摘要
电机电流信号特征分析(MCSA)是诊断鼠笼电机早期转子断条故障的常用方法。当电机在时变转速状态下运行时,转速和滑差连续变化,定子电流表现为非平稳信号,MCSA不再有效。本文提出一种鼠笼电机时变转速运行状态下的早期转子断条故障诊断新方法。该方法的核心是对定子电流Park矢量模平方信号作离散小波变换,然后根据转子断条故障特征频率2sf在转速连续变化期间的波形演变图谱以及小波能量变化判断故障发生与否。在3k W电机实验台上对所提出的方法进行实验验证,实验结果证实了所提方法的有效性。
Motor current signature analysis (MCSA) has been successfully used in squirrel cage motor for the diagnosis of incipient broken rotor bar defect. However, when the motor operates in time-varying rotating speed condition, the method fails as the rotating speed and slip vary, thus, the stator current is characterized as a non-stationary signal. This paper proposes a novel fault diagnosis method for the incipient broken rotor bar of squirrel cage motor in time-varying rotating speed operation condition. The core of the method is to conduct discrete wavelet transformation on the 3 phase stator current Park' s vector modulus square signal; and according to the waveform evolution spectrum of broken rotor bar fault frequency 2sf characteristic pattern and the wavelet energy changing during the speed continuous variation, it is judged if the broken rotor bar defect occurs. The experiment verification was performed on a 3kw motor experiment test bench; the experiment results prove the effectiveness of the proposed method.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2016年第4期834-842,共9页
Chinese Journal of Scientific Instrument
基金
中国科学院重点部署项目(KGZD-EW-302)资助
关键词
鼠笼电机
转子断条
Park矢量模
离散小波变换
故障诊断
squirrel cage motor
broken rotor bar
Park's vector modulus
discrete wavelet transformation (DWT)
fault diagnosis