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The main content of this paper is to realize non-contact and visual contamination detection and analysis in substation equipment. Firstly, the experimental platform is built, and the visible light of the incident spectrometer is arranged into the spectral database. Then the database is reduced and screened by convolutional neural network. The filtered new data are classified by YOLOv5s algorithm. When different types of insulators are background substrates, The influence of spectral contamination on classification recognition is different, It is mainly affected by the coverage of the dirty layer and the morphology of the dirty particles.
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LiNa et al. (2024) studied this question.
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