L2,s-norm and L2,p-norm distance metrics regularized deep belief network for fault diagnosis

An accurate and efficient fault detection model based on deep belief network (DBN) in this paper is proposed for rotating machinery. Due to the overlapping problem of different class features extracted by traditional networks, a L 2 , s -norm and L 2 , p -norm distance metrics regularized DBN for in...

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Veröffentlicht in:	Nonlinear dynamics 2023-11, Vol.111 (21), p.20217-20235
Hauptverfasser:	Ji, Zhulin, Zhang, Shunhua, Dong, Hanlin
Format:	Artikel
Sprache:	eng
Schlagworte:	Automotive Engineering Belief networks Classical Mechanics Clustering Control Dynamical Systems Engineering Fault detection Fault diagnosis Feature extraction Mechanical Engineering Optimization Original Paper Rotating machinery Vibration
Online-Zugang:	Volltext
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