A compensation method of the offset thermal drift of sensor using the neural network algorithm

The problem of the offset thermal drift affects the measurement accuracy of pressure sensor in practical applications. To solve the problem, we proposed an approach of the non-linear compensation of pressure sensor using the neural network algorithm with Chebyshev basis functions. The convergence of...

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Bibliographic Details
Published in2008 9th International Conference on Signal Processing pp. 1716 - 1718
Main Authors Zhezhao Zeng, Lulu Zheng, Dongmei Ling
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2008
Subjects
Chebyshev approximation
Curve fitting
Error compensation
Least squares methods
Neural networks
Neurons
Polynomials
Temperature sensors
Thermal engineering
Thermal sensors
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Summary:The problem of the offset thermal drift affects the measurement accuracy of pressure sensor in practical applications. To solve the problem, we proposed an approach of the non-linear compensation of pressure sensor using the neural network algorithm with Chebyshev basis functions. The convergence of the neural network algorithm is researched. To validate the validity of the algorithm, the example of the offset thermal drift compensation of the pressure sensor was given. The simulation result shows that the non-linear compensation approach using the neural network algorithm has high compensation accuracy. Therefore, the method of the non-linear compensation proposed is effective.
ISBN:1424421780
9781424421787
ISSN:2164-5221
DOI:10.1109/ICOSP.2008.4697468