最大二阶循环平稳指标盲解卷积(maximum second-order cyclostationarity blind deconvolution, CYCBD)能从强背景噪声信号中恢复周期脉冲，是轴承故障诊断的有效方法。故障特征频率是CYCBD的关键参数，由于滚动轴承存在制造误差、滚子滑移等现象，导致真实的故障特征频率与理论值存在偏差，降低了CYCBD的有效性。同时，故障轴承测试信号中含有大量噪声和谐波干扰，也降低了CYCBD的故障特征提取能力。对此，提出了一种基于连续交叉小波相干分析和自适应CYCBD的轴承故障诊断方法，首先，利用正常轴承、故障轴承测试信号的交叉小波相干分析获取轴承故障共振频带。其次，基于三种归一化的周期检测指标提出一种新的周期检测技术以获取真实的轴承故障特征频率。最后，基于轴承故障共振频带信号和真实轴承故障特征频率进行CYCBD滤波，并针对滤波信号进行Teager能量算子解调分析得到能量频谱，从而进行轴承故障诊断。仿真信号和高速列车牵引电机轴承试验信号的分析结果表明：该方法能够有效识别轴承故障特征，且优于传统的CYCBD方法。
Abstract
Maximum second-order cyclostationarity blind deconvolution method (CYCBD), an effective method for bearing fault diagnosis, can recover periodic impulse from strong background noise signals. The fault characteristic frequency is the key parameter of CYCBD, but there are deviations of fault characteristic frequency between the real value and the theoretical value because of manufacturing errors and roller slippage in rolling bearings that reduces the effectiveness of CYCBD. Meanwhile, the test signal of the fault bearing contains a large amount of noise and harmonic interference, which also reduces the fault feature extraction capability of CYCBD. In this regard, a bearing fault diagnosis method based on continuous cross wavelet coherence analysis and adaptive CYCBD was proposed. Firstly, the bearing fault resonance band is obtained using cross-wavelet coherence analysis of the test signals from normal and faulty bearings. Secondly, a new period detection technique based on three normalized period detection indicators is proposed to obtain accurate bearing fault characteristic frequencies. Finally, based on the bearing fault resonance band signal and the real bearing fault characteristic frequency, CYCBD filtering is performed, and Teager energy operator demodulation analysis is performed for the filtered signal to obtain the energy spectrum for bearing fault diagnosis. The analysis results of the simulation signals and the test signals of traction motor bearings in high-speed trains demonstrate that the method can effectively detect the bearing fault and is outperforming the traditional CYCBD method.
关键词
最大二阶循环平稳指标盲解卷积方法 /
连续交叉小波相干分析 /
轴承故障周期检测技术 /
高速列车牵引电机轴承 /
故障诊断
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Key words
maximum second-order cyclostationarity blind deconvolution /
continuous cross wavelet coherence analysis /
fault period detection techniques for bearings /
traction motor bearings in high-speed trains /
fault diagnosis
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