| 英文摘要 |
The safe and stable operation of electrical equipment plays a vital role in the safety and economy of substations. In order to monitor the operational status of equipment promptly and effectively, this study proposes a substation equipment fault diagnosis method based on infrared thermal imaging technology and machine vision technology. Firstly, the data samples of infrared equipment are collected by infrared camera. Then, the collected data is remotely transmitted to the monitoring center for image processing. Based on the temperature characteristics of infrared images, equipment thermal fault diagnosis is achieved by applying the related intelligent vision technology. Finally, the server is used to alarm the abnormal temperature equipment in real time to avoid accidents or further deterioration. The experimental results show that the proposed method can accurately locate the equipment and detect the abnormal temperature area of the equipment in real time, which provides theoretical support for the monitoring of substation equipment, improves the work efficiency of substation and reduces the frequency of equipment failure. |
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