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Title: 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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