| Título: | APSO-RBF Nonlinear Calibration Method in Carbon Anode Baking Temperature Measurement |
| Autores: |
Xiaobin, Li; Shanghai Institute of Technology Haiyan, Sun; Shanghai Institute of Technology Congdao, Han; Shanghai Institute of Technology Jie, Zhang; CECEP Wind-Power(Xinjiang)Corporation |
| Fecha: | 2013-05-01 |
| Publicador: | TELKOMNIKA: Indonesian journal of electrical engineering |
| Fuente: |
 |
| Tipo: |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| Tema: | No aplica |
| Descripción: | 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. |
| Idioma: | Inglés |