Halcon-Based Solar Panel Crack Detection

Driven by the national new energy policy, China's solar photovoltaic industry has ushered in unprecedented development opportunities. At present, China has become the world's largest producer of photovoltaic modules, and has reached the international advanced level in solar cell manufacturing. However, many enterprises still use manual checking in the process of detecting solar panels. The manual detection is subject to various factors of employees themselves, and it is prone to problems such as low detection efficiency, high false detection rate, high scrap rate and high labor cost. In this paper, a solar panel crack detection device based on the deep learning algorithm in Halcon image processing software is designed for the most common defect in solar panel production process, which can effectively detect cracked solar panels and reduce the rate of defective products in the late stage, improve the production quality of solar cells, and reduce energy waste and labor costs.