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دانشجوعلاقه‌مند یادگیری
کتابخوان حرفه‌ایلذت مطالعه
نویسندهالهام‌گیری

Computational Intelligence in Fault Diagnosis (Advanced Information and Knowledge Processing)

Vasile Palade; Lakhmi Jain; Cosmin Danut Bocaniala; SpringerLink (Online service)

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تحویل فوری
پرداخت امن
ضمانت فایل
پشتیبانی

مشخصات کتاب

سال انتشار
۲۰۰۶
فرمت
PDF
زبان
انگلیسی
حجم فایل
۷٫۵ مگابایت
شابک
9781281067555، 9781846283437، 9781846286315، 9781849965835، 9786611067557، 1281067555، 1846283434، 184628631X، 1849965838، 6611067558

دربارهٔ کتاب

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. 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. 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. Edited By Vasile Palade, Lakhmi Jain, Cosmin Danut Bocaniala. 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. This book presents the most recent concerns and research results in industrial fault diagnosis using intelligent techniques. It focuses on computational intelligence applications to fault diagnosis with real-world applications used in different chapters to validate the different diagnosis methods. The book includes one chapter dealing with a novel coherent fault diagnosis distributed methodology for complex systems. An overview of the state of the art in the development of computational intelligence techniques pertaining to fault diagnosis. Covering all computational intelligence techniques, the book gradually exposes the reader to these various methods in its eleven chapters

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