NDLI: A data-driven and probabilistic approach to residual evaluation for fault diagnosis

Content Provider	IEEE Xplore Digital Library
Author	Svard, Carl Nyberg, Mattias Frisk, Erik Krysander, Mattias
Copyright Year	2011
Description	Author affiliation: Department of Electrical Engineering, University of Linköping, SE-58183 Linkoping, Sweden (Svard, Carl; Nyberg, Mattias; Frisk, Erik; Krysander, Mattias)
Abstract	An important step in fault detection and isolation is residual evaluation where residuals, signals ideally zero in the no-fault case, are evaluated with the aim to detect changes in their behavior caused by faults. Generally, residuals deviate from zero even in the no-fault case and their probability distributions exhibit non-stationary features due to, e.g., modeling errors, measurement noise, and different operating conditions. To handle these issues, this paper proposes a data-driven approach to residual evaluation based on an explicit comparison of the residual distribution estimated on-line and a no-fault distribution, estimated off-line using training data. The comparison is done within the framework of statistical hypothesis testing. With the Generalized Likelihood Ratio test statistic as starting point, a more powerful and computational efficient test statistic is derived by a properly chosen approximation to one of the emerging likelihood maximization problems. The proposed approach is evaluated with measurement data on a residual for diagnosis of the gas-flow system of a Scania truck diesel engine. The proposed test statistic performs well, small faults can for example be reliable detected in cases where regular methods based on constant thresholding fail.
Starting Page	95
Ending Page	102
File Size	443890
Page Count	8
File Format	PDF
ISBN	9781612848006
ISSN	07431546
e-ISBN	9781612848013
e-ISBN	9781612847993
DOI	10.1109/CDC.2011.6160714
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-12
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Noise measurement Maximum likelihood estimation Approximation methods Probability distribution Uncertainty Convex functions Testing
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Modeling and Simulation

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A data-driven and probabilistic approach to residual evaluation for fault diagnosis.

Random convex programs: Dealing with the non-existing solution nuisance

Robust estimation of rotations from relative measurements by maximum likelihood

Maximum likelihood parameter estimation in probabilistic fuzzy classifiers

Analytic center and maximum likelihood estimators

A hybrid method for chance constrained control in uncertain environments

A probabilistic approach to optimal estimation part I: Problem formulation and methodology

Measurement noise distribution as a metric for parameter estimation in dynamical systems

Probabilistic pursuit-evasion games: a one-step Nash approach

A data-driven and probabilistic approach to residual evaluation for fault diagnosis

Similar Documents

A data-driven and probabilistic approach to residual evaluation for fault diagnosis.

Random convex programs: Dealing with the non-existing solution nuisance

Robust estimation of rotations from relative measurements by maximum likelihood

Maximum likelihood parameter estimation in probabilistic fuzzy classifiers

Analytic center and maximum likelihood estimators

A hybrid method for chance constrained control in uncertain environments

A probabilistic approach to optimal estimation part I: Problem formulation and methodology

Measurement noise distribution as a metric for parameter estimation in dynamical systems

Probabilistic pursuit-evasion games: a one-step Nash approach

A data-driven and probabilistic approach to residual evaluation for fault diagnosis