Graduate Thesis Or Dissertation
 

Extension of early stage failure analysis tools to Prognostics Health Management design

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/pc289n05m

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  • Modern complex mechanical systems have evolved to a point of incredible complexity. Many now operate with significant assistance from automated response functions, and some operate without human operators at all. These increasingly complex systems have also become more expensive and more ambitions in mission, bringing about higher risk to both money and life. In response to these risks, Prognostics and Health Management (PHM) systems are developed to detect, manage, notify, mitigate, and respond to the potential failures in these high risk complex systems. The responsibilities carried by PHM systems make them as integral to the successful operation of a complex machine as any other major system. While methods have been developed and are in use to consider risk and reliability in the early stage of complex system design, explicit consideration of PHM capability and architecture are often left for later stages in the design process. In this work, several risk and reliability based design techniques are discussed with consideration of PHM development. In particular, the Function Failure Identification Propagation (FFIP) framework provides a systematic process to identify potential failure points and the resulting functional losses from a model based architecture. Research into PHM and embedded system co-design indicates that FFIP is a good starting point for early stage PHM architecture development. In this body, FFIP is first augmented to more completely capture the data needed for preliminary PHM architecture and to begin to address PHM capability in early stage complex system design. Second, an embedded systems design process centered around StateCharts is developed for specific application to the FFIP process in order to facilitate PHM system design during early stage complex system design.
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file details thesis25maykramer_1_.pdf 2017-08-14 Público Descargar