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Journal Article

Fault Diagnosis Techniques for Dynamic Systems

TL;DR: A novel classification framework is proposed, which divides fault diagnosis approaches into two classes: qualitative analysis approaches and quantitative analysis approaches, with emphasis on the data-driven approaches.
About: This article is published in Acta Automatica Sinica.The article was published on 2009-01-01 and is currently open access. It has received 37 citations till now. The article focuses on the topics: Fault (power engineering).
Citations
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Journal ArticleDOI
TL;DR: In this article, the authors presented a mathematical problems in engineering journal Mathematical Problems in Engineering (MPIE), where the authors proposed a method to solve the problem of solving the problem.
Abstract: Published version of an article from the journal: Mathematical Problems in Engineering. Also available from the publisher:http://dx.doi.org/10.1155/2012/832836

134 citations

Journal ArticleDOI
TL;DR: A novel method for diagnosing faults using fault tree analysis and Bayesian networks (BN) to optimize system diagnosis and a diagnostic decision tree (DDT) was generated to guide the maintenance personnel to repair the system.

49 citations


Cites background from "Fault Diagnosis Techniques for Dyna..."

  • ...A new classification framework for fault diagnosis was proposed in [1], which divided fault diagnosis approaches into qualitative analysis approaches and quantitative analysis approaches....

    [...]

Journal ArticleDOI
TL;DR: A probabilistic fault diagnosis approach of SIS is presented, a hybrid approach based on fault tree analysis (FTA) and Bayesian network (BN) that will generate a diagnosis map that will be useful to guide repair actions.
Abstract: Safety instrumented systems (SISs) are used in the oil and gas industry to detect the onset of hazardous events and/or to mitigate their consequences to humans, assets, and environment. A relevant problem concerning these systems is failure diagnosis. Diagnostic procedures are then required to determine the most probable source of undetected dangerous failures that prevent the system to perform its function. This paper presents a probabilistic fault diagnosis approach of SIS. This is a hybrid approach based on fault tree analysis (FTA) and Bayesian network (BN). Indeed, the minimal cut sets as the potential sources of SIS failure were generated via qualitative analysis of FTA, while diagnosis importance factor of components was calculated by converting the standard FTA in an equivalent BN. The final objective is using diagnosis data to generate a diagnosis map that will be useful to guide repair actions. A diagnosis aid system is developed and implemented under SWI-Prolog tool to facilitate testing and diagnosing of SIS.

35 citations


Cites background from "Fault Diagnosis Techniques for Dyna..."

  • ...A classification for fault diagnosis was proposed by [10]; it considers qualitative and quantitative approaches which combine limited objective data and expert knowledge....

    [...]

Journal ArticleDOI
TL;DR: The results show that the established prediction model and the presented parameters optimization methods can deal with fault prediction problem effectively.
Abstract: In order to deal with fault prediction problems that involve both quantitative and qualitative information for nonlinear complex system, a new fault prediction model is established based on the evidential reasoning (ER) approach, and an optimal learning algorithm for training ER-based prediction model is presented based on the mean square error (MSE) criterion. This prediction model inherits the advantages of ER approach, which can deal with precise data, incomplete data and fuzzy data with nonlinear characteristic. In this model, the input signals transformed using rule based information transformation technique, are aggregated by analytical ER approach, and then the outputs of prediction model are constructed according to the types of system outputs. In addition, two fault decision criteria are defined to conduct fault identification. To overcome the difficulty in determining model parameters accurately and subjectively, a nonlinear optimization model is constructed and the optimal parameters are obtained. Two experimental studies are conducted to evaluate the performance of the proposed model. The results show that the established prediction model and the presented parameters optimization methods can deal with fault prediction problem effectively.

25 citations

Journal ArticleDOI
TL;DR: This article investigates weak thruster fault detection problem for autonomous underwater vehicle subject to the external disturbances and demonstrates the effectiveness of the developed method based on the combination of artificial immune system and single pre-processing.
Abstract: This article investigates weak thruster fault detection problem for autonomous underwater vehicle subject to the external disturbances. A weak thruster fault detection method is developed based on ...

21 citations


Cites background or methods from "Fault Diagnosis Techniques for Dyna..."

  • ...Nowadays, the fault diagnosis methods can be classified into qualitative diagnosis and quantitative diagnosis.(10) In the quantitative diagnosis methods, it includes dynamic model–based diagnosis and data-driven-based...

    [...]

  • ...diagnosis.(10) Since it does not need an accurate AUV dynamic model, the data-driven-based fault diagnosis has attracted an increasing number of researchers’ attention....

    [...]

  • ...Since it does not need an accurate AUV dynamic model, the data-driven-based fault diagnosis has attracted an increasing number of researchers’ attention.(10) Fault diagnosis method was proposed based on discrete wavelet transformation and neural network....

    [...]

References
More filters
Journal ArticleDOI
TL;DR: In this article, the authors presented a mathematical problems in engineering journal Mathematical Problems in Engineering (MPIE), where the authors proposed a method to solve the problem of solving the problem.
Abstract: Published version of an article from the journal: Mathematical Problems in Engineering. Also available from the publisher:http://dx.doi.org/10.1155/2012/832836

134 citations

Journal ArticleDOI
TL;DR: A novel method for diagnosing faults using fault tree analysis and Bayesian networks (BN) to optimize system diagnosis and a diagnostic decision tree (DDT) was generated to guide the maintenance personnel to repair the system.

49 citations

Journal ArticleDOI
TL;DR: A probabilistic fault diagnosis approach of SIS is presented, a hybrid approach based on fault tree analysis (FTA) and Bayesian network (BN) that will generate a diagnosis map that will be useful to guide repair actions.
Abstract: Safety instrumented systems (SISs) are used in the oil and gas industry to detect the onset of hazardous events and/or to mitigate their consequences to humans, assets, and environment. A relevant problem concerning these systems is failure diagnosis. Diagnostic procedures are then required to determine the most probable source of undetected dangerous failures that prevent the system to perform its function. This paper presents a probabilistic fault diagnosis approach of SIS. This is a hybrid approach based on fault tree analysis (FTA) and Bayesian network (BN). Indeed, the minimal cut sets as the potential sources of SIS failure were generated via qualitative analysis of FTA, while diagnosis importance factor of components was calculated by converting the standard FTA in an equivalent BN. The final objective is using diagnosis data to generate a diagnosis map that will be useful to guide repair actions. A diagnosis aid system is developed and implemented under SWI-Prolog tool to facilitate testing and diagnosing of SIS.

35 citations

Journal ArticleDOI
TL;DR: The results show that the established prediction model and the presented parameters optimization methods can deal with fault prediction problem effectively.
Abstract: In order to deal with fault prediction problems that involve both quantitative and qualitative information for nonlinear complex system, a new fault prediction model is established based on the evidential reasoning (ER) approach, and an optimal learning algorithm for training ER-based prediction model is presented based on the mean square error (MSE) criterion. This prediction model inherits the advantages of ER approach, which can deal with precise data, incomplete data and fuzzy data with nonlinear characteristic. In this model, the input signals transformed using rule based information transformation technique, are aggregated by analytical ER approach, and then the outputs of prediction model are constructed according to the types of system outputs. In addition, two fault decision criteria are defined to conduct fault identification. To overcome the difficulty in determining model parameters accurately and subjectively, a nonlinear optimization model is constructed and the optimal parameters are obtained. Two experimental studies are conducted to evaluate the performance of the proposed model. The results show that the established prediction model and the presented parameters optimization methods can deal with fault prediction problem effectively.

25 citations

Journal ArticleDOI
TL;DR: This article investigates weak thruster fault detection problem for autonomous underwater vehicle subject to the external disturbances and demonstrates the effectiveness of the developed method based on the combination of artificial immune system and single pre-processing.
Abstract: This article investigates weak thruster fault detection problem for autonomous underwater vehicle subject to the external disturbances. A weak thruster fault detection method is developed based on ...

21 citations