|本期目录/Table of Contents|

[1]卞欢,刘剑,刘学,等.基于GA-BP神经网络的巷道平均风速单点测试研究*[J].中国安全生产科学技术,2023,19(5):57-64.[doi:10.11731/j.issn.1673-193x.2023.05.008]
　BIAN Huan,LIU Jian,LIU Xue,et al.Research on single point test of average wind speed in roadway based on GA-BP neural network[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2023,19(5):57-64.[doi:10.11731/j.issn.1673-193x.2023.05.008]
点击复制

基于GA-BP神经网络的巷道平均风速单点测试研究*
分享到：

《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
19
期数:
2023年5期
页码:
57-64
栏目:
职业安全卫生管理与技术
出版日期:
2023-05-31

文章信息/Info

Title:
Research on single point test of average wind speed in roadway based on GA-BP neural network
文章编号:
1673-193X(2023)-05-0057-08
作者:
卞欢; 刘剑; 刘学; 王东
（1.辽宁工程技术大学 安全科学与工程学院，辽宁 葫芦岛 125105；
2.辽宁工程技术大学 矿山热动力灾害与防治教育部重点实验室，辽宁 葫芦岛 125105）
Author(s):
BIAN Huan;  LIU Jian;  LIU Xue;  WANG Dong
(1.College of Safety Science and Engineering,Liaoning Technical University,Huludao Liaoning 125105,China;
2.Key Laboratory of Mine Thermo-motive Disaster and Prevention,Ministry of Education,Liaoning Technical University,Huludao Liaoning 125105,China)
关键词:
速度场结构近似恒定理论; 巷道平均风速; GA-BP神经网络; CFD模拟; 单点测试
Keywords:
approximate constant theory of velocity field structure;  average wind speed of roadway;  GA-BP neural network;  CFD simulation;  single point test
分类号:
X936
DOI:
10.11731/j.issn.1673-193x.2023.05.008
文献标志码:
A
摘要:
为了快速准确获取巷道平均风速，采用计算流体力学(CFD)方法对实际巷道风流进行数值模拟，并基于速度场结构近似恒定理论，将矩形巷道断面的宽度、高度、壁面粗糙度、监测点位置及监测点风速作为输入参数，提出1种基于GA-BP神经网络的巷道平均风速单点测试模型。研究结果表明：该模型具有良好的预测性能，利用巷道断面内任意点传感器风速值，可以快速准确地预测巷道断面平均风速，且相对误差达到2%以下。采用Levenberg-Marquardt算法训练的GA-BP神经网络模型预测精度较高，其MAPE，RMSE和R2分别为0.68%，0.04和0.99。研究结果可为矿井通风智能监测系统建设提供参考。
Abstract:
In order to quickly and accurately obtain the average wind speed in the roadway,a computational fluid dynamics (CFD) method was used to numerically simulate the actual airflow in the roadway.Based on the approximate constant theory of velocity field structure,a single point test model of the average wind speed in roadway based on GA-BP neural network was proposed by using the width,height,wall roughness,monitoring point location,and wind speed at monitoring point of a rectangular roadway section as input parameters.The results showed that the model had good prediction performance.Using the wind speed values of sensor at any point in the roadway section,the average wind speed of roadway section could be quickly and accurately predicted,with a relative error of less than 2%.The prediction accuracy of the GA-BP neural network model trained by Levenberg-Marquardt algorithm was high,with the MAPE,RMSE and R2 of 0.68%,0.04 and 0.99,respectively.The research results can provide reference for the construction of intelligent monitoring system for mine ventilation.

参考文献/References:

［1］刘剑.矿井智能通风关键科学技术问题综述［J］.煤矿安全,2020,51(10):108-111,117. LIU Jian.Overview onkey scientific and technical issues of mine intelligent ventilation［J］.Safety in Coal Mines,2020,51(10):108-111,117.
［2］张庆华,姚亚虎,赵吉玉.我国矿井通风技术现状及智能化发展展望［J］.煤炭科学技术,2020,48(2):97-103. ZHANG Qinghua,YAO Yahu,ZHAO Jiyu.Status of mine ventilation technology in China and prospects for intelligent development［J］.Coal Science and Technology,2020,48(2):97-103.
［3］张浪.巷道测风站风速传感器平均风速测定位置优化研究［J］.煤炭科学技术,2018,46(3):96-102. ZHANG Lang.Optimized study on location to measure average air velocity with air velocity sensor in wind measuring station of underground mine［J］.Coal Science and Technology,2018,46(3):96-102.
［4］王英敏.内空气动力学与矿井通风系统［M］.北京:矿金工业出版社,1994.
［5］郝元伟,陈开岩,蒋中承,等.基于CFD模拟的巷道风速监测值修正处理［J］.煤矿安全,2011,42(2):1-3,7. HAO Yuanwei,CHEN Kaiyan,JIANG Zhongcheng,et al.Study on amendment of airflow velocity in roadway based on CFD［J］.Safety in Coal Mines,2011,42(2):1-3,7.
［6］罗永豪,赵阳升.煤矿井下不同粗糙度巷道内风速分布的风洞模拟［J］.太原理工大学学报,2015,46(2):235-237,252. LUO Yonghao,ZHAO Yangsheng.Wind tunnel simulation on wind speed distribution in coal mine roadways within different roughness［J］.Journal of Taiyuan University of Technology,2015,46(2):235-237,252.
［7］李雪冰.巷道风流湍动特性及平均风速单点测试实验研究［D］.阜新：辽宁工程技术大学,2017.
［8］刘剑,李雪冰,宋莹,等.基于速度场系数的主通风机风量单点统计测量方法［J］.有色金属工程,2018,8(2):114-117. LIU Jian,LI Xuebing,SONG Ying,et al.Single point statistical measurement method of main fan air volume based on velocity field coefficient［J］.Nonferrous Metals Engineering,2018,8(2):114-117.
［9］吴新忠,陈昌,耿柯,等.基于IFWA-BP神经网络的线风速数据融合研究［J］.电子测量与仪器学报,2021,35(5):16-23. WU Xinzhong,CHEN Chang,GENG Ke,et al.Research on line wind speed data fusion based on IFWA-BP neural network［J］.Journal of Electronic Measurement and Instrumentation,2021,35(5):16-23.
［10］刘剑,李雪冰,高科,等.井巷风速单点测试方法及其可行性研究［J］.中国安全生产科学技术,2016,12(8):23-27. LIU Jian,LI Xuebing,GAO Ke,et al.Study on single-point measurement method of roadway air velocity and its feasibility［J］.Journal of Safety Science and Technology,2016,12(8):23-27.
［11］王翰锋.基于Fluent巷道断面平均风速点定位监测模拟研究［J］.煤炭科学技术,2015,43(8):92-96. WANG Hanfeng.Simulation study on monitoring and measuring location of average air velocity in section of mine roadway based on Fluent［J］.Coal Science and Technology,2015,43(8):92-96.
［12］LIU Z,ZHAO Y,CHEN S,et al.Predicting distributed roughness induced transition with a four-equation laminar kinetic energy transition model［J］.Aerospace Science and Technology,2020,99(4):105736.

相似文献/References:

备注/Memo

备注/Memo:
收稿日期： 2022-10-25
* 基金项目： 国家自然科学基金项目（51574142，51904143）
作者简介： 卞欢，硕士研究生，主要研究方向为矿井通风。
通信作者： 刘剑，博士，教授，主要研究方向为通风及灾害防治。
更新日期/Last Update: 2023-06-12