abstract: 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. / Dissertation/Thesis / M.S. Computer Science 2010
| Identifer | oai:union.ndltd.org:asu.edu/item:8595 |
| Date | January 2010 |
| Contributors | Varadarajan, Gayathri (Author), Liu, Huan (Advisor), Ye, Jieping (Committee member), Davalcu, Hasan (Committee member), Arizona State University (Publisher) |
| Source Sets | Arizona State University |
| Language | English |
| Detected Language | English |
| Type | Masters Thesis |
| Format | 48 pages |
| Rights | http://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved |
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