Silicon solar cell surface defect detection and identification method

Abstract

The invention discloses a silicon solar cell surface defect detection and identification method. The method includes the steps of (1) obtaining an independent canonical variate analysis (ICA) reconstruction disjunct matrix and an independent component; (2) obtaining a solar assembly image reconstruction image to be detected; (3) detecting whether the reconstruction image has defects, and positioning and dividing a defected solar cell piece; (4) obtaining multiple small wave textural features of a solar cell piece surface image to be detected and detecting whether defects exist in a statistic unit; (5) extracting textural features of an independent component element (ICA) of a defected solar cell piece image to be classified; (6) training a support vector machine model; (7) identifying the textural features of a defected solar cell piece image combination to be classified in a classifying mode. The method is easy to operate, can effectively defect fine defects, and improves the detection rate of the defects; roughness and directivity of solar cell piece surface textures are described by means of ICA sparse texture features, so a classifier has strong robustness and high identification precision.

Description

technical field [0001] The invention belongs to the technical field of industrial visual detection and image processing, and in particular relates to a method for detecting and identifying surface defects of silicon solar cells based on independent component analysis and texture features. Background technique [0002] In today's world, with energy shortage and environmental crisis, solar energy, as a renewable clean energy, has become the fastest growing and most dynamic research field in recent years. In the near future, solar photovoltaic power generation will occupy an important position in the world's energy consumption. It will not only replace some conventional energy sources, but also become the main body of the world's energy supply. It is estimated that by 2030, the proportion of renewable energy in the total energy structure will reach more than 30%, and the share of solar photovoltaic power generation in the world's total power supply will also reach more than 10%...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the problems of low detection efficiency and low identification automation level of existing solar cell surface defects, the present invention provides a silicon solar cell surface defect detection and recognition method that can improve the detection efficiency and recognition effect of defects

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