An Automatic Vision System using Optical Scanning Mechanism

with Near-infrared Optics for Solar Cell Wafer

Gyung-bum Kim

Dept. of Aeronatical & Mechanical Eng, Korea National University of Transportaion, Chungju, South Korea

Keywords: Optical Scanning Mechanism, Solar Cell Wafer, Surface Inspection System, Near-infrared Optics.

Abstract: In this paper, an automatic vision system based on optical scanning mechanism is developed for solar cell

wafer. It consists of optical scanning mechanism with near-infrared(NIR) camera optics, machinery and

control system, algorithm of defect detection and software. Optical scanning mechanism is composed of

geometrical camera optics and structured hybrid illumination system(SHIS). It is used to inspection of

surface defects. Also, NIR camera optics is used for inspection of defects inside solar cell wafer. It is shown

that the automatic inspection system give satisfactory performance for micro defects in solar cell wafer.

1 INTRODUCTION

Solar energy using solar cell wafer is considered as

renewable green energy. The silicon wafer is an

inevitable part in solar cell. Its thickness has been

slim so far due to competition of cost. It is because

the cost of silicon wafer manufacturing is involved

more than 60% in solar cell manufacturing. A lot of

defects such as topology defects, surface defects and

internal micro defects, are generated in silicon wafer

manufacturing. They highly result from slimmer

thickness of silicon wafer. They result in high

manufacturing cost and lack of efficiency. Therefore,

the automatic inspection of defects in solar cell

wafer is urgently required.(Li, 2011)

In this paper, an automatic inspection system is

developed for solar cell wafer. It is composed of

optical scanning mechanism, NIR camera optics,

machinery and control system, defect detection

algorithm and software.

2 OPTICAL SCANNING

MECHANISM

2.1 Geometric Camera Optics

The optical scanning mechanism in Figure 1 is

designed for solar cell wafer. It is composed of

geometric camera optics, structured hybrid

illumination system(SHIS). High-speed machine

vision must be applied to manufacturing process of

solar cell wafer due to fast production line.(Golnabi,

2007) To implement the fast inspection, TDI(time

delay & integration) line scan camera is used. It has

high sensitivity and is used as inspection camera in

geometric camera optics. Also, an area camera with

high resolution is used as monitoring. The detail

specifications of optical scanning mechanism is in

Table 1.

Table 1: Specification of geometrical camera optics.

Lists Specification

Line scan

camera

Resolution: 8192×32TDI

Pixel size: 7×7 ㎛

Line rate: up to 34kHz

Area camera

Image sensor: SONY CCD

Resolution: 1280×1024

Frame rate: 15fp

Lens

Macro-

symmar

5.6/102

Focal length: 120mm

Mag.: 0.38 ~ 0.63x

Max aperture: F5.9

Zoom

70XL

Zoom range: 7:1

Mag.: 0.75 ~5.25x

Work distance: 89mm

Frame grabber

SOL 2M EV CLF

Data acquisition: Camera link

Image library MIL 9.0

The best focused position of camera can be found

Kim G..

An Automatic Vision System using Optical Scanning Mechanism with Near-infrared Optics for Solar Cell Wafer.

DOI: 10.5220/0004679200270030

In Proceedings of the 4th International Conference on Pervasive and Embedded Computing and Communication Systems (PECCS-2014), pages 27-30

ISBN: 978-989-758-000-0

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

automatically. To solve this problem, the hill

climbing algorithm(Cho, 2006) is used as auto

focusing method. It determines the direction of the

lens and camera movement in order to search for the

maximum value of the focus measure in Figure 2.

Also, lens magnification can be automatically

adjusted. the length between solar cell wafer and

lens is 'a' and length between lens and camera sensor

is 'b', the lens formula is formed by Gaussian lens

principle. Here, focal length of lens is f. Once f, a

and b are changed, magnification M is varied. The

optical scanning mechanism can change lens

magnification through controlling the interval of 'b'.,

Figure 1: Optical scanning mechanism.

Figure 2: Distribution of focus measure for autofocusing.

2.2 Structured Hybrid Illumination

System

An illumination system is used to keep uniformly

good contrast between object and background in

machine vision. Illumination conditions for high-

quality and reliable images are very important,

because suitable illumination conditions result in the

extraction of useful features.(Sunil, 2006) There are

a lot of illumination methods exclusive of

illumination sources such as bright field, dark field,

dome light, oblique front light, directional front

light, diffusion front light, back light, co-axial light

and structured light etc..

In this paper, SHIS(Kim, 2012) are designed to

optionally use bright field, dark field, oblique front

light, directional front light and diffusion front light,

in accordance with inspection environment. SHIS

consists of upper illumination in Fig. 3 ① and under

illumination in Fig 3 ②. SHIS is symmetry structure

against optical axis. The upper illumination is

mainly the bright field method and can use

directional front light because illumination channels

are separately controlled. The channel 1 and 4 are

Blue LED, channel 2 and 5 are Green LED and

channel 3 and 6 are Red LED. The under

illumination is usually used for dark field method

and oblique front light. The channel 7~15 consist of

Blue-Green-Red LED in order. Each channel row is

separately controlled but it is symmetrically

controlled in the same time. Also, angle of under

illumination can be adjusted in a certain range θ.

Illumination source is LED. The advantages of LED

are high efficiency, uniformity of luminance, no

flicker, long lifetime and requirement of low current.

All illumination channels are directed to one point.

The used LED specifications are in Table 2.

Diffusion filter is utilized in order to uniform and get

a smooth image. SHIS makes an efficient

combination of upper and under illumination. When

all upper and under illumination are used, SHIS can

be used as diffusion front light.

Figure 3: Structured hybrid illumination system.

Table 2: Specification of LED.

List Blue Green Red

Forward Current 35mA 35mA 30mA

Forward voltage 3.2V 3.2V 2.1V

Wavelength 471nm 525nm 628nm

Operation

temperature

-30 ~ 85 -30 ~ 85 -30 ~ 85

Luminous

intensity

8200mcd 9600mcd 12000mcd

2.3 NIR Camera Optics

Infrared ray is used as heat source. Solar cell wafer

PECCS2014-InternationalConferenceonPervasiveandEmbeddedComputingandCommunicationSystems

can be damaged by its longtime incidence.

Accordingly, The infrared spectrum band that has a

little transmittance as well as weak heat source

needs to be selected for solar cell wafer. It is

regarded as the spectrum of near-infrared ray. In

case NIR is incident to solar cell wafer, full

reflectance ray is represented from surface. Also,

while the phenomenon of transmittance and

reflectance is represented in repetition by optical

scattering inside wafer, the ray of absorption, body

reflectance and transmittance resulting in solar cell

wafer is dispersed in all direction.(Choi, 2006)

Inspection of internal micro defect uses

transmission characteristic of NIR because it is not

inspected in general illumination like LED and

halogen. NIR camera optics is known as temperature

detection of object because it is mainly affected by

heat source. But, NIR camera optics is not detection

of heat source. NIR camera optics acquires

wavelength that is not transmitted by visible ray.

Solar cell wafer has a relatively high transmission

characteristics about wavelength of 1 micron level.

Using this principle, images of internal defects can

be acquired in NIR camera when NIR light is

incident to solar cell wafer by back light method.

NIR camera optics in Fig. 4 is designed for internal

micro defect inspection of solar cell wafer. Its detail

specifications are in Table 3.

Figure 4: NIR camera optics.

3 AUTOMATIC INSPECTION

SYSTEM

The automatic inspection system for solar cell wafer

is described in Figure 5. It consists of optical

scanning mechanism with NIR camera optics,

machinery and control system, algorithm of defect

detection and software.

The inspection software is described in Figure 6,

and includes 15 software modules. They are as

follows; (1) Geometry: Translation and rotation of

Table 3: Specification of NIR camera optics.

Lists Specifications

NIR

camera

Array type: InGaAs

Spectral band: 900~1700nm

Pixels: 320×256 ㎛

Pixel operability: >99%

Frame rate: 100Hz, 12bit

Camera control: USB 2.0

Lens Compact VIS-NIR lens

Illumination

Infrared halogen light source: 1127nm

IR back light source: 850~940nm

inspected image (2) Configuration: confirmation and

modification and of inspected image information

from teaching reference image (3) Anisotropic

diffusion: Image filtering option (4) Model selection:

information save in specified region of reference

image (5) Teaching: Save of wafer information (6)

Image alignment: alignment of inspected image

based on reference image (7) Inspection: defect

detection of inspected wafer based on reference

image (8) Auto inspection: automatic execution of

detection and inspection process using Figure 7 (9)

Image open (10) Image save (11) Zoom in/out (12)

Inspection result: information of detection defect (13)

Number of defects.

Its inspection performance has been evaluated

for various defects such as pinhole, scratch, edge

defect, stain and sawmark, in terms of accuracy,

repeatability and undetected error rate. Inspected

wafers with no defect, pinhole, scratch, edge defect,

stain and sawmark, are prepared for the simulation

of real inspection. Their number is 50 sheets,

respectively. So, the total wafer number is 300. The

inspection results is shown in Table 4. The

developed algorithm results in 100% accuracy for

defects such as pinhole, stain and sawmark. It gives

excellent results. Also, its accuracy is 96% for edge

defect and 92% for edge defect. Its undetected error

rate is 4% and 8% for scratc and edge defect,

Figure 5: Automatic inspection system.

AnAutomaticVisionSystemusingOpticalScanningMechanismwithNear-infraredOpticsforSolarCellWafer

respectively. The developed algorithm gives 100%

detection repeatability. In case the inspected image,

relative to the reference image, two defects such as

edge defect and scratch can not be detected. This

result from non-uniformity of wafer edge and

internal wafer. As a result, the useful performance of

our algorithm is verified through detection

experiments using 5 types of defects.

Figure 6: The inspection software.

Figure 7: Flow chart of defect detection algorithm.

4 CONCLUSIONS

In this paper, an automatic vision inspection system

based on optical scanning mechanism with NIR

optics is developed for solar cell wafer. It consists of

optical scanning mechanism with NIR camera

optics, machinery and control system, algorithm of

Table 4: Results of performance evaluation.

Lists Accuracy Repeatability

Undetected

error rate

Pinhole 100% 100% -

Scratch 96% 100% 4%

Edge

defect

92% 100% 8%

Stain 100% 100% -

Sawmark 100% 100% -

defect detection and software. It is shown that the

developed inspection system gives useful and

excellent results in performance evaluation and is

applied to measurement and inspection processes

related with surface quality control as well as solar

cell manufacturing.

ACKNOWLEDGEMENTS

This research was supported by Basic Science

Research Program through the National Research

Foundation of Korea(NRF) funded by the Ministry

of Education, Science and Technology(2012001630)

REFERENCES

Li, W. C. and Tsai, D. M., 2011. Automatic Saw-mark

Detection in Multi-crystalline Solar Wafer Images,

Solar Energy Materials & Solar cells, DOI:

10.1016/j.solmat.2011.03.025.1.

Sunil, K. K., 2006. Lighting Design for Machine Vision

Application, Image & Vision Computing, Vol. 24, pp.

720-726.

Golnabi, H., Asadpour, A., 2007. Design and application

of industrial machine vision systems, Robotics and

Computer-Integrated Manufacturing, Vol. 23, pp. 630-

637.

Choi, M. Y., et al, 2006. Measurement of Defects and

Stress by Infrared Thermography, Journal of Korean

Society of Precision Engineers, Vol. 23, No. 10, pp.

30~35.

An, B. I. and Kim, G. B., 2012. Development of structured

hybrid illumination system and optimum illumination

condition selection for detection of surface defects on

silicon wafer in solar cell, Journal of the Korean

Society of Mechanical Engineers(A), Vol. 36, No. 5,

pp. 336~337.

Cho, H. S., 2006. Optomechatronics, Taylor & Francis.

Kim, G. B., 2010. A structured mechanism development

and experimental parameter selection of laser

scattering for the surface inspection of flat-panel

glasses, International Journal of Production Research,

Vol. 13, No.49, pp. 3911~3923.

Kim, G. B., Yeon, J. S., 2011. Development of laser

scattering system and inspection of micro defects in

crystalline silicon wafer of solar cell, Proceedings of

the 11th EUSPEN International Conference, pp.39-42.

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