Knowledge-Driven Board-Level Functional Fault Diagnosis

• Κύριοι συγγραφείς: Ye, Fangming (Συγγραφέας), Zhang, Zhaobo (Συγγραφέας), Chakrabarty, Krishnendu (Συγγραφέας), Gu, Xinli (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2017.
• Θέματα: Engineering.; Data mining.; Electronics.; Microelectronics.; Electronic circuits.; Circuits and Systems.; Data Mining and Knowledge Discovery.; Electronics and Microelectronics, Instrumentation.

 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.