Jing Tian a, Michael Pecht a, and Changning Li b
aCenter for Advanced Life Cycle Engineering (CALCE), University of Maryland, College Park, MD 20742, USA
bCenter for Prognostics and System Health Management City University, Hong Kong, China
The failure of rotating machinery sometimes involves several faulty components. Existence of both bearing fault and gearbox fault is widely observed and in this situation the vibration feature of the bearing fault can be masked by the faulty gearbox vibration signals. In this research, a method is proposed based on wavelet packet transform and envelope analysis to extract fault features of the rolling element bearing from the masking faulty gearbox signals. Wavelet packet of the test signal containing bearing fault information is selected by correlation analysis and the fault feature is extracted by envelope analysis. Case study shows that the proposed method can detect the outer race fault in a rolling element bearing from the masking signals of a gearbox with worn teeth. Compared with exist methods, the proposed method does not require gearbox fault information, and it reduces the amount of sensors.
Complete Article is available from the publisher and to CALCE consortium members.