Title :
A Novel Method of Extending the Linearity Range of Linear Variable Differential Transformer Using Artificial Neural Network
Author :
Mishra, Saroj Kumar ; Panda, Ganapati ; Das, Debi Prasad
Author_Institution :
Polarizone Technol., Ampang, Malaysia
fDate :
4/1/2010 12:00:00 AM
Abstract :
This paper proposes a simple and novel method of designing and developing high-linearity linear variable differential transformer (LVDT)-based displacement sensing systems. Conventionally, precise adjustment of windings is made to enhance the linearity range of LVDTs. The tedious job of pitch adjustment of windings of LVDTs can be overcome by using the proposed method. A functional link artificial neural network has been successfully used in this paper for nonlinear compensation of the LVDT. The effectiveness of the proposed method is demonstrated through computer simulation with the experimental data of two different LVDT. The complete algorithm with the practical setup for the development of a linear LVDT is presented in this paper.
Keywords :
differential transformers; neural nets; power engineering computing; artificial neural network; computer simulation; displacement sensing systems; linear variable differential transformer; nonlinear compensation; Artificial neural network (ANN); functional link ANN (FLANN); linear variable differential transformer (LVDT); nonlinearity compensation; sensor nonlinearity;
Journal_Title :
Instrumentation and Measurement, IEEE Transactions on
DOI :
10.1109/TIM.2009.2031385