Intelligent detection method for substation insulator defects based on CenterMask
نویسندگان
چکیده
With the development of intelligent operation and maintenance substations, daily inspection substations needs to process massive video image data. This puts forward higher requirements on processing speed accuracy defect detection. Based end-to-end learning paradigm, this article proposes an detection method for substation insulator defects based CenterMask. First, backbone network VoVNet is improved according residual connection eSE module, which effectively solves problems deep saturation gradient information loss. On basis, mask generation a spatial attention-directed mechanism proposed. Insulators with complex backgrounds are accurately segmented. Then, three strategies pixel-wise regression prediction, multi-scale features, centerness introduced. The anchor-free single-stage target detector locates points insulators. Finally, example analysis carried out power supply company in certain area verify effectiveness robustness proposed method.
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ژورنال
عنوان ژورنال: Frontiers in Energy Research
سال: 2022
ISSN: ['2296-598X']
DOI: https://doi.org/10.3389/fenrg.2022.985600