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Title: Processing data base information having nonwhite noise

Abstract

A method and system for processing a set of data from an industrial process and/or a sensor. The method and system can include processing data from either real or calculated data related to an industrial process variable. One of the data sets can be an artificial signal data set generated by an autoregressive moving average technique. After obtaining two data sets associated with one physical variable, a difference function data set is obtained by determining the arithmetic difference between the two pairs of data sets over time. A frequency domain transformation is made of the difference function data set to obtain Fourier modes describing a composite function data set. A residual function data set is obtained by subtracting the composite function data set from the difference function data set and the residual function data set (free of nonwhite noise) is analyzed by a statistical probability ratio test to provide a validated data base.

Inventors:
 [1];  [2]
  1. Bolingbrook, IL
  2. Park Ridge, IL
Issue Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
OSTI Identifier:
869855
Patent Number(s):
5410492
Assignee:
ARCH Development Corporation (Chicago, IL)
Patent Classifications (CPCs):
Y - NEW / CROSS SECTIONAL TECHNOLOGIES Y02 - TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE Y02E - REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
Y - NEW / CROSS SECTIONAL TECHNOLOGIES Y10 - TECHNICAL SUBJECTS COVERED BY FORMER USPC Y10S - TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
DOE Contract Number:  
W-31109-ENG-38
Resource Type:
Patent
Country of Publication:
United States
Language:
English
Subject:
processing; data; base; information; nonwhite; noise; method; set; industrial; process; sensor; calculated; related; variable; sets; artificial; signal; generated; autoregressive; moving; average; technique; obtaining; associated; physical; difference; function; obtained; determining; arithmetic; pairs; time; frequency; domain; transformation; obtain; fourier; modes; describing; composite; residual; subtracting; free; analyzed; statistical; probability; ratio; provide; validated; nonwhite noise; data base; frequency domain; difference function; data set; industrial process; residual function; probability ratio; process variable; composite function; data sets; artificial signal; processing data; average technique; moving average; statistical probability; obtain fourier; modes describing; domain transformation; dual function; fourier modes; arithmetic difference; physical variable; regressive moving; white noise; data related; /702/376/706/

Citation Formats

Gross, Kenneth C, and Morreale, Patricia. Processing data base information having nonwhite noise. United States: N. p., 1995. Web.
Gross, Kenneth C, & Morreale, Patricia. Processing data base information having nonwhite noise. United States.
Gross, Kenneth C, and Morreale, Patricia. Sun . "Processing data base information having nonwhite noise". United States. https://www.osti.gov/servlets/purl/869855.
@article{osti_869855,
title = {Processing data base information having nonwhite noise},
author = {Gross, Kenneth C and Morreale, Patricia},
abstractNote = {A method and system for processing a set of data from an industrial process and/or a sensor. The method and system can include processing data from either real or calculated data related to an industrial process variable. One of the data sets can be an artificial signal data set generated by an autoregressive moving average technique. After obtaining two data sets associated with one physical variable, a difference function data set is obtained by determining the arithmetic difference between the two pairs of data sets over time. A frequency domain transformation is made of the difference function data set to obtain Fourier modes describing a composite function data set. A residual function data set is obtained by subtracting the composite function data set from the difference function data set and the residual function data set (free of nonwhite noise) is analyzed by a statistical probability ratio test to provide a validated data base.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1995},
month = {1}
}

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