Reconstruction-based Contribution for Process Monitoring with Kernel Principal Component Analysis

Carlos F. ALCALA; S. Joe QIN

doi:10.1109/acc.2010.5531315

Reconstruction-based Contribution for Process Monitoring with Kernel Principal Component Analysis

Carlos F. ALCALA^*, S. Joe QIN

^*Corresponding author for this work

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Referred Conference Paper › peer-review

16 Citations (Scopus)

Abstract

This paper presents a new method for fault diagnosis based on kernel principal component analysis (KPCA). The proposed method uses reconstruction-based contributions (RBC) to diagnose simple and complex faults in nonlinear principal component models based on KPCA. Similar to linear PCA, a combined index, based on the weighted combination of the Hotelling's T² and SPE indices, is proposed. Control limits for these fault detection indices are proposed using second order moment approximation. The proposed fault detection and diagnosis scheme is tested with a simulated CSTR process where simple and complex faults are introduced. The simulation results show that the proposed fault detection and diagnosis methods are efective for KPCA. © 2010 AACC.

Original language	English
Title of host publication	Proceedings of the 2010 American Control Conference
Publisher	Institute of Electrical and Electronics Engineers
Pages	7022-7027
Number of pages	6
ISBN (Electronic)	9781424474271
ISBN (Print)	9781424474264
DOIs	https://doi.org/10.1109/acc.2010.5531315
Publication status	Published - Jun 2010
Externally published	Yes
Event	2010 American Control Conference, ACC 2010 - Baltimore, United States Duration: 30 Jun 2010 → 2 Jul 2010

Publication series

Name	Proceedings of the American Control Conference
Publisher	Institute of Electrical and Electronics Engineers
ISSN (Print)	0743-1619
ISSN (Electronic)	2378-5861

Conference

Conference	2010 American Control Conference, ACC 2010
Country/Territory	United States
City	Baltimore
Period	30/06/10 → 2/07/10

Access to Document

10.1109/acc.2010.5531315

Cite this

@inproceedings{b7a69e76dc634c52b654da3082059817,

title = "Reconstruction-based Contribution for Process Monitoring with Kernel Principal Component Analysis",

abstract = "This paper presents a new method for fault diagnosis based on kernel principal component analysis (KPCA). The proposed method uses reconstruction-based contributions (RBC) to diagnose simple and complex faults in nonlinear principal component models based on KPCA. Similar to linear PCA, a combined index, based on the weighted combination of the Hotelling's T2 and SPE indices, is proposed. Control limits for these fault detection indices are proposed using second order moment approximation. The proposed fault detection and diagnosis scheme is tested with a simulated CSTR process where simple and complex faults are introduced. The simulation results show that the proposed fault detection and diagnosis methods are efective for KPCA. {\textcopyright} 2010 AACC.",

author = "ALCALA, {Carlos F.} and QIN, {S. Joe}",

year = "2010",

month = jun,

doi = "10.1109/acc.2010.5531315",

language = "English",

isbn = "9781424474264",

series = "Proceedings of the American Control Conference",

publisher = "Institute of Electrical and Electronics Engineers",

pages = "7022--7027",

booktitle = "Proceedings of the 2010 American Control Conference",

note = "2010 American Control Conference, ACC 2010 ; Conference date: 30-06-2010 Through 02-07-2010",

}

ALCALA, CF & QIN, SJ 2010, Reconstruction-based Contribution for Process Monitoring with Kernel Principal Component Analysis. in Proceedings of the 2010 American Control Conference., 5531315, Proceedings of the American Control Conference, Institute of Electrical and Electronics Engineers, pp. 7022-7027, 2010 American Control Conference, ACC 2010, Baltimore, Maryland, United States, 30/06/10. https://doi.org/10.1109/acc.2010.5531315

Reconstruction-based Contribution for Process Monitoring with Kernel Principal Component Analysis. / ALCALA, Carlos F.; QIN, S. Joe.
Proceedings of the 2010 American Control Conference. Institute of Electrical and Electronics Engineers, 2010. p. 7022-7027 5531315 (Proceedings of the American Control Conference).

Research output: Book Chapters | Papers in Conference Proceedings › Conference paper (refereed) › Referred Conference Paper › peer-review

TY - GEN

T1 - Reconstruction-based Contribution for Process Monitoring with Kernel Principal Component Analysis

AU - ALCALA, Carlos F.

AU - QIN, S. Joe

PY - 2010/6

Y1 - 2010/6

N2 - This paper presents a new method for fault diagnosis based on kernel principal component analysis (KPCA). The proposed method uses reconstruction-based contributions (RBC) to diagnose simple and complex faults in nonlinear principal component models based on KPCA. Similar to linear PCA, a combined index, based on the weighted combination of the Hotelling's T2 and SPE indices, is proposed. Control limits for these fault detection indices are proposed using second order moment approximation. The proposed fault detection and diagnosis scheme is tested with a simulated CSTR process where simple and complex faults are introduced. The simulation results show that the proposed fault detection and diagnosis methods are efective for KPCA. © 2010 AACC.

AB - This paper presents a new method for fault diagnosis based on kernel principal component analysis (KPCA). The proposed method uses reconstruction-based contributions (RBC) to diagnose simple and complex faults in nonlinear principal component models based on KPCA. Similar to linear PCA, a combined index, based on the weighted combination of the Hotelling's T2 and SPE indices, is proposed. Control limits for these fault detection indices are proposed using second order moment approximation. The proposed fault detection and diagnosis scheme is tested with a simulated CSTR process where simple and complex faults are introduced. The simulation results show that the proposed fault detection and diagnosis methods are efective for KPCA. © 2010 AACC.

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U2 - 10.1109/acc.2010.5531315

DO - 10.1109/acc.2010.5531315

M3 - Conference paper (refereed)

SN - 9781424474264

T3 - Proceedings of the American Control Conference

SP - 7022

EP - 7027

BT - Proceedings of the 2010 American Control Conference

PB - Institute of Electrical and Electronics Engineers

T2 - 2010 American Control Conference, ACC 2010

Y2 - 30 June 2010 through 2 July 2010

ER -

Reconstruction-based Contribution for Process Monitoring with Kernel Principal Component Analysis

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