Additional information
by Rolf Isermann (Author)
This advanced text gives an introduction to advanced methods of fault detection and diagnosis (FDD). After definitions of important terms, the reliability, availability, safety and systems integrity of technical processes is considered. Then fault-detection methods for single signals without models like limit and trend checking and with harmonic and stochastic models, like Fourier analysis, correlation and wavelets are treated. This is followed by fault detection with process models using the relationships between signals like parameter estimation, parity equations, observers and principal component analysis. The treated fault-diagnosis methods include classification methods from Bayes classification to neural networks with decision trees and inference methods from approximate reasoning with fuzzy logic to hybrid fuzzy-neuro systems. Several practical examples for fault detection and diagnosis of DC motor drives, a centrifugal pump, automotive suspension and tire show applications.
Back Jacket
Supervision, health-monitoring, fault detection, fault diagnosis and fault management play an increasing role for technical processes and vehicles, in order to improve reliability, availability, maintenance and life-time. For safety-related processes fault-tolerant systems with redundancy are required in order to reach comprehensive system integrity.
This book gives an introduction into the field of fault detection, fault diagnosis and fault-tolerant systems with methods which have proven their performance in practical applications. It guides the reader in a structured tutorial style:
- supervision methods, reliability, safety, system integrity and related terminology;
- fault detection with signal-based methods for periodic and stochastic signals;
- fault detection with process model-based methods like parameter estimation, state estimation, parity equations and principal component analysis;
- fault diagnosis with classification and inference methods;
- fault-tolerant systems with hardware and analytical redundancy;
- many practical simulation examples and experimental results for processes like electrical motors, pumps, actuators, sensors and automotive components;
- end-of-chapter exercises for self testing or for practice.
The book is dedicated to graduate students of electrical, mechanical, chemical engineering and computer science and for practising engineers.
