基于多尺度线调频基稀疏信号分解的广义解调方法及其在齿轮故障诊断中的应用

Generalized Demodulation Method Based on Multi-scale Chirplet and Sparse Signal Decomposition and Its Application to Gear Fault Diagnosis

在基于多尺度线调频基稀疏信号分解的基础上,提出一种基于多尺度线调频基稀疏信号分解的广义解调方法,并将其应用于非平稳转速状态下的齿轮故障诊断。广义解调可以将时频分布呈曲线变化的多分量非平稳信号转化为时频分布平行于时间轴的平稳信号,因此非平稳信号经广义解调后满足傅里叶分析对平稳性的要求,而如何获取多分量信号的广义解调相位函数是广义解调方法的关键和难点。对信号进行基于多尺度线调频基的稀疏信号分解,得到分量信号的相位函数,再对分量信号进行广义解调和频谱分析得到齿轮故障特征频率。该方法非常适合于分析转速波动齿轮的多分量调幅—调频振动信号,仿真算例和应用实例说明了方法对变速齿轮箱故障诊断的有效性。

On the basis of multi-scale chirplet and sparse signal decomposition, a new method of generalized demodulation is proposed to be applied to the fault diagnosis of gear in a state of non-stationary rotating speed. The method of generalized demodulation can transform multi-component and non-stationary signals with time-frequency distribution consisting of curves into stationary signals with time-frequency distribution consisting of linear lines which are parallel to the time-axis. So after the implementation of generalized demodulation, the signals satisfy the standard of stationary demand in FFT analysis. The key point in generalized demodulation is how to obtain the phase functions of the multi-component signals. Through the sparse signal decomposition based on multi-scale chirplet of the signal, phase functions of the component signals are acquired and then generalized demodulation and frequency analysis are adopted to get the fault feature frequency components. The proposed method is suitable to analyze the multi-component AM - FM signals which fluctuate with the rotating speed. A simulation example and an example of its application prove the effectiveness of the method applied to fault diagnosis of the gearbox with rotating speed fluctuation.