基于Bayes判别法的矿井通风系统安全可靠性评价  

Reliability Assessment for Mine Ventilation System Safety Based on Bayes Discriminant Analysis

作　　者：范玉乾 何昌盛[1] FAN Yu-qian;HE Chang-sheng(Changsha Engineering&Research Institute of Nonferrous Metallurgy Xining Branch,Xi’ning 810000,Qinghai,China)

机构地区：[1]长沙有色冶金设计研究院有限公司西宁分公司,青海西宁810000

出　　处：《铜业工程》2020年第6期19-23,共5页Copper Engineering

摘　　要：针对传统通风系统安全可靠性评价方法存在的问题,本文采用多组逐步Bayes判别分析理论,并结合矿井通风系统对经济、安全方面的要求,选取16项指标作为判别因子,建立了基于Bayes判别法的矿井通风系统安全可靠性评价模型。利用国内某矿山提供的实测资料作为训练样本,得到了相应线性判别函数;并利用回代估计方法进行回检,误判率为0%;而后对3组检测样本进行评判,正确识别率为100%。最后,该模型对5个实测生产矿井通风系统数据进行测试,得出预测结果与实际吻合良好。综上所述:该模型对矿井通风系统的安全评价具有较高的可信度,也为矿井通风系统的安全可靠性评价提供了一条新方法。To solve problems caused by traditional ventilation system reliability assessment,this paper adopts the theory of multigroup step-by-step bayes discriminant analysis,and combines the economic and safety requirements of mine ventilation system,selects 16 indexes as discriminant factors,and establishes the safety and reliability evaluation model of mine ventilation system based on bayes discriminant method.Using the measured data provided by a mine in China as the training sample,the corresponding linear discriminant function is obtained,and the error rate is 0%,and then the correct recognition rate is 100%.The model tests the ventilation system data of 5 actual production mines,and the prediction results are in good agreement with the practice.In a word,the BDA model has a high credibility in assessing mine ventilation reliability safety reliability assessment,which provides a new and practical approach to forecast mine ventilation reliability.

关 键 词：矿井通风系统 安全可靠性评价 Bayes判别分析(BDA) 回代估计法 

分 类 号：TD72[矿业工程—矿井通风与安全]