Model-based Fault Diagnosis in Dynamic Systems Using Identification Techniques

1. Front Matter

   Pages i-xv

   PDF

2. Introduction

   • Silvio Simani, Cesare Fantuzzi, Ronald Jon Patton

   Pages 1-18

3. Model-Based Fault Diagnosis Techniques

   • Silvio Simani, Cesare Fantuzzi, Ronald Jon Patton

   Pages 19-60

4. System Identification for Fault Diagnosis

   • Silvio Simani, Cesare Fantuzzi, Ronald Jon Patton

   Pages 61-113

5. Residual Generation, Fault Diagnosis and Identification

   • Silvio Simani, Cesare Fantuzzi, Ronald Jon Patton

   Pages 115-156

6. Fault Diagnosis Application Studies

   • Silvio Simani, Cesare Fantuzzi, Ronald Jon Patton

   Pages 157-250

7. Concluding Remarks

   • Silvio Simani, Cesare Fantuzzi, Ronald Jon Patton

   Pages 251-259

8. Back Matter

   Pages 261-282

   PDF

Safety in industrial process and production plants is a concern of rising importance but because the control devices which are now exploited to improve the performance of industrial processes include both sophisticated digital system design techniques and complex hardware, there is a higher probability of failure. Control systems must include automatic supervision of closed-loop operation to detect and isolate malfunctions quickly. A promising method for solving this problem is "analytical redundancy", in which residual signals are obtained and an accurate model of the system mimics real process behaviour. If a fault occurs, the residual signal is used to diagnose and isolate the malfunction. This book focuses on model identification oriented to the analytical approach of fault diagnosis and identification covering: choice of model structure; parameter identification; residual generation; and fault diagnosis and isolation. Sample case studies are used to demonstrate the application of these techniques.

• Control
• Control Applications
• Control Engineering
• Dynamical Systems
• Fault Diagnosis
• Gas Turbines
• Identification
• Power Plants
• Residual Generation
• Sensor
• safety
• quality control, reliability, safety and risk

• Dipartimento di Ingegneria, Università di Ferrara, Ferrara, Italia

  Silvio Simani

• Dipartimento di Scienze per l’Ingegneria, Università di Modena e Reggio Emilia, Italia

  Cesare Fantuzzi

• School of Engineering, The University of Hull, Kingston-Upon-Hull, UK

  Ronald Jon Patton

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