Flotation Process Fault Diagnosis Via Structural Analysis

Pérez-Zúñiga, Gustavo; Sotomayor-Moriano, Javier; Chanthery, Élodie; Travé-Massuyès, Louise; Soto, Mario

doi:10.1016/j.ifacol.2019.09.191

Cited by 11 publications

(6 citation statements)

References 10 publications

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“…Given a bipartite graph, the structural redundancy ρ Σ of a set of equations Σ ⊆ Σ is defined as the difference between the number of equations and the number of unknown variables X [26].…”

Section: Definition 4 (Structural Redundancy)mentioning

confidence: 99%

“…Recently, structural analysis has been proposed as a potent method for designing FDI systems for complex industrial plants [26][27][28]. Structural analysis is an essential model based diagnosis method that uses graphic tools to competently assess fault detectability and the isolability of industrial plants without the accurate knowledge of plant parameters, and it can also be applied quantitatively to generate residuals for detecting and isolating faults [29].…”

Section: Introductionmentioning

confidence: 99%

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Fault Detection and Isolation System Based on Structural Analysis of an Industrial Seawater Reverse Osmosis Desalination Plant

et al. 2020

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Currently, the use of industrial seawater reverse osmosis desalination (ISROD) plants has increased in popularity in light of the growing global demand for freshwater. In ISROD plants, any fault in the components of their control systems can lead to a plant malfunction, and this condition can originate safety risks, energy waste, as well as affect the quality of freshwater. This paper addresses the design of a fault detection and isolation (FDI) system based on a structural analysis approach for an ISROD plant located in Lima (Peru). Structural analysis allows obtaining a plant model, which is useful to generate diagnostic tests. Here, diagnostic tests via fault-driven minimal structurally overdetermined (FMSO) sets are computed, and then, binary integer linear programming (BILP) is used to select the FMSO sets that guarantee isolation. Simulations shows that all the faults of interest (sensors and actuators faults) are detected and isolated according to the proposed design.

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Section: Definition 4 (Structural Redundancy)mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fault Detection and Isolation System Based on Structural Analysis of an Industrial Seawater Reverse Osmosis Desalination Plant

et al. 2020

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“…In (Zanella, 2017), || //l -diagnosability is presented to take into account temporal uncertainty into the diagnosability def-System Type Articles DES (Sampath, Sengupta, & Lafortune, 1995) and (Ye, Dague, & He, 2019) [Automata] (Zanella, 2017) [Twin plant : finite automata] (Basile, Chiacchio, & De Tommasi, 2012) [Labelled Petri Nets] (Yoo & Lafortune, 2002) [Finite-state automaton] (Madalinski, Nouioua, & Dague, 2010) [Labelled Petri Nets] CS (Staroswiecki & Comtet-Varga, 2001) [algebraic dynamic systems] (Zuniga, Sotomayor-Moriano, Chanthery, Travé-Massuyès, & Soto, 2019) (Cordier, Travé-Massuyes, Pucel, et al, 2006) HS (Zaatiti, Ye, Dague, & Gallois, 2017) [Partially observed hybrid automata] (Bayoudh & Travé-Massuyès, 2014) (Fourlas, Kyriakopoulos, & Krikelis, 2002) [Hybrid I/O Automata] HtS (Hsieh & Chen, 2008) [distributed] (Hua, Li, Ren, & Liu, 2016) Table 1. Reviewed articles on diagnosability classified by system types inition for systems modeled by automata.…”

Section: Diagnosability In Desmentioning

confidence: 99%

overview on diagnosability and prognosability for system monitoring

Vignolles,

Chanthery,

Ribot

2020

PHME_CONF

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The complexification of systems has brought the emergence of a new field of study: system health monitoring. This field is deemed necessary because it improves system availability and it avoids unnecessary maintenance costs. System health monitoring is performed through diagnosis and prognosis methods. Diagnosis consists in detecting and identifying faults that may lead to system failures. Prognosis is related to the prediction of the system Remaining Useful Life (RUL) that corresponds to the remaining time until the system failure. This paper aims at giving an overview on the properties related to diagnosis and prognosis on different types of systems. We will focus on the diagnosability and prognosability properties. This paper will first briefly present the different types of systems of interest for the system health monitoring community. We will consider Discrete Event Systems (DES), Continuous Systems (CS), Hybrid Systems (HS) or Heterogeneous Systems (HtS). The rest of this paper will present the definitions given in the literature for the concepts of diagnosability and prognosability. The similarities and differences in these definitions for the different types of systems will be highlighted. Some metrics associated with the prognosability property will also be discussed.

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“…Structural analysis is a model-based fault diagnosis method [10]. It differs from the prior model-based fault diagnosis approaches that depended on the correct analytical model's design, analysis, and derivation.…”

Section: Introductionmentioning

confidence: 99%

A Review of Research on Diagnosability of Control Systems Based on Structural Analysis

Gu,

Shi

2023

Applied Sciences

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Structural analysis, a model-based fault diagnosis approach, has been extensively highlighted since it does not depend on an exact analytical system model. The structural analysis approach focuses on obtaining the required information for fault detection and fault-tolerant control from the structural model of the control system. Diagnosability is a design attribute that indicates the fault diagnosis capabilities. Diagnosability design not only guarantees that the structure of the control system gives adequate fault information but also that the control system achieves the fault diagnosis with the least cost and the most excellent efficiency. In this paper, in combination with the research progress of structural analysis, the study first designs the structural diagnosability model of the control system based on structural analysis; secondly, the essential techniques of diagnosability evaluation and diagnosability design based on structural analysis are analyzed and summarized, and the diagnosability index system based on structural analysis is designed based on the structural detectability and structural isolation; this lays the foundation for the development of the diagnosability; lastly, the study summarizes the problems of diagnosability research based on structural analysis and the future development direction.

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Flotation Process Fault Diagnosis Via Structural Analysis

Cited by 11 publications

References 10 publications

Fault Detection and Isolation System Based on Structural Analysis of an Industrial Seawater Reverse Osmosis Desalination Plant

Fault Detection and Isolation System Based on Structural Analysis of an Industrial Seawater Reverse Osmosis Desalination Plant

overview on diagnosability and prognosability for system monitoring

A Review of Research on Diagnosability of Control Systems Based on Structural Analysis

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