Computational Intelligence in Fault Diagnosis

ISBN-13: 9781849965835 / Angielski / Miękka / 2010 / 362 str.

Vasile Palade; Cosmin Danut Bocaniala; Lakhmi C. Jain

Opis

Presenting the latest developments and research results on fault diagnosis approaches using computational intelligence methodologies, this book opens with a review of the state-of-the-art before focusing on various theoretical aspects of computational intelligence methodologies applied to real-world fault diagnosis problems. Chapters deal with topics such as fuzzy sets applications to fault diagnosis, neural network based fault diagnosis applications and neuro-fuzzy techniques for fault diagnosis. The last chapter considers the problem of diagnosing large scale complex systems using local agents which, can be implemented using computational intelligence based fault diagnosis techniques. Several case studies are used. This book presents the most recent concerns and research results in industrial fault diagnosis using intelligent techniques, and will be of interest to application engineers/technologists, graduates and researchers wishing to apply these techniques, as well as build up a foundation for further study.

Recenzje

From the reviews:

"This book is a collection of 11 chapters written mostly by authors from European countries and Malaysia. The focus is on fault diagnosis using computational intelligence techniques. ... This book will be useful to doctoral students interested in the application of neural and neural-fuzzy techniques to diagnose problems arising in mechanical and aeronautical engineering disciplines." (Rao Vemuri, Computing Reviews, January, 2007)

Spis treści

Computational Intelligence Methodologies in Fault Diagnosis: Review and State of the Art.- A Fuzzy Logic Approach to Gas Path Diagnostics in Aero-engines.- Fault Detection and Isolation of Industrial Processes Using Optimized Fuzzy Models.- A Fuzzy Classification Technique Applied to Fault Diagnosis.- Fuzzy-Statistical Reasoning in Fault Diagnosis.- Artificial Neural Networks in Fault Diagnosis: A Gas Turbine Scenario.- Two-Stage Neural Networks Based Classifier System for Fault Diagnosis.- Soft Computing Models for Fault Diagnosis of Conductive Flow Systems.- Fault Diagnosis in a Power Generation Plant Using a Neural Fuzzy System with Rule Extraction.- Fuzzy Neural Networks Applied to Fault Diagnosis.- Causal Models for Distributed Fault Diagnosis of Complex Systems.

O autorze

Presenting the latest developments and research results on fault diagnosis approaches using computational intelligence methodologies, Computational Intelligence in Fault Diagnosis reviews the state of the art before focusing on theoretical aspects of computational intelligence methodologies applied to real-world fault diagnosis problems. Chapters deal with topics such as fuzzy sets applications to fault diagnosis, neural network based fault diagnosis applications and neuro-fuzzy techniques for fault diagnosis. The final chapter considers the problem of diagnosing large scale complex systems using local agents which can be implemented using computational intelligence based fault diagnosis techniques. The text offers case studies, including applying computational intelligence techniques to aero-engines fault diagnosis, and diagnosing faults to various industrial devices such as a flow control valve and a hydraulic installation in a rolling mill plant. This book presents the most recent concerns and research results in industrial fault diagnosis using intelligent techniques.

Blurb

Presenting the latest developments and research results on fault diagnosis approaches using computational intelligence methodologies, this book opens with a review of the state-of-the-art before moving on to focus on various theoretical aspects of computational intelligence methodologies applied to real-world fault diagnosis problems.

Chapters deal with topics such as fuzzy sets applications to fault diagnosis, neural network based fault diagnosis applications and neuro-fuzzy techniques for fault diagnosis. The last chapter considers the problem of diagnosing large scale complex systems using local agents which, in particular, can be implemented using computational intelligence based fault diagnosis techniques. Several case studies are used including applying computational intelligence techniques to aero-engines fault diagnosis and diagnosing faults to various industrial devices, such as a flow control valve and a hydraulic installation in a rolling mill plant.

Computational Intelligence in Fault Diagnosis presents the most recent concerns and research results in industrial fault diagnosis using intelligent techniques, and will be of interest to application engineers/technologists, graduates and researchers wishing to apply these techniques, enhance their knowledge, as well as build up a foundation for further study.