxi Province (2008GQN0029, 2007GZN0266), Special Science and Technology-Support Program for Foreign Science and Technology Cooperation Plan (2009BHB15200), Technological expertise and academic leaders training program of Jiangxi Province (2009DD00700).


Huilan Zhou
email: hlanz@tom.com

Design of Tread Flange Injection Mold Based On Pro/E

Keywords: tread flange, maneuvering tread demolding way, Pro/E; EMX4.1

In the paper, analyzing the tread flange structure characteristics ,its injection mold is designed and the maneuvering tread demolding way is applied to get out flang tread .When designing demolding parts, hydraulic pressure motor and chain-gear mechanism are used. Besides, parting plane and the forming parts can be gained automatically in Pro/E(Pro/Engineer Wildfire3.0)and standard moldbase can be achieved by EMX4.1 including gating ,cooling, and guiding system, etc. The designing ways and structure is proved rational and can be taken as reference for the similar injection mold especially for those with longer tread.

Introduction

For plastic parts, many have thread with them, and it's most critical how to design its automatric tread demolding as the tread demolding structure will effect the mold life and the plastic part quality directly . How to simplify the mold and prolong its life needs to be considered in designing. Besides, with wide application, rapid updating and high quality of plastic parts, digital designing ways such as CAD tools are used in the mold designing and manufacturing in many fields. Among those tools, Pro/E and UG are used most widely. These two softwares have become standard ones in the mold industry of many countries. In the paper, the tread flange injection mold design based on Pro/E is introduced.

Tread Flange Structure and Process Analysis

The tread flange's size is 60mm 70mm 20mm with 12mm external tread, and it has five pleurotus around which can prevent part from rotating in tread demolding shown in Fig. 1. Tread flange's material is PP(Polypropylene) [START_REF] Hong | Practical Mold Design And Injection[END_REF][START_REF] Qu | Injection Mold Design And Molding Process[END_REF][START_REF]the writers of Manual Of Injection Mold: Manual of Injection Mold[END_REF] with mass production. PP is a kind of material with following character: density 0.90 ~0.91g/cm3 , melting point 164 ~170 ℃. PP also has good heat resistance, fine flow performance, less shrinkage and smooth surface.

the Mold Parting Plane Design

The mold parting plane is generally utilized to separate workpiece or block into mold forming parts, which is composed of a surface or several surfaces. It's important to create correct parting plane and use it to obtain mold forming parts such as cavity, core and pins in mold designing in Pro/E.

For tread flange, after using Pro/E to create its parting plane and separating workpiece with it, the tread flange mold forming parts can be achieved following in Fig. 2.

the Mold Overall Structure

The mold overall structure is shown in Fig. 3. As the tread flange has greater total (a)main view (b)left view 1-movable base plate 2-Screw3-supporting plate 4-chain5-Sprocket I6-hydraulic Motor7-pin8-Screw2 9-Guide column10-guide sleeve11-fixed base plate 12-Determined distance pole13-Screw314fixing plate15-Spring16-closing mold tool17-resisting plate18-seperating watar plate19-up mold core 20-water mouth21-fixed plate22-fixed mold plate 23-movable plate 24 screw core25-gear26-movable mold plate 27-Sleeve 28-bearing 29-bearing cover 30-seals31-Seal adhesive32-Sleeve2 33-Sprocket 34-Key 35-briquetting 36-screw4 37-Guide column38-guide sleeve 39-Gate sets 40-pulling pole41-screw4 Fig. 3 overall structure of the mold length and longer external tread, some difficulty will confront in its designing and manufacturing , among which separating mechanism according to distance and auto tread demolding must be resolved in designing .

Injection Machine Selection

With calculating tools in Pro/E , the tread flange's total volume including gating system and the plastic part itself can be calculated as 111.822 cm3.Apart from that, considering clamping force and opening stroke, the injecting machine G54-S200/400 is selected, whose Specifications is following: Rated injection volume/㎝3:200-400 Screw diameter/㎜:55

the Maneuvering Tread Demolding Structure Design

There are three common methods for tread demolding: manual tread demolding, forcing tread demolding and auto tread demolding. For those plastic parts of high quality with mass production, auto tread demolding ways which include maneuvering demolding, half-sliding demolding and combined mold demolding can be applied. In the tread frange mold, maneuvering tread demolding is selected.

The maneuvering tread demolding has the advantage of high efficiency and steady, and in designing, its feasibility, stability and wearing property must be considered seriously and resolved successfully.

AS the tread flange has greater total length and longer external tread, when maneuvering tread demolding , if the traditional rack and pinion is applied, problems must occur in designing and manufacturing as its opening distance is too long. So in the mold, hydraulic pressure motor and chain-gear mechanism are selected in demolding agency. Compared with electric motor, hydraulic pressure motor is more steady , lower noise, and stepless speed regulation. And compared with belt drive, chain drive has nonslipping with good transmitting ratio, small tension, and small load played on axis. Now hydraulic pressure motor and chain-gear mechanism have become a more popularizd thread demolding agency. [START_REF] Hong | Guide of Mechanical Design[END_REF] Design

the Transmission Mechanism

The main chain-gear transmission diagram in the mold is in Fig. 4. z1:tooth number of driving gear z2:tooth number of drived gear z3:tooth number of driving sprocket z4: tooth number of drivied sprocket Axis with parts on it is located by bearing and bearing cover in axial and radial directions for the stability.

According to the force loaded on the axis ,the deep groove ball bearing 61805 is selected in the design.

(3)Chain transmission parameter According to reference [START_REF] Dang | Mold Design And Manufacture[END_REF] , the plastic part enveloping force can be calculated as following: F=28.1KN.

Considering the enveloping force on the core coming from the plastic part, the chain 16B in GB/T 1243-1997 is selected whose tensile load is 60KN and pitch 25.4mm with single row and short pitch.

The parameters of the Sprocket in the mold is designed as: z3=54 ,z4=20.

(4)The transmission ration calculation As the total thread's length is 12mm, and thread pitch is 1.5mm, so the thread number can be calculated as 8.

The formular of overall ratio is next: i=(z2/z1)(z4/z3)≈0.26 (1) In the formula, the meanings of z1,z2,z3 and z4 are shown in Fig. 4.It can be illustrated from the formula(1) that in order to pull the thread out of the core thoroughly the gear must be drived by the hydraulic pressure motor to work at least 32 rounds.

Hydraulic Pressure Motor Selection

Considering the plastic part previous enveloping force , and after composite calculating, the hydraulic pressure motor Nmh1-163 is selected ,whose Specifications are next:

Rating torque/ n.m: 225 Wept volume/ ml/r: 64 rated pressure/ mpa :25 rated torque/ n.m: 472 speed range/ r/min: 15-1500 weight/ kg: 20 Besides, in order to protect the thread from being breaked, it is better to run the hydraulic pressure motor slowly.

Separating Mechanism According to Distance and Mold Working Process

Three plates mod is adopted shown in Fig. 3, in which the hydraulic pressure motor and chain-gear mechanism are used to realize auto thread demolding. The mold primary working process is as following: at first, after mold being closed and cavity being filled fully, the parting plane I opens and the pin point gate separates from the plastic part under the action of spring 15 ; secondly, with the help of the die locker 16, the parting plane II can be ensured to be opened before the parting plane III, as a result cooling slag of the runner can be get out; finally, under the action of separating mechanism, movable mold can be separated totally from fixed one and then the cooled plastic part will be removed from core in movable side by motor-chain-gear mechanism .

the Moldbase Design

Most of injection moldbase have already been standardized. From standardized moldbase loading, sliding-block creating to casting system designing, and from ejecting mechanism to cooling system, all of them could be achieved in standardized moldbase. EMX(Expert Moldbase Extension)4.1 is such a tool ,which is a plug-in belongs to Pro/E and can be used to design standard moldbase parts such as mold plate, sliding block, pin and cooling system and so on. Besides, emulation of mold opening and interference checking can also be realized in EMX 4.1 [START_REF] Xiao | Practical teaching of Mold Design and Manufacture In Chinese With Pro/Engineer Wildfire[END_REF][START_REF] Hua | Quick Design of Injection Moldbased on Pro/E[END_REF] .

The moldbase main designing steps in EMX4.1 are as following:

(1) Assemble the forming parts such as mold core , cavity and sliding block into the moldbase so that EMX4.1 can identify them; (2) Definite mold subassembly including moldbase type selection, the mold plate dimension, mold layout, locating ring and sprue bush; (3) Design the gating system. The sprue runner, sub-runner and gate can be quickly achieved in EMX4.1 using standard runner tool; (4) Design sliding block mechanism including outside core-pulling and inner side core-drawing mechanism; (5) Design ejector mechanism. As the hydraulic pressure motor and chain-gear mechanism are used to realize auto thread demolding, ejector mechanism needn't be designed in the tread frange mold; (6) Design cooling system. After cooling waterline has been drawn in the cooled parts, cooling system can be gained automatically using EMX's gating tool.

Conclusions

(1)In the mold, the hydraulic pressure motor and chain-gear mechanism are applied to realize maneuvering thread demolding successfully. .Compared with other mechanism, this kind of mechanism can work accurately and stable for demolding, with low noise, good quality and high efficiency.

(2)The CAD technology has been used in the mold and moldbase design by means of Pro/E and EMX4.1, thus the cycle of developing a new part can be shorten rapidly and the mold costs in designing and manufacturing can be reduced greatly.

The maneuvering thread demolding way and CAD technology in the mold designing can be considered as a successful example for other similar mold with tread structure.

  (a) plastic part diagram (b)3D diagram Fig.1 tread flange

Fig. 4

 4 Fig.4 chain-gear transmission diagram (1) The gear parameter design In the moldbase of tread flange, the center distance between two gearing shafts is 120mm, and the main gear parameters are following: Diametrical pitch/mm: 2.5 Tooth number: z1=28,z2=20 Pitch circle diameter/mm: D1=70, D2=50 Gear width/mm: B1=20, B2=30 (2) Bearing selectionAxis with parts on it is located by bearing and bearing cover in axial and radial directions for the stability.According to the force loaded on the axis ,the deep groove ball bearing 61805 is selected in the design.(3)Chain transmission parameter According to reference[START_REF] Dang | Mold Design And Manufacture[END_REF] , the plastic part enveloping force can be calculated as following: F=28.1KN.Considering the enveloping force on the core coming from the plastic part, the chain 16B in GB/T 1243-1997 is selected whose tensile load is 60KN and pitch 25.4mm with single row and short pitch.The parameters of the Sprocket in the mold is designed as: z3=54 ,z4=20.(4)The transmission ration calculation As the total thread's length is 12mm, and thread pitch is 1.5mm, so the thread number can be calculated as 8.The formular of overall ratio is next: i=(z2/z1)(z4/z3)≈0.26 (1) In the formula, the meanings of z1,z2,z3 and z4 are shown in Fig.4.It can be illustrated from the formula(1) that in order to pull the thread out of the core

( 7 )

 7 Fig.5 moldbase


Jiwen Ren
email: renjiwen@163.com

Jianshu Liu

Jinju Yin

Simulation of Transient Temperature Field in the Selective Laser Sintering Process of W/Ni Powder Mixture

Keywords: Selective laser sintering, Finite element simulation, Temperature field, Molten pool

Selective laser sintering (SLS) is an attractive rapid prototyping and manufacturing (RP&M) technology as well as two-component metal powder has high melting pointer, high mechanical properties and high wear resistance. Hence, it's meaningful to analyze its temperature field distribution and dynamical evolution rule in sintering process. A three-dimensional transient finite element model of SLS on the two-component metal powder W/Ni has been developed to predict the temperature field distribution in this paper. The dynamically loading of the moving Gaussian laser thermal resource was realized using the element "birth and death" technology and the ANSYS Parameter Design Language (APDL) in the model. Considering comprehensively thermal convection and the non-linear behavior of material properties etc., the temperature evolution of SLS process has been simulated effectively. The interrelation between the temperature field distribution and the processing parameters are analyzed. The sintering width and depth under certain selected sintering parameters are obtained so as to judge the metallurgical bonding performance between substrate and layers. The result of simulation can provide the theoretical basis for selecting reasonable processing parameters.

Introduction

Selective laser sintering(SLS) is an attractive process in the new field of rapid prototyping (RP) which is such an advance manufacturing technology that integrates laser technology, precision machinery, computer-aided design, computer-aided manufacturing, computer numerical control, control technology, and material technology [START_REF] Wang | Optimizing process parameters for selective laser sintering based on neural network and genetic algorithm[END_REF]. Direct metal laser sintering (DMLS) is a method of rapid prototyping and manufacturing (RP&M) which three-dimensional parts are formed directly from metal powders. It includes three major materials such as single-component metal powder, multi-component metal powder and pre-alloyed powder. Multi-component powder can overcome the shortcomings of the single-component metal powder such as difficult forming, which consists of two metal materials with significantly different melting points. The low melting metal powder acts as the bonding phase while the high melting metal powder acts as the framework phase [START_REF] Xiong | Progress on metal powder materials used for direct selective laser sintering[END_REF]. Research shows that multi-component metal could reduce plastic deformation in the high temperature and improve mechanical properties of the SLS parts [START_REF] Cui | The present application and materials for selective laser sintering[END_REF]. Therefore, the research on direct laser sintering high melting metal powder has attracted more and more attention. Nowadays, many scholars at home and abroad work on SLS temperature field simulation [START_REF] Kolossov | 3D FE simulation for temperature evolution in the selective laser sintering process[END_REF][START_REF] Guo | 3D finite simulation for temperature field of direct metal laser sintering[END_REF][START_REF] Zhou | Finite element simulation for the temperature field in multi-layer thin-wall metal part formed by DMLS[END_REF], but there is little research on temperature field simulation of twocomponent metal powder with high melting point. Therefore, it's necessary to systematically analyze the temperature field distribution and the dynamical evolution rules in sintering process of two-component metal powder and carries out accurate simulation and prediction, which can provide the theoretical basis and guidance to experiments of direct laser sintering high melting point metal powder. With the development of computer technology and finite element theory, it has becomes a reasonable way to study the laser sintering temperature field using finite element method (FEM). In this paper, a finite element model for laser sintering has been developed and the load of moving heat source at different times and locations is carried out by ANSYS Parametric Design Language (APDL). At the same time, the formation and evolution of transient temperature field sintering two-component metal powder during SLS and formation mechanism of two-component metal powder has been discussed.

2

Establishment of Model

Establishment of Finite Element Model

The finite element model of sintering is shown in Fig. 1. The established finite element model is divided into two parts, namely substrate and powder. The Upper of model is two-component metal powder which is a mixture of W and Ni and its size is 3.4mm×1.6 mm×0.2 mm. The substrate material is 45 steel and its size is 4.4 mm×3mm×0.6 mm. In order to ensure the accuracy of the calculation, the sintering powder is meshed by Solid70 with hexahedral and eight-node and the grid size is 0.1mm×0.1 mm×0.1 mm while the substrate is meshed by Solid90. To save calculation time and improve efficiency, the larger grids are applied to the substrate.

Initial Conditions and Boundary Conditions

SLS is a very complex heat treatment process, which is accompanied by three ways of heat transfer including heat conduction, heat convection and heat radiation [START_REF] Gu | Numerical simulations of temperature field in direct metal laser sintering process[END_REF]. Before solving the heat balance equation, we should assume that powder bed has a uniform initial temperature 0 T , which is at room temperature or reaches a certain uniform temperature through preheating, then the initial conditions as follows:

0 0 ) , , , ( T t z y x T t = = .
(

) 1
The convection and radiation between surrounding environment and substrate and the boundaries of powder bed belong to the third type boundary condition, which is expressed as follows.

q T T T T h z T k E E z e = - + - + ∂ ∂ - = ) ( ) ( 4 4 0 σε . ( 2
)
Where is the thermal conductivity of the material, is convection heat transfer coefficient, T is the temperature of metal powder at a certain moment,

Load of Gauss Heat Source

In the process of sintering, laser energy moving at a certain rate is input to powder bed in the form of heat flux. Generally speaking, the laser energy below 3kw obeys the Gaussian distribution [START_REF] Weng | Effect of process parameters on the temperature field evolution of Fe Powder laser sintering[END_REF].

) 2 exp( 2 ) , ( 2 2 2 ω πω r AP y x q - = . ( 3
)
Where is laser power density, ) , ( y x q ρ is laser power, A is absorption rate of powder bed to laser, is distance between any point on the powder bed and laser spot center and

2 0 2 0 2 ) ( ) ( y y x x r - + - = ω is radius of laser spot.
In order to make this simulation close to reality, it needs to use the technique of "element birth/death" to exert the heat load at different times at different spots. First, all the element of powder bed is killed in the beginning. Then, the element which needs to be loaded is activated as the sintering goes on, which is used to simulate dynamic sintering process. Next, the heat flux is exerted on the activated element meantime in the meantime the heat flux of last load step should be removed and the previous solution results are used as the initial conditions for this solution to calculate thermal conductivity matrix and specific heat matrix. The circle is in turn until the whole sintering process completed.

Thermal Physical Properties of Material

The sintering powder is obtained by mixing W powder and Ni powder according to the percentage of 55% Ni and 45% W. The material parameters of Ni ,W and the substrate material of 45 steel are shown [START_REF] Yang | 3D finite element temperature field modeling for direct laser fabrication[END_REF][START_REF] Tan | Thermal physical properties of engineering alloys[END_REF]. The equivalent thermal physical parameters of mixture powder such as density and specific heat can be determined by the law of Kopp-Neumann. Among all the thermal physical parameters which have great influence on the performance of powder sintering, the effective thermal conductivity of powder bed is the most important. However, due to the heat transfer mechanism is complex, the precise value is difficult to determine. So the area without sintering cannot be directly defined with thermal physical properties of material, but could be estimated by the following equation [START_REF] Shen | Simulation of 3D transient temperature field during selective laser sintering of multi-component metal powder[END_REF].

× - + ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎣ ⎡ + - - = ϕ ϕ ϕ 1 1 ) 1 1 ( g r g e k k k k ⎥ ⎥ ⎥ ⎥ ⎥ ⎦ ⎤ ⎢ ⎢ ⎢ ⎢ ⎢ ⎣ ⎡ + ⎟ ⎟ ⎟ ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎜ ⎜ ⎜ ⎝ ⎛ - ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ - - g r g s s g s g k k k k k k k k 1 ln 1 1 1 2 . ( 4
)
Where is the thermal conductivity of environment, is effective thermal conductivity of solid, g k s k ϕ is initial porosity and is heat transfer coefficient of powder bed cased by radiation, which can be expressed by the following equation. (

) 5
Where σ is Stefan-Boltzmann constant, is average diameter of powder particles, is temperature of powder particles and is apparent coefficient approximately taken as 1/3.

Simulation Results and Discussion

Fig. 2 shows the scanning pattern of simulation. It includes two layers. Each layer has five scanning paths and the scanning width is 0.3mm. The other simulation parameters include the laser power, the spot diameter, the scanning speed, the thermal absorptivity, the initial temperature and the coefficient of air convection under normal temperature. The values are 300W, 0.4mm, 80mm/s, 0.3, 298K and 10, respectively. In order to master the variation of temperature field in sintering process, some special points on scanning line are selected to analyze, as shown in Fig. 2. Among which point 1, point 2 and point 3 is the midpoint of line 1,line 2 and line 5, respectively. And the mid-point of the first scanning path of the second layer is marked as point 4. Fig. 3 shows the temperature distribution at time 0.0125S,0.025S,0.0375S. As seen from Fig. 3,With the moving of laser beam the temperature field distribution is different from distribution of rotundity temperature field of stationary laser beam. The concrete expression is that the isotherm of the sintered front-end is closer than that of the sintered area, namely, temperature gradient of the sintered front-end is greater than that of sintered area. The reason is that with the rapidly moving of the highenergy laser beam the heat of laser center spreads around during the sintering process. While the density and thermal conductivity of sintering area are higher than them of powder front-end, thus heat is more easily to spread backward and makes the distance of isotherm of the sintered area enlarge and the temperature distribution exhibit "comet" shape. The simulation results show that zone affected by heat expands constantly and the temperature of substrate and powder bed has increased to some extent as the sintering goes on. This is mainly due to the accumulation of heat during sintering process. Fig. 3 shows that the temperatures of molten pool have exceeded the melting point of Ni(1728K) while the maximum temperatures of molten pool fail to reach the melting point of W (3650K). Therefore, Ni powder has change into liquid while the W powder keeps on solid phase. It has ensured that the molten pool formed by solid-liquid mixture state. The solid particles of the molten pool dissolved in the liquid phase rearrange, move closer to each other and bond into the frame by the role of liquid surface tension. The remaining liquid evenly distributes in the gap of the skeleton, which avoids effectively the "balling" phenomenon of sintering in pure liquid phase. Fig. 4 is the temperatures of point 1, point 2 and point 3 vary with time. When point 1 is sintering, its temperature rises rapidly to 2628K and exceed the melting point of Ni, so the Ni powder melts. Its temperature gradually reduces when the spot's far away and there's a similar fluctuation with the increase of scanning lines. For sintering two layers and each layer with five scanning, temperature of every point has about 10 similar fluctuations. Moreover in each layer, with the distance between scanning path and point 1 increasing, fluctuation gradually decline, namely, the effect on the temperature of point 1 decrease gradually. In the meantime the highest temperature of subsequent scanning path is little higher than that of previous scanning path, and it has the similar regularity to other points. Fig. 4 shows that the temperatures of point 1, point 2 and point 3 show upward trends throughout all the sintering process, which is due to heat accumulation caused by sustained action of laser beam. Fig. 5 is the temperatures of point 1 and point 4 vary with time. Point 4 is the midpoint of the first sintering path of the second layer. While sintering the first layer, the element of point 4 has been killed, so the temperature of point 4 is still the initial temperature (298K) at the time 0.19375S. While sintering the second layer, the temperature of point 4 rises gradually. when the laser beam scans through point 4, the temperature of point 4 sharply rises to near 3000K and the temperature of point 1, under point 4, correspondingly rises, which is lower than point 4 because of separating a sintering layer and higher than melting point of Ni. The sintering depth is more than 0.1mm, which shows that these process parameters ensure the metallurgical bonding between layers as well as the bonding strength between layers of sintered parts. Fig. 6 is the temperature distribution of Y-direction and Z-direction of point 1 and point 2. From Fig. 6(a), we could see the width of point 2, above the melting point of Ni powder (1728K), is about 0.425mm,which is larger than sintering width(0.3mm) and ensures the metallurgical bonding between scan paths. Fig. 6(b) shows that the temperature has decreased with the increase of depth of sintering, the temperature at 0.1mm has reached the melting point of Ni powder, which shows that the powder of sintering layer could be melt completely and makes sintering layer and the substrate are bonding firmly. The temperature distribution of point 1 is similar to that of point 2, except for the temperature of point 2 is little higher than point 1 because of the heat accumulation. Compared Fig. 6(a) with Fig. 6(b), we can find that temperature gradient of Y-direction is larger than that of Z-direction, hence, the heat lose is mainly along Z-direction. So it is necessary to find out the influencing factors of the depth of molten pool, which are adjusted to stabilize the molten pool and improve the precision of parts.

Fig. 1 .

 1 Fig.1. 3-D finite element model of laser sintering.

Fig. 2 .

 2 Fig. 2. Scanning pattern of laser sintering.

Fig. 3 .

 3 (a) at 0.0125S. (b) at 0.025S. (c) at 0.0375S. Temperature distribution at different moment.

Fig. 4 .

 4 Fig. 4. Temperatures of point 1,point 2 and point 3 varying with time.

Fig. 5 .

 5 Fig. 5. Temperatures of point 1 and point 4 varying with time.

  (a) Temperature distribution of Y-direction. (b) Temperature distribution of Z-direction.

Fig. 6 .

 6 Fig. 6. Temperature distribution of point 1 and point 2.

Acknowledgements

We are thankful that the study is supported by Natural Science Foundation of Jiangxi Province of China(2008GZC0055) and Foundation of Jiangxi Educational Committee(GJJ09209).

Considering comprehensively the influence of temperature-related thermal physical properties, Gaussian laser beam, thermal conduction and heat convection etc., a finite element model of SLS on the two-component metal powder has been developed using APDL and the temperature field has been simulated effectively using the element "birth and death" technology and the dynamical loading of the moving laser beam, which could dynamically reflect the form and change of temperature field during sintering process. The results show that the highest temperature during sintering process is higher than the melting point of Ni powder, but not reaches the melting point of W powder, so the sintering mechanism is an incomplete molten mechanism, Which is also consistent with forming mechanism of SLS powder mixture. The heat accumulation makes the area affected by heat expand and the whole temperature of substrate and powder bed rise as sintering goes on. It's reasonable to select SLS process parameters according to the width and depth of the molten pool.


Dongsheng Wu

Jun Li

Xiaoping Shu

Xiaojing Zha

Beili Xu

Test analysis and theoretical calculation on braking distance of automobile with ABS

Keywords: Automobile with ABS, Testing, Braking distance, Theoretical calculation

Braking performance test methods are compared and analyzed .ABS will not work if the speed is too low when the automobile is tested by tester and load testing. Since the braking performance can not be evaluated accurately in this case, the theoretical calculation of braking distance is given in this paper. The calculation result shown the potential of braking performance is mainly on high speed for the automobile with ABS. High-speed road test is designed, and the test results are close to calculation ones, so calculation model is of accuracy. It is less error and better precision than existing calculation way, this method is effective and accurate.

Introduction

The ABS automobile is a vehicle with anti-lock braking system. The Braking performance reflects the ability that the vehicle stops in a short time and keeps traveling stability. The braking distance is the distance required for a vehicle moving at a specified velocity to come to a complete stop after its brakes have been activated. It is an important indicator for braking performance evaluation, but the error is big for braking distance test of automobiles with ABS [START_REF] Alvarez | Emergency braking control with an observer-based dynamic tire/road friction model and wheel angular velocity measurement[END_REF] . So its performance can't be accurately shown from test results [START_REF] Schinkel | Anti-lockbraking control using a sliding mode like approach[END_REF] . Therefore, the ABS braking distance is simulated through this theory method. Simulation results must be compared with the road test to verify the simulation accuracy. For the road test of ABS brake performance, the United States, Japan and the European Economic Community, Economic Commission for Europe have enacted stringent norms and regulations, and also put forward specific requirements from different perspectives. By theoretical calculation, initial speed in these norms and regulations has been discussed whether it can truly reflect potential braking performance in the line brake. It can be more targeted to amend road test so that the braking performance of vehicle with ABS can be comprehensive evaluated [START_REF] Song | A study on anti-lock braking system controller and rear-wheel controller to enhance vehicle lateral stability[END_REF][START_REF] Sugai | New Control Techniaue for Maximizing Braking Force on Antilock Braking System[END_REF] .

Braking distance test of automobile with ABS

There are two methods for testing braking performance of automobiles with ABS, one is by tester and the other is by road testing. The brake distance can be measured by road testing. At present, towing method is mainly used on the road testing, that is to say, the press and drag mark is used to evaluate the braking performance when a vehicle moving at a specified speed brakes. This method is simple and visual, but the disadvantage is also obvious. This method is limited by many factors such as weather, road, driver [START_REF] Shiming | Research of Bed-testing Evaluation Method of ABS Performance[END_REF] . Test data is easily impacted on human and test condition. Therefore, the value is different after many tests and evaluation of braking performance is not exact.

Calculation method of braking distance of automobile with ABS

In order to get reference for road test results, calculation equation is derived through analysis of braking process.

Establishment of calculation model

The reaction time t 0 mainly depends on the driver, as well as the positions of accelerator pedal and brake pedal.

Usually, it only takes 0.3~1.0 seconds so the distance that the vehicle moves during t 0 at the speed of v 0 can be ignored according to equation 1 0 0

s v t = ⋅ . 0 F ' F 0 2 M F δ - 0 F M δ -

Fig.1 Braking process of automobile with ABS

The second step is the growth of braking force t 1 . The braking force keeps increasing with the driver moving the brake pedal until it is up to the maximum. Due to the gap between brake shoe and brake drum, braking force will work after a short period of time. To compare the results with the one in Reference 6, this period can also be ignored. So the brake reaction time can be regarded as t 1 . At this period, the automobile's braking performance is the best because of ABS working.

Supposed the maximum braking force just reaches the maximum ground braking force, according to the force analysis of wheels during braking, the maximum deceleration F 0 is as followed:

0 p F g M ϕ = ⋅ ⋅ (1)
Where, φ p is peak adhesion coefficient, g is acceleration of gravity, which is 9.8m/s2.

During the growing step of braking force, the growth is a linear function of time, whose average braking force 1

F is:

1 1 0 1 1 1 2 T p p mg dT T F mg T ϕ ϕ = = ∫ (2)
In this step, according to Newton's second law, the average deceleration a 1 and terminal velocity v 1 can be expressed as followed:

1 1 1 2 p F a g m ϕ = = (3) 1 1 0 0 1 0 1 2 t p p g v v tdt v g t t ϕ 1 ϕ = - = - ∫ (4)
According to the functional relationship, the work of braking force on the car is equal to kinetic energy increase before and after braking, so 1

F is:

2 1 1 1 0 1 1 1 2 2 2 p F S mg S mv mv ϕ ⋅ = = - 2 1 (5)
Then braking distance of second step s1 is:

2 2 0 1 1 p v v S gϕ - = (6)
The third step is braking duration. So pressure regulation frequency ω and amplitude δ are considered as design parameters, and pressure regulation process of ABS is simulated by cosine function, then coordinate is transformed (shown in Fig. 1). The equations can be gotten as below:

0 1 ' cos ' 2 ' ( 2
' M F t M F F F t t t δ ω δ ⎫ = ) ⎪ ⎪ ⎪ = - - ⎬ ⎪ ⎪ ⎪ = - ⎭ (7)
Eq.7 is converted to original coordinate system, as shown below:

[ 2 2 0 2 M F M (F ) cos ( ) 2 2 d S t t dt δ δ ω ⋅ = = -+ -] 1 2 (8)
Solving Eq.8, then it can get the braking distance of second step, so the total value is:

1 S S S = + (9)

Initial conditions and solution of model

Initial conditions of Eq.8 are shown in Eq.10: To braking requirements of ECE13 on the high friction coefficient road, initial braking speed is 50 km/h , and ABS braking performance is not significant [START_REF] Sugai | New Control Techniaue for Maximizing Braking Force on Antilock Braking System[END_REF] because it is difficult to find a complete cycle in this moment.

1 2 0 2 2 2 0 1 1 1 ( ) p t t p d S a g dt V V S t S g ϕ ϕ = ⎫ = = ⎪ ⎪ ⎬ -⎪ = = ⎪ ⎭ (10)
Therefore, in Eq.10, for the high-speed braking situation, the initial velocity is respectively taken 100km/h and 130km/h. Simulated calculation is happened on the dry and wet concrete road, and the peak friction coefficient is respectively 0.9 and 0.8. t1 is the time of the brake force growth which depends on the speed of the driver stepped on the brake pedal and the brake system structure, generally, t 1 is from 0.15s to 0.2s in hydraulic brake system, and is 0.3s ~ 0.9s [START_REF] Jun | The:Theory and Practice of ABS Automobile[END_REF] in air pressure brake system and the vacuum servo brake. 0.4s is taken in this calculation.

Substitute related values in Eq.8, Eq.9 and Eq.10 and solve it, and the results are shown in Tab.2. with results of using the calculation methods in this paper, the brake performance reliability for this car can be evaluated.

Tab. 3 The brake distance values of the Benz car on concrete road at high speed [START_REF] Zhisheng | Automobile Theory[END_REF] program concrete road Initial speed(km/h) Brake distance(m) Brake distance(m) From Tab.3, it can be told that the brake distance test values are almost the same as the calculated values in this paper except the ones in Program 1, which tested on dry concrete road at an initial speed 100km/h. Under the some conditions, the brake distance results were calculated by the method mentioned in Doc.6. Comparing the tested results, the calculated results with the method in Doc.6 and the calculated values in this paper, Fig. 2 can be obtained as below. The results in Doc.6 were calculated in the condition that the brake system obtained the biggest brake force during continuous brake process with ABS. So ideal ABS model is called and the results should be smaller than the actual ones. Fig. 2 shows that the calculated results are bigger than the ones of the ideal model except Program 1. Consequently, the brake distance calculation method in this paper is reasonable.

Error analysis

Fig.3 brake distance error comparison

The error between the calculation result with the method in Doc.6 and tested results is calculated, and is compared with the error between the results from this paper and actual vehicle test. As shown in Fig. 3, the calculation result error with the method in this paper fluctuates around the horizontal axis and tends to be smaller, whereas, the result error of Doc.6 tends to be larger. With the increasing of vehicle's speed, the error of this paper is rather stationary, and the calculation result is fairly reliable. However, the calculation result error with the method in Doc.8 is a litter larger. So the calculation result with the method in this paper is reliable and stable.

Conclusions

1.A calculation model of brake distance is come up, which showed that brake distance for ABS vehicles during continuous brake process is relevant to brake initial speed, road condition, ABS control system's regulating frequency and amplitude. This calculation method can be applied to brake distance calculating and analyzing for various kinds of vehicles.

2.Comparing the brake distance calculation results in this paper with the results from actual vehicle road test, it can be concluded that the calculation in this paper is effective and accurate, which also can evaluated properly on the brake distance results in the test.

3.Evaluation is made on one road test. According to the calculation results in this paper, it can be gotten that the brake distance results of Program 1 are doubtful and need further confirmation.

Fig. 2

 2 Fig.2 brake distance results comparison

  By comparing the brake distance values which are recorded for a Benz car with ABS in Doc.8 through test road

	Tab.2 The brake distance simulation results on the dry and wet concrete road with high-speed braking
	calculation conditions	calculation results
	concrete road	Initial velocity(km/h)	brake distance(m)
	dry	100	51.382
	wet	100	58.129
	dry	130	84.946
	wet	130	95.317
	4 Road test and error analysis
	4.1 Road test verification

Acknowledgement

The work is supported by the Department of Transportation of Jiangxi Province (2009T0053).


Chun-Hua Xiao

Shao-Kun Li

Ke-Ru Wang

Yan-Li Lu

Jun-Hua Bai

Rui-Zhi Xie

Shi-Ju Gao

Fang- Qiong Wang

Yong Wang

Xiao Chun-Hua

L I Shao-Kun

Wang Ke-Ru

L U Yan-Li

Bai Jun-Hua

Xie Rui-Zhi

Gao Shi-Ju

Wang Fang-Yong

A Leaf Layer Spectral Model for Estimating Protein Content of Wheat Grains

Keywords: wheat canopy, leaf distribution, direction spectra, view angle, model

des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The spectral characteristics of a crop canopy are determined not only by biophysical and biochemical features and also plant structural attributes. Leaf optical properties are a main factor for canopy spectral.

Crop canopy spectral characteristics represent important information needed to guide crop management. Crop composition and structure are difficult to assess by traditional spectral measurement with vertical canopy direction. The direction spectrum includes a great deal of crop canopy information.

Multiangle data significantly improved the accuracy of recovering forest parameters when inverting 3-D optical models (Kimes et al., 2002) but forest vertical structure can not be captured accurately using only the 4 spectral bands in the nadir view or all view angles with a single spectral band (Kimes et al.,2006).

Directional radiances in or near the principal plane of the sun provides information that leads to more accurate prediction of canopy structure parameters than from other azimuth planes (Gobron et al., 2000).

Canopy emissivity increased with increasing view angle due to the greater proportion of vegetation observed at off-nadir view angles; when the proportion of leaves was lower than that of soil, canopy emissivity grew with increasing view angle (Sobrino et al., 2005).

It should be noted that these models assume a Lambertian behaviour for soil and vegetation surfaces.

Although vegetation surfaces show a near Lambertian behaviour, bare soil surfaces do not and the angular variation on emissivity can not be neglected. Lidars, multiangle radiometers, radars and imaging spectrometers have been identified as systems that can capture information in the vertical dimension. This requires a capability to remotely measure the vertical and spatial distribution of forest structural parameters that are needed for more accurate models of energy, carbon, and water flux over regional, continental, and global scales. Thus, we examined the utility of hyperspectral data for the quantitative characterization of vertical wheat structure.

Most remote sensing systems provided an image of the horizontal scope, but could not provide the vertical information on biochemical distribution in a crop canopy, thereby reducing the accuracy of measurement.

Multi-angle data can increase the precision of forest parameters (Kimes,et al., 2006).

The distribution of tissues in a crop canopy has certain characteristics -biochemical distribution is different because of transfer of matter during the growth stage. Leaves in a wheat canopy are composed of under, middle, upper layer and ear layers (Wang et al.,2004). The spectral characteristic differed among canopy leaves because of the different reflection and scatter, so their effect on canopy spectra was different (Wang et al., 2004).

Various biochemical (foliar lignin and nitrogen) and biophysical factors influencing canopy reflectance signatures have been studied in previous works.

Information on biochemical parameters is important and the multi-angle spectra which provide information on different directions can facilitate a more exact prediction of biochemical parameters. To date, there are no studies on the relative importance of vertical distribution of wheat leaves that determines canopy reflectance across the shortwave (350-2500nm) spectrum. The contribution of each leaf layer relative to all other factors has also not been adequately

determined. Yet, it is the interaction of these factors, including their potential covariance or unique behavior, that must be understood if advances in remote sensing are to be achieved.

In this study, the leaf slice method was used to characterize a wheat canopy, evaluate the spectral response of leaf vertical distribution in the canopy, determine the characteristics of spectral curve for different leaf layers and develop a methodology for predicting the biochemistry of the canopy. -4). Canopy layers were severed with a scissors from the ear layer to lower layer (Fig. 3).

Measured traits and methods

All canopy spectral measurements were taken from a height of 1.3 m above ground (the height of the wheat was 90 cm at maturity), under clear sky conditions and lower leaves layer(LLL)(Fig. 2).

Leaf samples from EL,ULL,LLL were taken almost synchronously with the spectral measurements.

Measurements were conducted at jointing, heading, anthesis, milking and waxing stages. These samples were oven-dried at 70℃ and nitrogen content was

Data analysis

The hyperspectral data were analyzed using the Matlab6.5 software and quantitative data were analyzed using an analysis of variance (ANOVA) procedure.

Lower layer

Upper layer 1/2H

3.1The spectral curves following removal of different leaf layers

The lower leaves of the canopy changed the spectral reflectivity (Fig. 3) with different view angles at 350-700nm, 800-1300nm and 1400-1800nm. This is important for pigment content within the visible wave band (350-700nm). The reflectivity of near infrared (800-1300nm) is influenced by canopy characteristics.

The wavebands (1400-1800nm) provide information on the water content. In this paper, we analyzed the characteristics of visible (350-700nm) and near infrared (800-1300nm) wavebands. Comparing the direction spectral characteristic of the two wheat canopies, the spectral response of Jingdong8 with different view angles was more significant than that of Zhongyou9507 at visible and near infrared wavebands; the max reflectivity of Jingdong8 was 31% higher than that of Zhongyou9507 at 350-700nm and 22.4% higher at 800-1300nm.

The spectral curve of doing away with different leaves at the 60° view angle showed that the leaf influenced the curve of visible and near infrared wavebands (Fig. 4). The change for Jingdong8 was more significant than for Zhongyou9507; the spectral reflectivity of Jingdong8 was 11.2% higher than that of Zhongyou9507 at 350-700nm and 26.8% higher at 800-1300nm.

To further analyze the relation between canopy spectra and leaves, we selected six spectral reflectivities at 450, 550, 670, 980, 1090, 1200nm.

Analysis of spectral reflectivity of leaf layers at different view angles

As shown in Fig. 5, for Jingdong8, the spectral reflectivity of the whole canopy was similar with the Jingdong8 Zhongyou9507 Zhongyou9507 Jingdong8 Compared to the 90° view angle, the reflectivity at 30 and 60° had more information on the lower leaves, which were important for reflectivity of the canopy.

The reflectivity at 0° contained very important information on upper leaves.

The canopy spectral reflectivity of Zhongyou9507 was lower than that of Jingdong8 (Fig. 6) at1090nm; the reflectivity due to ILLC-3 at 0° view angle changed 4.4%, while that due to ILLC-1 changed14.7%; at 90° view angle, the changes were 5.9 and 46.8%; at 30°, they were 16.9 and 44.4% and at 60° they were 16.8

Analysis of variance (ANOVA) of spectral reflectivity for different leaf layers

The ANOVA of mean reflectivities across six wavelengths showed that the reflectivity of Jingdong8 was lower than that of Zhongyou9507 (Table 1). For Jingdong8, the response of canopy spectra due to ILLC-1 and ELC were significant at the 0° view angle; at 30° as for 60°, the effects of ELC, ILLC-1, ILLC-2 and ILLC-3 were significant; at 90°, the ELC and ILLC-1 were important and at 120, 150 and 180° view angles, the ELC and ILLC-1 were significant. The ELC and ILLC-1 were important for canopy spectra and the influence of lower leaves were less. For the view angles of 0°, 90°, 120°, 150°, 180°), the under leaves were less influential; at 30 and 60°, the response of lower leaves were significant. The canopy spectral responses of different leaves for Zhongyou9507 differed from that of Jingdong8; at 0 and 90° view angles, the ELC and ILLC-1 effects were significant at 30 and 60°, the ELC, ILLC-1, ILLC-2 effects were significant.

At the same view angle, the ELC and ILLC-1 were more important than the lower leaves.

The spectral response of lower leaves was related to the view angle. With vertical and horizontal measurements, the influence of lower leaves were less than that of other view angles.

Correlation of spectral parameters of leaf layers with leaf nitrogen content (LNC)

The correlation between canopy spectral parameters, spectral grads and corresponding nitrogen content in different leaf layers (Table 2 was significant between △RVI[670,890] and leaf layer grads at the flowering stage for Jingdong8 and milky stage for Zhongyou9507.

Leaf layer spectral model for protein content in wheat grains

A prediction model for GPC based on spectra of leaf layers was developed as follows:

a) Jingdong8 at the flowering stage:

GPC (%) = 12.0168△RVI + 15.6975

R 2 =0.7727**, n=24 (3)
b) Zhongyou9507 at the milk stage:

GPC (%)=-8.9028△RVI+18.7397 R 2 =0.7838**, n=24 (4)
The conventional spectral model using 90°view

angle was also developed as follows:

a) Jingdong8 at the flowering stage: GPC (%) = 11.98RVI +16.71

R 2 =0.6537**, n=24 (5)
b) Zhongyou9507 at the milk stage:

GPC (%) = 19.21RVI +13.59 R 2 =0.6659**, n=24 (6)
The determinant coefficients, R 2 of models ( 5) and ( 6) were 18 and 17% higher than those of models ( 3) and ( 4), hence, the predicted GPC model of leaf layer spectral was better. The root mean square error (RMSE) was used to test the reliability and estimation accuracy of these models for grain protein content. The RMSE of Jingdong8 was 0.7500 while that of Zhongyou9507 was 0.6461. The determinant coefficients, R2 between measured and estimated grain protein contents were 0.7467 and 0.7599, respectively (Fig. 7). These result indicated

Validation of the predicted GPC model of leaf layer spectra

Conclusions

The crop canopy has a three-dimensional structure In this study, two wheat varieties differing in plant-type were studied using the leaf layer slice method by analyzing the spectral changes for different leaf layers at different view angles in the plane of vertical wheat line. We noted that:

(1) The spectral characteristics varied in 300-700nm, 800-1300nm and 1400-1800nm wave bands because of removal of leaf layers and differences in view angle.

The change in the visible wave bands was less than that in near infrared wave bands and that in Jingdong8 was less than that in Zhongyou9507.

(2) Compared with the traditional 90° view angle, the spectral information of under leaves were more at 30 and 60° than other view angles; for upper leaves the information was more at 0° view angle. The spectral influence of upper leaves of Zhongyou9507 at 0° view angle was less than that of Jingdong8. The upper leaves of the lax-leafed wheat captured much radiation because of their horizontal orientation, the proportion of upward leaves was bigger than that of downwards leaves. In contrast, the radiation characteristics were complicated in the erect leaf plant-type,.

(3) The predicted GPC model by leaf layer spectra using 0° view angle were feasible, the RMSE was 0.7500 for Jingdong8 and 0.6461 for Zhongyou9507.

The determinant coefficients, R 2 between measured and estimated grain protein contents were 0.7467 and 0.7599. Thus, the leaf layer model would be reliable for predicting grain protein content.

In precision agriculture, it is important to accurately measure the state of a crop's growth using remote

between 10 :

 10 00 and 14:00 (Beijing local time), using an ASD FieldSpec Pro spectrometer (Analytical Spectral Devices, Boulder, CO,USA) fitted with a 258 field of view fiber optics, operating in the 350-2500 nm spectral region with a sampling interval of 1.4 nm between 350 and 1050 nm and 2 nm between 1050 and 2500 nm and with spectral resolutions of 3 nm at 700 nm and10 nm at 1400 nm. A 40 cm ×40 cm BaSO4 calibration panel was used for calculation of reflectance. The spectra were measured with view angles of 0, 30,60,90,120, 150, and 180° to the line vertical to the wheat row using the Simple multi-angle spectral measurement equipment (Fig.1) after every layer was removed (N2 treatment). The model spectra were measured with a view angle of 0° using other treatments at ear layer (EL), upper leaves layer (ULL)

  ,1981) using a B-339 DistillationUnit (BUCHIAnalyticalLtd, Flawil, Switzerland). Wheat grain protein content estimated from the formula : Pro% =6.25 × Nitr (% ).

Fig. 1

 1 Fig. 1 Simple multi-angle spectral measurement equipment Fig. 2 Sketch of measured method by layer

Fig. 3

 3 Fig.3 Spectra of removing the forth leaf layer at different angles for Jingdong8 and Zhongyou9507 wheat

  leaf layer removal treatment, ILLC-4; doing away with ELC and ILLC-1 reduced the reflectivity. The changes in reflectivity at 550nm were more obvious than at 450 and 670nm. In visible wave bands, changes were evident for 980, 1090,1200nm in near infrared wave bands. At different view angles, the reflectivity of the 90° view angle was the lowest and with increasing distance from the vertical measurement, the reflectivity increased, especially in visible wave bands than in near infrared. The reflectivity changes due to ILLC-1 and ELC were more obvious than those of other leaf layers.The reflectivity changes due to LLC-3 at 1090nm were 8.8% at 0° view angle and 48.6% for ILLC-1. At 90° view angle, the changes were 5.6 and 40.7%; at 30°, they were 12.9 and 27.7% and at 60° they were 12.2 and 34%, respectively. The change was less pronounced at the 180, 150 and 120° view angles.

Fig. 5 Fig. 6

 56 Fig.5 Spectral characteristics following removal of different leaf layers in Jingdong8

Fig. 7

 7 Fig.7 Estimated and measured grain protein contents (GPC) in Jingdong 8 and Zhongyou 9507

  whose characteristics are determined by species composition and the three-dimensional distribution of leaves. The biochemical content has some regulatory role in the distribution of the canopy space. The horizontal radiation balances are likely to occur if the internal variability of derived surface products, the typical distances that photons may travel horizontally within such 3-D media extend to spatial scales that are similar to or larger than those of the measuring sensor In order to maintain the energy balance of the overal forest domain, lacal canopy volumes with rather large positive net horizontal fluxes must also exist,thus underscoring the importance of properly locating local flux measurement equipment(Jean-Luc Widlowski, 2006). The more accurate modeling of energy are required for remotely measure the vertical and spatial distribution of forest structure. The potential of using a multi-angle spectral sensor to predict forest vertical structure were researched, the results showed the multi-angle spectral provided a relatively direct measure of vertical structure(D.S.Kimes 2006). The anisotropic scattering of both the vegetation canopy and the background is taken into consideration in a two-layer model of the bidirectional reflectance of homogeneous vegetation canopies(S.Liangrocapart, 2002).

  sensing techniques. In this study, we analyzed the canopy spectral characteristics of two wheat types and observed that canopy spectra were influenced by leaf layers and view angles; the spectral response of under leaves varied with different view angles. A quantitative study of different leaf layers and their spectra is needed for precise crop management. Since results were obtained only in Peking region, more experiments should done in other regions.

Table 1

 1 Canopy spectral characteristic of different leaf layers of Jingdong8 and Zhongyou9507

	Average value

Note: Means followed by different lower case letters differ significantly at P< 0.05; those followed by different upper case letters differ significantly at P<0.01.

Table 2

 2 Correlation coefficients between nitrogen contents at different layers and spectral characteristics ( SC ) and ** : significant correlations at 0.05 and 0.01 probability levels, respectively. ULNC: upper layer nitrogen content; LLNC: lower layer nitrogen content; △LNC: the difference between ULNC and LLNC. LSCP: spectral

	LSCP

*

Acknowledgments

This work was supported with grants (2006AA10Z207, 2006AA10A302) from the National High Tech R&D Program and (30760109) from the National Natural Science Fundation of China and (2002BAH12B02) National Key Technology R&D Program