A method for detecting the appearance of dirty defects of polycrystalline silicon solar cells

Abstract

The invention provides a method for detecting appearance dirt defects of polycrystalline silicon solar cells. The method is mainly divided into two steps: the first step is to preprocess the cells to obtain the area of ​​interest, and subsequent operations are based on this; Identify and mark dirty areas in two steps. The preprocessing part includes: dividing the collected three-channel images into R channel, G channel, and B channel images, selecting the R channel image with strong contrast between the defect and the background for subsequent processing; smoothing the selected R channel image, Suppress the interference of image noise and high-frequency components, then perform a rotation correction operation on the image to make the image edge parallel to the coordinate system, and then segment the image with a fixed threshold. Based on the area, set upper and lower critical values ​​to eliminate the impact of the conveyor belt area on image processing. Interference; then perform morphological closed-loop operation on the image to eliminate small black holes produced when threshold segmentation is insufficient, and finally realize the detection of appearance dirt defects of polycrystalline silicon solar cells.

Description

technical field [0001] The invention relates to the technical field of photovoltaic cell detection, and mainly relates to a method for detection of appearance dirt defects of polycrystalline silicon solar cells. Background technique [0002] The application of photovoltaic power generation is becoming more and more widespread. According to research, starting from 2030, solar photovoltaic power generation will increase by more than 10% every ten years in the world's total power supply, and by the end of the 21st century, renewable energy will account for more than 80% of the energy structure. , solar power generation accounted for more than 60%, solar power generation shows an important strategic significance. The production process of polycrystalline silicon solar cells is complicated, and various defects are prone to appear in the production process. After these defective cells are assembled, they not only affect the overall appearance, but also have a great impact on the e...

AI Technical Summary

Problems solved by technology

[0003] Existing defect detection methods mainly rely on traditional manual naked eye detection, which will be affected by subjectivity and visual fatigue, which will easily cause missed detection, false detection, and low efficiency. With the labor cost, the production cost of the enterprise will also increase

Because polysilicon cells are affected by their own crystal lattice, the image texture on the surface is uneven, and defect feature extraction is difficult, which causes great troubles to the current defect detection. Therefore, the use of machine vision to detect cell defects has not been widely promoted.

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