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

Volume

3

fYear

2001

fDate

2001

Firstpage

1797

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference, 2001. IMTC 2001. Proceedings of the 18th IEEE

Conference_Location

Budapest

ISSN

1091-5281

Print_ISBN

0-7803-6646-8

Type

conf

DOI

10.1109/IMTC.2001.929510

Filename

929510