Data-Driven Technology for Engineering Systems Health Management

Design Approach, Feature Construction, Fault Diagnosis, Prognosis, Fusion and Decisions
Softcover Nachdruck of the original 1. Auflage 2017
ISBN: 978-981-10-9509-2
Verlag: Springer Nature Singapore

Buch, Englisch, 357 Seiten, Previously published in hardcover, Format (B × H): 155 mm x 235 mm, Gewicht: 5621 g

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.

Zielgruppe

Research

Autoren/Hrsg.

Niu, Gang

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik EDV | Informatik Technische Informatik Hardware: Grundlagen und Allgemeines
• Technische Wissenschaften Maschinenbau | Werkstoffkunde Produktionstechnik Zuverlässigkeitstechnik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

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.