Industrial Process Surveillance System
Abstract
A system and method 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.
- Inventors:
-
- Bolingbrook, IL
- Glendale Heights, IL
- Naperville, IL
- Idaho Falls, ID
- Issue Date:
- Research Org.:
- Argonne National Laboratory (ANL), Argonne, IL (United States)
- OSTI Identifier:
- 879503
- Patent Number(s):
- 6181975
- Application Number:
- 09/028443
- Assignee:
- ARCH Development Corporation (Chicago, IL)
- Patent Classifications (CPCs):
-
G - PHYSICS G05 - CONTROLLING G05B - CONTROL OR REGULATING SYSTEMS IN GENERAL
- DOE Contract Number:
- W-31-109-ENG-38
- Resource Type:
- Patent
- Country of Publication:
- United States
- Language:
- English
Citation Formats
Gross, Kenneth C, Wegerich, Stephan W, Singer, Ralph M, and Mott, Jack E. Industrial Process Surveillance System. United States: N. p., 2001.
Web.
Gross, Kenneth C, Wegerich, Stephan W, Singer, Ralph M, & Mott, Jack E. Industrial Process Surveillance System. United States.
Gross, Kenneth C, Wegerich, Stephan W, Singer, Ralph M, and Mott, Jack E. Tue .
"Industrial Process Surveillance System". United States. https://www.osti.gov/servlets/purl/879503.
@article{osti_879503,
title = {Industrial Process Surveillance System},
author = {Gross, Kenneth C and Wegerich, Stephan W and Singer, Ralph M and Mott, Jack E},
abstractNote = {A system and method 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.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jan 30 00:00:00 EST 2001},
month = {Tue Jan 30 00:00:00 EST 2001}
}
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