Recently, Guo Shili, a 2023 graduate student majoring in electronic information from the School of Electronic and Electrical Engineering, and Associate Professor Liu Ye, supervisor, presented a presentation titled "Defect Detection of Photovoltaic Modules Based on Electroluminescence Images" at the International Conference on "Intelligent Automation and System Security" and "Autonomous Unmanned Systems" (ICAIS & ISAS, May 24-25, 2025, Xi'an). The latest research results of the "A RCLM-YOLO Method" provide innovative solutions in the field of photovoltaic module defect detection.

Aiming at the contradiction between accuracy and efficiency in defect detection in photovoltaic electroluminescence (EL) images, a lightweight detection algorithm RCLM-YOLO is proposed. This achievement constructs a lightweight technical framework for photovoltaic EL image defect detection, providing an accurate and economical solution for online quality inspection of photovoltaic modules, and has important engineering value for promoting the development of intelligent detection technology in the new energy industry. The research was supported by the Shanghai Municipal Science and Technology Commission project.

It is reported that the ICAIS & ISAS international conference focuses on the frontier of intelligent systems and unmanned technology, and this achievement demonstrates the research strength of our institute in the field of intelligent detection of new energy equipment, further enhancing the international influence of the discipline.