Knowledge-Driven Board-Level Functional Fault Diagnosis / by Fangming Ye, Zhaobo Zhang, Krishnendu Chakrabarty, Xinli Gu

Von:

Ye, Fangming [aut]

Mitwirkende(r):

Resource type: Ressourcentyp: Buch (Online)Buch (Online)Sprache: Englisch Reihen: SpringerLink Bücher | Springer eBook Collection EngineeringVerlag: Cham : Springer, 2017Beschreibung: Online-Ressource (XIII, 147 p. 75 illus., 65 illus. in color, online resource)ISBN:

9783319402109

Schlagwörter:

Andere physische Formen: 9783319402093 | Druckausg.: 978-3-319-40209-3 | Printed edition: 9783319402093 LOC-Klassifikation:

TK7888.4

DOI: DOI: 10.1007/978-3-319-40210-9Online-Ressourcen:

Zusammenfassung: This book provides a comprehensive set of characterization, prediction, optimization, evaluation, and evolution techniques for a diagnosis system for fault isolation in large electronic systems. Readers with a background in electronics design or system engineering can use this book as a reference to derive insightful knowledge from data analysis and use this knowledge as guidance for designing reasoning-based diagnosis systems. Moreover, readers with a background in statistics or data analytics can use this book as a practical case study for adapting data mining and machine learning techniques to electronic system design and diagnosis. This book identifies the key challenges in reasoning-based, board-level diagnosis system design and presents the solutions and corresponding results that have emerged from leading-edge research in this domain. It covers topics ranging from highly accurate fault isolation, adaptive fault isolation, diagnosis-system robustness assessment, to system performance analysis and evaluation, knowledge discovery and knowledge transfer. With its emphasis on the above topics, the book provides an in-depth and broad view of reasoning-based fault diagnosis system design. • Explains and applies optimized techniques from the machine-learning domain to solve the fault diagnosis problem in the realm of electronic system design and manufacturing; • Demonstrates techniques based on industrial data and feedback from an actual manufacturing line; • Discusses practical problems, including diagnosis accuracy, diagnosis time cost, evaluation of diagnosis system, handling of missing syndromes in diagnosis, and need for fast diagnosis-system developmentZusammenfassung: Introduction -- Diagnosis System Design for Higher Accuracy -- Adaptive Diagnosis Process -- Handling Missing Syndromes -- Information-Theoretic Evaluation of Diagnosis System -- Knowledge Discover and Knowledge Transfer -- ConclusionPPN: PPN: 1658676785Package identifier: Produktsigel: ZDB-2-ENG

Exemplare ( 0 )

Dieser Titel hat keine Exemplare