Process Decomposition and Test Selection for Distributed Fault Diagnosis

Chanthery, Élodie; Sztyber, Anna; Travé-Massuyès, Louise; Pérez-Zúñiga, Gustavo

doi:10.1007/978-3-030-55789-8_78

Cited by 5 publications

(3 citation statements)

References 15 publications

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“…In future work, there is interest in investigating the double problem of choosing the system decomposition and diagnosis tests while minimizing inter-subsystem communication and maximizing diagnosability. A preliminary proposal along these lines is presented in [51]. Additionally, the impact of different inter-level communication constraints on the diagnosis results should be analyzed.…”

Section: Discussionmentioning

confidence: 99%

Near-Optimal Decentralized Diagnosis via Structural Analysis

Pérez-Zúñiga

Chanthery

Travé-Massuyès

et al. 2022

IEEE Trans. Syst. Man Cybern, Syst.

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Health monitoring of current complex systems significantly impacts the total cost of the system. Centralized fault diagnosis architectures are sometimes prohibitive for large-scale interconnected systems such as distribution systems, telecommunication networks, water distribution networks or fluid power systems. Confidentiality constraints are also an issue. This paper presents a decentralized fault diagnosis method that only requires the knowledge of local models and limited knowledge of their neighboring subsystems. The method, implemented in the Decentralized Diagnoser Design (D 3 ) algorithm, is based on structural analysis and can advantageously be applied to high dimensional systems, linear or non-linear. Using the concept of isolation on request, a hierarchy is built according to diagnostic objectives. The resulting diagnoser is based on analytical redundancy relations generated along the hierarchy. Their number is optimized via binary integer linear programming while still guaranteeing maximal diagnosability at each level. D 3 proves of lower time complexity than its centralized equivalent. It is successfully applied to a non-linear combined cycle gas turbine power plant.

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Section: Discussionmentioning

confidence: 99%

Near-Optimal Decentralized Diagnosis via Structural Analysis

Pérez-Zúñiga

Chanthery

Travé-Massuyès

et al. 2022

IEEE Trans. Syst. Man Cybern, Syst.

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“…In the structural analysis (SA) (Blanke et al, 2015;Krysander, 2006;Frisk and Krysander, 2007;Travé-Massuyés et al, 2006;Chanthery et al, 2020;Jung, 2020) the system is modelled as a set of components.…”

Section: 2mentioning

confidence: 99%

A graph theory-based approach to the description of the process and the diagnostic system

Kościelny,

Bartyś,

Syfert

et al. 2022

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The paper proposes an original, comprehensive, and methodically consistent graph theory-based approach to the description of the diagnosed process and the diagnosing system. The main baseline of the presented approach is in the dichotomous approach to diagnosing. It involves a separate description of both the process and the diagnostic system. This approach reflects the practice of designing implementable diagnostic systems. Thus, it can be seen as a proposal of a new, alternative, and, at the same time, flexible design procedure with great potential for applications. The primary motivation behind it was an attempt to circumvent the numerous limitations of well-known and well-established diagnosis approaches proposed by the communities working on fault detection and isolation (FDI) and artificial intelligence theories for diagnosis (DX). Accordingly, the paper identifies and provides an extensive discussion and a critical analysis of the existing limitations. Numerous examples and references to practical applications of the approach are indicated.

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“…In the literature, various model-based methods have been designed for fault detection and isolation. Among which state estimation [20], parameter estimation [11] and parity equations [8]. This class of methods is used to residuals generation.…”

Section: Introductionmentioning

confidence: 99%

Methodology to knowledge discovery for fault diagnosis of hybrid dynamical systems: demonstration on two tanks system

Achbi¹,

Mhamdi²,

Kechida³

et al. 2020

Diagnostyka

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The work carried out in this article concerns on the implementation off a diagnostic procedure for hybrid dynamic systems (HDS) whose objective is to guarantee the proper functioning of industrial installations. In this context, the main contributions of this work are summarized into three parts: The first part is oriented to the modeling approach dedicated to HDS. The aim is to find an adequate model combining both aspects (continuous and discrete dynamics). The use of Neuro-fuzzy networks makes it possible to build a model of the system and to follow all the modes without it being necessary to identify or discern them. The second part concerns the synthesis of a fault diagnostic technique based on a fuzzy inference system. A Neuro-Fuzzy network based is used for residual generation, while for the residual evaluation, a fuzzy reasoning model is used which can mainly introduce heuristic information into the analysis scheme and takes the appropriate decision regarding the actual behaviour of the process. The proposed approach is successfully applied to monitoring faults of a non-linear three-tank system and the results confirm the effectiveness of this approach.

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Process Decomposition and Test Selection for Distributed Fault Diagnosis

Cited by 5 publications

References 15 publications

Near-Optimal Decentralized Diagnosis via Structural Analysis

Near-Optimal Decentralized Diagnosis via Structural Analysis

A graph theory-based approach to the description of the process and the diagnostic system

Methodology to knowledge discovery for fault diagnosis of hybrid dynamical systems: demonstration on two tanks system

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