Affiliations: [a] Korea Electric Power Research Institute, National Lab,
Daejon, Korea. E-mail: darkhosoon@hanmail.net
| [b] Department of Electrical and Computer Engineering,
Chonbuk National University, Jeonju, Korea 561-756. E-mail:
kitchong@chonbuk.ac.kr; hua_su@chonbuk.ac.kr
Correspondence:
[*]
Corresponding author: Professor Kil To Chong, PhD, Department of
Electrical and Computer Engineering, Chonbuk National University, Jeonju, Korea
561-756. Tel.: +82 63 270 2478; Fax: +82 63 270 2451; E-mail:
kitchong@chonbuk.ac.kr
Abstract: Induction motors play an important role in the safe and efficient
operation of industrial plants because they are considered inherently reliable
due to their robust and relatively simple design. Therefore, there is an
indispensable need to monitor their health and performance. And the detection
and diagnosis of motor faults is the base to improve the efficiency of
industrial plants. In this paper, a residual model-based fault detection method
is proposed for steady state vibration signals of induction motors. The
stationary signal had been extracted from the entire signal using data
segmentation. The reference model in spectra is obtained statistically to
represent the healthy condition. The ratio of RMS of residuals is used as a
fault indicator for detecting motor faults. The effectiveness of the proposed
approach in detecting a wide range of mechanical faults is demonstrated through
the experiments applied on an 800 hp motor, and it is shown that a robust and
reliable induction motor fault detection system has been produced.
Keywords: Fault detection, induction motors, vibration signal
