组合赋权-灰色聚类的煤与瓦斯突出危险评价

doi:10.16265/j.cnki.issn1003-3033.2023.S1.0593

中国安全科学学报 ›› 2023, Vol. 33 ›› Issue (S1): 52-57.doi: 10.16265/j.cnki.issn1003-3033.2023.S1.0593

• 安全社会科学与安全管理 • 上一篇下一篇

组合赋权-灰色聚类的煤与瓦斯突出危险评价

史洪恺¹(), 祁云²^,^**(), 张国恩¹, 姜晓宇¹, 何向¹, 孙远航³

¹ 中国神华神东煤炭分公司乌兰木伦煤矿, 内蒙古鄂尔多斯 017000
² 山西大同大学煤炭工程学院, 山西大同 037000
³ 中国神华神东煤炭分公司石圪台煤矿, 陕西榆林 719300

收稿日期:2023-02-16 修回日期:2023-05-08 出版日期:2023-06-30
通讯作者:
**祁云(1988—),男,安徽淮北人,博士,副教授,硕士生导师,主要从事系统决策理论及安全评价、应急技术与管理和矿井灾害防治的研究。E-mail:qiyun_sx@163.com。
作者简介:
史洪恺 (1989—),男,山西平遥人,本科,工程师,从事矿山机电设备管理、电气自动化等方面的工作。E-mial:502698638@qq.com。
张国恩高级工程师
基金资助:
山西省基础研究计划(自由探索类)青年项目(202203021222300); 山西省高等学校科技创新计划项目(2022L449); 山西省高等学校科技创新计划项目(2022L448); 国家重点研发计划资助项目(2018YFC0807900); 山西大同大学博士科研启动项目(2020-B-08); 山西大同大学博士科研启动项目(2020-B-18)

Risk assessment of coal and gas outburst based on combination weighting and grey clustering

SHI Hongkai¹(), QI Yun²^,^**(), ZHANG Guoen¹, JIANG Xiaoyu¹, HE Xiang¹, SUN Yuanhang³

¹ Ulan Mulun Coal Mine, Shenhua Shendong Coal Group Corporation Limited, Ordos Inner Mongolia 017000, China
² School of Coal Engineering, Shanxi Datong University, Datong Shanxi 037000, China
³ Shigetai Coal Mine, Shenhua Shendong Coal Group Co., Ltd., Yulin Shaanxi 719300, China

Received:2023-02-16 Revised:2023-05-08 Published:2023-06-30

摘要/Abstract

摘要：

为有效预防煤矿井下煤与瓦斯突出事故,构建基于组合赋权-灰色聚类的煤与瓦斯突出危险评价模型。首先,基于轨迹交叉理论,从煤层物理学性质、瓦斯指标、煤层赋存条件3个方面选取预测指标,构建危险评价指标体系;然后,运用改进的层次分析法(IAHP)和熵权法(EWM),确定各指标权重,结合灰色聚类原理构建各指标的灰色模糊评价规范化等级判断矩阵,并根据最大隶属度原则预测煤与瓦斯突出等级;最后,以乌兰木伦煤矿12407综放工作面为应用实例,验证组合赋权-灰色聚类评价模型的科学性和有效性。结果表明:该工作面煤与瓦斯突出危险等级为Ⅴ,模型计算结果与现场实际基本吻合,其中,煤层物理学性质为主要诱导因素,评判结果与实际相吻合,证明文中所建模型具有一定的科学性和有效性。

关键词: 煤与瓦斯突出, 组合赋权, 灰色聚类, 危险评价, 突出等级

Abstract:

In order to effectively prevent coal and gas outburst accidents in coal mines, a combined weighting grey clustering risk assessment model for coal and gas outburst is proposed. Firstly, based on trajectory crossover theory, prediction indicators are selected from three aspects: coal seam physical properties, gas indicators, and coal seam occurrence conditions, and a risk assessment index system is constructed. Then, the Improved Analytic Hierarchy Process (IAHP) and Entropy Weight Method (EWM) are used to determine the weights of each indicator, and a grey fuzzy evaluation standardized level judgment matrix for each indicator is constructed based on the grey clustering principle. The coal and gas outburst level is predicted based on the principle of maximum membership degree. Finally, taking the 12407 fully mechanized top coal caving face of Ulan Mulun Coal Mine as an application example, the effectiveness of the combination weighting grey clustering evaluation model was verified. The results show that the danger level of coal and gas outburst in this working face is Ⅴ. The model calculation results are basically consistent with the actual situation on site. The physical properties of coal seams are the main inducing factors. The evaluation results are consistent with the actual situation. It is proved that the model is scientific and effective.

Key words: coal and gas outburst, combination weighting, grey clustering, hazard assessment, outstanding level

史洪恺, 祁云, 张国恩, 姜晓宇, 何向, 孙远航. 组合赋权-灰色聚类的煤与瓦斯突出危险评价[J]. 中国安全科学学报, 2023, 33(S1): 52-57.

SHI Hongkai, QI Yun, ZHANG Guoen, JIANG Xiaoyu, HE Xiang, SUN Yuanhang. Risk assessment of coal and gas outburst based on combination weighting and grey clustering[J]. China Safety Science Journal, 2023, 33(S1): 52-57.

图/表 3

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组合赋权-灰色聚类的煤与瓦斯突出危险评价

Risk assessment of coal and gas outburst based on combination weighting and grey clustering

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