Research on Predictive Model of Gas Concentration for Driving Ventilation in Coal Mine Based on Neural Network

Abstract:

In order to predict accurately gas concentration in driving ventilation process under different gas emission and different ventilation scheme conditions in coal mine, based on the analysis of various ventilation factors, the prediction model structure of gas concentration of driving ventilation was designed based on RBF neural network in this paper. Then MATLAB software and the observation data obtained from the coal mine sites were used to establish and test the prediction models of gas concentration in driving ventilation process based RBF. And then the better accuracy and performance prediction model based on RBF were obtained through testing and comparative analysis. Finally, the prediction model of gas concentration was applied to forecast gas concentration of heading face under different driving ventilation equipment layout and configuration parameters in the actual coal mine and then confirm the reasonable effective and energy-saving driving ventilation equipment layout and configuration parameter scheme. The research results can provide a certain theory basis for dynamics prediction of gas concentration and ventilation scheme optimization in the driving ventilation process.

• Periodical: Applied Mechanics and Materials (Volumes 295-298)
• Pages: 2997-3000
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.295-298.2997
• Online since: February 2013
• Authors: Xiao Yan Gong*, Jun Guo, Dong Hui Yan, Zhe Wu, He Xue
• Keywords: Driving Ventilation, Gas Concentration, Prediction Model, RBF Neural Network

References

[1] Xiaoyan Gong, Yage Dang. Analysis of vibration modals of blade of FBD series local fan used in mine. Mining & Processing Equipment, 2010, 12(38): 54-57.

[2] Jianjun Cheng, Yougen Jia, Shaoren Cheng. Problems and solutions in head ventilation[J]. Safety & Environmental Protection, 2005, 32(1): 72-75.

[3] Haijiang Chan, Guoshan Wei. Talk about local ventilation in heading face[J]. Heilongjiang Science and Technology Information, 2010, 96(10): 1.

[4] Wenguang Hou. Analysis and application of gas concentration law from heading face in Liyazhuang Mine[J]. Shanxi coal, 2010, 20(2): 52-55.

[5] Zhuxiang Hu, Baishun Wang. Research on a point gas concentration in heading face[J]. Coal Science and Technology in shandong, 2005, 25(5): 67-69.

[6] Xiaoyan Gong. The local ventilation system reliability assessment and enhancement measures in mine[D]. Journal, Xi'an Mining Institute, (1993).

[7] Xiaoyan Gong Fault diagnosis approach of local ventilation system in coal mines based on multidisciplinary technology. Chinese Journal of Mining Sciences & Technology (English Edition), 2006, 9, 16(3): 317-320.