Detection and Classification of Faults in PV Systems Based on Thermal Imaging and Fuzzy Logic Algorithm
摘要
Fault detection and classification systems in PV fields have become a top concern to ensure the functioning of PV panels. According to the literature, many studies have been conducted to address this issue. This work attempts to offer a defect detection and classification approach in PV panels using image processing of a thermal picture in this context. To detect and classify the degree and existence of the errors, the k-means and fuzzy logic methods were employed, respectively. The simulations indicate that using the suggested approach enables the accurate detection and classification of faults in solar panels.