Title :
Motor bearing damage detection via wavelet analysis of the starting current transient
Author :
Eren, Levent ; Devaney, Michael J.
Author_Institution :
Missouri Univ., Columbia, MO, USA
Abstract :
Preventive maintenance of induction motors plays an important role in avoiding expensive shut-downs due to motor failures. Motor Current Signature Analysis, MCSA, provides a non-intrusive way to assess the health of a machine. In this paper, the starting current transient of an induction motor is analyzed via discrete wavelet transform to detect bearing faults. The frequency subbands for bearing pre-fault and post-fault conditions are compared to identify the effects of bearing/machine resonant frequencies as the motor starts
Keywords :
condition monitoring; discrete wavelet transforms; induction motors; machine bearings; machine testing; maintenance engineering; signal processing; starting; transient analysis; DWT; bearing faults; bearing post-fault conditions; bearing pre-fault conditions; bearing/machine resonant frequencies; discrete wavelet transform; frequency subbands; induction motors; motor bearing damage detection; motor current signature analysis; starting current transient; wavelet analysis; Condition monitoring; Discrete wavelet transforms; Equations; Fault detection; Frequency; Geometry; Induction motors; Manufacturing industries; Transient analysis; Wavelet analysis;
Conference_Titel :
Instrumentation and Measurement Technology Conference, 2001. IMTC 2001. Proceedings of the 18th IEEE
Conference_Location :
Budapest
Print_ISBN :
0-7803-6646-8
DOI :
10.1109/IMTC.2001.929510
