A detection method for edge chipping and blunt and v-shaped notches of photovoltaic cells

Abstract

The method for detecting edge collapse and blunt and V-shaped notches of photovoltaic cells provided by the present invention performs preprocessing of image correction and image conversion on each frame of images collected, and can obtain target images of photovoltaic cells; Cap transformation, which can obtain the image of the photovoltaic cell that only includes the grid line part, threshold segmentation, fills the grid line part, can eliminate the influence of the inside of the grid line on defect detection, obtains the foreground image that only contains the grid line part, and thresholds to segment the background The image is processed by morphological closed operation, which can fill the edge collapse, blunt and V-shaped gaps, and make a difference between the morphologically processed background image and the unprocessed background image, which can realize edge collapse, blunt shape and V The detection of type gaps overcomes the shortcomings of manual detection, and can effectively improve the accuracy of detection of defects in photovoltaic cells, which has great application value for the photovoltaic industry.

Description

technical field [0001] The invention relates to the technical field of detection of surface defects of photovoltaic cells, in particular to a method for detecting edge chipping and blunt and V-shaped notches of photovoltaic cells. Background technique [0002] In recent years, people have become more and more dependent on clean energy, and the output of photovoltaic cells has further expanded. As an important power generation carrier, photovoltaic cells have the advantages of high light energy conversion efficiency, long service life, relatively mature production technology, and low cost. As a result, photovoltaic cells are prone to various defects, and the existence of defects will reduce their conversion efficiency and service life. Therefore, the detection of photovoltaic cell defects is an indispensable part of the production process. [0003] At present, the field mainly relies on manual visual inspection, the detection efficiency and quality are relatively low, and th...

AI Technical Summary

Problems solved by technology

As an important power generation carrier, photovoltaic cells have the advantages of high light energy conversion efficiency, long service life, relatively mature production technology, and low cost. As a result, photovoltaic cells are prone to various defects, and the existence of defects will reduce their conversion efficiency and service life. Therefore, the detection of photovoltaic cell defects is an indispensable part of the production process.

[0003] At present, the field mainly relies on manual visual inspection, the detection efficiency and quality are relatively low, and the detection repeatability is poor, and the cost is high. Therefore, the traditional manual detection can no longer meet the needs of the field.

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