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Data-Driven Technology for Engineering Systems Health Management Design Approach, Feature Construction, Fault Diagnosis, Prognosis, Fusion and Decisions /

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...

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Main Author: Niu, Gang. (Author, http://id.loc.gov/vocabulary/relators/aut)
Corporate Author: SpringerLink (Online service)
Language:English
Published: Singapore : Springer Singapore : Imprint: Springer, 2017.
Edition:1st ed. 2017.
Subjects:
Quality control.
Reliability.
Industrial safety.
Computer system failures.
Applied mathematics.
Engineering mathematics.
Data mining.
Pattern recognition.
Quality Control, Reliability, Safety and Risk.
System Performance and Evaluation.
Applications of Mathematics.
Data Mining and Knowledge Discovery.
Pattern Recognition.
Online Access:https://doi.org/10.1007/978-981-10-2032-2
Summary: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.
Physical Description:XIII, 357 p. 204 illus. online resource.
ISBN:9789811020322

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