Data-Driven Technology for Engineering Systems Health Management

Design Approach, Feature Construction, Fault Diagnosis, Prognosis, Fusion and Decisions

Nonfiction, Science & Nature, Technology, Quality Control, Computers, Computer Hardware
Cover of the book Data-Driven Technology for Engineering Systems Health Management by Gang Niu, Springer Singapore
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Author: Gang Niu ISBN: 9789811020322
Publisher: Springer Singapore Publication: July 27, 2016
Imprint: Springer Language: English
Author: Gang Niu
ISBN: 9789811020322
Publisher: Springer Singapore
Publication: July 27, 2016
Imprint: Springer
Language: English

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.

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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.

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