A self-validating control system based approach to plant fault detection and diagnosis
Jun Chen,John Howell +1 more
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TLDR
In this paper, an approach is proposed in which fault detection and diagnosis (FDD) tasks are distributed to separate FDD modules associated with each control system located throughout a plant.About:
This article is published in Computers & Chemical Engineering.The article was published on 2001-03-15 and is currently open access. It has received 31 citations till now. The article focuses on the topics: Control reconfiguration & Fault detection and isolation.read more
Citations
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Journal ArticleDOI
Integrated Framework of Probabilistic Signed Digraph Based Fault Diagnosis Approach to a Gas Fractionation Unit
TL;DR: An integrated implementation solution and theoretical framework of fault diagnosis approach based on probabilistic signed digraph (PSDG) is proposed and applied to a gas fractionation unit and the qualitative ambiguities in PSDG can be reduced to so...
Proceedings ArticleDOI
Application of Signed Directed Graph Based Fault Diagnosis of Atmospheric Distillation Unit
TL;DR: The results prove that the SDG based fault diagnosis and decision support system can not only arrive at the fundamental requirement of diagnosis: correctness, completeness and real-timed, but also provide decision support for operators to decrease the possibility of unscheduled shut-down or more serious accident due to abnormal situation.
Journal ArticleDOI
A Sequential Bayesian Partitioning Approach for Online Steady-State Detection of Multivariate Systems
TL;DR: A novel joint monitoring approach, where the multivariate signal is sequentially partitioned into segments of constant mean and covariance through an online Bayesian inference scheme, and once the current segment duration is sufficiently large, the signal is considered steady.
Proceedings Article
State estimation and fault diagnosis of industrial process by using of particle filters
TL;DR: A probabilistic approach to state estimation and fault diagnosis in complex industrial processes is presented and a Jump Markov Linear Gaussian model is adapted to describe a continuous stirred tank reactor.
Proceedings ArticleDOI
An Efficient Method for Online Identification of Steady State for Multivariate System
TL;DR: The article proposes an efficient online method for multivariate steady state detection that estimates the covariance matrices using two different approaches, namely, the mean-squared-deviation and mean-Squared-successive-difference and can accurately detect the steady state of a multivariate system.
References
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Modern Control Systems
Richard C. Dorf,Naresh K. Sinha +1 more
TL;DR: This book presents a control engineering methodology that, while based on mathematical fundamentals, stresses physical system modeling and practical control system designs with realistic system specifications.
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Qualitative process theory
TL;DR: This paper describes the basic concepts of qualitative process theory, several different kinds of reasoning that can be performed with them, and discusses its implications for causal reasoning.
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A qualitative physics based on confluences
Johan de Kleer,John Seely Brown +1 more
TL;DR: A fairly encompassing account of qualitative physics, which introduces causality as an ontological commitment for explaining how devices behave, and presents algorithms for determining the behavior of a composite device from the generic behavior of its components.
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Statistical Process Control of Multivariate Processes
TL;DR: An overview of multivariate statistical methods use for the statistical process control of both continuous and batch multivariate processes and examples are provided of their use for analysing the operations of a mineral processing plant, for on-line monitoring and fault diagnosis of a continuous polymerization process and for the on- line monitoring of an industrial batch polymerization reactor.
Journal ArticleDOI
Assessment of control loop performance
TL;DR: In this article, an estimate of the best possible control can be obtained by fitting a univariate time series to process data collected under routine control, and the use of this technique is demonstrated with pilot plant and production data.