Sun Peng, Liao Yuhe, Lin Jin
Shaanxi Key Laboratory of Mechanical Product Quality Assurance and Diagnostics, Xi'an Jiaotong University, Xi'an 710049, China.
State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Sensors (Basel). 2017 Mar 8;17(3):535. doi: 10.3390/s17030535.
The properties of the time domain parameters of vibration signals have been extensively studied for the fault diagnosis of rolling element bearings (REBs). Parameters like kurtosis and Envelope Harmonic-to-Noise Ratio are the most widely applied in this field and some important progress has been made. However, since only one-sided information is contained in these parameters, problems still exist in practice when the signals collected are of complicated structure and/or contaminated by strong background noises. A new parameter, named Shock Pulse Index (SPI), is proposed in this paper. It integrates the mutual advantages of both the parameters mentioned above and can help effectively identify fault-related impulse components under conditions of interference of strong background noises, unrelated harmonic components and random impulses. The SPI optimizes the parameters of Maximum Correlated Kurtosis Deconvolution (MCKD), which is used to filter the signals under consideration. Finally, the transient information of interest contained in the filtered signal can be highlighted through demodulation with the Teager Energy Operator (TEO). Fault-related impulse components can therefore be extracted accurately. Simulations show the SPI can correctly indicate the fault impulses under the influence of strong background noises, other harmonic components and aperiodic impulse and experiment analyses verify the effectiveness and correctness of the proposed method.
振动信号时域参数的特性已在滚动轴承故障诊断中得到广泛研究。峰度和包络谐波信噪比等参数在该领域应用最为广泛，并取得了一些重要进展。然而，由于这些参数仅包含单方面信息，当采集到的信号结构复杂和/或受到强背景噪声污染时，在实际应用中仍存在问题。本文提出了一种名为冲击脉冲指数（SPI）的新参数。它综合了上述两个参数的优点，能够在强背景噪声、无关谐波分量和随机脉冲干扰的情况下，有效地识别与故障相关的脉冲分量。SPI对最大相关峭度解卷积（MCKD）的参数进行了优化，用于对所考虑的信号进行滤波。最后，通过Teager能量算子（TEO）解调，可以突出滤波后信号中包含的感兴趣的瞬态信息。因此，可以准确提取与故障相关的脉冲分量。仿真表明，SPI能够在强背景噪声、其他谐波分量和非周期脉冲的影响下正确指示故障脉冲，实验分析验证了所提方法的有效性和正确性。
