An analysis and modeling method of the diagnostic characteristics of a mechanical or electromechanical system is presented. Diagnosability analysis is especially relevant given the complexities and functional interdependencies of modern-day systems, since improvements in diagnosability can lead to a reduction of a system's life-cycle costs. The diagnosis process of a mechanical system, involving an observation phase and a testing phase, is described, as well as how failure types (the way particular system failure modes occur) impact the diagnostic process. Failure and diagnostic analysis leads to system diagnosability modeling with the Failure Modes and Effects Analysis (FMEA) and component-indication relationship analysis. Finally, methods are developed for translating the diagnosability model into mathematical methods for computing metrics such as distinguishabilty, testability, and Mean Time Between Unscheduled Removals (MTBUR). These methods involve the use of matrices to represent the failure and replacement characteristics of the system. Diagnosability metrics are extracted by matrix multiplication. These metrics are useful when comparing the diagnosability of proposed designs or predicting the life-cycle costs of fault isolation. / Graduation date: 2000
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/33087 |
| Date | 21 January 2000 |
| Creators | Henning, Scott A. |
| Contributors | Paasch, Robert K. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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