Predicting Failures and Estimating Duration of Remaining Service Life from Satellite Telemetry
dc.contributor.author | Losik, Len | |
dc.contributor.author | Wahl, Sheila | |
dc.contributor.author | Owen, Lewis | |
dc.date.accessioned | 2016-06-01T18:00:48Z | |
dc.date.available | 2016-06-01T18:00:48Z | |
dc.date.issued | 1996-10 | |
dc.identifier.issn | 0884-5123 | |
dc.identifier.issn | 0074-9079 | |
dc.identifier.uri | http://hdl.handle.net/10150/611451 | |
dc.description | International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California | en_US |
dc.description.abstract | This paper addresses research completed for predicting hardware failures and estimating remaining service life for satellite components using a Failure Prediction Process (FPP). It is a joint paper, presenting initial research completed at the University of California, Berkeley, Center for Extreme Ultraviolet (EUV) Astrophysics using telemetry from the EUV EXPLORER (EUVE) satellite and statistical computation analysis completed by Lockheed Martin. This work was used in identifying suspect "failure precursors." Lockheed Martin completed an exploration into the application of statistical pattern recognition methods to identify FPP events observed visually by the human expert. Both visual and statistical methods were successful in detecting suspect failure precursors. An estimate for remaining service life for each unit was made from the time the suspect failure precursor was identified. It was compared with the actual time the equipment remained operable. The long-term objective of this research is to develop a resident software module which can provide information on FPP events automatically, economically, and with high reliability for long-term management of spacecraft, aircraft, and ground equipment. Based on the detection of a Failure Prediction Process event, an estimate of remaining service life for the unit can be calculated and used as a basis to manage the failure. | |
dc.description.sponsorship | International Foundation for Telemetering | en |
dc.language.iso | en_US | en |
dc.publisher | International Foundation for Telemetering | en |
dc.relation.url | http://www.telemetry.org/ | en |
dc.rights | Copyright © International Foundation for Telemetering | en |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
dc.subject | Telemetry | en |
dc.subject | Analysis | en |
dc.subject | Anomaly Resolution | en |
dc.subject | Failure Prediction | en |
dc.subject | Anomaly Prediction | en |
dc.subject | Statistical Pattern Recognition | en |
dc.title | Predicting Failures and Estimating Duration of Remaining Service Life from Satellite Telemetry | en_US |
dc.type | text | en |
dc.type | Proceedings | en |
dc.contributor.department | Lockheed Martin Telemetry & Instrumentation | en |
dc.contributor.department | Lockheed Martin Advanced Technology Center | en |
dc.identifier.journal | International Telemetering Conference Proceedings | en |
dc.description.collectioninformation | Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection. | en |
refterms.dateFOA | 2018-06-17T18:49:07Z | |
html.description.abstract | This paper addresses research completed for predicting hardware failures and estimating remaining service life for satellite components using a Failure Prediction Process (FPP). It is a joint paper, presenting initial research completed at the University of California, Berkeley, Center for Extreme Ultraviolet (EUV) Astrophysics using telemetry from the EUV EXPLORER (EUVE) satellite and statistical computation analysis completed by Lockheed Martin. This work was used in identifying suspect "failure precursors." Lockheed Martin completed an exploration into the application of statistical pattern recognition methods to identify FPP events observed visually by the human expert. Both visual and statistical methods were successful in detecting suspect failure precursors. An estimate for remaining service life for each unit was made from the time the suspect failure precursor was identified. It was compared with the actual time the equipment remained operable. The long-term objective of this research is to develop a resident software module which can provide information on FPP events automatically, economically, and with high reliability for long-term management of spacecraft, aircraft, and ground equipment. Based on the detection of a Failure Prediction Process event, an estimate of remaining service life for the unit can be calculated and used as a basis to manage the failure. |