Fault Diagnosis Research of Bearing in Unstable Operation Combining with Order Tracking and Dual-tree Complex Wavelet
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摘要: 风力发电机、转炉等设备常工作于变速工况下，滚动轴承作为设备的重要零部件之一，在非稳定运行时，传统的FFT分析存在"频率混叠"现象，难以提取有效的故障特征信息，故提出阶次跟踪和双树复小波相结合的故障诊断方法。首先运用阶次跟踪将非平稳的时域振动信号转化为平稳的角域信号，再应用双树复小波降低角域信号的信噪比，最后进行阶次谱分析，从而实现对滚动轴承在非稳定运行时的故障特征识别。通过仿真和实验数据分析，验证了该方法的可行性和有效性。Abstract: The wind turbine and converter often operate under the condition of variable speed, the traditional FFT analysis of rolling bearings which is one of the important parts of the equipment causes frequency aliasing during the variable speed operation, and it is difficult to extract the effective fault feature information. Therefore, a new failure diagnosis method of rolling bearings which combines order tracking and dual-tree complex wavelet is proposed in this paper. First, the order tracking is used to transform the non-stationary time domain vibration signal into a stationary angular domain signal, and then the dual-tree complex wavelet transforms is used to reduce the noise-signal ratio of the angular domain signal. Finally, the order spectrum analysis is carried out to recognize the fault feature of the rolling bearing in the unstable operation. The feasibility and effectiveness of the method are verified by simulation and experimental data analysis.
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Key words:
- order tracking /
- dual-tree complex wavelet /
- rolling bearing /
- wavelet transforms /
- order spectrum /
- fault diagnosis /
- vibration
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