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Title: A universal, fault-tolerant, non-linear analytic network for modeling and fault detection

Conference ·
OSTI ID:5418765
 [1]; ; ; ;  [2]
  1. Advanced Modeling Techniques Corp., Idaho Falls, ID (United States)
  2. Argonne National Lab., Idaho Falls, ID (United States)

The similarities and differences of a universal network to normal neural networks are outlined. The description and application of a universal network is discussed by showing how a simple linear system is modeled by normal techniques and by universal network techniques. A full implementation of the universal network as universal process modeling software on a dedicated computer system at EBR-II is described and example results are presented. It is concluded that the universal network provides different feature recognition capabilities than a neural network and that the universal network can provide extremely fast, accurate, and fault-tolerant estimation, validation, and replacement of signals in a real system.

Research Organization:
Argonne National Lab., Idaho Falls, ID (United States)
Sponsoring Organization:
USDOE; USDOE, Washington, DC (United States)
DOE Contract Number:
W-31109-ENG-38
OSTI ID:
5418765
Report Number(s):
ANL/CP-75747; CONF-920538-14; ON: DE92011840
Resource Relation:
Conference: 8. power plant dynamics, control and testing symposium, Knoxville, TN (United States), 27-29 May 1992
Country of Publication:
United States
Language:
English