Saidi Lotfi, Ali Jaouher Ben, Fnaiech Farhat
University of Tunis, Tunis National Higher School of Engineering (ENSIT), Laboratory of Signal Image and Energy Mastery (SIME), 5 avenue Taha Hussein, PO Box 56, 1008 Tunis, Tunisia.
University of Tunis, Tunis National Higher School of Engineering (ENSIT), Laboratory of Signal Image and Energy Mastery (SIME), 5 avenue Taha Hussein, PO Box 56, 1008 Tunis, Tunisia.
ISA Trans. 2014 Sep;53(5):1650-60. doi: 10.1016/j.isatra.2014.06.002. Epub 2014 Jun 26.
Empirical mode decomposition (EMD) has been widely applied to analyze vibration signals behavior for bearing failures detection. Vibration signals are almost always non-stationary since bearings are inherently dynamic (e.g., speed and load condition change over time). By using EMD, the complicated non-stationary vibration signal is decomposed into a number of stationary intrinsic mode functions (IMFs) based on the local characteristic time scale of the signal. Bi-spectrum, a third-order statistic, helps to identify phase coupling effects, the bi-spectrum is theoretically zero for Gaussian noise and it is flat for non-Gaussian white noise, consequently the bi-spectrum analysis is insensitive to random noise, which are useful for detecting faults in induction machines. Utilizing the advantages of EMD and bi-spectrum, this article proposes a joint method for detecting such faults, called bi-spectrum based EMD (BSEMD). First, original vibration signals collected from accelerometers are decomposed by EMD and a set of IMFs is produced. Then, the IMF signals are analyzed via bi-spectrum to detect outer race bearing defects. The procedure is illustrated with the experimental bearing vibration data. The experimental results show that BSEMD techniques can effectively diagnosis bearing failures.
经验模态分解（EMD）已被广泛应用于分析振动信号行为以检测轴承故障。由于轴承本质上是动态的（例如，速度和负载条件随时间变化），振动信号几乎总是非平稳的。通过使用EMD，复杂的非平稳振动信号基于信号的局部特征时间尺度被分解为多个平稳的固有模态函数（IMF）。双谱作为一种三阶统计量，有助于识别相位耦合效应，双谱对于高斯噪声理论上为零，对于非高斯白噪声则是平坦的，因此双谱分析对随机噪声不敏感，这对于检测感应电机中的故障很有用。利用EMD和双谱的优势，本文提出了一种用于检测此类故障的联合方法，称为基于双谱的EMD（BSEMD）。首先，通过EMD对从加速度计收集的原始振动信号进行分解，生成一组IMF。然后，通过双谱对IMF信号进行分析以检测外圈轴承缺陷。该过程通过实验轴承振动数据进行说明。实验结果表明，BSEMD技术可以有效地诊断轴承故障。
