NDLI: Diagnosis of sensor failure detection and information rebuilding using Polynomial Chaos Theory

Content Provider	IEEE Xplore Digital Library
Author	Huimin Li Monti, A.
Copyright Year	2009
Description	Author affiliation: Dept. of Electr. Eng., Univ. of South Carolina, Columbia, SC, USA (Huimin Li) \|\| E.ON Energy Res. Center, RWTH Aachen Univ., Aachen, Germany (Monti, A.)
Abstract	A new strategy applying polynomial chaos theory (PCT) to diagnose sensor failure is presented in this paper. Using PCT and uncertainty of parameters, the original state space model of a system is expanded to PCT domain. Variations of sensor output due to parameter uncertainty are calculated by a PCT estimator and presented as PCT output boundaries based on the probability density function (PDF) of uncertain parameters. Along with PCT boundaries, an algorithm is used to diagnose and declare failed sensors. Meanwhile, outputs of failed sensors are frozen and missing information is rebuilt with best-case estimations from PCT estimator. Effectiveness of this method is also verified with two examples.
Sponsorship	IEEE Instrum. Meas. Soc.
Starting Page	753
Ending Page	758
File Size	568791
Page Count	6
File Format	PDF
ISBN	9781424433520
ISSN	10915281
DOI	10.1109/IMTC.2009.5168551
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-05
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Polynomials Chaos Equations Uncertainty Uncertain systems Intelligent sensors Artificial intelligence Analytical models Stochastic systems State-space methods stochastic differential equations uncertain systems induction motor drive
Content Type	Text
Resource Type	Article
Subject	Instrumentation Electrical and Electronic Engineering

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