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Title: Industrial process surveillance system

Abstract

A system and method are disclosed for monitoring an industrial process and/or industrial data source. The system includes generating time varying data from industrial data sources, processing the data to obtain time correlation of the data, determining the range of data, determining learned states of normal operation and using these states to generate expected values, comparing the expected values to current actual values to identify a current state of the process closest to a learned, normal state; generating a set of modeled data, and processing the modeled data to identify a data pattern and generating an alarm upon detecting a deviation from normalcy. 96 figs.

Inventors:
; ; ;
Issue Date:
Research Org.:
Univ. of Chicago, IL (United States)
Sponsoring Org.:
USDOE, Washington, DC (United States)
OSTI Identifier:
672541
Patent Number(s):
5764509
Application Number:
PAN: 8-666,938
Assignee:
Univ. of Chicago, IL (United States)
DOE Contract Number:  
W-31109-ENG-38
Resource Type:
Patent
Resource Relation:
Other Information: PBD: 9 Jun 1998
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; INDUSTRIAL PLANTS; MONITORING; PROCESS CONTROL; DATA ANALYSIS; DATA ACQUISITION SYSTEMS; OPERATION; ALARM SYSTEMS

Citation Formats

Gross, K C, Wegerich, S W, Singer, R M, and Mott, J E. Industrial process surveillance system. United States: N. p., 1998. Web.
Gross, K C, Wegerich, S W, Singer, R M, & Mott, J E. Industrial process surveillance system. United States.
Gross, K C, Wegerich, S W, Singer, R M, and Mott, J E. Tue . "Industrial process surveillance system". United States.
@article{osti_672541,
title = {Industrial process surveillance system},
author = {Gross, K C and Wegerich, S W and Singer, R M and Mott, J E},
abstractNote = {A system and method are disclosed for monitoring an industrial process and/or industrial data source. The system includes generating time varying data from industrial data sources, processing the data to obtain time correlation of the data, determining the range of data, determining learned states of normal operation and using these states to generate expected values, comparing the expected values to current actual values to identify a current state of the process closest to a learned, normal state; generating a set of modeled data, and processing the modeled data to identify a data pattern and generating an alarm upon detecting a deviation from normalcy. 96 figs.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1998},
month = {6}
}