Artificial Neural Network and the Taguchi Method Application for Robust Wheatstone Bridge Design
Abstract
The primary function of the Wheatstone bridge is to measure an unknown resistance. The elements of this well-known measurement circuit will take on different values depending upon the range and accuracy required for a particular application. The Taguchi approach to parameter design is used to select values for the measurement circuit elements so as to reduce measurement error. Next we introduce the use of an artificial neural network to extrapolate limited experimental results to predict system response over a wide range of applications. This approach can be employed for on-line quality control of the manufacture of such device.
Recommended Citation
Jung-Eui Hong et al., "Artificial Neural Network and the Taguchi Method Application for Robust Wheatstone Bridge Design," Proceedings of the ASME Design Engineering Technical Conference, pp. 37 - 41, article no. 0110, American Society of Mechanical Engineers, Jan 1994.
The definitive version is available at https://doi.org/10.1115/DETC1994-0110
Department(s)
Engineering Management and Systems Engineering
International Standard Book Number (ISBN)
978-079189768-3
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 American Society of Mechanical Engineers, All rights reserved.
Publication Date
01 Jan 1994
