Paper Title:
Study on Support Vector Machine Based on Nonlinear Correction of Double Parallel Beam Weighing Transducer
  Abstract

According to the non-linear problem caused by temperature and circuit interference during the detection process of the double parallel beam weighing transducer, a nonlinear compensation method is proposed based on the support vector machine theory. The nonlinear characteristics of measured values of sensor are analyzed, and the support vector machine (SVM) inverse model is established while the displacement parameters as the output and voltage parameter as input. The effectiveness of SVM inverse model is verified by the simulation. Compared with the RBF neural network model, the SVM model is efficiency. The average error of the model prediction is 0.027g mm, so it has good linearity, and nonlinear compensation of the double Parallel beam weighing transducer is realized.

  Info
Periodical
Chapter
Chapter 4: Mechatronics and Information
Edited by
Dongye Sun, Wen-Pei Sung and Ran Chen
Pages
2299-2303
DOI
10.4028/www.scientific.net/AMM.121-126.2299
Citation
L. H. Zhao, K. Q. Wang, Y. H. Xie, "Study on Support Vector Machine Based on Nonlinear Correction of Double Parallel Beam Weighing Transducer", Applied Mechanics and Materials, Vols. 121-126, pp. 2299-2303, 2012
Online since
October 2011
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