摘要
在异步电动机发生转子断条故障时,定子电流中会出现(1-2s)f频率分量,以此作为故障特征频率分量,但相对于基频f,其幅值较小且靠近基频,容易被淹没。本文采用的一种基于小波包分解与单节点重构改进算法,可以突出故障特征频率分量(1-2s)f,避免基频影响。仿真和实验结果均表明,该方法能够准确地诊断出电机转子断条故障。
When rotor bar breaking of asynchronous motor occurred, frequency components ( 1-2s )f regarded as tault feature frequency were appeared in the stator current.However, when it is relative to the tundamental frequency f, its amplitude is small and close to the fundamental frequency easily be drowned. An improved algorithm of wavelet packet decomposition and reconstruction of single node which can highlight the fault feature frequency components ( 1-2s)f and avoid the influence of fundamental frequency was used in this paper. The results of simulation and experiments showed that the method can accurately diagnose rotor bar breaking fault.
出处
《电测与仪表》
北大核心
2012年第8期1-4,50,共5页
Electrical Measurement & Instrumentation
基金
国家科技支撑计划资助项目(2008BAB36B09)
关键词
异步电动机
转子断条
小波包
asynchronous motor, rotor bar breaking, wavelet packet