基于动态故障树的煤矿突水风险概率评价
投稿时间:2015-07-05  修订日期:2016-07-09  点此下载全文
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作者单位E-mail
王华蓥 北京科技大学土木与环境工程学院 why_ustb@163.com 
李仲学 北京科技大学土木与环境工程学院  
赵怡晴 北京科技大学土木与环境工程学院 yiqingzhao@foxmail.com 
雷炜 北京科技大学土木与环境工程学院  
舒杨 北京科技大学土木与环境工程学院  
中文摘要:故障树分析是煤矿突水的常用风险评估方法,考虑随着时间的推移基本事件和布尔逻辑关系变化的动态故障树是煤矿安全事故研究的热点领域,而其中一个难题是在动态故障树仿真时,难以获得基本事件在不同时间点的失效或修复概率。本文邀请专家评价我国煤矿突水动态故障树分析中基本事件的失效或修复可能性,采用三角模糊数对专家的评价语言量化,通过反模糊化和矩量法,计算基本事件失效和修复时间的Weibull分布参数,依据计算和查阅的数据,对煤矿突水动态故障树模型进行Monte Carlo仿真,结果表明我国煤矿在动工2.5年后突水事故发生概率在0.001上下波动。
中文关键词:煤矿突水  动态故障树  三角模糊数
 
DFT based evaluation of risk probabilities for underground coal mine water inrush
Abstract:Fault tree analysis (FTA) has been widely utilized as a tool for water inrush risk assessment in coal mines, and dynamic fault tree analysis (DFT) is still being studying, which takes the fact into consideration that the probability of basic events (BE) and Boolean logic will be changing. While one problem is that it’s difficult to obtain failure and repair probability data at different time when simulates DFT. This study models DFT of water inrush in Chinese coal mine and invites experts to estimate the failure and repair probability of BE, then triangular fuzzy numbers are adopted to quantify experts’ estimate. Using defuzzification and moment method, the shape and scale parameters of Weibull distribution about failure and repair time are achieved. The result of Monte Carlo simulation for DFT illustrates that the probability of underground coal mine water inrush is about 0.001 in 2.5 years since the mine begin its capital construction.
keywords:water inrush in coal mines  dynamic fault tree analysis  triangular fuzzy number
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