Detection of Incipient Process Faults using Approximate Parametric Models
Search citation statements
Paper Sections
Citation Types
Year Published
Publication Types
Relationship
Authors
Journals
Cited by 3 publications
References 5 publications
Aquesta tesi tracta sobre la metodologia del raonament inductiu difús (FIR, de l’anglès fuzzy inductive reasoning) aplicada a sistemes de detecció i diagnòstic de fallades. La metodologia FIR sorgeix de l’enfocament del general systems problem solver (GSPS) proposat per Klir l’any 1989 i és una eina per analitzar i estudiar els modes de comportament dels sistemes dinàmics. FIR és una metodologia de modelització i simulació qualitativa de sistemes basada principalment en l’observació del comportament del sistema. Aquesta metodologia ha anat evolucionant al llarg del temps amb l'objectiu d'ampliar la classe de problemes que es poden abordar amb FIR. El treball desenvolupat en aquesta tesi té el propòsit de contribuir a reduir els esforços de modelització i simulació de sistemes industrials reals complexos. En aquesta línia, s’ha aconseguit augmentar, mitjançant diferents aportacions, la robustesa de FIR i desenvolupar una nova metodologia que permeti crear sistemes de detecció i diagnòstic de fallades robustos i eficients. L’objectiu principal d’aquesta tesi és reduir tant com sigui possible la sensibilitat de la metodologia FIR, és a dir, maximitzar-ne la robustesa, de manera que esdevingui una eina cabdal per desenvolupar sistemes de detecció i diagnòstic de fallades eficients. Les contribucions principals de la tesi són: •Incrementar la robustesa del FIR creant una nova eina, anomenada Visual-FIR, que permet identificar models i predir comportaments futurs de sistemes dinàmics en un entorn molt senzill d’utilitzar i molt eficient. •Desenvolupar una nova metodologia per crear sistemes de detecció i diagnòstic de fallades basats en FIR. S’ha desenvolupat una tècnica de detecció, anomenada envolupant, i una mesura per al diagnòstic, anomenada mesura d’acceptabilitat del model, que han permès millorar i fer més sòlids els processos de detecció i diagnòstic de fallades del FIRFDDS (sistema de detecció i diagnòstic de fallades basat en FIR). •Desenvolupar una eina que permeti crear de manera senzilla i altament eficient FIRFDDS per a aplicacions específiques. S’ha desenvolupat una plataforma, anomenada VisualBlock-FIR, que permet que l’usuari creï, d’una manera senzilla, sistemes de detecció i diagnòstic de fallades basats en el FIR. Per validar la metodologia i les eines desenvolupades es mostren un parell de casos d’estudi. El primer correspon al problema de referència de la vàlvula automàtica de Damadics, en què es proposen quatre fallades de petita i mitjana magnitud que es detecten i s’aïllen/s’identifiquen d’una manera molt ràpida i eficient. En el segon es posa a prova el VisualBlock-FIR en una pila de combustible simulada a la qual s’apliquen cinc fallades diferents, les quals són detectades i identificades correctament. Finalment, es comprova la robustesa afegint soroll blanc, en diferents magnituds, a les sortides de la pila de combustible. This thesis deals with the Fuzzy Inductive Reasoning (FIR) methodology applied to fault detection and diagnosis systems. FIR, based on the General Systems Problem Solver (GSPS) proposed by Klir in 1989, is a methodological tool for data-driven construction of dynamical systems and for studying their conceptual modes of behavior. FIR is a qualitative modeling and simulation methodology that is based on observation of the input¿output behavior of the system to be modeled, rather than on structural knowledge about its internal composition. This methodology has evolved over time with the aim of enlarging the class of problems that can be dealt with by FIR. The work presented in this thesis aims to contribute to reducing modeling and simulation efforts of real industrial complex systems. Several methodological contributions have been made to increase FIR robustness as well as to develop a new methodology to create robust and efficient fault detection and diagnosis systems. The main objective of this thesis is to reduce as much as possible the sensitivity of the FIR methodology, by maximizing its robustness, in such a way that it becomes a fundamental tool for developing efficient fault detection and diagnosis systems. The main contributions of this thesis are: ¿To improve the robustness of FIR by creating a new tool, Visual-FIR, that identifies patterns and predicts future behavior of dynamical systems in a very efficient and simple to use environment. ¿To develop a new methodology for creating fault detection and diagnosis systems based on FIR. We have developed a detection technique, the enveloping, and a diagnosis measure, known as the acceptability measure, that allow improving and making more robust the fault detection and diagnosis processes of the FIRFDDS (fault detection and diagnosis system based on FIR). ¿To develop a tool that allows to easily create highly efficient FIRFDDS for specific applications. A platform, named VisualBlock-FIR, has been developed that allows the user to create, in a simple way, fault detection and diagnosis systems based on FIR. In order to validate the methodological contributions and the developed tools a couple of case studies have been presented in this dissertation. The first corresponds to the benchmark problem of the Damadics automatic valve system, which proposes four failures of small and medium sizes that are detected and isolated / identified in a quick and highly efficient way. The second is a simulated fuel cell where five different faults are applied. The five faults are detected and identified correctly. Finally, we check the robustness of the FIRFDDS by adding white noise, at different magnitudes, to the outputs of the fuel cell. Manresa
Aquesta tesi tracta sobre la metodologia del raonament inductiu difús (FIR, de l’anglès fuzzy inductive reasoning) aplicada a sistemes de detecció i diagnòstic de fallades. La metodologia FIR sorgeix de l’enfocament del general systems problem solver (GSPS) proposat per Klir l’any 1989 i és una eina per analitzar i estudiar els modes de comportament dels sistemes dinàmics. FIR és una metodologia de modelització i simulació qualitativa de sistemes basada principalment en l’observació del comportament del sistema. Aquesta metodologia ha anat evolucionant al llarg del temps amb l'objectiu d'ampliar la classe de problemes que es poden abordar amb FIR. El treball desenvolupat en aquesta tesi té el propòsit de contribuir a reduir els esforços de modelització i simulació de sistemes industrials reals complexos. En aquesta línia, s’ha aconseguit augmentar, mitjançant diferents aportacions, la robustesa de FIR i desenvolupar una nova metodologia que permeti crear sistemes de detecció i diagnòstic de fallades robustos i eficients. L’objectiu principal d’aquesta tesi és reduir tant com sigui possible la sensibilitat de la metodologia FIR, és a dir, maximitzar-ne la robustesa, de manera que esdevingui una eina cabdal per desenvolupar sistemes de detecció i diagnòstic de fallades eficients. Les contribucions principals de la tesi són: •Incrementar la robustesa del FIR creant una nova eina, anomenada Visual-FIR, que permet identificar models i predir comportaments futurs de sistemes dinàmics en un entorn molt senzill d’utilitzar i molt eficient. •Desenvolupar una nova metodologia per crear sistemes de detecció i diagnòstic de fallades basats en FIR. S’ha desenvolupat una tècnica de detecció, anomenada envolupant, i una mesura per al diagnòstic, anomenada mesura d’acceptabilitat del model, que han permès millorar i fer més sòlids els processos de detecció i diagnòstic de fallades del FIRFDDS (sistema de detecció i diagnòstic de fallades basat en FIR). •Desenvolupar una eina que permeti crear de manera senzilla i altament eficient FIRFDDS per a aplicacions específiques. S’ha desenvolupat una plataforma, anomenada VisualBlock-FIR, que permet que l’usuari creï, d’una manera senzilla, sistemes de detecció i diagnòstic de fallades basats en el FIR. Per validar la metodologia i les eines desenvolupades es mostren un parell de casos d’estudi. El primer correspon al problema de referència de la vàlvula automàtica de Damadics, en què es proposen quatre fallades de petita i mitjana magnitud que es detecten i s’aïllen/s’identifiquen d’una manera molt ràpida i eficient. En el segon es posa a prova el VisualBlock-FIR en una pila de combustible simulada a la qual s’apliquen cinc fallades diferents, les quals són detectades i identificades correctament. Finalment, es comprova la robustesa afegint soroll blanc, en diferents magnituds, a les sortides de la pila de combustible. This thesis deals with the Fuzzy Inductive Reasoning (FIR) methodology applied to fault detection and diagnosis systems. FIR, based on the General Systems Problem Solver (GSPS) proposed by Klir in 1989, is a methodological tool for data-driven construction of dynamical systems and for studying their conceptual modes of behavior. FIR is a qualitative modeling and simulation methodology that is based on observation of the input¿output behavior of the system to be modeled, rather than on structural knowledge about its internal composition. This methodology has evolved over time with the aim of enlarging the class of problems that can be dealt with by FIR. The work presented in this thesis aims to contribute to reducing modeling and simulation efforts of real industrial complex systems. Several methodological contributions have been made to increase FIR robustness as well as to develop a new methodology to create robust and efficient fault detection and diagnosis systems. The main objective of this thesis is to reduce as much as possible the sensitivity of the FIR methodology, by maximizing its robustness, in such a way that it becomes a fundamental tool for developing efficient fault detection and diagnosis systems. The main contributions of this thesis are: ¿To improve the robustness of FIR by creating a new tool, Visual-FIR, that identifies patterns and predicts future behavior of dynamical systems in a very efficient and simple to use environment. ¿To develop a new methodology for creating fault detection and diagnosis systems based on FIR. We have developed a detection technique, the enveloping, and a diagnosis measure, known as the acceptability measure, that allow improving and making more robust the fault detection and diagnosis processes of the FIRFDDS (fault detection and diagnosis system based on FIR). ¿To develop a tool that allows to easily create highly efficient FIRFDDS for specific applications. A platform, named VisualBlock-FIR, has been developed that allows the user to create, in a simple way, fault detection and diagnosis systems based on FIR. In order to validate the methodological contributions and the developed tools a couple of case studies have been presented in this dissertation. The first corresponds to the benchmark problem of the Damadics automatic valve system, which proposes four failures of small and medium sizes that are detected and isolated / identified in a quick and highly efficient way. The second is a simulated fuel cell where five different faults are applied. The five faults are detected and identified correctly. Finally, we check the robustness of the FIRFDDS by adding white noise, at different magnitudes, to the outputs of the fuel cell. Manresa
The main purpose of this paper is to emphasize the particularities of models needed for modelbased fault detection and isolation (FDI) in contrast to the models used for control. Of special interest is the question of complexity of the model, which is of great importance for the practical implementation. This, of course, depends basically on the given situation such as the kind of plant, the measurements, the kind and number of faults to be detected and the demands for fault isolation and robustness. However, the paper shows that diagnostic models, in contrast to the wide-spread opinion that those have always to be more complex than the functional models for control, may be even less complex, because they are restricted to only those parts of the system in which the faults occur. The issue of model complexity is discussed in terms of different model-based FDI approaches ± analytical, knowledge-based and data-based. The ideas are illustrated in a case study, where several types of model-based FDI techniques are compared with the same plant, the amira three tank system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
Contact Info
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Product
Resources
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.
