Using Data-Driven Prognostic Algorithms for Completing Independent Failure Analysis
ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada === Current failure analysis practices use diagnostic technology developed over the past 100 years of design...
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ndltd-arizona.edu-oai-arizona.openrepository.com-10150-5957682016-02-07T03:00:40Z Using Data-Driven Prognostic Algorithms for Completing Independent Failure Analysis Losik, Len Failure Analysis Failure Analysis Independent Failure Analysis Fault Analysis Prognostics Failure Analysis Diagnostics Telemetry Analysis Failure Isolation Identification and Recovery ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada Current failure analysis practices use diagnostic technology developed over the past 100 years of designing and manufacturing electrical and mechanical equipment to identify root cause of equipment failure requiring expertise with the equipment under analysis. If the equipment that failed had telemetry embedded, prognostic algorithms can be used to identify the deterministic behavior in completely normal appearing data from fully functional equipment used for identifying which equipment will fail within 1 year of use, can also identify when the presence of deterministic behavior was initiated for any equipment failure. 2011-10 text Proceedings 0884-5123 0074-9079 http://hdl.handle.net/10150/595768 International Telemetering Conference Proceedings en_US http://www.telemetry.org/ Copyright © held by the author; distribution rights International Foundation for Telemetering International Foundation for Telemetering |
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en_US |
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Failure Analysis Independent Failure Analysis Fault Analysis Prognostics Failure Analysis Diagnostics Telemetry Analysis Failure Isolation Identification and Recovery |
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Failure Analysis Independent Failure Analysis Fault Analysis Prognostics Failure Analysis Diagnostics Telemetry Analysis Failure Isolation Identification and Recovery Losik, Len Using Data-Driven Prognostic Algorithms for Completing Independent Failure Analysis |
description |
ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada === Current failure analysis practices use diagnostic technology developed over the past 100 years of designing and manufacturing electrical and mechanical equipment to identify root cause of equipment failure requiring expertise with the equipment under analysis. If the equipment that failed had telemetry embedded, prognostic algorithms can be used to identify the deterministic behavior in completely normal appearing data from fully functional equipment used for identifying which equipment will fail within 1 year of use, can also identify when the presence of deterministic behavior was initiated for any equipment failure. |
author2 |
Failure Analysis |
author_facet |
Failure Analysis Losik, Len |
author |
Losik, Len |
author_sort |
Losik, Len |
title |
Using Data-Driven Prognostic Algorithms for Completing Independent Failure Analysis |
title_short |
Using Data-Driven Prognostic Algorithms for Completing Independent Failure Analysis |
title_full |
Using Data-Driven Prognostic Algorithms for Completing Independent Failure Analysis |
title_fullStr |
Using Data-Driven Prognostic Algorithms for Completing Independent Failure Analysis |
title_full_unstemmed |
Using Data-Driven Prognostic Algorithms for Completing Independent Failure Analysis |
title_sort |
using data-driven prognostic algorithms for completing independent failure analysis |
publisher |
International Foundation for Telemetering |
publishDate |
2011 |
url |
http://hdl.handle.net/10150/595768 |
work_keys_str_mv |
AT losiklen usingdatadrivenprognosticalgorithmsforcompletingindependentfailureanalysis |
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1718181965305217024 |