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Application of power spectrum, cepstrum, higher order spectrum and neural network analyses for induction motor fault diagnosis
B. Liang
, S. D. Iwnicki, Y. Zhao
Department of Engineering and Technology
School of Computing and Engineering
Centre for Efficiency and Performance Engineering
Research output
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Contribution to journal
›
Article
›
peer-review
103
Citations (Scopus)
Overview
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Engineering & Materials Science
Power spectrum
100%
Induction motors
85%
Failure analysis
79%
Neural networks
56%
Fourier transforms
45%
Condition monitoring
24%
Spectrum analysis
23%
Signal processing
18%
Decomposition
16%
Engines
14%
Experiments
8%