基于改进SVD和LS-Prony的电机转子断条故障诊断  

Diagnosis of broken rotor bars faults in induction motor using improvedsingular value decomposition and LS-Prony

作　　者：贾朱植 康云娟 祝洪宇[2] 张博[2] 宋向金 Jia Zhuzhi;Kang Yunjuan;Zhu Hongyu;Zhang Bo;Song Xiangjin(Institute of Applied Technology,University of Science and Technology Liaoning,Anshan 114051,China;School of Electronic and Information Engineering,University of Science and Technology Liaoning,Anshan 114051,China;School of Electrical and Information Engineering,Jiangsu University,Zhenjiang 212013,China)

机构地区：[1]辽宁科技大学应用技术学院,鞍山114051 [2]辽宁科技大学电子与信息工程学院,鞍山114051 [3]江苏大学电气信息工程学院,镇江212013

出　　处：《电子测量技术》2025年第3期100-111,共12页Electronic Measurement Technology

基　　金：国家自然科学基金青年基金(52007078);辽宁省教育厅基本科研项目(JYTMS20230946)资助。

摘　　要：采用电机定子电流信号特征分析诊断转子断条故障时,基频两侧的故障特征频率和幅值是判断故障发生与否和严重程度的重要参数。FFT算法的诊断能力严重依赖于所分析的数据长度,最小二乘Prony分析算法虽然具有短时数据分析能力,但是该方法对噪声异常敏感,当电机低频低负载运行时同样存在故障特征提取能力不足和诊断失效的问题。为解决上述问题,提出改进奇异值分解和LS-PA算法相结合的转子断条故障诊断方法。首先采用按列截断方式重构奇异值分解矩阵,根据奇异值差商确定有效阶次,进而对定子电流信号进行预处理以适度抑制噪声,然后运用LS-PA算法对预处理后的信号做故障特征识别和诊断。有限元仿真和实验分析结果表明,所提出的方法能有效抑制电流信号噪声,具有短时数据高分辨率的诊断性能,在工频和变频供电时均能实现电机轻载到满载全工况稳定运行条件下的转子断条故障诊断,诊断性能高于经典的FFT方法。When diagnosing rotor bar faults using motor current signature analysis,the fault characteristic frequencies and amplitudes on both sides of the fundamental frequency are crucial parameters for determining whether a fault has occurred and its severity.The diagnostic capability of FFT algorithm heavily depends on the length of the analyzed data.Although the least squares prony analysis algorithm has short-time data analysis capabilities,it is highly sensitive to noise levels and suffer from insufficient fault feature extraction,and failure may occur when the motor operates at low frequencies and low loads.To address these issues,an improved method combining singular value decomposition and LS-PA algorithms for diagnosing rotor bar faults is proposed.Initially,the SVD matrix is reconstructed using truncated data of original current signal,and effective order is determined based on the difference quotient of singular values.Subsequently,pre-processes technique is used to moderately suppress noise in stator current signal.Finally,the LS-PA algorithm is applied to identify and diagnose fault features from the preprocessed signal.Finite element simulation and experimental results demonstrate that the proposed method can effectively suppress signal noise and has the diagnostic performance of short-time data with high resolution.It achieves stable diagnosis of rotor bar faults under full load conditions,from light to full load,both in constant frequency and variable frequency power supply scenarios,outperforming traditional FFT methods.

关 键 词：故障诊断 奇异值分解 最小二乘Prony算法 电机定子电流信号特征分析 

分 类 号：TH17[机械工程—机械制造及自动化] TN06[电子电信—物理电子学]