Research And Implementation Of Surface Crack Detection Algorithm For Photovoltaic Cell Module

With the rapid development of the solar photovoltaic industry,research on the protection of solar cell arrays has become increasingly important.Solar cell modules are an important part of photovoltaic power generation systems,and their damage will directly affect the output power of the system.The detection of surface cracks on solar cells is a very important link.At present,the method of manual visual inspection is mainly used for detection.This method is labor-intensive and is affected by the subjective factors of the inspectors.Therefore,this paper conducts research on the surface crack detection algorithm of solar cell modules,which aims to solve the problems of existing detection methods and provide a strong impetus for the development of the photovoltaic industry.First,analyze the solar cell principle and crack detection technology,and combine the basic structure and principle analysis of the solar cell module to further study the photovoltaic characteristics of the solar cell module,including the polarity,performance parameters and volt-ampere characteristics of the solar cell.Analyze the cause of the cracks based on the manufacturing process,and perform performance comparisons in multiple aspects to select the appropriate method to complete the research in this paper.Optimized on the basis of the original Canny edge detection algorithm,including the improvement of the filtering process and the gradient calculation process,the preprocessing of the original image,including the grayscale of the color image and the normalization of the image pixel space,and then the processed The image is filtered by Gaussian to remove the noise signal in the image,and the pixel space is subjected to maximum suppression processing to merge dual-threshold filtering,calculate the image gradient at this time,and determine whether the gradient at this time meets the needs of crack recognition.Secondly,a dynamic threshold segmentation algorithm for intelligent detection and marking of photovoltaic cell module cracks is designed.The area is located by means of different aspect ratio smoothing,the smoothed image and the original image are used for absolute difference and interference is eliminated,then the difference map is thresholded,a small area is filtered to remove impurities,and the cracks are marked by closed calculation fitting.Use this to identify photovoltaic modules with cracks and failures.Finally,the algorithm simulation results show that the improved edge detection algorithm has a detection accuracy of 83%,while the dynamic threshold segmentation algorithm has a detection accuracy of 91%.Although both can detect the crack information on the photovoltaic cell module,the dynamic threshold segmentation The performance of the algorithm is more superior,its crack detection accuracy is higher,and it is fully labeled,and it has achieved good results in detection speed,accuracy,and stability.The detection method greatly improves the efficiency of the inspection work of the photovoltaic power generation system,and has strong practicability and promotion value.