An Integrated Health Condition Detection Method for Rotating Machinery Using Refined Composite Multivariate Multiscale Amplitude-Aware Permutation Entropy

With a view to realizing the fault diagnosis of rotating machinery effectively, an integrated health condition detection approach for rotating machinery based on refined composite multivariate multiscale amplitude-aware permutation entropy (RCmvMAAPE), max-relevance and min-redundancy (mRmR), and wh...

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Veröffentlicht in:	Mathematical problems in engineering 2020, Vol.2020 (2020), p.1-23
Hauptverfasser:	Shen, Jinxing, Feng, Ke, Liu, Wuqiang, Zhou, Fuming, Gong, Peiping
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Amplitudes Artificial neural networks Classifiers Decomposition Efficiency Entropy Fault detection Fault diagnosis Feature extraction Feature recognition Identification methods Machine learning Machinery Methods Multivariate analysis Optimization Optimization algorithms Pattern recognition Permutations Redundancy Rotating machinery Support vector machines Time series
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