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.
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.
 
Computational Intelligence in Fault Diagnosis
362 
Computational Intelligence in Fault Diagnosis
362Paperback(Softcover reprint of hardcover 1st ed. 2006)
Product Details
| ISBN-13: | 9781849965835 | 
|---|---|
| Publisher: | Springer London | 
| Publication date: | 12/09/2010 | 
| Series: | Advanced Information and Knowledge Processing | 
| Edition description: | Softcover reprint of hardcover 1st ed. 2006 | 
| Pages: | 362 | 
| Product dimensions: | 6.10(w) x 9.25(h) x 0.03(d) | 
