Research on the Prediction of CO Concentration in Single-head Roadway Based on Curve Fitting and Neural Network
Received date: 2023-07-31
Revised date: 2023-11-07
Online published: 2024-03-22
In order to realize the prediction of CO concentration in the single-head roadway of the mine，based on the monitoring data of CO concentration in the heading face of the single-head roadway in the 1800 transport lane of Laochang tin mine in Yunnan Province.Firstly，the MATLAB curve fitting toolbox was used to fit the curve of the change of CO concentration with time in the single-head roadway，and the mathematical model of the change of CO concentration with time in the single-head roadway of the mine was established.Through the model，the time required for the CO concentration value in the single-head roadway of the mine to reach the CO concentration value required by the safety regulations was obtained.Then，the convolutional neural network time series prediction model（CNN model） and the BP neural network time series prediction model（BP model） were used to predict the CO concentration，and the two evaluation indexes of R2 and RMSE were compared.The results show that the BP neural network time series prediction model has the better prediction effect on the CO concentration of the single-head roadway，which provides an accurate and reliable theoretical basis for the monitoring and control of the CO concentration value of the single-head roadway in the mine.
Changwei ZHOU , Xianping XIE , Xidong DU . Research on the Prediction of CO Concentration in Single-head Roadway Based on Curve Fitting and Neural Network[J]. Gold Science and Technology, 2024 , 32(1) : 75 -81 . DOI: 10.11872/j.issn.1005-2518.2024.01.108
| null | Adedipupo O O， Ayodele A A， Abideen L T，et al，2022.Detection of appropriate model for nigeria population growth using Root Mean Square Error （RMSE）［J］.International Journal of Systems Science and Applied Mathematics，7（3）：46-51. |
| null | Cao Y， Ji H， Zhang Y，et al，2018.Study on distribution of CO and concentration prediction in blind gallery after blasting operation［J］.Archives of Mining Sciences，63（2）：283-300. |
| null | Chen Chao， Nie Hexiang， Li Qiong，et al，2022.Prediction model of CO pollutant concentration distribution characteristics in urban underground roads based on traffic wind conditions［J］.China Journal of Highway，35 （5）：161-169. |
| null | Gao Qiuying， Wang Lili， Wang Rongzhong，2021.Research on least squares curve fitting and optimization algorithm［J］.Industrial Control Computer，34 （11）：100-101. |
| null | Ji Hongguang， Cao Yang， Zhang Ge，et al，2014.Prediction of smoke exhaust time during excavation of single-head roadway［J］.Metal Mine，43（5）：142-145. |
| null | Gong Xiaoyan， Sun Yuheng， Liu Zhuangzhuang，et al，2023.Study on airflow intelligent control model of fully mechanized heading face based on BP neuralnet work［J］.Safety and Environmental Engineering，30（30）：138-145. |
| null | Jiang Feng， Han Xingyu， Wang Hui，2023.Prediction of PM2.5 concentration in Yangtze River Economic Belt based on graph neural network［J］.Environmental Science and Te-chnology，46（11）：90-101. |
| null | Li Peng， Duan Shuqing， Wang Kun，et al，2014.Grey model and curve fitting settlement prediction and correlation analysis［J］.Journal of Underground Space and Engineering，10 （1）：109-115. |
| null | Yanhong Lü， Wang Qin，2013.Research on tunnel CO concentration prediction based on neural network information fusion［J］.Information Technology，37 （9）：128-131. |
| null | Piepho H P，2019.An adjusted coefficient of determination （R2） for generalized linear mixed models in one go［J］.Biometrical Journal，61（4）：860-872. |
| null | Shi Xiuzhi， Fan Yuqian， Shang Xueyi，2016.Filling strength prediction based on PCA-BP neural network model［J］.Gold Science and Technology，24（3）：64-69. |
| null | Wang Shibin， Chen Rihui， Liu Shitao，et al，2014.Analysis and prediction of CO concentration change after blasting in heading face ［J］.Science and Technology and Engineering，14 （6）：101-103，107. |
| null | Wu F， Shi S， Lu Y，et al，2023.Analysis of CO source and prediction model of gushing concentration at the return air corner of working face in shallow coal seam mine［J］.Combustion Science and Technology：1-16. |
| null | Wu Min， Pan Chunrong，2023.Application of one-dimensional convolutional neural network in magnetite separation［J / OL］.Nonferrous Metals（Mineral Processing Section）： 1-6［2023-07-28 ］. |
| null | Wu Y， Zhang Y， Zhou C，et al，2021.Study of CO sources and early-warning concentration of spontaneous combustion at air return corner in fully mechanized mining faces［J］.Combustion Science and Technology，193（9）：1587-1604. |
| null | Xie Raoqing， Chen Jianhong， Xiao Wenfeng，2022.Prediction method of stope stability based on NPCA-GA-BP neural network［J］.Gold Science and Technology，30（2）：272-281. |
| null | Yang Tingting， Gao Qian， Li Haoqian，et al，2022.Fault warning of coal mill based on convolutional neural network-long short-term memory neural network［J］.Thermal Power Generation，51（10）：122-129. |
| null | Zeng Junhui， Li Xibing，2019.Prediction of mine subsidence area based on chaotic time series analysis method ［J］.Gold Science and Technology，27 （2）：249-256. |
| null | Zhai Xiaowei， Ma Lingjun， Deng Jun，2011.Research and application of CO concentration prediction model in upper corner of working face［J］.Coal Science and Technology，39 （11）：59-62. |
| null | Zhang Ge， Cao Yang， Ji Hongguang，et al，2014.Model test study on the emission law and concentration prediction of gun smoke in single-head roadway［J］.Modern Tunnel Te-chnology，51（4）：150-154. |
| null | Zhang Zhigang， Xu Ying， Zhang Jinqiu，et al，2022.Prediction model of CO gas concentration in highway tunnel based on random forest［J］.Science and Technology and Engineering，22 （26）：11729-11735. |
| null | Zhou Kaihong， Ran Hongmei， Jiang Qinggu，et al，2023.Nonlinear error compensation of digital dial gauge based on improved BP neural network［J］.Modern Manufacturing Engineering，（7 ）：117-122. |
| null | 陈超，聂鹤翔，李琼，等，2022.基于交通风条件多点进出城市地下道路CO污染物浓度分布特性预测模型［J］.中国公路学报，35（5）：161-169. |
| null | 高秋英，王丽丽，王荣忠，2021.最小二乘法曲线拟合及优化算法研究［J］.工业控制计算机，34（11）：100-101. |
| null | 纪洪广，曹杨，张舸，等，2014.独头巷道掘进过程中排烟时间预测［J］.金属矿山，43（5）：142-145. |
| null | 龚晓燕，孙育恒，刘壮壮，等，2023.基于BP神经网络的煤矿综掘面风流智能调控模型研究 ［J］.安全与环境工程，30（30）：138-145. |
| null | 蒋锋，韩兴钰，王辉，2023.基于图神经网络的长江流域经济带PM2.5浓度预测［J］.环境科学与技术，46（11）：90-101. |
| null | 李篷，段淑清，王堃，等，2014.灰色模型与曲线拟合沉降预测及相关性分析［J］.地下空间与工程学报，10（1）：109-115. |
| null | 吕燕红，王芹，2013.基于神经网络信息融合隧道CO浓度预测研究［J］.信息技术，37（9）：128-131. |
| null | 史秀志，范玉乾，尚雪义，2016.基于PCA-BP神经网络模型的充填体强度预测［J］.黄金科学技术，24（3）：64-69. |
| null | 王时彬，陈日辉，刘世涛，等，2014.独头掘进面爆破后CO浓度变化分析及预测［J］.科学技术与工程，14（6）：101-103，107. |
| null | 吴敏，潘春荣，2023.一维卷积神经网络在磁铁矿分选中的应用［J/OL］.有色金属（选矿部分）：1-6［2023-07-28］. |
| null | 谢饶青，陈建宏，肖文丰，2022.基于NPCA-GA-BP神经网络的采场稳定性预测方法［J］.黄金科学技术，30（2）：272-281. |
| null | 杨婷婷，高乾，李浩千，等，2022.基于卷积神经网络—长短时记忆神经网络的磨煤机故障预警［J］.热力发电，51（10）：122-129. |
| null | 曾俊晖，李夕兵，2019.基于混沌时间序列分析方法的矿山塌陷区范围预测［J］.黄金科学技术，27（2）：249-256. |
| null | 翟小伟，马灵军，邓军，2011.工作面上隅角CO浓度预测模型的研究与应用［J］.煤炭科学技术，39（11）：59-62. |
| null | 张舸，曹杨，纪洪广，等，2014.独头巷道中炮烟散发规律及浓度预测模型试验研究［J］.现代隧道技术，51（4）：150-154. |
| null | 张志刚，徐莹，张锦秋，等，2022.基于随机森林的公路隧道CO气体浓度预测模型［J］.科学技术与工程，22（26）：11729-11735. |
| null | 周凯红，冉红梅，蒋青谷，等，2023.基于改进BP神经网络的数显千分表非线性误差补偿［J］.现代制造工程，（7）：117-122. |
/
| 〈 |
|
〉 |