Process fault diagnosis with model- and knowledge-based approaches: Advances and opportunities

Li, Weijun; Li, Hui; Gu, Sai; Chen, Tao

doi:10.1016/j.conengprac.2020.104637

Cited by 65 publications

(28 citation statements)

References 205 publications

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“…Decision-making response surfaces were built on the basis of methods proposed earlier using a fuzzy inference algorithm [22] for a model-oriented decision support system (Fig. 5, 6).…”

Section: Decision-making Methods To Assess the Impact Of Possible Disturbances On Accident Rate And Performancementioning

confidence: 99%

Improving the ship's power plant automatic control system by using a model-oriented decision support system in order to reduce accident rate under the transitional and dynamic modes of operation

Voytetsky

Voytetskaya

Vyshnevskyi

et al. 2021

EEJET

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This paper proposes a method to improve the performance of a ship's power plant by reducing accidents within it under transitional operating modes. The method is based on decreasing the number of service personnel errors by using a model-oriented decision support system. In order to implement the proposed method, the structure of the system of automatic control of the ship's power plant has been improved. Such an improvement of the control system implied the integration of a modeling unit and a decision support unit into its structure. The modeling unit makes it possible to predict values of the controlled parameters under a transition mode of operation before they actually appear in the system as a result of the operator's actions. A mathematical model of the automatic control system under transitional operating modes has been built for this unit. In order to implement the decision support unit, a method has been devised to formalize the task of managing the power plant under transitional operating modes. The method essentially involves modeling a transitional operating regime, followed by an evaluation of the results based on regulatory requirements and an empirical criterion for assessing the quality of enabling the diesel generators to work in parallel. In addition, a method has been developed for the decision support unit to reduce the accident rate and improve performance with the help of a mathematical apparatus of fuzzy inference, fuzzy logic, and fuzzy sets. Transitional operating regimes resulting from actual erroneous operator actions during ship flights were investigated. As a result of using the proposed system, the power plant performance increases

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“…Decision-making response surfaces were built on the basis of methods proposed earlier using a fuzzy inference algorithm [22] for a model-oriented decision support system (Fig. 5, 6).…”

Section: Decision-making Methods To Assess the Impact Of Possible Disturbances On Accident Rate And Performancementioning

confidence: 99%

Improving the ship's power plant automatic control system by using a model-oriented decision support system in order to reduce accident rate under the transitional and dynamic modes of operation

Voytetsky

Voytetskaya

Vyshnevskyi

et al. 2021

EEJET

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“…There have been many methods of FDD [2], [11], [12] which can be classified into signal-based approaches [13], knowledge-based approaches [12], [14], and process model-based approaches [12], [13] which contain state observer-based method representing an analytical method having achieved several results in this field, and which depends on the mathematical model of the studied system without needing other components. Many publications have been interested in the design of observers for FDD [15]- [24] and have presented fruitful results.…”

Section: Introductionmentioning

confidence: 99%

State and fault estimation based on fuzzy observer for a class of Takagi-Sugeno singular models

Ouarid

Essabre

Assoudi

et al. 2022

IJEECS

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Singular nonlinear systems have received wide attention in recent years, and can be found in various applications of engineering practice. On the basis of the Takagi-Sugeno (T-S) formalism, which represents a powerful tool allowing the study and the treatment of nonlinear systems, many control and diagnostic problems have been treated in the literature. In this work, we aim to present a new approach making it possible to estimate simultaneously both non-measurable states and unknown faults in the actuators and sensors for a class of continuous-time Takagi-Sugeno singular model (CTSSM). Firstly, the considered class of CTSSM is represented in the case of premise variables which are non-measurable, and is subjected to actuator and sensor faults. Secondly, the suggested observer is synthesized based on the decomposition approach. Next, the observer’s gain matrices are determined using the Lyapunov theory and the constraints are defined as linear matrix inequalities (LMIs). Finally, a numerical simulation on an application example is given to demonstrate the usefulness and the good performance of the proposed dynamic system.

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“…The fault diagnosis method is the key to ensure safe and effective operation of the process [ 10 ]. Generally, fault diagnosis methods can be divided into three categories: model-based [ 11 ], knowledge-based [ 12 ], and data-based [ 13 ] methods. Among them, the principal component analysis (PCA) in data-based methods is widely used for process and sensor fault diagnosis in chemical processes [ 14 , 15 ].…”

Section: Introductionmentioning

confidence: 99%

Integrated Diagnostic Framework for Process and Sensor Faults in Chemical Industry

Zhang

Luo

Dai

2021

Sensors

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This study considers the problem of distinguishing between process and sensor faults in nonlinear chemical processes. An integrated fault diagnosis framework is proposed to distinguish chemical process sensor faults from process faults. The key idea of the framework is to embed the cycle temporal algorithm into the dynamic kernel principal component analysis to improve the fault detection speed and accuracy. It is combined with the fault diagnosis method based on the reconstruction-based contribution graph to diagnose the fault variables and then distinguish the two fault types according to their characteristics. Finally, the integrated fault diagnosis framework is applied to the Tennessee Eastman process and acid gas absorption process, and its effectiveness is proved.

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Process fault diagnosis with model- and knowledge-based approaches: Advances and opportunities

Cited by 65 publications

References 205 publications

Improving the ship's power plant automatic control system by using a model-oriented decision support system in order to reduce accident rate under the transitional and dynamic modes of operation

Improving the ship's power plant automatic control system by using a model-oriented decision support system in order to reduce accident rate under the transitional and dynamic modes of operation

State and fault estimation based on fuzzy observer for a class of Takagi-Sugeno singular models

Integrated Diagnostic Framework for Process and Sensor Faults in Chemical Industry

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