小波理论-近似熵在风机故障诊断中的应用  

A application based on wavelet theory approximate entropy in fault diagnosis method for fan

作　　者：刘金魁[1] 杨育红[1] 

机构地区：[1]山东电力工程咨询院,济南250013

出　　处：《仪器仪表用户》2008年第3期52-54,共3页Instrumentation

摘　　要：风机的振动信号是一种典型的非平稳时变信号,具有混沌特征。提出用小波理论的滤波算法对风机原始振动信号进行降噪处理,用近似熵来定量描述风机的工作状态,进而对风机进行故障诊断。通过对风机不同工作状态下振动信号的分析,结果表明,风机在不同工作状态下所对应的近似熵有明显的变化,小波理论近似熵的方法适用于风机故障的检测。The fan vibration signal is a typical non - stationary time - varied signal with chaotic characteristic. Introduce a threshold filtering algorithm based on the wavelet for reducing noise, approximate entropy to take description quantitatively condition characterizing and fault diagnosis for fan. The fan vibration signals under different working conditions are analyzed. The result shows that the approximate entropy is able to identify the fan different conditions and wavelet approximate entropy theory is suited to detecting fan fault.

关 键 词：小波理论 近似熵 风机 故障诊断 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]