Solar cell panel crack detection using Particle Swarm Optimization algorithm

A solar cell panel as an efficient power source for the production of electrical energy has long been considered. Any defect on the solar cell panel´s surface will be lead to reduced production of power and loss in the yield. In this case, inspection of the solar cell panel is essential to be performed to obtain a product of high quality. Some inspection methods have been developed, but in any event non-contact, non-destructive and efficient testing methods are necessary. This paper proposes an automated inspection system based on an image-processing approach for solar cell panel application in order to detect any cracks which may be appeared on the surface of solar cell panel. The Particle Swarm Optimization (PSO) algorithm as a main constituent of our proposed method is used for edge detection in the solar cell panel. Subsequently, some features like cracks and bus bars will be extracted and we will classify defected products and cracks based on the positions of the bus bars using Fuzzy logic. In this proposed method, an automated inspection system of solar cell panel proposed which has potential to get good results based on Particle Swarm optimization algorithm.