全矢小波包-包络分析方法及其在齿轮故障诊断中的应用

在旋转机械故障诊断中，针对传统单源信息采集的不全面性，提出了一种基于全矢谱技术的小波包-包络分析方法。首先对同源双通道信息分别采用小波包分解，根据需要选择频段的信息，并对提取的信号进行重构。然后采用全矢Hilbert解调分析方法对重构信号实现包络解调，并与两单源信息的包络解调相比较，说明了仅以单源信息为诊断依据的不足。利用全矢谱技术进行融合的全矢小波包-包络解调技术，不仅继承了小波包-包络分析方法的优势，而且更加全面地反映出了信号的真实性。最后通过仿真信号对其算法的可行性进行了验证，同时又以齿轮的故障振动信号为例，进一步表明了该方法在故障诊断中的有效性。

Application of full vector wavelet packet and envelope analysis method in gear fault diagnosis

Aiming at limitations of traditional vibration signal analysis in fault diagnosis of a rotating machinery,an approach of wavelet packet and envelope analysis based on full vector spectrum technology was proposed.Firstly,vibration signals in two different directions were respectively decomposed with wavelet packet transformation,and the Abstracted signals were recomposed.Then,the recomposed signals were processed via envelope demodulation using the full vector Hilbert transformation.Compared to the new method,fault diagnosis method based on single source data was imperfect.The new approach was more effective than others due to its inheritance and all-sided features.Finally,the data fusion of the simulated vibration signals was considered as evidences for verification of the new technique.Furthermore,gearbox vibration signal analysis results showed that the proposed method is effective for diagnosing gear faults.