局域波近似熵及其在机械故障诊断中的应用

APPLICATION OF LOCAL WAVE APPROXIMATE ENTROPY IN MECHANICAL FAULT DIAGNOSIS

根据信号经局域波分解后所得各基本模式分量的特性,提出了用各分量的近似熵来描述各模式分量的复杂程度,从而量化故障特征。分析结果表明:在相同故障状态下,同一模式分量有相近的近似熵,而在不同故障下,近似熵明显不同,因此近似熵可用于故障的特征提取。转子故障诊断结果表明了该方法的有效性和工程实用性,从而为机械状态监测与故障诊断提供了一种有效途径。

Approximate Entropy is a new concept which can classify complex systems and has many advantages in sigal analysis.Approximate Entropy combining with Local Wave are used in mechanical fault diagnosis.Application indicates that the method described in the paper is a good way to quantify the complexity of signals,and can distiguish different faults.The diagnosis results for faults of a rotorsystem by using this method show the effectiveness and applicability of the proposed method.It provides an useful means for state monitoring and fault diagnosis of machineries.