Abstract
With the expansion of power grid scale, the method of manual inspection is more and more difficult to implement. Nowadays, it is possible to use infrared imaging equipment and target detection method based on deep learning technology to intelligently detect zero-sequence insulator. In this paper, zero-sequence insulator detection technology based on in-depth learning is proposed to detect zero-sequence insulators with different contamination, air humidity and different locations. This technology has the characteristics of low investment cost, high accuracy and strong adaptability in complex environment, which can reduce the labor intensity and workload of power grid patrol personnel. The high accuracy of the system can effectively reduce the outage accidents caused by the deterioration of insulators in the power grid, thus ensuring the safe and stable operation of the power grid.
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