YOU Wen-jian, LIANG Bing, LI Yin-jun. Research of output characteristic fitting of eddy-current sensor based on radial-basis function neural network[J]. Journal of Mine Automation, 2013, 39(2): 47-50.
Citation: YOU Wen-jian, LIANG Bing, LI Yin-jun. Research of output characteristic fitting of eddy-current sensor based on radial-basis function neural network[J]. Journal of Mine Automation, 2013, 39(2): 47-50.

Research of output characteristic fitting of eddy-current sensor based on radial-basis function neural network

  • In view of problem that eddy-current sensor cannot reflect measured physical quantity accurately caused by higher nonlinear of output characteristic parameter, the paper proposed a scheme of using RBF neural network to fit output characteristic parameter of eddy-current sensor. The scheme uses newrb function to create RBF neural network, and takes measured physical quantity as input matrix and output of eddy-current sensor as output matrix to train the RBF neural network, so as to obtain low root-mean-square error and smooth output characteristic fitting curve of eddy-current sensor. The simulation result showed that RBF neural network can effectively realize fitting of output characteristic of eddy-current sensor by selecting proper creating function and expanding coefficient.
  • loading

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return