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A Review of Diagnostic Techniques for ISHM ApplicationsSystem diagnosis is an integral part of any Integrated System Health Management application. Diagnostic applications make use of system information from the design phase, such as safety and mission assurance analysis, failure modes and effects analysis, hazards analysis, functional models, fault propagation models, and testability analysis. In modern process control and equipment monitoring systems, topological and analytic , models of the nominal system, derived from design documents, are also employed for fault isolation and identification. Depending on the complexity of the monitored signals from the physical system, diagnostic applications may involve straightforward trending and feature extraction techniques to retrieve the parameters of importance from the sensor streams. They also may involve very complex analysis routines, such as signal processing, learning or classification methods to derive the parameters of importance to diagnosis. The process that is used to diagnose anomalous conditions from monitored system signals varies widely across the different approaches to system diagnosis. Rule-based expert systems, case-based reasoning systems, model-based reasoning systems, learning systems, and probabilistic reasoning systems are examples of the many diverse approaches ta diagnostic reasoning. Many engineering disciplines have specific approaches to modeling, monitoring and diagnosing anomalous conditions. Therefore, there is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system. For instance, the conventional approaches to diagnosing failures in rotorcraft applications are very different from those used in communications systems. Further, online and offline automated diagnostic applications are integrated into an operations framework with flight crews, flight controllers and maintenance teams. While the emphasis of this paper is automation of health management functions, striking the correct balance between automated and human-performed tasks is a vital concern.
Document ID
20060019235
Acquisition Source
Ames Research Center
Document Type
Conference Paper
Authors
Patterson-Hine, Ann
(NASA Ames Research Center Moffett Field, CA, United States)
Biswas, Gautam
(Vanderbilt Univ. Nashville, TN, United States)
Aaseng, Gordon
(Honeywell Defense and Space Electronics Systems Glendale, AZ, United States)
Narasimhan, Sriam
(University Affiliated Research Center Moffett Field, CA, United States)
Pattipati, Krishna
(Connecticut Univ. Storrs, CT, United States)
Date Acquired
August 23, 2013
Publication Date
January 1, 2005
Subject Category
Systems Analysis And Operations Research
Meeting Information
Meeting: ISHEM Forum 2005
Location: Napa, CA
Country: United States
Start Date: November 7, 2005
End Date: November 10, 2005
Funding Number(s)
CONTRACT_GRANT: 21-612-40-84-20
Distribution Limits
Public
Copyright
Public Use Permitted.
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