An Automatic Bearing Fault Diagnosis Method Based on Characteristics Frequency Ratio

Sensors

Jianwen Wang¹  Tian He¹  Lin Lai²  Hongxing Liu²  Hong Wang²  Dengyun Wu³  Tao Xie³ 

[1] School of Transportation Science and Engineering, Beijing 100191, China;Science and Technology on Space Intelligent Control Laboratory, Beijing Key Laboratory of Long-life Technology of Precise Rotation and Transmission Mechanisms, Beijing Institute of Control Engineering, Beijing 100194, China;State Key Laboratory of Robotics and System, Harbin Institute of Technology, Harbin 150001, China;

关键词: rolling bearings;    automatic fault diagnosis;    envelope analysis;    characteristics frequency ratio;    ensemble empirical mode decomposition;   

DOI  :  10.3390/s20051519

来源: DOAJ

【 摘 要 】

Bearing is a key component of satellite inertia actuators such as moment wheel assemblies (MWAs) and control moment gyros (CMGs), and its operating state is directly related to the performance and service life of satellites. However, because of the complexity of the vibration frequency components of satellite bearing assemblies and the small loading, normal running bearings normally present similar fault characteristics in long-term ground life experiments, which makes it difficult to judge the bearing fault status. This paper proposes an automatic fault diagnosis method for bearings based on a presented indicator called the characteristic frequency ratio. First, the vibration signals of various MWAs were picked up by the bearing vibration test. Then, the improved ensemble empirical mode decomposition (EEMD) method was introduced to demodulate the envelope of the bearing signals, and the fault characteristic frequencies of the vibration signals were acquired. Based on this, the characteristic frequency ratio for fault identification was defined, and a method for determining the threshold of fault judgment was further proposed. Finally, an automatic diagnosis process was proposed and verified by using different bearing fault data. The results show that the presented method is feasible and effective for automatic monitoring and diagnosis of bearing faults.

【 授权许可】

Unknown