Ebook: Computational Intelligence in Fault Diagnosis

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.

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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.

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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.

Content:
Front Matter....Pages i-xviii
Computational Intelligence Methodologies in Fault Diagnosis: Review and State of the Art....Pages 1-36
A Fuzzy Logic Approach to Gas Path Diagnostics in Aero-engines....Pages 37-79
Fault Detection and Isolation of Industrial Processes Using Optimized Fuzzy Models....Pages 81-104
A Fuzzy Classification Technique Applied to Fault Diagnosis....Pages 105-123
Fuzzy-Statistical Reasoning in Fault Diagnosis....Pages 125-177
Artificial Neural Networks in Fault Diagnosis: A Gas Turbine Scenario....Pages 179-207
Two-Stage Neural Networks Based Classifier System for Fault Diagnosis....Pages 209-230
Soft Computing Models for Fault Diagnosis of Conductive Flow Systems....Pages 231-285
Fault Diagnosis in a Power Generation Plant Using a Neural Fuzzy System with Rule Extraction....Pages 287-304
Fuzzy Neural Networks Applied to Fault Diagnosis....Pages 305-334
Causal Models for Distributed Fault Diagnosis of Complex Systems....Pages 335-356
Back Matter....Pages 357-362

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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.

Content:
Front Matter....Pages i-xviii
Computational Intelligence Methodologies in Fault Diagnosis: Review and State of the Art....Pages 1-36
A Fuzzy Logic Approach to Gas Path Diagnostics in Aero-engines....Pages 37-79
Fault Detection and Isolation of Industrial Processes Using Optimized Fuzzy Models....Pages 81-104
A Fuzzy Classification Technique Applied to Fault Diagnosis....Pages 105-123
Fuzzy-Statistical Reasoning in Fault Diagnosis....Pages 125-177
Artificial Neural Networks in Fault Diagnosis: A Gas Turbine Scenario....Pages 179-207
Two-Stage Neural Networks Based Classifier System for Fault Diagnosis....Pages 209-230
Soft Computing Models for Fault Diagnosis of Conductive Flow Systems....Pages 231-285
Fault Diagnosis in a Power Generation Plant Using a Neural Fuzzy System with Rule Extraction....Pages 287-304
Fuzzy Neural Networks Applied to Fault Diagnosis....Pages 305-334
Causal Models for Distributed Fault Diagnosis of Complex Systems....Pages 335-356
Back Matter....Pages 357-362
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