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Data-Driven Technology for Engineering Systems Health Management

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

Language EnglishEnglish
Book Paperback
Book Data-Driven Technology for Engineering Systems Health Management GANG NIU
Libristo code: 19704309
Publishers Springer Verlag, Singapore, June 2018
This book introduces condition-based maintenance (CBM)/data-driven prognostics and health management... Full description
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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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About the book

Full name Data-Driven Technology for Engineering Systems Health Management
Author GANG NIU
Language English
Binding Book - Paperback
Date of issue 2018
Number of pages 357
EAN 9789811095092
ISBN 9789811095092
Libristo code 19704309
Publishers Springer Verlag, Singapore
Weight 5621
Dimensions 155 x 235 x 21

Categories

Technology, Engineering, Agriculture > Mechanical engineering & materials > Production engineering > Industrial quality control
Computing & Information Technology > Computer science > Artificial intelligence > Computer vision
Mathematics & Science > Mathematics > Algebra
Mathematics & Science > Mathematics > Applied mathematics
Computing & Information Technology > Digital lifestyle > E-book readers, tablets & other portable devices: consumer / user guides
Computing & Information Technology > Databases > Data mining
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