Key points and quality control method of electrical equipment 
installation process based on machine learning

Jun Xu; Zhongyue Huang; Aijuan Zhu; Yikai Zhang

doi:10.1117/12.2686647

10 August 2023 Key points and quality control method of electrical equipment installation process based on machine learning

Jun Xu, Zhongyue Huang, Aijuan Zhu, Yikai Zhang

Author Affiliations +

Proceedings Volume 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023); 127590T (2023) https://doi.org/10.1117/12.2686647
Event: 2023 3rd International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB 2023), 2023, Xiamen, China

Abstract

Conventional electrical equipment installation quality control methods mainly use EPLAN electrical drawing software for quality assessment, which is vulnerable to the impact of dynamic installation environment changes, resulting in low quality factor evaluation indicators. Therefore, a new electrical equipment installation quality control method needs to be designed based on machine learning. That is, according to the key points of the installation process, the factors affecting the installation quality of electrical equipment are analyzed, the installation status of electrical equipment is diagnosed using machine learning technology, and the hierarchical control points for the installation quality of electrical equipment are constructed, thus completing the installation quality control of electrical equipment. The case analysis results show that the quality factor evaluation index of the designed electrical equipment installation quality control method based on machine learning is high, which proves that its control effect is good, reliable, and has certain application value, and has made certain contributions to the subsequent electrical equipment installation optimization.

Citation Download Citation

Jun Xu, Zhongyue Huang, Aijuan Zhu, and Yikai Zhang "Key points and quality control method of electrical equipment installation process based on machine learning", Proc. SPIE 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023), 127590T (10 August 2023); https://doi.org/10.1117/12.2686647

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