A Novel Fault Detection and Identification Framework for Rotating Machinery Using Residual Current Spectrum

A Novel Fault Detection and Identification Framework for Rotating Machinery Using Residual Current Spectrum

A novel framework of model-based fault detection and identification (MFDI) for induction motor (IM)-driven rotating machinery (RM) is proposed in this study. A data-driven subspace identification (SID) algorithm is employed to obtain the IM state-space model from the voltage and current signals in a...

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Bibliographic Details
Main Authors: Widagdo Purbowaskito, Chen-Yang Lan, Kenny Fuh
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Sensors
Subjects:
model-based fault detection
fault identification
induction motors
residual spectrum
subspace identification
Q-function
Online Access:https://www.mdpi.com/1424-8220/21/17/5865

Internet

https://www.mdpi.com/1424-8220/21/17/5865

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