Dynamic Thresholds for a Reliable Diagnosis of Switched Systems

Safety, availability and reliability are the main concern of many industries. Thus, fault detection and isolation of industrial machines, which are in most cases switched systems, is a primary task in many companies. The presented paper proposes a new diagnostic approach for switched systems using two powerful tools: bond graph and observer. A diagnostic layer detects model errors using bond graph, and a smart algorithm identifies and locates faults using observer. Although observers serve as fault detectors, they also have their own errors caused by convergence delay of calculations; even in the case of no sensor defect, the residue does not converge to zero. In this paper, we propose a new method to solve this problem by integrating dynamic thresholds in the detection procedure, which helped to avoid false alarms and ensure a highly reliable diagnosis.

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LFT Bond Graph for Online Robust Fault Detection and Isolation of Hybrid Multi-Source System

Journal of Physics Conference Series ◽

10.1088/1742-6596/2065/1/012010 ◽

2021 ◽

Vol 2065 (1) ◽

pp. 012010

Author(s):

Mahdi Boukerdja ◽

Youness Radi ◽

Omprakash ◽

Sumit Sood ◽

Belkacem Ould-Bouamama ◽

...

Keyword(s):

Fault Detection ◽

Online Monitoring ◽

Detection Algorithm ◽

Bond Graph ◽

Fault Detection And Isolation ◽

False Alarms ◽

Parameter Uncertainties ◽

Safety Issues ◽

Robust Fault Detection ◽

Production Of Hydrogen

Abstract Green hydrogen is undoubtedly the most promising energy vector of the future because it is captured by renewable and inexhaustible sources, such as wind and/or solar energy, and can be stored over the long in high-pressure cylinders, which can be used to feed the fuel cells to produce the electricity without emitting any pollutants. The system incorporated renewable sources and process used to produce the green hydrogen is the hybrid multi-source system (HMS). The production of hydrogen needs a reliable HMS, which always requires online monitoring for real-time Fault Detection and Isolation (FDI) because the risk of accidents in HMS and safety issues increases due to the possibility of faults. However, online monitoring of FDI is challenging due to the multi-physics dynamics of HMS and the inclusion of uncertain parameters and several disturbances. This paper proposes an online robust fault detection algorithm to detect system faults based on the properties of the graphical linear fractional transformation bond graph (LFT-BG) modeling approach. Here, the analytical redundancy relations (ARRs) and their uncertain parts extracted from the LFT-BG model are used to develop an online robust FDI algorithm for HMS. Numerical evaluations of ARRs and their uncertain parts, respectively, generate the residual signals known as “faults indicators” and their uncertain bounds known as “adaptive thresholds.” These thresholds evolve with system variables in the presence of parameter uncertainties for ensuring robust FDI for HMS to minimize false alarms. The validation of this approach is carried out using 20sim software that is familiar with BG modeling.

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Hybrid bond graph model based for robust fault detection and isolation

Proceedings of the Institution of Mechanical Engineers Part I Journal of Systems and Control Engineering ◽

10.1177/0959651815616026 ◽

2015 ◽

Vol 230 (2) ◽

pp. 145-163 ◽

Cited By ~ 4

Author(s):

Mohamed Ilyas Rahal ◽

Belkacem Ould Bouamama ◽

Abdelmajid Meghebbar

Keyword(s):

Fault Detection ◽

Graph Model ◽

Bond Graph ◽

Fault Detection And Isolation ◽

Model Based ◽

Robust Fault Detection

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Fault Detection and Isolation of Electrical Trimmable Horizontal Stabilizer Actuator Based on Bond Graph

10.1007/978-981-16-6324-6_31 ◽

2021 ◽

pp. 295-304

Author(s):

Chaoqun Zheng ◽

Jian Fu ◽

Wensen Zhang ◽

Xudong Han

Keyword(s):

Fault Detection ◽

Bond Graph ◽

Fault Detection And Isolation

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A PCA Based Fault Detection and Isolation Method for Train Locating System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.20-23.688 ◽

2010 ◽

Vol 20-23 ◽

pp. 688-693

Author(s):

Jiang Liu ◽

Bai Gen Cai ◽

Tao Tang ◽

Jian Wang

Keyword(s):

Fault Detection ◽

Fault Tolerant ◽

Fault Detection And Isolation ◽

Practical Application ◽

Isolation Method ◽

Efficiency Factors ◽

Simulation Results ◽

And Performance ◽

Locating System ◽

Fault Detectors

Fault tolerance is crucial to the operating safety and performance of train locating system. Based on the requirements of reliability and safety for train locating, the fault characteristics of location measuring sensors are analyzed. Based on the structure of the train locating system, the fault-tolerant design of the system is given with the location filtering module for case, in which six fault detectors are employed to determine the configuration of the module. Then a PCA based fault detection and isolation method is proposed with Hawkins T2 statistics and the corresponding control limit. By dynamically adjusting the efficiency factors, fault could be detected and isolated as prior defined isolating strategies, and then the fault tolerant performance will be guaranteed. Simulation results demonstrate the high fault tolerant ability of the proposed approach and certain practical application value.

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