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在分析小波变换理论和齿轮振动信号特点的基础上,提出用小波分析法提取齿轮故障特征。齿轮振动信号具有非平稳性,并且受各种噪声干扰,小波分析法具有处理非平稳信号的突出优点。在MATLAB环境中,建立了齿轮振动仿真信号,采用小波函数对受噪声污染的信号进行软阖值消噪处理,通过功率谱分析提取特征频率。仿真表明,该方法可有效抑制噪声,提取特征频率,从而为齿轮故障诊断提供依据。
On the basis of analyzing the characteristics of wavelet transform theory and gear vibration signal, the wavelet analysis method is proposed to extract the characteristics of gear fault. Gear vibration signal with non-stationary, and a variety of noise interference, wavelet analysis has the outstanding advantages of dealing with non-stationary signals. In the MATLAB environment, the simulation signal of gear vibration was established. The wavelet function was used to de-noising the signal contaminated by noise and the characteristic frequency was extracted by power spectrum analysis. The simulation results show that this method can effectively suppress the noise and extract the characteristic frequency, so as to provide the basis for gear fault diagnosis.