基于信息熵的涡旋压缩机故障诊断研究  

Study on the Fault Diagnosis for Scroll Compressor Based on Information Entropy

作　　者：刘涛[1] 黄成东[1] 

机构地区：[1]兰州理工大学机电工程学院,甘肃兰州730050

出　　处：《压缩机技术》2012年第1期1-4,8,共5页Compressor Technology

基　　金：国家自然科学基金资助项目(编号50965011);甘肃省自然科学基金资助项目(编号1014RJZA025);甘肃省高等学校基本科研业务费项目

摘　　要：为了定量描述涡旋压缩机运行状态,在状态特征提取的基础上,从振动信号分析的思路出发,结合信息论中熵和灰关联度的理论,建立了一种基于时域的奇异谱熵、频域的功率谱熵、时-频域小波能量谱熵和小波空间特征谱熵的故障诊断方法,并作为综合评价涡旋压缩机振动状态的定量特征指标,可实现对涡旋压缩机几种故障的较好识别,证明了该故障诊断方法的有效性。In order to make a quantitative description for the running status of the scroll compressor, on the basis of the state feature extraction, in view of the notion of vibration signal analysis, combined with the theory of en- tropy and grey incidence degrees in information theory, the paper sets up a fault diagnosis method of information entropy which based on singular spectrum entropy in time domain, power spectrum entropy in frequency domain, wavelet power spectrum entropy and wavelet space feature spectrum entropy in time - frequency domain, which is used as the comprehensive appraisal index of quantitative feature for the scroll compressor＇s vibrational status. An instance proves that the method is effective and can be able to identify several kinds of fault state of scroll compressor well

关 键 词：涡旋压缩机 信息熵 灰关联度 故障诊断 

分 类 号：TH455[机械工程—机械制造及自动化]