Fault diagnosis in dynamic systems: theory and application
Fault diagnosis in dynamic systems: theory and application
Discrete-time signal processing
Discrete-time signal processing
Detection of abrupt changes: theory and application
Detection of abrupt changes: theory and application
Robust model-based fault diagnosis for dynamic systems
Robust model-based fault diagnosis for dynamic systems
Modelling and Simulation in Thermal and Chemical Engineering: A Bond Graph Approach
Modelling and Simulation in Thermal and Chemical Engineering: A Bond Graph Approach
Model-Based Fault Diagnosis in Dynamic Systems Using Identification Techniques
Model-Based Fault Diagnosis in Dynamic Systems Using Identification Techniques
Diagnosis and Fault-Tolerant Control
Diagnosis and Fault-Tolerant Control
Issues of Fault Diagnosis for Dynamic Systems
Issues of Fault Diagnosis for Dynamic Systems
Analytical redundancy relations for fault detection and isolation in algebraic dynamic systems
Automatica (Journal of IFAC)
Construction of classification models for credit policies in banks
International Journal of Electronic Finance
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To ensure safe operation of industrial processes, automated Fault Detection and Isolation (FDI) procedures are implemented in their supervision platforms. In the safety-critical and environmentally hazardous processes, it is impossible to introduce all kinds of faults and then to derive their consequences. Qualitative determination of consequences of different faults can be misleading in complex dynamical systems. Therefore, simulation of a prototype model turns out to be a practical and an economical solution for the development of a complete Knowledge-Base (KB). Consequently, the intelligence acquired by KB from the simulated models is used to fine-tune the Decision Support System (DSS) such that false alarms and misdetections are minimised. A method for model-based multiple FDI by using Analytical Redundancy Relations (ARRs) and parameter estimation is developed in this paper. Parameter estimation is an essential prerequisite for fault accommodation through system reconfiguration or Fault Tolerant Control (FTC). Bond graph modelling is used to describe the process models and then the model is used to derive the ARRs and fault candidates. Parameter values corresponding to the fault-subspace are estimated by minimising a function of the ARRs. Modelling uncertainties arising out of parameter estimation and sensor noise are taken care by using a passive approach for robust FDI. The developed technique is applied to monitor an open-loop non-linear thermo-fluid process.