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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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.
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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.
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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.
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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.
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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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Formulation of linear data reconciliation using information theory
TL;DR: In this paper, the authors reformulated linear data reconciliation by maximizing the information entropy to obtain probability distributions of the data with the minimum incorporation of prior knowledge, and then the reconciled measurements are obtained by maximum likelihood, subject to the process constraints.
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Structuring diagnostic knowledge for large-scale process systems
TL;DR: In this article, a set of guidelines for generating an initial organization of knowledge for distributed diagnosis of a process plant is described, where the diagnostic knowledge is organized hierarchically by primary processing systems (commonly feed, reaction, and separation in chemical plants), subsystems, components, behaviors and malfunction modes.
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Robust fault diagnosis based on clustered symptom trees
TL;DR: In this article, a new methodology for fault diagnosis, based on the signed digraph (SDG), was proposed in developing the fault-diagnostic system of a boiler plant, which uses a new model, the clustered symptom tree (CST).
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An industrial application of an on-line data reconciliation and optimization problem
TL;DR: In this article, a three years project on the installation in an Olefins Plant of an on-line Optimizer is described in some details for the following items: Plant Modeling, Plant Constraints, Plant Measures, Data Reconciliation, On-Online Optimization, Numerical Approaches and Results.
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On the Performance of Principal Component Analysis in Multiple Gross Error Identification
TL;DR: In this article, the authors used principal component analysis (PCA) for the identification stage of three existing collective compensation strategies: UBET, SEGE, and SICC.