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YE Dapeng
College of Mechanical & Electronic
Engineering,
Fujian Agriculture and Forestry
University,
Fuzhou 350002, China
DING Qiquan
Mechatronic Engineering Department, Ningbo Institute of
Technology,
Zhejiang University,
Ningbo 315000, China
WU Zhaotong
Institute of Contemporary Manufacturing Engineering,
Zhejiang University,
Hangzhou 310027, China |
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2D-HIDDEN MARKOV MODEL
FEATURE EXTRACTION STRATEGY
OF ROTATING MACHINERY
FAULT DIAGNOSIS*
Abstract:
A new feature extraction method based on 2D-hidden Markov model(HMM) is proposed. Meanwhile the time index and frequency index are introduced to represent the new features. The new feature extraction strategy is tested by the experimental data that collected from Bently rotor experiment system. The results show that this methodology is very effective to extract the feature of vibration signals in the rotor speed-up course and can be extended to other non-stationary signal analysis fields in the future.
Key words:
Fault diagnosis Rotating machinery 2D-hidden Markov model(HMM) Feature extraction
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