Study on the Energy Saving of Mine Ventilator Based on Artificial Intelligence Control System

Author

Xinhui Du ; Song, Jiancheng ; Zhu, Shanjun

Author_Institution

Coll. of Electr. & Power Eng., Taiyuan Univ. of Technol., Taiyuan, China

fYear

2010

fDate

25-27 June 2010

Firstpage

2154

Lastpage

2157

Abstract

Radial Basis Function(RBF) is used to identify the model of mine ventilator, frequency control system is introduced to control the speed of ventilator, and traditional control strategy used PID is replaced by FNN. The MATLAB simulation results show that the ventilator modeling by RBF neural network can better reflect its nonlinear characteristic, the speed of ventilator controlled by FNN changed with the gas´s concentration. The paper take a mine of Shanxi for example to calculate the energy saving index, the result reveals it has produced not only direct economic benefit but also great social and environmental benefit.

Keywords

frequency control; mining; neurocontrollers; radial basis function networks; velocity control; ventilation; RBF neural network; artificial intelligence control system; energy saving; frequency control system; mine ventilator; radial basis function network; ventilator speed; Artificial neural networks; Biological system modeling; Control systems; Fuel processing industries; Fuzzy control; MATLAB; Mathematical model; FNN control; energy saving; mine ventilator; radial neural network;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Control Engineering (ICECE), 2010 International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-6880-5

Type

conf

DOI

10.1109/iCECE.2010.530

Filename

5631744