Abstract
With the increasing demand of power supply reliability for electrical equipment in power grid and the continuous development of infrared thermal imaging technology, infrared thermal imaging technology has been widely used in electrical equipment detection. Using infrared instruments to detect and diagnose thermal fault of electrical equipment has become one of the mainstream methods of electric equipment inspection. However, at present, fault detection relies heavily on personnel’s experience and has low detection efficiency. In order to improve the intelligent level of power system and solve the problem of accurate detection of thermal faults of electrical equipment in substations, this paper applies Faster RCNN algorithm to infrared detection to realize automatic detection of electrical equipment faults. The average recognition accuracy of equipment can reach more than 85%, which has good effect.
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Yuan, H., Chen, X., Wang, Y., Su, M. (2019). State Detection of Electrical Equipment Based on Infrared Thermal Imaging Technology. In: Lin, Z., et al. Pattern Recognition and Computer Vision. PRCV 2019. Lecture Notes in Computer Science(), vol 11857. Springer, Cham. https://doi.org/10.1007/978-3-030-31654-9_22
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DOI: https://doi.org/10.1007/978-3-030-31654-9_22
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