Average Accumulative Based Time Variant Model for Early Diagnosis and Prognosis of Slowly Varying Faults

Average Accumulative Based Time Variant Model for Early Diagnosis and Prognosis of Slowly Varying Faults

Early detection of slowly varying small faults is an essential step for fault prognosis. In this paper, we first propose an average accumulative (AA) based time varying principal component analysis (PCA) model for early detection of slowly varying faults. The AA based method can increase the fault s...

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Bibliographic Details
Main Authors: Funa Zhou, Ju H. Park, Chenglin Wen, Po Hu
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:Sensors
Subjects:
early detection
fault prognosis
RUL prediction
average accumulative
error correction
Online Access:http://www.mdpi.com/1424-8220/18/6/1804

Internet

http://www.mdpi.com/1424-8220/18/6/1804

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