skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

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:
;
Publication Date:
Research Org.:
Intellectual Assets LLC, Lake Tahoe, NV (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1163977
Patent Number(s):
8,892,478
Application Number:
13/803,436
Assignee:
Intellectual Assets LLC (Lake Tahoe, NV)
DOE Contract Number:  
FG02-04ER83949
Resource Type:
Patent
Resource Relation:
Patent File Date: 2013 Mar 14
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Bickford, Randall L, and Palnitkar, Rahul M. Adaptive model training system and method. United States: N. p., 2014. Web.
Bickford, Randall L, & Palnitkar, Rahul M. Adaptive model training system and method. United States.
Bickford, Randall L, and Palnitkar, Rahul M. 2014. "Adaptive model training system and method". United States. https://www.osti.gov/servlets/purl/1163977.
@article{osti_1163977,
title = {Adaptive model training system and method},
author = {Bickford, Randall L and Palnitkar, Rahul M},
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 = {},
url = {https://www.osti.gov/biblio/1163977}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Nov 18 00:00:00 EST 2014},
month = {Tue Nov 18 00:00:00 EST 2014}
}

Works referenced in this record:

System for monitoring an industrial process and determining sensor status
patent, October 1995


Surveillance of industrial processes with correlated parameters
patent, December 1996


Neural net controlled tag gas sampling system for nuclear reactors
patent, February 1997


Neural network based system for equipment surveillance
patent, April 1998


Industrial process surveillance system
patent, June 1998


System for monitoring an industrial or biological process
patent, June 1998


Ultrasensitive surveillance of sensors and processes
patent, November 1999


Dual sensitivity mode system for monitoring processes and sensors
patent, August 2000


Neuro-parity pattern recognition system and method
patent, September 2000


Self tuning system for industrial surveillance
patent, October 2000


Industrial process surveillance system
patent, January 2001


Ultrasensitive surveillance of sensors and processes
patent, March 2001


System for surveillance of spectral signals
patent, May 2001


System for surveillance of spectral signals
patent, April 2003


System for surveillance of spectral signals
patent, October 2004


System for surveillance of spectral signals
patent, February 2006


Generating an Interpretable Family of Fuzzy Partitions From Data
journal, June 2004


Real-time sensor validation for propulsion systems
conference, February 2013


A turbine engine real-time test data validation and analysis system, generation 1.0
conference, February 2013


Works referencing / citing this record:

Adaptive model training system and method
patent, November 2014