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Open AccessJournal ArticleDOI

A self-validating control system based approach to plant fault detection and diagnosis

Jun Chen, +1 more
- 15 Mar 2001 - 
- Vol. 25, Iss: 2, pp 337-358
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.

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Citations
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Journal ArticleDOI

Application of signed digraphs-based analysis for fault diagnosis of chemical process flowsheets

TL;DR: Two case studies are presented to illustrate SDG-based analysis of process flowsheets containing many units and control loops and it is shown that digraph-based steady-state analysis results in good diagnostic resolution.
Journal ArticleDOI

A Systematic Framework for the Development and Analysis of Signed Digraphs for Chemical Processes. 1. Algorithms and Analysis

TL;DR: In this paper, the authors focus on the systematic development of graph models and the conceptual relationship between the analysis of graph model and the underlying mathematical description and the analysis procedures for the graph model.
Journal ArticleDOI

A Signed Directed Graph and Qualitative Trend Analysis-Based Framework for Incipient Fault Diagnosis

TL;DR: A combined signed directed graph (SDG) and qualitative trend analysis (QTA) framework for incipient fault diagnosis that combines the completeness property of SDG with the high diagnostic resolution property of QTA.
Journal ArticleDOI

A signed directed graph-based systematic framework for steady-state malfunction diagnosis inside control loops

TL;DR: In this paper, a unified SDG model for control loops is discussed, in which both disturbances (sensor bias, etc.) as well as structural faults can be easily modeled under steady-state conditions.
Journal ArticleDOI

A systematic framework for the development and analysis of signed digraphs for chemical processes. 2. Control loops and flowsheet analysis

TL;DR: In this paper, the authors present a signed digraph (SDG) model for control loops and discuss a framework for application of graph-based approaches at a flowsheet level.
References
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Proceedings ArticleDOI

A wavelet theory-based adaptive trend analysis system for process monitoring and diagnosis

TL;DR: W-ASTRA performs process-monitoring and diagnosis and uses the adaptive algorithm for identification of sensor trends and the knowledge base generated by the automated framework for diagnosing fault origins from the identified trends.
Journal ArticleDOI

The possible cause and effect graphs (PCEG) model for fault diagnosis—I. Methodology

TL;DR: A new model of diagnostic reasoning called the “possible cause-effect graphs” (PCEG) model is proposed, and can be viewed as a generalization of the signed digraph model of process diagnosis.
Journal ArticleDOI

Integral approach to plant linear dynamic reconciliation

TL;DR: In this paper, an integral method is proposed that performs dynamic data reconciliation on linear systems, in contrast with recent methods that utilize differential algebraic equations, in which the differential equations representing this system are first rearranged to obtain a system of equations containing only redundant measurements.
Journal ArticleDOI

Manufacturing performance enhancement through multivariate statistical process control

TL;DR: In this article, the concept of process performance monitoring through an industrial application to a fluidized bed-reactor and a comprehensive simulation of a batch methyl methacrylate polymerization reactor is presented.
Journal ArticleDOI

Application of wavelets and neural networks to diagnostic system development, 2, an integrated framework and its application

TL;DR: An integrated framework combining wavelet feature extraction and an unsupervised neural network for identification of operational states is described and application of the system to a refinery residual fluid catalytic cracking process is presented.
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