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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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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description 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_str_mv 10.1109/WISP.2005.1531678
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source IEEE Electronic Library (IEL) Conference Proceedings
subjects Adaptive control
Application software
Electrical equipment industry
Fuzzy logic
Intelligent sensors
MIMO
Nonlinear equations
Predictive models
Signal analysis
Signal mapping
title Nonlinear scaling of signals for intelligent analyzers
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