Central Library

Normal view MARC view ISBD view

Data-Driven Technology for Engineering Systems Health Management [electronic resource] : Design Approach, Feature Construction, Fault Diagnosis, Prognosis, Fusion and Decisions / by Gang Niu.

By: Niu, Gang [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: XIII, 357 p. 204 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9789811020322.Subject(s): Security systems | Electronic digital computers—Evaluation | Mathematics | Data mining | Pattern recognition systems | Security Science and Technology | System Performance and Evaluation | Applications of Mathematics | Data Mining and Knowledge Discovery | Automated Pattern RecognitionAdditional physical formats: Printed edition:: No title; Printed edition:: No title; Printed edition:: No titleDDC classification: 621 Online resources: Click here to access online
Contents:
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.
In: Springer Nature eBookSummary: 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.
    average rating: 0.0 (0 votes)
No physical items for this record

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.

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.

There are no comments for this item.

Log in to your account to post a comment.