Knowledge-Driven Board-Level Functional Fault Diagnosis

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...

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Hlavní autor: Ye, Fangming (Autor)
Další autoři: Zhang, Zhaobo (Autor)
Chakrabarty, Krishnendu (Autor)
Gu, Xinli (Autor)
Korporace: SpringerLink (online služba)  
Médium: E-kniha
Jazyk:angličtina
Vydáno: Cham : Springer International Publishing, 2017
Žánr/forma:elektronické knihy
ISBN:978-3-319-40210-9
9783319402093
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Shrnutí: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
Fyzický popis:1 online zdroj (XIII, 147 stran) : 75 ilustrací, 65 barevných ilustrací