Temperature compensation for six-dimension force/torque sensor based on Radial Basis Function Neural Network

2014 ◽  
Author(s):  
Yongjun Sun ◽  
Yiwei Liu ◽  
Hong Liu
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Basis Function ◽  
Temperature Compensation ◽  
Torque Sensor ◽  
Radial Basis

A Method for Vibration-Cylinder Air-Pressure Sensor Temperature Compensation Based on Radial Basis Function (RBF) Neural Network

2012 ◽  
Vol 236-237 ◽  
pp. 1232-1237
Author(s):  
Yan Ren ◽  
Duan Xu ◽  
Fang Ling Qin
Keyword(s):  
Neural Network ◽  
Radial Basis Function ◽  
Pressure Sensor ◽  
Basis Function ◽  
Temperature Compensation ◽  
Rbf Neural Network ◽  
Air Pressure ◽  
Environment Temperature ◽  
Radial Basis ◽  
Sensor Temperature

There is a nonlinear measurement error of the vibration-cylinder air-pressure sensor when the environment temperature changes; To solve the problem, the paper carried out a research on vibration-cylinder air-pressure sensor temperature compensation based on radial basis function(RBF) neural network; The temperature error characteristics of the sensor was studied; The sensor temperature compensation of RBF neural network structures and algorithms was designed; The centers, variances, weights, and the hidden layer neuron number of the radial basis function were determined. The experiments showed that the trained RBF neural network can approximate the input-output relationship of the vibration-cylinder air-pressure sensor in high accuracy.

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