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.