Knowledge-Driven Board-Level Functional Fault Diagnosis

di Krishnendu Chakrabarty (Autore)

Xinli Gu (Autore)

Fangming Ye (Autore)

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Springer, 2016

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.

• Autore: Krishnendu Chakrabarty, Xinli Gu, Fangming Ye
• Anno edizione: 2016
• Editore: Springer
• Formato: EPUB2 con Adobe DRM
• Lingua: Inglese
• Compatibilità: Tutti i dispositivi (eccetto Kindle)
• Layout: Reflowable
• EAN: 9783319402109