Data-Driven Technology for Engineering Systems Health Management
Design Approach, Feature Construction, Fault Diagnosis, Prognosis, Fusion and Decisions
(Sprache: Englisch)
This book introduces condition-based maintenance (CBM)/data-driven prognostics and health management (PHM) in detail, first explaining the PHM design approach from a systems engineering perspective, then summarizing and elaborating on the data-driven...
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This book introduces condition-based maintenance (CBM)/data-driven prognostics and health management (PHM) in detail, first explaining the PHM design approach from a systems engineering perspective, then summarizing and elaborating on the data-driven methodology for feature construction, as well as feature-based fault diagnosis and prognosis. The book includes a wealth of illustrations and tables to help explain the algorithms, as well as practical examples showing how to use this tool to solve situations for which analytic solutions are poorly suited. It equips readers to apply the concepts discussed in order to analyze and solve a variety of problems in PHM system design, feature construction, fault diagnosis and prognosis.Inhaltsverzeichnis zu „Data-Driven Technology for Engineering Systems Health Management “
Background of Systems Health Management.- Design Approach for Systems Health Management.- Overview of Data-driven PHM.- Data Acquisition and Preprocessing.- Statistic Feature Extraction.- Feature Selection Optimization.- Intelligent Fault Diagnosis Methodology.- Science of Prognostics.- Data Fusion Strategy.- System Support and Logistics.
Autoren-Porträt von Gang Niu
Bibliographische Angaben
- Autor: Gang Niu
- 2016, 1st ed. 2017, XIII, 357 Seiten, Maße: 16 x 24,1 cm, Gebunden, Englisch
- Verlag: Springer, Berlin
- ISBN-10: 9811020310
- ISBN-13: 9789811020315
Sprache:
Englisch
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