Comments on the applicability of “An improved weighted recursive PCA algorithm for adaptive fault detection”-Reference-Cited by-同舟云学术

Comments on the applicability of “An improved weighted recursive PCA algorithm for adaptive fault detection”

Published:2017-01 Issue: Volume:58 Page:254-255
ISSN:0967-0661
Container-title:Control Engineering Practice
language:en
Short-container-title:Control Engineering Practice

Author:

Quiñones-Grueiro Marcos,Verde Cristina

Funder

Mexican Government Scholarship Program

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering

Reference11 articles.

1. Isolation enhanced principal component analysis;Gertler;AIChE Journal,1999

2. Henley, E. J., (1984). Application of expert systems to fault diagnosis. In AIChE annual meeting. San Francisco, California.

3. Fault-diagnosis applications: model-based condition monitoring: actuators, drives, machinery, plants, sensors, and fault-tolerant systems;Isermann,2011

4. Adaptive process monitoring using efficient recursive PCA and moving window PCA algorithms;Jeng;Journal of the Taiwan Institute of Chemical Engineers,2010

5. Recursive {PCA} for adaptive process monitoring;Li;Journal of Process Control,2000

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