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

• Κύριος συγγραφέας: Niu, Gang (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Singapore : Springer Singapore : Imprint: Springer, 2017.
• Θέματα: Engineering.; Computer system failures.; Data mining.; Pattern recognition.; Applied mathematics.; Engineering mathematics.; Quality control.; Reliability.; Industrial safety.; Quality Control, Reliability, Safety and Risk.; System Performance and Evaluation.; Applications of Mathematics.; Data Mining and Knowledge Discovery.; Pattern Recognition.
• Φυσική περιγραφή: XIII, 357 p. 204 illus. online resource.
• ISBN: 9789811020322

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.