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Title: Automated method for the systematic interpretation of resonance peaks in spectrum data

A method is described for spectral signature interpretation. The method includes the creation of a mathematical model of a system or process. A neural network training set is then developed based upon the mathematical model. The neural network training set is developed by using the mathematical model to generate measurable phenomena of the system or process based upon model input parameter that correspond to the physical condition of the system or process. The neural network training set is then used to adjust internal parameters of a neural network. The physical condition of an actual system or process represented by the mathematical model is then monitored by extracting spectral features from measured spectra of the actual process or system. The spectral features are then input into said neural network to determine the physical condition of the system or process represented by the mathematical model. More specifically, the neural network correlates the spectral features (i.e. measurable phenomena) of the actual process or system with the corresponding model input parameters. The model input parameters relate to specific components of the system or process, and, consequently, correspond to the physical condition of the process or system. 1 fig.
Inventors:
;
Issue Date:
OSTI Identifier:
504940
Assignee:
Martin Marietta Energy Systems, Inc., Oak Ridge, TN (United States) PTO; SCA: 990200; PA: EDB-97:104363; SN: 97001815614
Patent Number(s):
US 5,623,579/A/
Application Number:
PAN: 8-443,292
Contract Number:
AC05-84OR21400
Resource Relation:
Other Information: PBD: 22 Apr 1997
Research Org:
Lockheed Martin Energy Syst Inc
Country of Publication:
United States
Language:
English
Subject:
99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; NEURAL NETWORKS; SPECTRA; MATHEMATICAL MODELS; TRAINING; RESONANCE; DATA ANALYSIS; AUTOMATION