黑龙江科技大学学报2025，Vol.35Issue(2)：329-336,8.DOI:10.3969/j.issn.2095-7262.2025.02.024
基于ARO和TWSVM的高压断路器故障诊断方法
Fault diagnosis method for high voltage circuit breaker based on ARO and TWSVM
摘要
Abstract
This paper describes a study designed to improve the diagnosis performance of the twin support vector machine on the fault state of high voltage circuit breaker and proposes an artificial rabbit algorithm to improve the parameters of the twin support vector machine.The study is enabled by using the wavelet packet improvement threshold method to denoise the vibration signals of the high voltage circuit breaker,extracting a certain number of order intrinsic mode function components by the ensemble empiri-cal modal decomposition,selecting first seven order intrinsic mode function components characterizing the main information of the vibration signals to calculate the feature quantity of the diagnostic model of the sample entropy,optimizing the kernel function parameter and the penalty parameter of the twin support vector machine by the artificial rabbit algorithm;and diagnosing the fault state of the high voltage circuit breaker.The experimental results show that the accuracy rate of the fault diagnosis model proposed in this paper reaches 97.5%,and compared with the twin support vector machine,grey wolf optimized twin support vector machine and other models,its training time is shortest,verifying the better diagnosis re-sults.关键词
高压断路器/故障诊断/振动信号/样本熵/人工兔算法/孪生支持向量机Key words
high voltage circuit breaker/fault diagnosis/vibration signal/sample entropy/artificial rabbit algorithm/twin support vector machine分类
信息技术与安全科学引用本文复制引用
赵岩,徐天,王梓毅..基于ARO和TWSVM的高压断路器故障诊断方法[J].黑龙江科技大学学报,2025,35(2):329-336,8.基金项目
黑龙江省省属高等学校基本科研业务费项目(2021-KYYWF-1476) （2021-KYYWF-1476）
