Wang Yan, Ye Min, Li Jiabo, Tian Di, Zhang Cuihong, He Yutian
Xi'an Key Laboratory of Wellbore Integrity Evaluation, Xi'an Shiyou University, Xi'an, 710065, China.
Key Laboratory of Expressway Construction Machinery of Shaanxi Province, Chang'an University, Xi'an, 710054, China.
Sci Rep. 2024 Dec 28;14(1):31256. doi: 10.1038/s41598-024-82634-x.
Rolling bearings of the vibration exciter are prone to failure due to long-term high amplitude alternating impact loads, causing economic losses and threatening production safety. The heavy environmental noise during the operation of the vibration exciter and the high vibration level generated by the eccentric block make the weak bearing fault features submerged and difficult to extract. Teager-Kaiser energy operator is a popular method for extracting bearing fault features. However, it has poor noise-robustness and low accuracy of frequency estimation of the exciter with heavy noise and multiple disturbances. Therefore, three enhanced energy operators-symmetric higher-order analytical energy operator (SHAEO), multi-resolution symmetric difference energy operator (MSDAEO), and symmetric higher-order frequency weighted energy operator (SHFWEO) have been introduced. This paper compares and studies the three energy operators through theoretical analysis and vibration exciter bearing fault diagnosis experiments. The results show that MSDAEO has the most outstanding noise robustness, but has the minimum effect on improving the signal-to-interference ratio (SIR) of the signal among the three energy operators. SHFWEO has the most prominent performance on improving SIR but is sensitive to the signal energy. SHAEO can increase the amplitude of the signal, and its ability to improve signal SIR is higher than MSDAEO but lower than SHFWEO. Its ability to improve signal SNR is the weakest among the three. Finally, the characteristics of preprocessing methods that can be jointly used by the three energy operators in different application scenarios are presented.
由于长期承受高幅值交变冲击载荷，振动激振器的滚动轴承容易出现故障，从而造成经济损失并威胁生产安全。振动激振器运行过程中的环境噪声较大，且偏心块产生的振动水平较高，使得轴承微弱故障特征被淹没，难以提取。Teager-Kaiser能量算子是一种常用的提取轴承故障特征的方法。然而，对于噪声较大且存在多种干扰的激振器，它的抗噪声能力较差，频率估计精度较低。因此，引入了三种增强型能量算子——对称高阶解析能量算子（SHAEO）、多分辨率对称差分能量算子（MSDAEO）和对称高阶频率加权能量算子（SHFWEO）。本文通过理论分析和振动激振器轴承故障诊断实验，对这三种能量算子进行了比较研究。结果表明，MSDAEO具有最突出的抗噪声能力，但在这三种能量算子中，其对提高信号干扰比（SIR）的效果最小。SHFWEO在提高SIR方面表现最为突出，但对信号能量敏感。SHAEO可以增大信号幅值，其提高信号SIR的能力高于MSDAEO但低于SHFWEO。在这三种算子中，其提高信号信噪比（SNR）的能力最弱。最后，给出了三种能量算子在不同应用场景下可联合使用的预处理方法的特点。
