Study on the Modeling of Main Mine Ventilator Based on Artificial Intelligence

Xin Hui Du; Shu Niu; Xing Min Wang; Pu Hui Wang

doi:10.4028/www.scientific.net/AMM.130-134.3526

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 130-134Study on the Modeling of Main Mine Ventilator...

Study on the Modeling of Main Mine Ventilator Based on Artificial Intelligence

Abstract:

The parameters of main ventilator in mine such as air flow, wind speed, gas concentration and other conditions are closely related, for its complexity, it’s difficult to establish the nonlinear mathematic model, and it’s hard describe the model properties by traditional identification method. Neural network and Fuzzy system are used in mine main ventilator model identification. A Neural network based on RBF is used in neural network, and a T-S fuzzy model based on triangle membership function is used in Fuzzy identification. The simulation results show that the two methods can satisfy the needs of identification precision, convergence rate, stability and tracking ability simultaneous.

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Periodical:

Applied Mechanics and Materials (Volumes 130-134)

Pages:

3526-3530

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.130-134.3526

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Online since:

October 2011

Authors:

Xin Hui Du, Shu Niu, Xing Min Wang, Pu Hui Wang

Keywords:

RBF Neural Network, System Identification, T-S Model, Ventilator Model

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