Intelligent assessment method for rockburst hazard areas based on image recognition technology
-
摘要:
针对传统冲击地压危险评价方法计算量大、危险区域划分精度低等问题，为适应冲击地压防治智能化、可视化的发展需求，提出了一种基于图像识别技术的冲击地压危险区域智能化评价方法。采用半定量化估算方法，对11项冲击地压危险的动静载主控因素进行量化表征；基于OpenCV机器视觉库和深度学习模型，实现对单一主控因素的图像识别；通过构建图像灰阶与应力集中系数的映射矩阵，实现对单一影响因素的线性与非线性叠加，得到评价区域的应力集中系数矩阵；采用min−max标准化法构建冲击地压危险区域的“无、弱、中等、强”4级判别标准，实现分级分区评价。基于Python语言开发了冲击地压危险智能化评价软件，并对软件实际应用效果进行了检验，结果表明：软件将传统仅针对巷道的一维线性危险区域划分方法改进为针对整个采掘空间的二维平面划分方法，显著提高了评价效率和危险区域划分精度，降低了人工成本；评价结果与微震能量密度云图、现场实测矿压规律一致性较高，可为现场冲击地压防治工作提供有效指导。
Abstract:In traditional rockburst hazard assessment methods, there are problems of large computational complexity and low precision in dividing hazardous areas. In order to meet the development needs of intelligent and visual prevention and control of rockburst, an intelligent assessment method for rockburst hazard areas based on image recognition technology is proposed. Using a semi quantitative estimation method, the method quantitatively characterizes the main controlling factors of dynamic and static loads for 11 types of rockburst hazards. Based on OpenCV machine vision library and deep learning model, the method achieves image recognition for a single main control factor. By constructing a mapping matrix between the grayscale of the image and the stress concentration coefficient, linear and nonlinear superposition of a single influencing factor is achieved to obtain the stress concentration coefficient matrix of the assessment area. Using the min max standardization method to construct a 4-level discrimination standard of "no, weak, moderate, and strong" for the hazard area of rockburst, the method achieves graded and division assessment. A software for intelligent assessment of rockburst hazards is developed based on Python language, and the actual application effect of the software is tested. The results show that the software improves the traditional one-dimensional linear hazard area division method for roadways to a two-dimensional plane division method for the entire mining space. It significantly improvies the assessment efficiency and precision of hazard area division and reduces labor costs. The assessment results are highly consistent with the microseismic energy density cloud map and the on-site measured mining pressure pattern, which can provide effective guidance for the prevention and control of on-site rockburst.
-
Key words:
- coal mining /
- rockburst /
- hazard assessment /
- hazard area division /
- image recognition
-
图 1 冲击地压危险主控因素及影响范围
Figure 1. Main controlling factors and influence range of rock burst hazard
图 3 工作面回采接近断层时煤体应力集中系数变化曲线
Figure 3. Change curve of stress concentration coefficient of coal body when mining face approaches fault
图 4 采空区形成后煤体应力集中系数变化曲线
Figure 4. Change curve of stress concentration coefficient of coal body after the formation of goaf
图 5 不同区段煤柱宽度下煤体应力集中系数变化曲线
Figure 5. Change curve of stress concentration coefficient of coal body under different coal pillar widths
图 6 终采线外错区域煤体垂直应力分布
Figure 6. Vertical stress distribution of coal body in staggered area outside terminal line
图 7 终采线外错区域煤体应力集中系数变化曲线
Figure 7. Change curve of stress concentration coefficient in staggered area outside terminal line
图 9 “T”型和“X”型交叉巷道区域数值模拟结果
Figure 9. Numerical simulation results of "T" and "X" shaped cross-roadway
图 10 21104工作面冲击地压危险主控因素的量化表征与图形识别
Figure 10. Quantitative characterization and graphic identification of main controlling factors of rock burst hazard in 21104 working face
图 13 冲击地压危险智能化评价软件界面
Figure 13. Interface of intelligent evaluation software of rock burst hazard
图 14 冲击地压危险性评价结果与微震能量密度云图对比
Figure 14. Comparison between rock burst hazard assessment results and cloud picture of microseismic energy density
图 15 21104工作面冲击地压危险预警及矿压异常区域分布
Figure 15. Distribution of rock burst hazard early warning area and abnormal area of mine pressure in 21104 working face
表 1 冲击地压危险主控因素的量化表征结果
Table 1. Quantitative characterization results of main controlling factors of rock burst hazard
序号 影响因素 识别主体 影响范围 应力集中系数 1 采深 采深 （400，600] m 1.20 （600，800] m 1.30 （800，1 000] m 1.40 （1 000，+∞） m 1.60 2 褶曲 倾角≤15°褶曲 褶曲轴部前后10 m 1.20 倾角＞15°褶曲 褶曲轴部前后20 m 1.40 3 断层 落差＞10 m断层 断层前后30～50 m 1.40 断层前后10～30 m 1.90 断层前后<10 m 2.05 落差≤10 m断层 断层前后30 m 1.20 4 采空区 采空区 采空区外缘50 m 1.50 5 区段煤柱 区段煤柱宽度 [50，+∞） m或（－∞，5] m 1.00 （5，10] m 1.30 （10，30] m 2.20 （30，50] m 1.50 6 开切眼外错 开切眼外错拐点 外错点前后30～50 m 1.50 外错点前后30 m 2.10 7 终采线外错 终采线外错拐点 外错点前后30～50 m 1.50 外错点前后30 m 2.10 8 巷道交叉 “T”型交叉 “T”型交叉前后30 m 1.05 “X”型交叉 “X”型交叉前后30 m 1.10 9 初次来压 初次来压线 初次来压前后20 m 1.70 10 “见方”破断 初次“见方”线 初次“见方”前后50 m 1.50 二次“见方”线 二次“见方”前后50 m 1.70 11 矿震动载 矿震平均能量 （103～104] J的工作面 1.10 （104～105] J的工作面 1.20 （105，+∞） J的工作面 1.60 
下载: 导出CSV
表 2 冲击地压危险区域的划分标准
Table 2. Classification standard of rock burst hazard area
冲击地压
危险等级应力集中系数 灰阶 无 $ [0,{\lambda _{\min }}) $ $ [0,k{\lambda _{\min }}) $ 弱 $ [{\lambda _{\min }},\left({{{\lambda _{\max }} - {\lambda _{\min }}}}\right)/{3}) $ $ [k{\lambda _{\min }},{{k({\lambda _{\max }} - {\lambda _{\min }})}}/{3}) $ 中等 $ \left[\dfrac{{{\lambda _{\max }} - {\lambda _{\min }}}}{3},\dfrac{{2({\lambda _{\max }} - {\lambda _{\min }})}}{3}\right) $ $ \left[\dfrac{{k({\lambda _{\max }} - {\lambda _{\min }})}}{3},\dfrac{{2k({\lambda _{\max }} - {\lambda _{\min }})}}{3}\right) $ 强 $ [{{2({\lambda _{\max }} - {\lambda _{\min }})}}/{3}, + \infty ) $ $ [{{2k({\lambda _{\max }} - {\lambda _{\min }})}}/{3}, + \infty ) $
下载: 导出CSV
-
[1] 齐庆新,窦林名. 冲击地压理论与技术[M]. 徐州:中国矿业大学出版社,2008.QI Qingxin,DOU Linming. Theory and technology of rock burst[M]. Xuzhou:China University of Mining and Technology Press,2008. [2] 窦林名,田鑫元,曹安业,等. 我国煤矿冲击地压防治现状与难题[J]. 煤炭学报,2022,47(1):152-171.DOU Linming,TIAN Xinyuan,CAO Anye,et al. Present situation and problems of coal mine rock burst prevention and control in China[J]. Journal of China Coal Society,2022,47(1):152-171. [3] 齐庆新,李一哲,赵善坤,等. 我国煤矿冲击地压发展70年:理论与技术体系的建立与思考[J]. 煤炭科学技术,2019,47(9):1-40.QI Qingxin,LI Yizhe,ZHAO Shankun,et al. Seventy years development of coal mine rockburst in China:establishment and consideration of theory and technology system[J]. Coal Science and Technology,2019,47(9):1-40. [4] 窦林名,王盛川,巩思园,等. 冲击矿压风险智能判识与监测预警云平台[J]. 煤炭学报,2020,45(6):2248-2255.DOU Linming,WANG Shengchuan,GONG Siyuan,et al. Cloud platform of rock-burst intelligent risk assessment and multi-parameter monitoring and early warning[J]. Journal of China Coal Society,2020,45(6):2248-2255. [5] 何生全,何学秋,宋大钊,等. 冲击地压多参量集成预警模型及智能判识云平台[J]. 中国矿业大学学报,2022,51(5):850-862.HE Shengquan,HE Xueqiu,SONG Dazhao,et al. Multi-parameter integrated early warning model and an intelligent identification cloud platform of rockburst[J]. Journal of China University of Mining & Technology,2022,51(5):850-862. [6] 潘俊锋,冯美华,卢振龙,等. 煤矿冲击地压综合监测预警平台研究及应用[J]. 煤炭科学技术,2021,49(6):32-41.PAN Junfeng,FENG Meihua,LU Zhenlong,et al. Research and application of comprehensive monitoring and early warning platform for coal mine rock burst[J]. Coal Science and Technology,2021,49(6):32-41. [7] 姜福兴,曲效成,王颜亮,等. 基于云计算的煤矿冲击地压监控预警技术研究[J]. 煤炭科学技术,2018,46(1):199-206,244.JIANG Fuxing,QU Xiaocheng,WANG Yanliang,et al. Study on monitoring & control and early warning technology of mine pressure bump based on cloud computing[J]. Coal Science and Technology,2018,46(1):199-206,244. [8] 窦林名,贺虎,何江,等. 冲击危险评价的相对应力集中系数叠加法[J]. 煤炭学报,2018,43(2):327-332.DOU Linming,HE Hu,HE Jiang,et al. New method of rockburst risk assessment using relative stress concentration factor superposition[J]. Journal of China Coal Society,2018,43(2):327-332. [9] 姜福兴,刘懿,翟明华,等. 基于应力与围岩分类的冲击地压危险性评价研究[J]. 岩石力学与工程学报,2017,36(5):1041-1052.JIANG Fuxing,LIU Yi,ZHAI Minghua,et al. Evaluation of rock burst hazard based on the classification of stress and surrounding rock[J]. Chinese Journal of Rock Mechanics and Engineering,2017,36(5):1041-1052. [10] 曹安业,王常彬,窦林名,等. 临近断层孤岛面开采动力显现机理与震动波CT动态预警[J]. 采矿与安全工程学报,2017,34(3):411-417.CAO Anye,WANG Changbin,DOU Linming,et al. Dynamic manifestation mechanism of mining on the island coalface along fault and dynamic pre-warning of seismic waves with seismic tomography[J]. Journal of Mining & Safety Engineering,2017,34(3):411-417. [11] 邓志刚. 基于三维地应力场反演的宏观区域冲击危险性评价[J]. 煤炭科学技术,2018,46(10):78-82.DENG Zhigang. Danger evaluation of pressure bump in macro area based on 3D geostress field inversion[J]. Coal Science and Technology,2018,46(10):78-82. [12] 王爱文,王岗,代连朋,等. 基于临界应力指数法巷道冲击地压危险性评价[J]. 煤炭学报,2020,45(5):1626-1634.WANG Aiwen,WANG Gang,DAI Lianpeng,et al. Evaluation on the rock burst risks of roadway using critical stress index method[J]. Journal of China Coal Society,2020,45(5):1626-1634. [13] 夏永学. 冲击地压动−静态评估方法及综合预警模型研究[D]. 北京:煤炭科学研究总院,2020.XIA Yongxue. Research on the method of dynamic-static evaluation of rockburst and comprehensive early warning model[D]. Beijing:CCTEG Chinese Institute of Coal Science,2020. [14] 齐庆新,史元伟,刘天泉. 冲击地压粘滑失稳机理的实验研究[J]. 煤炭学报,1997,22(2):34-38.QI Qingxin,SHI Yuanwei,LIU Tianquan. Mechanism of instability caused by viscous sliding in rock burst[J]. Journal of China Coal Society,1997,22(2):34-38. [15] 窦林名,白金正,李许伟,等. 基于动静载叠加原理的冲击矿压灾害防治技术研究[J]. 煤炭科学技术,2018,46(10):1-8.DOU Linming,BAI Jinzheng,LI Xuwei,et al. Study on prevention and control technology of rockburst disaster based on theory of dynamic and static combined load[J]. Coal Science and Technology,2018,46(10):1-8. [16] 李曼,段雍,曹现刚,等. 煤矸分选机器人图像识别方法和系统[J]. 煤炭学报,2020,45(10):3636-3644.LI Man,DUAN Yong,CAO Xiangang,et al. Image identification method and system for coal and gangue sorting robot[J]. Journal of China Coal Society,2020,45(10):3636-3644. [17] 孙继平,程继杰,王云泉. 基于彩色图像的煤矿冲击地压和煤与瓦斯突出感知报警方法[J]. 工矿自动化,2022,48(11):1-5.SUN Jiping,CHENG Jijie,WANG Yunquan. Coal mine rock burst and coal and gas outburst perception alarm method based on color image[J]. Journal of Mine Automation,2022,48(11):1-5. [18] 陈彪,卢兆林,代伟,等. 基于轻量化HPG−YOLOX−S模型的煤矸石图像精准识别[J]. 工矿自动化,2022,48(11):33-38.CHEN Biao,LU Zhaolin,DAI Wei,et al. Accurate recognition of coal-gangue image based on lightweight HPG-YOLOX-S model[J]. Journal of Mine Automation,2022,48(11):33-38. [19] 解嘉豪,韩刚,吕玉磊,等. 蒙陕地区工作面冲击危险的增量叠加法评价[J]. 煤炭科学技术,2020,48(增刊1):59-65.XIE Jiahao,HAN Gang,LYU Yulei,et al. Assessment method of incremental superposition for rockburst risk of working face in Mengshan Areas[J]. Coal Science and Technology,2020,48(S1):59-65. [20] 朱斯陶,姜福兴,刘金海,等. 复合厚煤层巷道掘进冲击地压机制及监测预警技术[J]. 煤炭学报,2020,45(5):1659-1670.ZHU Sitao,JIANG Fuxing,LIU Jinhai,et al. Mechanism and monitoring and early warning technology of rock burst in the heading face of compound thick coal seam[J]. Journal of China Coal Society,2020,45(5):1659-1670. [21] 闫耀东,潘俊锋,席国军,等. 综放开采见方构造区冲击危险性分析及防治研究[J]. 工矿自动化,2021,47(10):7-13.YAN Yaodong,PAN Junfeng,XI Guojun,et al. Impact hazard analysis and prevention research of square structure area in fully mechanized working face[J]. Industry and Mine Automation,2021,47(10):7-13. [22] 贺虎,郑有雷,张雄,等. 基于动静应力分析的复杂工作面冲击危险评价[J]. 煤炭科学技术,2019,47(7):265-270. doi: 10.13199/j.cnki.cst.2019.07.036HE Hu,ZHENG Youlei,ZHANG Xiong,et al. Rock burst risk evaluation based on dynamic-static stress analysis in complex working face[J]. Coal Science and Technology,2019,47(7):265-270. doi: 10.13199/j.cnki.cst.2019.07.036 -
点击查看大图
计量
- 文章访问数: 262
- HTML全文浏览量: 48
- PDF下载量: 26
- 被引次数: 0
