Insulator Defect Detection Based on EfficientDet and Binocular Camera

doi:10.11930/j.issn.1004-9649.202006315

Abstract

Abstract: Insulator is an important component of transmission lines. The defective insulator will cause hidden dangers to the lines. Image detection technology can improve the efficiency of insulator defect detection and greatly reduce the maintenance cost. However, the existing insulator defect detection technology has the disadvantages of low accuracy and long detection time. Aiming at this problem, an insulator defect detection method is proposed based on EfficientDet and binocular camera. Firstly, a data collection method is designed for binocular camera to solve the problem of insufficient open source data set; Secondly, the problem of excessive resources occupied by EfficientDet is solved by a labeled classification first algorithm; Finally, the proposed algorithm is compared with three conventional algorithms. It is found that the mAP of the proposed algorithm is 50.04, which is superior to other three algorithms. The accuracy rate of insulator and defect identification and positioning is more than 95% and 90%, respectively, which shows the proposed algorithm’s good efficiency and practicability.

Key words: neural network, binocular camera, insulator, defect detection, machine vision

LIU Yifan, WANG Shuqing, QING Yihui, WANG Chenxi, LAN Tianze, YAO Ruotian. Insulator Defect Detection Based on EfficientDet and Binocular Camera[J]. Electric Power, 2021, 54(2): 156-163,196.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202006315

https://www.electricpower.com.cn/EN/Y2021/V54/I2/156

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