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Knowledge-Driven Board-Level Functional Fault Diagnosis

  1. Údaje o názvuKnowledge-Driven Board-Level Functional Fault Diagnosis [electronic resource] / by Fangming Ye, Zhaobo Zhang, Krishnendu Chakrabarty, Xinli Gu.
    NakladatelCham : Springer International Publishing : Imprint: Springer, 2017.
    Fyz.popisXIII, 147 p. 75 illus., 65 illus. in color. online resource.
    ISBN9783319402109
    Úplný obsahIntroduction -- Diagnosis System Design for Higher Accuracy -- Adaptive Diagnosis Process -- Handling Missing Syndromes -- Information-Theoretic Evaluation of Diagnosis System -- Knowledge Discover and Knowledge Transfer -- Conclusion.
    Poznámky k dostupnostiPřístup pouze pro oprávněné uživatele
    Dal.odpovědnost Zhang, Zhaobo.
    Chakrabarty, Krishnendu.
    Gu, Xinli.
    Dal.odpovědnost SpringerLink (Online service)
    Předmět.hesla Engineering. * Data mining. * Electronics. * Microelectronics. * Electronic circuits.
    Forma, žánr elektronické knihy electronic books
    Země vyd.Německo
    Jazyk dok.angličtina
    Druh dok.Elektronické knihy
    URLPlný text pro studenty a zaměstnance UPOL
    book

    book


    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 development.

    Introduction -- Diagnosis System Design for Higher Accuracy -- Adaptive Diagnosis Process -- Handling Missing Syndromes -- Information-Theoretic Evaluation of Diagnosis System -- Knowledge Discover and Knowledge Transfer -- Conclusion.

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