Diagnosing process faults using neural network models [electronic resource].
- Published:
- Washington, D.C. : United States. Dept. of Energy, 1993.
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy. - Physical Description:
- 10 pages : digital, PDF file
- Additional Creators:
- Los Alamos National Laboratory
United States. Department of Energy
United States. Department of Energy. Office of Scientific and Technical Information - Access Online:
- www.osti.gov
- Summary:
- In order to be of use for realistic problems, a fault diagnosis method should have the following three features. First, it should apply to nonlinear processes. Second, it should not rely on extensive amounts of data regarding previous faults. Lastly, it should detect faults promptly. The authors present such a scheme for static (i.e., non-dynamic) systems. It involves using a neural network to create an associative memory whose fixed points represent the normal behavior of the system.
- Subject(s):
- Note:
- Published through SciTech Connect.
11/01/1993.
"la-ur--93-3598"
" conf-9309272--1"
"DE94002633"
Allerton conference on communication, control, and computing,Urbana, IL (United States),29 Sep - 1 Oct 1993.
Jones, R.D.; Buescher, K.L.; Messina, M.J. - Funding Information:
- W-7405-ENG-36
View MARC record | catkey: 14114208