Abstract This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network (GNN) according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness, on-line modelling and high precision. The maximum nonlinearity error can be reduced to 0.037% by using GNN. However, the maximum nonlinearity error is 0.075% using the least square method.
Received: 15 July 2007
Revised: 22 August 2007
Accepted manuscript online:
(Electrical and electronic instruments and components)
Fund: Project supported by the Natural
Science Foundation of the Higher Education Institutions of Jiangsu
Province, China and by the Foundation of Huaiyin Teachers College
Professor, China (Grant Nos 07KJD510027 and 06HSJS020).
Cite this article:
Yu A-Long(俞阿龙) Numeral eddy current sensor modelling based on genetic neural network 2008 Chin. Phys. B 17 878
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