Fault Detection and Diagnosis Approach based on Observers and SVD-PCA

Luís Palma; Bruno Ferreira; Paulo Gil; Fernando Coito

doi:10.1109/ICIT.2015.7125106

Fault Detection and Diagnosis Approach based on Observers and SVD-PCA

Luís Palma, Bruno Ferreira, Paulo Gil, Fernando Coito

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this paper, a new combined approach for fault detection and diagnosis (FDD) of abrupt additive actuator and sensor faults, based on Kalman observer (KFO), on sliding mode observers (SMO), on singular values decomposition (SVD), and on principal component analysis (PCA), is proposed. The main contribution is the combined approach proposed for FDD based on ratios between singular values of the adaptive slidingwindow SVD-PCA model and on an improved SMO observer that estimates the faults magnitude. In order to show the performance, simulation results with a DTS-200 benchmark linear model are presented.

Original language	English
Title of host publication	Proceedings of the 2015 IEEE International Conference on Industrial Technology
Place of Publication	Seville, Spain
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	246-251
Number of pages	6
ISBN (Print)	978-1-4799-7800-7
DOIs	https://doi.org/10.1109/ICIT.2015.7125106
Publication status	Published - 2015
Event	2015 IEEE International Conference on Industrial Technology, ICIT 2015 - Seville, Spain Duration: 17 Mar 2015 → 19 Mar 2015

Conference

Conference	2015 IEEE International Conference on Industrial Technology, ICIT 2015
Country/Territory	Spain
City	Seville
Period	17/03/15 → 19/03/15

Keywords

SLIDING MODE OBSERVERS

Access to Document

10.1109/ICIT.2015.7125106Licence: Unspecified

Cite this

@inproceedings{7155780ed1f74fb8acf8035bea857373,

title = "Fault Detection and Diagnosis Approach based on Observers and SVD-PCA",

abstract = "In this paper, a new combined approach for fault detection and diagnosis (FDD) of abrupt additive actuator and sensor faults, based on Kalman observer (KFO), on sliding mode observers (SMO), on singular values decomposition (SVD), and on principal component analysis (PCA), is proposed. The main contribution is the combined approach proposed for FDD based on ratios between singular values of the adaptive slidingwindow SVD-PCA model and on an improved SMO observer that estimates the faults magnitude. In order to show the performance, simulation results with a DTS-200 benchmark linear model are presented.",

keywords = "SLIDING MODE OBSERVERS",

author = "Lu{\'i}s Palma and Bruno Ferreira and Paulo Gil and Fernando Coito",

note = "Sem PDF.; 2015 IEEE International Conference on Industrial Technology, ICIT 2015 ; Conference date: 17-03-2015 Through 19-03-2015",

year = "2015",

doi = "10.1109/ICIT.2015.7125106",

language = "English",

isbn = "978-1-4799-7800-7",

pages = "246--251",

booktitle = "Proceedings of the 2015 IEEE International Conference on Industrial Technology",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

}

Palma, L, Ferreira, B, Gil, P & Coito, F 2015, Fault Detection and Diagnosis Approach based on Observers and SVD-PCA. in Proceedings of the 2015 IEEE International Conference on Industrial Technology., 7125106, Institute of Electrical and Electronics Engineers (IEEE), Seville, Spain, pp. 246-251, 2015 IEEE International Conference on Industrial Technology, ICIT 2015, Seville, Spain, 17/03/15. https://doi.org/10.1109/ICIT.2015.7125106

Fault Detection and Diagnosis Approach based on Observers and SVD-PCA. / Palma, Luís; Ferreira, Bruno; Gil, Paulo et al.
Proceedings of the 2015 IEEE International Conference on Industrial Technology. Seville, Spain: Institute of Electrical and Electronics Engineers (IEEE), 2015. p. 246-251 7125106.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Fault Detection and Diagnosis Approach based on Observers and SVD-PCA

AU - Palma, Luís

AU - Ferreira, Bruno

AU - Gil, Paulo

AU - Coito, Fernando

N1 - Sem PDF.

PY - 2015

Y1 - 2015

N2 - In this paper, a new combined approach for fault detection and diagnosis (FDD) of abrupt additive actuator and sensor faults, based on Kalman observer (KFO), on sliding mode observers (SMO), on singular values decomposition (SVD), and on principal component analysis (PCA), is proposed. The main contribution is the combined approach proposed for FDD based on ratios between singular values of the adaptive slidingwindow SVD-PCA model and on an improved SMO observer that estimates the faults magnitude. In order to show the performance, simulation results with a DTS-200 benchmark linear model are presented.

AB - In this paper, a new combined approach for fault detection and diagnosis (FDD) of abrupt additive actuator and sensor faults, based on Kalman observer (KFO), on sliding mode observers (SMO), on singular values decomposition (SVD), and on principal component analysis (PCA), is proposed. The main contribution is the combined approach proposed for FDD based on ratios between singular values of the adaptive slidingwindow SVD-PCA model and on an improved SMO observer that estimates the faults magnitude. In order to show the performance, simulation results with a DTS-200 benchmark linear model are presented.

KW - SLIDING MODE OBSERVERS

U2 - 10.1109/ICIT.2015.7125106

DO - 10.1109/ICIT.2015.7125106

M3 - Conference contribution

SN - 978-1-4799-7800-7

SP - 246

EP - 251

BT - Proceedings of the 2015 IEEE International Conference on Industrial Technology

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Seville, Spain

T2 - 2015 IEEE International Conference on Industrial Technology, ICIT 2015

Y2 - 17 March 2015 through 19 March 2015

ER -

Fault Detection and Diagnosis Approach based on Observers and SVD-PCA

Abstract

Conference

Keywords

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