Detection of punching circle defects of electric power tower based on GA-BP network

Zhendong He; Liangjian Cui; Jie Liu; Suna Zhao; Shiju Ge

doi:10.1117/12.2636794

29 April 2022 Detection of punching circle defects of electric power tower based on GA-BP network

Zhendong He, Liangjian Cui, Jie Liu, Suna Zhao, Shiju Ge

Proceedings Volume 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022); 122471Y (2022) https://doi.org/10.1117/12.2636794
Event: 2022 International Conference on Image, Signal Processing, and Pattern Recognition, 2022, Guilin, China

Abstract

Aiming at the characteristics of the angle steel punching circle defect, this paper proposes a method for detecting the punching circle defect based on the genetic algorithm to optimize the BP neural network. Using BP neural network to detect the defects of the punching circle can effectively solve the problem of nonlinear mapping between the input and output of the punching circle defect. The traditional BP neural network model is easy to fall into the local minimum and cause the risk of model failure. The genetic algorithm is used to optimize the weights and thresholds of the BP neural network, and the obtained optimal weights and thresholds are substituted into the prediction model for defects. Detection can improve the stability and predictive ability of the model. Experiments show that the GA-BP network has higher accuracy and generalization ability than the unoptimized BP network, and can accurately detect the punching circle defects of the power tower angle steel.

Citation Download Citation

Zhendong He, Liangjian Cui, Jie Liu, Suna Zhao, and Shiju Ge "Detection of punching circle defects of electric power tower based on GA-BP network", Proc. SPIE 12247, International Conference on Image, Signal Processing, and Pattern Recognition (ISPP 2022), 122471Y (29 April 2022); https://doi.org/10.1117/12.2636794

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