黑龙江科技大学学报2024，Vol.34Issue(1)：125-131,7.DOI:10.3969/j.issn.2095-7262.2024.01.019
基于XALO-SVM的同步电机转子绕组匝间短路故障诊断方法
Fault diagnosis method for inter-turn short circuit in rotor windings of synchronous motor based on XALO-SVM
摘要
Abstract
This paper aims to improve the detectability of interturn short circuit fault in dynamic winding and proposes a new method for early fault detection of interturn short circuit in rotor winding of synchronous motor.By analyzing rotor data of synchronous motor,combined with grey correlation degree and principal component analysis method,the approach works by developing a model of antlion algorithm and support vector machine;exacting the key fault data as input variables of the support vector machine model;optimizing the key parameters of SVM algorithm by using the improved antlion algorithm;and ver-ifying the fault diagnosis mode by fault data.The results show that the diagnosis accuracy of the fault di-agnosis model based on XALO-SVM can reach over 97%,and the diagnosis time is shortened,which provides technical support for fault detection.关键词
同步电机/蚁狮算法/支持向量机/故障诊断Key words
synchronous motor/ant lion algorithm/support vector machine/fault diagnosis分类
信息技术与安全科学引用本文复制引用
付强..基于XALO-SVM的同步电机转子绕组匝间短路故障诊断方法[J].黑龙江科技大学学报,2024,34(1):125-131,7.基金项目
黑龙江省教育厅高等教育教改项目(SJGY20210775) （SJGY20210775）
