爆破振动对民房破坏效应预测的BDA模型及应用
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摘要
爆破振动危险程度的预测与控制是爆破工程中不容忽视的重要内容。基于Bayes判别分析理论,建立爆破振动对民房破坏效应预测的Bayes判别分析模型(BDA);选用爆破振动幅值、主频率主频率持续时间、灰缝强度、砖墙面积率、房屋高度、屋盖形式、圈梁构造柱、施工质量、场地条件等10个影响因素作为判别因子;将该方法应用到铜绿山矿露天采场爆破振动对民房破坏效应预测问题中,对现场实测的64组爆破振动数据作为学习样本进行训练,建立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0.0938;用另外12组现场数据作为预测样本进行测试。研究结果表明:经过训练后的BDA模型预测结果与实际情况吻合较好,预测精度高,回代估计的误判率低,为露天采矿爆破振动对民房破坏效应的预测提供了一种新思路。
The control and prediction of blasting vibration hazards is an essential study content in blast engineering.Based on the principles of Bayes discriminating analysis(BDA),the Bayes discriminating analysis model to predict the destructive effect of blast vibration on housing was established here.Ten indexes,i.e.,blasting vibration amplitude,dominant frequency,dominant frequency duration,gray joints intensity,the rate of brick walls,height of housing,roof forms,the structural column of circle beam,the quality of construction,and site conditions were used as blast vibration prediction of houses discriminating factors.A BDA model was obtained through training 64 measured data of blasting vibration.The re-substitution method was introduced to verify the stability of the BDA model and the ratio of mis-discrimination was 0.0938.The BDA model was used to discriminate 12 new samples and the prediction results agreed well with actual situation.The results showed that the BDA model has better classifying performance,higher prediction accuracy and lower misdiscrimination rate and can be used widely in practical blast engineering.
引文
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