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      Research on Insulator Defect Detection Based on an Improved MobilenetV1-YOLOv4.

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          Abstract

          Insulator devices are important for transmission lines, and defects such as insulator bursting and string loss affect the safety of transmission lines. In this study, we aim to investigate the problems of slow detection speed and low efficiency of traditional insulator defect detection algorithms, and to improve the accuracy of insulator fault identification and the convenience of daily work; therefore, we propose an insulator defect detection algorithm based on an improved MobilenetV1-YOLOv4. First, the backbone feature extraction network of YOLOv4 'Backbone' is replaced with the lightweight module Mobilenet-V1. Second, the scSE attention mechanism is introduced in stages of preliminary feature extraction and enhanced feature extraction, sequentially. Finally, the depthwise separable convolution substitutes the 3 × 3 convolution of the enhanced feature extraction network to reduce the overall number of network parameters. The experimental results show that the weight of the improved algorithm is 57.9 MB, which is 62.6% less than that obtained by the MobilenetV1-YOLOv4 model; the average accuracy of insulator defect detection is improved by 0.26% and reaches 98.81%; and the detection speed reaches 190 frames per second with an increase of 37 frames per second.

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          Author and article information

          Journal
          Entropy (Basel)
          Entropy (Basel, Switzerland)
          MDPI AG
          1099-4300
          1099-4300
          Nov 02 2022
          : 24
          : 11
          Affiliations
          [1 ] School of Electrical & Information Engineering, Anhui University of Science and Technology, Huainan 232001, China.
          [2 ] School of Electrical and Opto Electronic Engineering, West Anhui University, Lu'an 237012, China.
          Article
          e24111588
          10.3390/e24111588
          9689300
          36359678
          21fd800b-d821-4f48-a6ef-b1096b0771df
          History

          depthwise separable convolution,YOLOv4,Mobilenet-V1,scSE attention mechanism,insulator defect detection

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