Content Provider	IEEE Xplore Digital Library
Author	Li, Qiaochu Jauberthie, Carine Denis-Vidal, Lilianne Cherfi, Zohra
Copyright Year	2015
Description	Author affiliation: Sorbonne University, Université de Technologie de Compiègne, 60 203 cedex, France (Li, Qiaochu; Denis-Vidal, Lilianne; Cherfi, Zohra) \|\| LAAS, CNRS, 7 avenue du Colonel Roche, France Université de Toulouse, UPS, F-31400, France (Jauberthie, Carine)
Abstract	Through parameter estimation schemes, one could be able to detect, localize and identify the occurring fault via simple computation. Yet, certain faults may not be discovered even be mistaken in a normal condition with unknown noises by trend checking or state monitoring. A more informative way when a correct model is present to analyses the data via parameter estimation. In this paper, we propose by using interval analysis a diagnosis scheme, from which we can extract the guaranteed diagnostic results to inform the supervisor so that appropriate actions could be taken. Sending them the results in a guaranteed way to tell the diagnostician which kind of fault exist is firstly taken care in diagnosis context. Our original fault detection and localization procedure has been firstly proposed in an interval analysis context for the constant fault in parameters. Moreover, another new technique in parameter estimation is the distance check, which speed up the estimation procedure. Some drawbacks have been discussed in the end.
Starting Page	330
Ending Page	335
File Size	626612
Page Count	6
File Format	PDF
ISBN	9789897581496
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-21
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	SCITEPRESS
Subject Keyword	Context Fault diagnosis Parameter Estimation Analytical models Parameter estimation Nonlinear Systems Computational modeling Fault detection Estimation Interval Analysis Diagnosis
Content Type	Text
Resource Type	Article

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