Cart (Loading....) | Create Account
Close category search window

Applying Radial Basis Function Neural Network to Data Fusion for Temperature Compensation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Zhun Yu ; Dept. of Power Eng., North China Electr. Power Univ., Baoding ; You-Yin Jing ; Ying-Bai Xie ; Cheng Tian

In order to decrease the impact of environmental temperature on pressure transducer measurements with temperature compensation, a new method of data fusion based on radial basis function (RBF) neural network was proposed, at the same period, a practical test was carried out with the environmental temperature ranging from 10 to 60 degC and the pressure as 15 kPa. The results of the investigation showed that the relational curves between output voltage of the transducer and environmental temperature was horizontal after compensation, and the convergency of RBF neural network was faster than BP neural network, in addition, the maximum difference of the output voltage before compensation was 9.48 mv while it was 0.03 mv after compensation. The results of the present work implied that the objective of temperature compensation has been achieved essentially, furthermore, RBF neural network was better than BP neural network while used on temperature compensation to pressure transducers and the influence of temperature variation could be greatly reduced

Published in:

Machine Learning and Cybernetics, 2006 International Conference on

Date of Conference:

13-16 Aug. 2006

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.