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

✍ Scribed by Gang Niu (auth.)

Publisher: Springer Singapore
Year: 2017
Tongue: English
Leaves: 364
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages i-xiii
Background of Systems Health Management....Pages 1-14
Design Approach for Systems Health Management....Pages 15-33
Overview of Data-Driven PHM....Pages 35-48
Data Acquisition and Preprocessing....Pages 49-99
Statistic Feature Extraction....Pages 101-138
Feature Selection Optimization....Pages 139-171
Intelligent Fault Diagnosis Methodology....Pages 173-258
Science of Prognostics....Pages 259-291
Data Fusion Strategy....Pages 293-341
System Support and Logistics....Pages 343-354
Back Matter....Pages 355-357

✦ Subjects

Quality Control, Reliability, Safety and Risk;System Performance and Evaluation;Applications of Mathematics;Data Mining and Knowledge Discovery;Pattern Recognition

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