HYBRID DCA-PCA MULTIPLE FAULTS DIAGNOSIS METHOD

Funa Zhou, Tianhao Tang, Chenglin Wen

2009

Abstract

As it can avoid the pattern compounding problem of PCA, designated component analysis (DCA) can be used to implement multiple fault diagnosis for a multivariate process. But designated fault pattern must be defined in advance, which limited its application in unknown fault diagnosis. In this paper, a hybrid DCA-PCA method is developed for unknown multiple faults diagnosis. the main idea is: Implement DCA in the first step. Removing the designated fault pattern from the observation data, then implement PCA to the residual, and use the first loading vector as the new fault pattern to extend the fault pattern base. In the third step, implement DCA for the new fault pattern and compute the significance of the new fault pattern. Simulation for data involved 4 faults shows the efficiency of the progressive DCA fault diagnosis method.

Paper Citation

in Harvard Style

Zhou F., Tang T. and Wen C. (2009). HYBRID DCA-PCA MULTIPLE FAULTS DIAGNOSIS METHOD . In Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 978-989-8111-99-9, pages 367-370. DOI: 10.5220/0002201103670370

in Bibtex Style

@conference{icinco09,
author={Funa Zhou and Tianhao Tang and Chenglin Wen},
title={HYBRID DCA-PCA MULTIPLE FAULTS DIAGNOSIS METHOD},
booktitle={Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2009},
pages={367-370},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002201103670370},
isbn={978-989-8111-99-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - HYBRID DCA-PCA MULTIPLE FAULTS DIAGNOSIS METHOD
SN - 978-989-8111-99-9
AU - Zhou F.
AU - Tang T.
AU - Wen C.
PY - 2009
SP - 367
EP - 370
DO - 10.5220/0002201103670370