Part One: Motivation. 1. Introduction. 2. Maintainability: a Historical Perspective. 3. Field Diagnosis and Repair: the Problem. Part Two: Analysis and Application. 4. Bottom-Up Modeling for Diagnosis. 5. System Level Analysis for Diagnosis. 6. The Information Flow Model. 7. System Level Diagnosis. 8. Evaluating System Diagnosability. 9. Verification and Validation. 10. Architecture for System Diagnosis. Part Three: Advanced Topics. 11. Inexact Diagnosis. 12. Partitioning Large Problems. 13. Modeling Temporal Information. 14. Adaptive Diagnosis. 15. Diagnosis -- Art versus Science. References. Index.
System Test and Diagnosis is the first book on test and diagnosis at the system level, defined as any aggregation of related elements that together form an entity of sufficient complexity for which it is impractical to treat all of the elements at the lowest level of detail. The ideas presented emphasize that it is possible to diagnose complex systems efficiently. Since the notion of system is hierarchical, these ideas are applicable to all levels.
The philosophy is presented in the context of a model-based approach, using the information flow model, that focuses on the information provided by the tests rather than the functions embedded in the system. Detailed algorithms are offered for evaluating system testability, performing efficient diagnosis, verifying and validating the models, and constructing an architecture for system maintenance. Several advanced algorithms, not commonly available in existing diagnosis tools, are discussed, including reasoning with inexact or uncertain test data, breaking large problems into manageable smaller problems, diagnosing systems with time sensitive information and time dependent tests and learning from experience.
The book is divided into three parts. The first part provides motivation for careful development of the subject and the second part provides the tools necessary for analyzing system testability and computing diagnostic strategies. The third part presents advanced topics in diagnosis.
Several case studies are provided, including a single detailed case study. Smaller case studies describe experiences from actual applications of the methods discussed. The detailed case study walks the reader through a complete analysis of a system to illustrate the concepts and describe the analyses that are possible. All case studies are based upon real systems that have been modeled for the purposes of diagnosis.
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