Expert system for testing industrial processes and determining sensor status

Gross, Kenneth C; Singer, Ralph M

Title: Expert system for testing industrial processes and determining sensor status

Abstract

A method and system for monitoring both an industrial process and a sensor. The method and system include determining a minimum number of sensor pairs needed to test the industrial process as well as the sensor for evaluating the state of operation of both. The technique further includes generating a first and second signal characteristic of an industrial process variable. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the pair 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:

Gross, Kenneth C ^[1]; Singer, Ralph M ^[2]

Bolingbrook, IL
Naperville, IL

Issue Date:: 1998-06-02

Research Org.:: Argonne National Lab. (ANL), Argonne, IL (United States)

OSTI Identifier:: 871601

Patent Number(s):: 5761090

Assignee:: University of Chicago (Chicago, IL)

Patent Classifications (CPCs):: G - PHYSICS G05 - CONTROLLING G05B - CONTROL OR REGULATING SYSTEMS IN GENERAL

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

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G - PHYSICS G05 - CONTROLLING G05B - CONTROL OR REGULATING SYSTEMS IN GENERAL
G05B2219/37326 - Automatic configuration of multisensor, adaptive, active sensing
G05B19/4184 - {characterised by fault tolerance, reliability of production system}
G05B2219/37325 - Multisensor integration, fusion, redundant

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
Y10S706/906 - Process plant

G - PHYSICS G05 - CONTROLLING G05B - CONTROL OR REGULATING SYSTEMS IN GENERAL
G05B2219/34048 - Fourier transformation, analysis, fft

Y - NEW / CROSS SECTIONAL TECHNOLOGIES Y02 - TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE Y02P - CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
Y02P90/02 - Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

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DOE Contract Number:: W-31109-ENG-38

Resource Type:: Patent

Country of Publication:: United States

Language:: English

Subject:: expert; testing; industrial; processes; determining; sensor; status; method; monitoring; process; minimum; pairs; evaluating; operation; technique; generating; signal; characteristic; variable; obtaining; signals; associated; physical; difference; function; obtained; arithmetic; pair; time; frequency; domain; transformation; obtain; fourier; modes; describing; composite; residual; subtracting; free; nonwhite; noise; analyzed; statistical; probability; ratio; nonwhite noise; signal characteristic; industrial processes; frequency domain; difference function; industrial process; residual function; probability ratio; process variable; composite function; signals associated; sensor status; statistical probability; obtain fourier; modes describing; domain transformation; dual function; fourier modes; arithmetic difference; physical variable; determining sensor; white noise; /714/706/

Citation Formats


                    Gross, Kenneth C, and Singer, Ralph M. Expert system for testing industrial processes and determining sensor status.  United States: N. p., 1998. 
        Web.

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                    Gross, Kenneth C, & Singer, Ralph M. Expert system for testing industrial processes and determining sensor status.  United States.

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                    Gross, Kenneth C, and Singer, Ralph M. Tue .  
        "Expert system for testing industrial processes and determining sensor status".  United States.  https://www.osti.gov/servlets/purl/871601.

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@article{osti_871601,

  title        = {Expert system for testing industrial processes and determining sensor status},

  author       = {Gross, Kenneth C and Singer, Ralph M},

  abstractNote = {A method and system for monitoring both an industrial process and a sensor. The method and system include determining a minimum number of sensor pairs needed to test the industrial process as well as the sensor for evaluating the state of operation of both. The technique further includes generating a first and second signal characteristic of an industrial process variable. After obtaining two signals associated with one physical variable, a difference function is obtained by determining the arithmetic difference between the pair 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         = {1998},

  month        = {6}

}

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Title: Expert system for testing industrial processes and determining sensor status

Abstract

Citation Formats

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

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

Sequential Probability Ratio Tests for Reactor Signal Validation and Sensor Surveillance Applications journal, August 1990

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
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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

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

Sequential Probability Ratio Tests for Reactor Signal Validation and Sensor Surveillance Applications
journal, August 1990