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Proceedings Paper

Nonlinear identification of eddy current sensors based on artificial neural networks
Author(s): Hairong Zou
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Paper Abstract

The nonlinear identification of the input-output characteristic of the eddy current sensor is an important research task in the application of the eddy current sensor. At first, the working principle and the working characteristics of the eddy current sensor were introduced in this paper. Then the nonlinear identification of the eddy current sensor was analyzed in detail. To aim at the error problem of the eddy current sensor with the nonlinear factors, a feasible project of nonlinear identification of the eddy current sensor was researched applied the modeling method of artificial neural networks, and a new artificial neural network is presented to realize the nonlinear identification of the eddy current sensor without linearization processing. Its design, modeling and implement technology based on a new internal recurrent neural networks were advanced, and then the data experiments were processed with MATLAB software, thus the measure precision of the eddy current sensor was enhanced. In the end, the measuring error is no more than 0.1%, and the dynamic responding time is less than 0.5 second. This method can increase the measuring accuracy and be advantageous for the test analysis and the data statistics though the online data processing of the computer.

Paper Details

Date Published: 31 December 2008
PDF: 6 pages
Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 713013 (31 December 2008); doi: 10.1117/12.819577
Show Author Affiliations
Hairong Zou, Shanghai Dian Ji Univ. (China)


Published in SPIE Proceedings Vol. 7130:
Fourth International Symposium on Precision Mechanical Measurements
Yetai Fei; Kuang-Chao Fan; Rongsheng Lu, Editor(s)

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