中国安全科学学报 ›› 2018, Vol. 28 ›› Issue (9): 142-147.doi: 10.16265/j.cnki.issn1003-3033.2018.09.024

• 安全卫生工程技术 • 上一篇    下一篇

金矿采场环境因素变化分析及灰色聚类评价

张天宝1, 纪洪广1 教授, 李颂2   

  1. 1 北京科技大学 土木与资源工程学院,北京 100083
    2 山东黄金归来庄矿业有限公司,山东 临沂 273300
  • 收稿日期:2018-06-04 修回日期:2018-07-27 出版日期:2018-09-28 发布日期:2020-09-28
  • 作者简介:张天宝(1993—),男,湖北黄冈人,硕士研究生,研究方向为金属矿山建井工程风险评价。
  • 基金资助:
    国家重点研发计划项目(2016YFC0600801)。

Analysis of environmental factors change in mining face of a gold mine and its grey cluster assessment

ZHANG Tianbao1, JI Hongguang1, LI Song2   

  1. 1 School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China
    2 Guilaizhuang Mining Co. Ltd., Shandong Gold Group, Linyi Shandong 273307, China
  • Received:2018-06-04 Revised:2018-07-27 Online:2018-09-28 Published:2020-09-28

摘要: 为改善地下采场环境状况,保护作业人员安全与健康,利用灰色聚类模型(GCM),研究山东某金矿地下采场环境质量随采深的变化。监测并调查金矿-30、-70、-110、-150、-190、-230 和-300 m水平的7个采场中O2、CO2、温度、相对湿度、粉尘、有毒气体、噪声及照度等采场环境指标,研究采场环境中单一指标随采深增加的变化趋势;运用GCM及G1法定权综合评价采场环境并分级;对该矿生产人员进行采场环境主观满意度问卷调查。结果表明:采场综合环境质量等级(EQGs)随采深增加而降低;问卷调查结果与灰色聚类评价结果有较好的一致性。

关键词: 金矿, 采场, 环境因素, 灰色聚类模型(GCM), G1法, 综合评价

Abstract: GCM was applied to research the quality of the environment of a certain gold mine in Shandong as a function of the exploitation depth. Monitoring tests and investigations were carried out on environmental factors, such as O2, CO2, dust, toxic gases, micro-climate, noise and illumination for the mining faces being at exploitation depths of -30, -70, -110, -150, -190, -230 and -300 m respectively. Trends in changes of environmental factors in the underground mining faces were analyzed. An assessment of comprehensive environment quality was made for the mining faces via introducing GCM integrated with G1 method for determining the weight values of the environmental factors. A questionnaire survey on subjective satisfaction was carried out into a part of staff of the gold mine. The results show that there is a negative correlation between the environment quality grade(EQGs) of mining face and the exploitation depth of mining face, and obtained findings coincide with the assessment results via GCM.

Key words: gold mine, mining face, environmental factors, grey clustering model(GCM), G1 model, comprehensive assessment

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