Introduction of Intelligent Machine Fault Diagnosis & Prognosis
Seiten
2011
Nova Science Publishers Inc (Verlag)
978-1-60692-263-7 (ISBN)
Nova Science Publishers Inc (Verlag)
978-1-60692-263-7 (ISBN)
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Condition monitoring, fault diagnosis and prognosis of machinery have received considerable attention and they are important in industry because of the need to increase reliability. This book is suitable for those who want to study feature-based intelligent machine fault diagnosis and prognosis techniques.
Condition monitoring, fault diagnosis and prognosis of machinery have received considerable attention in recent years and they are increasingly becoming important in industry because of the need to increase reliability and decrease possible loss of production due to the fault of equipments. Early fault detection, diagnosis and prognosis can increase equipment availability and performance, reduce consequential damage, prolong machine life and reduce spare parts inventories and break down maintenance. With the development of the artificial intelligence techniques, many intelligent systems have been employed to assist the maintenance management task to correctly interpret the fault data. The book is very easy to study; even if the reader is a beginner in the fault diagnosis area, they do not need special prerequisite knowledge to understand the contents of this book. The book is equipped with software under MATLAB and offers many examples which are related to fault diagnosis processes. It will be very useful to readers who want to study feature-based intelligent machine fault diagnosis and prognosis techniques. The book is dedicated to graduate students of mechanical and electrical engineering, computer science and for practising engineers.
Condition monitoring, fault diagnosis and prognosis of machinery have received considerable attention in recent years and they are increasingly becoming important in industry because of the need to increase reliability and decrease possible loss of production due to the fault of equipments. Early fault detection, diagnosis and prognosis can increase equipment availability and performance, reduce consequential damage, prolong machine life and reduce spare parts inventories and break down maintenance. With the development of the artificial intelligence techniques, many intelligent systems have been employed to assist the maintenance management task to correctly interpret the fault data. The book is very easy to study; even if the reader is a beginner in the fault diagnosis area, they do not need special prerequisite knowledge to understand the contents of this book. The book is equipped with software under MATLAB and offers many examples which are related to fault diagnosis processes. It will be very useful to readers who want to study feature-based intelligent machine fault diagnosis and prognosis techniques. The book is dedicated to graduate students of mechanical and electrical engineering, computer science and for practising engineers.
Preface; Introduction; Data Acquisition, Processing and Analysis; Feature Extraction and Clustering; Feature Selection; Fault Classification Algorithms; Decision Fusion Algorithms; Fault Prognosis Algorithms; Index.
| Verlagsort | New York |
|---|---|
| Sprache | englisch |
| Maße | 255 x 175 mm |
| Gewicht | 676 g |
| Themenwelt | Technik ► Elektrotechnik / Energietechnik |
| Technik ► Maschinenbau | |
| ISBN-10 | 1-60692-263-7 / 1606922637 |
| ISBN-13 | 978-1-60692-263-7 / 9781606922637 |
| Zustand | Neuware |
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