DOE Patents title logo U.S. Department of Energy
Office of Scientific and Technical Information

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 Laboratory (ANL), Argonne, IL (United States)
OSTI Identifier:
869855
Patent Number(s):
5410492
Assignee:
ARCH Development Corporation (Chicago, IL)
Patent Classifications (CPCs):
G - PHYSICS G05 - CONTROLLING G05B - CONTROL OR REGULATING SYSTEMS IN GENERAL
G - PHYSICS G21 - NUCLEAR PHYSICS G21C - NUCLEAR REACTORS
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 = {Sun Jan 01 00:00:00 EST 1995},
month = {Sun Jan 01 00:00:00 EST 1995}
}

Works referenced in this record:

Signal validation with control-room information-processing computers
journal, January 1985


A Methodology for the Design and Analysis of a Sensor Failure Detection Network
journal, January 1993


An Integrated Signal Validation System for Nuclear Power Plants
journal, December 1990


Fault detection method using power supply spectrum analysis
journal, January 1990


Microcomputer-based fault detection using redundant sensors
journal, January 1988


Process hypercube comparison for signal validation
journal, April 1991


Algorithm-based fault detection for signal processing applications
journal, January 1990


4. Knowledge-based systems in process fault diagnosis
journal, April 1989


Early fault detection and diagnosis in Finnish nuclear power plants
journal, January 1988


Power Signal Validation for Taiwan Research Reactor
journal, January 1989


Instrument Fault Detection in a Pressurized Water Reactor Pressurizer
journal, January 1982


Construction and evaluation of fault detection network for signal validation
journal, January 1992


Signal validation techniques and power plant applications
journal, January 1988


An Expert System for Sensor Data Validation and Malfunction Detection
book, January 1988


On-Line Test of Signal Validation Software on the LOBI-MOD2 Facility in Ispra, Italy
journal, January 1992