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Data driven framework for prognostics

Posted on:2011-06-14Degree:M.SType:Thesis
University:Arizona State UniversityCandidate:Varadarajan, GayathriFull Text:PDF
GTID:2448390002957300Subject:Computer Science
Abstract/Summary:
Prognostics and health management (PHM) is a method that permits the reliability of a system to be evaluated in its actual application conditions. This work involved developing a robust system to determine the advent of failure.;Using the data from the PHM experiment, a model was developed to estimate the prognostic features and build a condition based system based on measured prognostics. To enable prognostics, a framework was developed to extract load parameters required for damage assessment from irregular time-load data. As a part of the methodology, a database engine was built to maintain and monitor the experimental data. This framework helps in significant reduction of the time-load data without compromising features that are essential for damage estimation. A failure precursor based approach was used for remaining life prognostics.;The developed system has a throughput of 4MB/sec with 90% latency within 100msec. This work hence provides an overview on Prognostic framework survey, Prognostics Framework architecture and design approach with a robust system implementation.
Keywords/Search Tags:Prognostics, Framework, System, Data
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