基于自相关能量算子解调的旋转机械故障诊断方法

Fault Diagnosis of Rotating Machinery Based on the Autocorrelation Energy Operator Demodulation Approach

旋转机械的故障信号通常呈现出调幅调频特性,早期故障尤为明显,然而由于调制源微弱,且受到噪声的干扰,使得其故障特征难以提取。为此,将自相关变换与能量算子解调法相结合,提出了基于自相关能量算子解调的故障诊断方法。首先,对信号进行自相关变换处理,抑制信号中的噪声成分;然后,用能量算子解调法对信号的自相关函数进行解调,提取故障特征。通过对仿真信号分析和实例分析,结果证明了该方法的有效性;通过与Hilbert解调法的对比,结果证明了该方法优越性。

The fault signal of rotating machinery often shows some AM-FM features, especially in the early stages of the fault.However, fanlt feature were difficult to extract due to the weak modulation source, and disturbed by the noise. To this end, with the autocorrelation transform and energy operator demodulation, presents a fault diagnosis method based on self correlation energy operator demodulation. First of all, using autocorrelation analysis method to reduce the noise in the signal; then, uses the energy operator to demodulate the autocorrelation function, and to extract the fault features. The analysis result of the simulation signal and the experimental signal demonstrates the effectiveness of the method; by comparing with the Hilbert demodulation method, the results prove the superiority of the method.