Thermal infrared inspection is a non-destructive testing method that utilizes infrared cameras to capture thermal images of PV arrays. . To address the challenges of high missed detection rates, complex backgrounds, unclear defect features, and uneven difficulty levels in target detection during the industrial process of photovoltaic panel defect detection, this article proposes an infrared detection method based on computer vision. . Photovoltaic (PV) panel faults caused by weather, ground leakage, circuit issues, temperature, environment, age, and other damage can take many forms but often symptomatically exhibit temperature differences. Included is a mini survey to review these common faults and PV array fault detection. . Infrared (IR) anomaly detection has become a powerful tool for spotting issues like diode failures, hotspots, electrical isolation problems, and string outages. The editors of the document are Ul ared machine vision (IRMV) is an important supplement to MV. Devices included. . As solar energy continues to gain traction as a reliable and sustainable power source, maintaining the efficiency and safety of photovoltaic (PV) arrays becomes increasingly important. The classifiers are Decision tre, K-Nearest Neighbours algorithm (KNN), and Support-vector machine (SVM).
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