Method of rebar detection in cement pole based on BP neural network

Zongyi Luo; Xiang Bao; Jianjie He; Zhongdong Yu; Kecheng Qiu; Bowen Deng; Zhanlong Zhang

doi:10.1117/12.2611402

14 October 2021 Method of rebar detection in cement pole based on BP neural network

Zongyi Luo, Xiang Bao, Jianjie He, Zhongdong Yu, Kecheng Qiu, Bowen Deng, Zhanlong Zhang

Proceedings Volume 11930, International Conference on Mechanical Engineering, Measurement Control, and Instrumentation; 119301V (2021) https://doi.org/10.1117/12.2611402
Event: International Conference on Mechanical Engineering, Measurement Control, and Instrumentation (MEMCI 2021), 2021, Guangzhou, China

Abstract

Power cement poles made of reinforced concrete are widely used in low-voltage transmission lines as pillars and overhead wires. However, when the manufacturer uses stretched and polished waste rebar whose diameter is smaller than the designed size and the quality is unqualified, it will greatly increase the potential safety hazards of the transmission line. Therefore, the accurate detection of the parameters of the rebar in the cement pole can effectively maintain its safe operation. There are many concrete rebar detection methods, but most of them cannot simultaneously measure the diameter and buried depth of the rebar. Therefore, the article proposes a rebar magnetic measurement method based on BP (Back Propagation) neural network algorithm. First, the article theoretically analysis the influence of the magnetization effect of rebar on the space magnetic field and the principle of magnetic measurement, and then builds an experimental platform to verify the feasibility of the detection method, and further combines the BP neural network algorithm model to train and verify the detection data, finally obtain accurate rebar diameter and buried depth parameters.

Citation Download Citation

Zongyi Luo, Xiang Bao, Jianjie He, Zhongdong Yu, Kecheng Qiu, Bowen Deng, and Zhanlong Zhang "Method of rebar detection in cement pole based on BP neural network", Proc. SPIE 11930, International Conference on Mechanical Engineering, Measurement Control, and Instrumentation, 119301V (14 October 2021); https://doi.org/10.1117/12.2611402

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