Long term prediction of rockbursts at Canadian Diamond Mines

加拿大钻石矿岩爆的长期预测

• 批准号: RGPIN-2019-04572
• 负责人: Apel, Derek
• 金额: $ 1.89万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=681553
• 关键词: Long; term; prediction; rockbursts; Canadian

Rockburst is a type of unstable geological hazard in overstressed areas, which is in most times induced by underground mining and constitute a serious threat to the safety of miners and equipment during underground work in both mining and civil engineering projects. All mining countries have records about rockburst events. Long-term rockburst prediction is based on a combination of evaluation of rockburst liability and field conditions. Many mining sites around the world are using rockbursting indicators that have been developed to measure the rock bursting behaviour. However, rockburst occurrence relates to a number of factors, including geologic structure, mining or excavation methods, mechanical properties of rocks, in-situ stress and so on. Furthermore, the mutual effects of these impact factors for occurrence of rockburst are still not clear. As such, current prediction methods have significant limitations in engineering. Therefore, this proposal aims to use data base from case studies around the world where rockburst have occurred and use machine learning techniques for long term prediction of rockbursts.

岩爆是超应力区的一种不稳定地质灾害，大多数情况下是由地下开采引起的，严重威胁着矿山和土木工程井下作业人员和设备的安全。所有矿业国家都有岩爆事件的记录。岩爆长期预测是在岩爆危险性评价和现场条件相结合的基础上进行的。世界各地的许多采矿场正在使用已开发的岩爆指标来测量岩爆行为。然而，岩爆的发生与地质构造、采矿或开挖方法、岩石力学性质、地应力等诸多因素有关，而且这些影响因素对岩爆发生的相互影响尚不清楚。因此，目前的预测方法在工程上具有显著的局限性。因此，本建议旨在使用来自世界各地发生岩爆的案例研究的数据库，并使用机器学习技术进行岩爆的长期预测。