Probability-Relevant Incipient Fault Detection and Diagnosis Methodology With Applications to Electric Drive Systems

By dealing with the crowding problem caused by incipient faults, this brief will develop a new fault detection and diagnosis (FDD) scheme called probability-relevant principal component analysis from the probability view point. The proposed methodology cooperates with Kullback-Leibler divergence fro...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on control systems technology 2019-11, Vol.27 (6), p.2766-2773
Main Authors: Chen, Hongtian, Jiang, Bin, Ding, Steven X., Lu, Ningyun, Chen, Wen
Format: Article
Language:English
Subjects:
Bayes methods
Bayesian analysis
Bayesian inference
Divergence
electric drive systems
Electric drives
False alarms
Fault detection
Fault diagnosis
High speed rail
incipient faults
Kullback–Leibler divergence (KLD)
Machine learning
Mathematical analysis
Multivariate statistical analysis
Principal component analysis
Principal components analysis
probability-relevant principal component analysis (PRPCA)
Statistical analysis
Statistical inference
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!