APSO-RBF Nonlinear Calibration Method in Carbon Anode Baking Temperature Measurement

Li Xiaobin, Sun Haiyan, Han Congdao, Zhang Jie

Abstract


A correcting nonlinear errors of the thermocouple sensor based on Radial Basis Function Neural Network using particle swarm optimization are introduced. It solves t he shortcoming of Thermocouple Sensor’s application on large data. The result of experiment shows that the nonlinear calibration based on APSO-RBF has higher precision than the method based on RBF and ANFIS. Then, APSO-RBF is used to test fire path temperature in the anode baking. It is proved that the method is effective.

 

DOI: http://dx.doi.org/10.11591/telkomnika.v11i5.2463


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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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