小波包结合希尔伯特变换的轴承故障诊断

Bearing Fault Diagnosis Based on Wavelet Packet and Hilbert

针对小波包络解调法在轴承故障诊断中,当轴承故障加深时,频段选择不当对诊断结果干扰较大,为解决该问题,提出了一种小波包能量谱结合希尔伯特变换的方法对轴承故障特征进行提取。使用小波包变换对信号进行分解、重构。对重构后的信号进行小波包能量谱分析得出能量较集中的节点,提取该节点对应的频段信号,并通过希尔伯特变换对相应频段进行包络分析诊断出轴承故障。以实验室实测信号故障轴承数据为对象分析,验证了结合小波包能量谱结合希尔伯特变换准确地识别轴承故障类型。

In bearing fault diagnosis using wavelet envelope demodulation method,when the bearing fault deepens,improper selection of frequency bands will greatly interfere with the diagnosis results.To solve this problem,this paper proposes a method of wavelet packet energy spectrum combined with Hilbert transform to extract bearing fault features.The signal is decomposed and reconstructed using the wavelet packet transform.The wavelet packet energy spectrum analysis is performed on the reconstructed signal to obtain the node with more concentrated energy,the frequency band signal corresponding to the node is extracted,and the corresponding frequency band is analyzed by Hilbert transform to diagnose the bearing fault.Taking the fault bearing data measured in the laboratory as the object,it is verified that the combination of wavelet packet energy spectrum and Hilbert transform can accurately identify the bearing fault type.