Nonlinear scaling of signals for intelligent analyzers

Operating conditions are often changing so strongly that the changes in nonlinearities must be taken into account. A nonlinear mapping has been developed to extract meanings of variables from measurement signals. The scaling function scale the real values of variables to the range of [-2, +2] which...

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Bibliographic Details
Main Author: Juuso, E.K.
Format: Conference Proceeding
Language:English
Subjects:
Adaptive control
Application software
Electrical equipment industry
Fuzzy logic
Intelligent sensors
MIMO
Nonlinear equations
Predictive models
Signal analysis
Signal mapping
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Summary:Operating conditions are often changing so strongly that the changes in nonlinearities must be taken into account. A nonlinear mapping has been developed to extract meanings of variables from measurement signals. The scaling function scale the real values of variables to the range of [-2, +2] which combines normal operation [-1, +1] with handling of warnings and alarms. The nonlinear scaling provides a practical basis for modeling nonlinear multivariable systems with linear methodologies. The approach improves understanding of the meaning of measurement values. The generalized approach is based on a more detailed analysis of the measurement distributions. This can be extended to various applications in digital signal processing
DOI:10.1109/WISP.2005.1531678