Close category search window
 

Linearizing E-Type Thermocouple Output Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference Systems

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

2 Author(s)
Dalkiran, I. ; Elektrik ve Elektron. Muhendisligi Bolumu, Erciyes Univ., Kayseri ; Danisman, K.

A high precision temperature measurement unit is designed in this study. Artificial intelligence and curve fitting techniques are used to linearize output of E-type thermocouple that is preferred due to wide operational range and high emf values. The experimental data that is essential to train and test ANN and ANFIS is obtained using Wavetek 9100 calibration unit. After the successful training completion, the temperature measurement unit is realized and ANN and ANFIS based real time temperature measurement is individually achieved using thermocouple output voltage

Published in:
Signal Processing and Communications Applications, 2006 IEEE 14th

Date of Conference: 17-19 April 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 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.