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Title: Adaptive model training system and method

Abstract

An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.

Inventors:
; ;
Issue Date:
Research Org.:
Intellectual Assets LLC, Lake Tahoe, NV, USA
Sponsoring Org.:
USDOE
OSTI Identifier:
1129186
Patent Number(s):
8700550
Application Number:
12/798,152
Assignee:
Intellectual Assets LLC (Lake Tahoe, NV)
Patent Classifications (CPCs):
G - PHYSICS G01 - MEASURING G01K - MEASURING TEMPERATURE
G - PHYSICS G01 - MEASURING G01N - INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
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, Palnitkar, Rahul M, and Lee, Vo. Adaptive model training system and method. United States: N. p., 2014. Web.
Bickford, Randall L, Palnitkar, Rahul M, & Lee, Vo. Adaptive model training system and method. United States.
Bickford, Randall L, Palnitkar, Rahul M, and Lee, Vo. Tue . "Adaptive model training system and method". United States. https://www.osti.gov/servlets/purl/1129186.
@article{osti_1129186,
title = {Adaptive model training system and method},
author = {Bickford, Randall L and Palnitkar, Rahul M and Lee, Vo},
abstractNote = {An adaptive model training system and method for filtering asset operating data values acquired from a monitored asset for selectively choosing asset operating data values that meet at least one predefined criterion of good data quality while rejecting asset operating data values that fail to meet at least the one predefined criterion of good data quality; and recalibrating a previously trained or calibrated model having a learned scope of normal operation of the asset by utilizing the asset operating data values that meet at least the one predefined criterion of good data quality for adjusting the learned scope of normal operation of the asset for defining a recalibrated model having the adjusted learned scope of normal operation of the asset.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Apr 15 00:00:00 EDT 2014},
month = {Tue Apr 15 00:00:00 EDT 2014}
}

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