Abstract
With the continuous expansion of artificial intelligence in power system, the reliability, security and operation ability of power system have been greatly improved. With the massive collection of data for transmission and transformation operation and maintenance, in-depth learning, as a typical representative of data-driven in the system of artificial intelligence methods, is increasingly appearing in the application scenarios of intelligent state assessment of transmission and transformation equipment. Its excellent robustness can eliminate many kinds of interference in complex environment background, accurately identify and evaluate the target points under test, and greatly reduce the detection of transportation and inspection personnel. The workload of data analysis, processing, evaluation and other links can improve work efficiency and accuracy. This paper attempts to summarize the development process of in-depth learning, relevant landmark achievements and typical applications in the operation and inspection of power transmission and transformation equipment. This paper attempts to summarize the research progress of target recognition, target segmentation, image classification algorithms in depth learning in different spectral cameras of visible light, ultraviolet corona imaging and infrared thermal imaging.
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