高压电器2025，Vol.61Issue(2)：130-140,11.DOI:10.13296/j.1001-1609.hva.2025.02.015
基于INGO-SVM的输电铁塔地脚螺栓螺母缺失无损检测方法
Non-destructive Detection Method for Nuts Missing Defect on Anchor Bolts of Transmission Tower Based on INGO-SVM
摘要
Abstract
For non-destructively detecting the missing and defect of nuts on the anchor bolts of the transmission tower buried in the concrete and ensuring safe operation of the transmission line,a kind of support vector machine(SVM)classification detection method based on an improved northern goshawk optimization(INGO)is proposed in this pa-per.Firstly,Cubic chaotic mapping and pinhole imaging reverse learning strategy are used to increase the diversity of the northern goshawk optimization(NGO)population and,at the same time of optimizing the initial solution,expand the search area of the population,increase the search area for the population and make the algorithm find potential op-timal solutions as much as possible and analyze optimization results.Secondly,INGO is applied to optimize the core parameters of SVM to obtain the classification model.Finally,the screw diameter,protective coating thickness,gas-ket thickness,and the magnetic field strength detected by electromagnetic non-destructive testing are used as the in-put,the number of nuts on the anchor bolt of the screw is output to determine the type of defect.The experimental re-sults show that compared with SVM,the root mean square error,average relative error and average absolute error of the proposed INGO-SVM in the missing anchor bolt and nut classification of transmission tower are reduced by 31.7%,60.7%and 68.9%,respectively.The effectiveness of the method in solving the non-destructive detection and classification problem of missing nuts in foundation bolts is verified.关键词
输电铁塔地脚螺栓/螺母缺失缺陷/改进北方苍鹰优化算法/支持向量机/电磁无损检测Key words
anchor bolts of transmission tower/nut missing defect/improved northern goshawk optimization/support vector machine/electromagnetic non-destructive testing引用本文复制引用
刘阳,张璐,吴德强,周青,张川,王彦海..基于INGO-SVM的输电铁塔地脚螺栓螺母缺失无损检测方法[J].高压电器,2025,61(2):130-140,11.基金项目
国家自然科学基金资助项目(U22A20600,52079070).Project Supported by National Natural Science Foundation of China(U22A20600,52079070). （U22A20600,52079070）
