基于自适应动态猫群优化SVM的PMSM故障诊断方法

doi:10.16182/j.issn1004731x.joss.201711038

系统仿真学报 ›› 2017, Vol. 29 ›› Issue (11): 2881-2889.doi: 10.16182/j.issn1004731x.joss.201711038

基于自适应动态猫群优化SVM的PMSM故障诊断方法

王艳, 汪鑫, 纪志成, 严大虎

江南大学物联网技术应用教育部工程研究中心,无锡 214122

收稿日期:2016-12-08 发布日期:2020-06-05
作者简介:王艳(1978-),女,江苏,博士,副教授,硕导,研究方向为无线传感器网络、制造物联技术、产业协同创新。
基金资助:
国家自然科学基金(61572238),江苏省杰出青年基金(BK20160001),江苏省产学研联合创新资金-前瞻性联合研究项目(BY2016022-24)

Fault Diagnosis Method of PMSM Based on Adaptive Dynamic Cat Swarm Optimization of SVM

Wang Yan, Wang Xin, Ji Zhicheng, Yan Dahu

Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China

Received:2016-12-08 Published:2020-06-05

摘要/Abstract

摘要： 针对永磁同步电机(Permanent Magnet Synchronous Motor,PMSM)常见的匝间短路故障并基于已有的永磁同步电机的基本模型,建立了相应的电机故障模型。利用能量频谱分析提取特征向量。其次,采用自适应动态猫群算法(adaptive dynamic cat swarm optimization,ADACSO)优化SVM的惩罚因子和RBF核函数参数,将优化后的SVM用于电机故障诊断。以能量频谱得到的特征向量作为样本数据来进行仿真实验,结果表明,相对于其他优化算法,采用ADACSO优化SVM参数能够使SVM在永磁同步电机故障诊断中具有更高的诊断精度和准确率。

关键词: 永磁同步电机, 匝间短路故障, 支持向量机, 能量频谱, 自适应动态猫群算法

Abstract: In order to solve the problems of common inter-turn short circuit faults of permanent magnet synchronous motor (PMSM), a corresponding motor fault model based on the existing basis of PMSM is established. The eigenvector is extracted by energy spectrum analysis. The penalty factor and RBF-kernel parameter of SVM are optimized by adaptive dynamic cat swarm optimization (ADACSO) algorithm. The optimized SVM is adopted to motor fault diagnosis. The eigenvector obtained by energy spectrum analysis is taken as sample data to conduct simulation experiment. The experiment results indicate that, compared with other optimization algorithms, using ADACSO to optimize SVM parameters can improve the accuracy of SVM in fault diagnosis of PMSM.

Key words: permanent magnet synchronous motor, inter-turn short circuit fault, support vector machine, energy frequency spectrum, adaptive dynamic cat swarm optimization

中图分类号:

TP18
TM341

王艳, 汪鑫, 纪志成, 严大虎. 基于自适应动态猫群优化SVM的PMSM故障诊断方法[J]. 系统仿真学报, 2017, 29(11): 2881-2889.

Wang Yan, Wang Xin, Ji Zhicheng, Yan Dahu. Fault Diagnosis Method of PMSM Based on Adaptive Dynamic Cat Swarm Optimization of SVM[J]. Journal of System Simulation, 2017, 29(11): 2881-2889.

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基于自适应动态猫群优化SVM的PMSM故障诊断方法

Fault Diagnosis Method of PMSM Based on Adaptive Dynamic Cat Swarm Optimization of SVM

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