System for monitoring an industrial process and determining sensor status
Abstract
A method and system for monitoring an industrial process and a sensor. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test.
 Inventors:

 Bolingbrook, IL
 Chicago, IL
 Columbia, MD
 Issue Date:
 Research Org.:
 Argonne National Lab. (ANL), Argonne, IL (United States)
 OSTI Identifier:
 870122
 Patent Number(s):
 5459675
 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 CROSSREFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
 DOE Contract Number:
 W31109ENG38
 Resource Type:
 Patent
 Country of Publication:
 United States
 Language:
 English
 Subject:
 monitoring; industrial; process; determining; sensor; status; method; generating; signal; characteristic; variable; signals; artificial; generated; auto; regressive; moving; average; technique; obtaining; associated; physical; difference; function; obtained; arithmetic; pairs; time; frequency; domain; transformation; obtain; fourier; modes; describing; composite; residual; subtracting; free; nonwhite; noise; analyzed; statistical; probability; ratio; nonwhite noise; signal characteristic; frequency domain; difference function; signal generated; industrial process; residual function; probability ratio; process variable; composite function; signals associated; sensor status; artificial signal; average technique; moving average; statistical probability; obtain fourier; modes describing; domain transformation; dual function; fourier modes; arithmetic difference; physical variable; regressive moving; determining sensor; white noise; /702/376/706/
Citation Formats
Gross, Kenneth C, Hoyer, Kristin K, and Humenik, Keith E. System for monitoring an industrial process and determining sensor status. United States: N. p., 1995.
Web.
Gross, Kenneth C, Hoyer, Kristin K, & Humenik, Keith E. System for monitoring an industrial process and determining sensor status. United States.
Gross, Kenneth C, Hoyer, Kristin K, and Humenik, Keith E. Sun .
"System for monitoring an industrial process and determining sensor status". United States. https://www.osti.gov/servlets/purl/870122.
@article{osti_870122,
title = {System for monitoring an industrial process and determining sensor status},
author = {Gross, Kenneth C and Hoyer, Kristin K and Humenik, Keith E},
abstractNote = {A method and system for monitoring an industrial process and a sensor. The method and system include generating a first and second signal characteristic of an industrial process variable. One of the signals can be an artificial signal generated by an auto regressive moving average technique. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the two pairs of signals over time. A frequency domain transformation is made of the difference function to obtain Fourier modes describing a composite function. A residual function is obtained by subtracting the composite function from the difference function and the residual function (free of nonwhite noise) is analyzed by a statistical probability ratio test.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1995},
month = {1}
}