形态分量分析在转子早期碰摩故障诊断中的应用

提出了一种基于形态分量分析的转子早期碰摩故障诊断方法,该方法用形态分量分析从转子早期碰摩故障信号中提取出冲击成分。形态分量分析根据信号中各组成成分的形态差异,构建不同的稀疏表示字典对各组成成分进行分离。当转子系统中出现早期碰摩时,其振动信号往往由以转频及其谐波为主要成分的周期成分、包含转子早期碰摩故障信息的冲击成分及随机噪声构成。周期成分表现为信号中的平滑部分,而冲击成分则表现为信号中的细节部分,因此,可根据周期成分与冲击成分的形态差异,用形态分量分析实现二者的分离。对形态分量分析的阈值方法进行了改进,提出了基于半软阈值的形态分量分析,仿真结果表明,基于半软阈值的形态分量分析要优于基于硬阈值的形态分量分析。对某转子早期碰摩故障信号进行了分析,结果表明,基于半软阈值的形态分量分析能有效地提取转子早期碰摩故障信号中的冲击成分,进而诊断转子早期碰摩故障。

Early Rub-impact Diagnosis of Rotors Using Morphological Component Analysis

A new method for the fault diagnosis of early rub-impact of a rotor by using morphological component analysis(MCA) is proposed in this paper. The proposed method uses MCA to extract impulses from vibration signals of a rotor with early rub-impact fault. According to the morphological difference of each component in the signal, different sparse dictionaries are built by MCA to separate each component from the signal. When the early rub-impact occuring in a rotor system, the vibration signal is often composed of periodic signal with rotor frequency component and its harmonics,transient impulse signal with rotor fault information and random noise. Periodic signals represent the smooth part of the signal, while impulse signals represent the detail part of the signal, therefore, the two kinds of signals can be separated according its morphological difference. Though the improvement of threshold method of MCA, the MCA based on semisoft shrinkage is proposed. The simulation result shows that the MCA based on semisoft shrinkage is superior to the MCA based on hard threshold. Analysis result of the vibration signal of early rub-impact of a rotor shows that the MCA based on semisoft shrinkage is effective in extracting impulse component from the vibration signal of early rub-impact of a rotor, and diagnosis the fault of early rub-impact of a rotor.