Abstract
At present, the converter station is generally equipped with visible light, infrared, and ultraviolet monitoring systems, and some of them have alarm functions, but the automation is insufficient, the sensitivity is not high, and it is easy to be falsely reported. At the same time, a large amount of data is collected for the operation and maintenance personnel to judge and increase the operation and maintenance workload. At the same time, it is impossible to help the operation and maintenance personnel to detect potential accidents early, curb the spread of accidents in advance, and help to prevent the occurrence of fires at the converter station. Therefore, this paper studies the online state evaluation method of the UHV (Ultra High Voltage) converter valve tower based on infrared/ultraviolet image recognition. Through artificial intelligence image recognition technology, it can accurately diagnose and identify abnormalities such as open flame, heat, discharge and water seepage in valve hall equipment.
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