Dynamic data filtering system and method
Abstract
A computer-implemented dynamic data filtering system and method for selectively choosing operating data of a monitored asset that modifies or expands a learned scope of an empirical model of normal operation of the monitored asset while simultaneously rejecting operating data of the monitored asset that is indicative of excessive degradation or impending failure of the monitored asset, and utilizing the selectively chosen data for adaptively recalibrating the empirical model to more accurately monitor asset aging changes or operating condition changes of the monitored asset.
- Inventors:
- Issue Date:
- Research Org.:
- Intellectual Assets LLC, Lake Tahoe, NV, USA
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1129896
- Patent Number(s):
- 8712929
- Application Number:
- 12/798,128
- Assignee:
- Intellectual Assets LLC (Lake Tahoe, NV)
- Patent Classifications (CPCs):
-
G - PHYSICS G01 - MEASURING G01D - MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE
G - PHYSICS G05 - CONTROLLING G05B - CONTROL OR REGULATING SYSTEMS IN GENERAL
- DOE Contract Number:
- FG02-04ER83949
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING
Citation Formats
Bickford, Randall L, and Palnitkar, Rahul M. Dynamic data filtering system and method. United States: N. p., 2014.
Web.
Bickford, Randall L, & Palnitkar, Rahul M. Dynamic data filtering system and method. United States.
Bickford, Randall L, and Palnitkar, Rahul M. Tue .
"Dynamic data filtering system and method". United States. https://www.osti.gov/servlets/purl/1129896.
@article{osti_1129896,
title = {Dynamic data filtering system and method},
author = {Bickford, Randall L and Palnitkar, Rahul M},
abstractNote = {A computer-implemented dynamic data filtering system and method for selectively choosing operating data of a monitored asset that modifies or expands a learned scope of an empirical model of normal operation of the monitored asset while simultaneously rejecting operating data of the monitored asset that is indicative of excessive degradation or impending failure of the monitored asset, and utilizing the selectively chosen data for adaptively recalibrating the empirical model to more accurately monitor asset aging changes or operating condition changes of the monitored asset.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2014},
month = {4}
}
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