A mathematical framework for new fault detection schemes in nonlinear stochastic continuous-time dynamical systems

Zufiria Zatarain, Pedro Jose (2012). A mathematical framework for new fault detection schemes in nonlinear stochastic continuous-time dynamical systems. "Applied Mathematics and Computation", v. 218 (n. 23); pp. 11391-11403. ISSN 0096-3003. https://doi.org/10.1016/j.amc.2012.05.024.

Description

Title: A mathematical framework for new fault detection schemes in nonlinear stochastic continuous-time dynamical systems
Author/s:
  • Zufiria Zatarain, Pedro Jose
Item Type: Article
Título de Revista/Publicación: Applied Mathematics and Computation
Date: August 2012
ISSN: 0096-3003
Volume: 218
Subjects:
Freetext Keywords: Fault diagnosis; Continuous-time dynamical systems; Quickest detection; Ornstein–Uhlenbeck stochastic process
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Matemática Aplicada a las Tecnologías de la Información [hasta 2014]
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

n this work, a mathematical unifying framework for designing new fault detection schemes in nonlinear stochastic continuous-time dynamical systems is developed. These schemes are based on a stochastic process, called the residual, which reflects the system behavior and whose changes are to be detected. A quickest detection scheme for the residual is proposed, which is based on the computed likelihood ratios for time-varying statistical changes in the Ornstein–Uhlenbeck process. Several expressions are provided, depending on a priori knowledge of the fault, which can be employed in a proposed CUSUM-type approximated scheme. This general setting gathers different existing fault detection schemes within a unifying framework, and allows for the definition of new ones. A comparative simulation example illustrates the behavior of the proposed schemes.

More information

Item ID: 16809
DC Identifier: http://oa.upm.es/16809/
OAI Identifier: oai:oa.upm.es:16809
DOI: 10.1016/j.amc.2012.05.024
Official URL: http://www.sciencedirect.com/science/article/pii/S0096300312005097
Deposited by: Memoria Investigacion
Deposited on: 11 Aug 2013 08:05
Last Modified: 21 Apr 2016 17:10
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