Robust model-based fault diagnosis for dynamic systems
Robust model-based fault diagnosis for dynamic systems
Optimal Real-time Control of Sewer Networks (Advances in Industrial Control)
Optimal Real-time Control of Sewer Networks (Advances in Industrial Control)
Dynamic multiple fault diagnosis: mathematical formulations and solution techniques
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference
Issues of Fault Diagnosis for Dynamic Systems
Issues of Fault Diagnosis for Dynamic Systems
Diagnosis of Complex Systems: Bridging the Methodologies of the FDI and DX Communities
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Hybrid estimation of complex systems
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Diagnosability Analysis Based on Component-Supported Analytical Redundancy Relations
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Model-Based Diagnosis of Hybrid Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An Efficient Algorithm for Finding Minimal Overconstrained Subsystems for Model-Based Diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Sensor Placement for Fault Diagnosis
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Integrated Model-Based and Data-Driven Diagnosis of Automotive Antilock Braking Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An event-based distributed diagnosis framework using structural model decomposition
Artificial Intelligence
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This paper proposes a fault diagnosis method using a timed discrete-event approach based on interval observers that improves the integration of fault detection and isolation tasks. The interface between fault detection and fault isolation considers the activation degree and the occurrence time instant of the diagnostic signals using a combination of several theoretical fault signature matrices that store the knowledge of the relationship between diagnostic signals and faults. The fault isolation module is implemented using a timed discrete-event approach that recognizes the occurrence of a fault by identifying a unique sequence of observable events (fault signals). The states and transitions that characterize such a system can directly be inferred from the relation between fault signals and faults. The proposed fault diagnosis approach has been motivated by the problem of detecting and isolating faults of the Barcelona's urban sewer system limnimeters (level meter sensors). The results obtained in this case study illustrate the benefits of using the proposed approach in comparison with the standard fault detection and isolation approach.