(1. 北京科技大学 土木与资源工程学院，北京 100083；
2. 包钢钢联巴润矿业分公司，包头 014080)
摘 要: 针对爆破振动对矿山边坡稳定性评价中存在诸多不确定性因素的问题，采用距离判别分析理论并对该模型进行加权赋值的改进，用以区别不同参数之间的重要性。选用振动速度峰值(水平、垂直)、振动主频(水平、垂直)、爆心距共5个影响因素作为判别因子，建立露天采矿受到爆破振动时产生边坡危害判别的距离判别分析模型(DDA模型)和改进加权距离判别分析模型(改进DDA模型)；通过6次现场爆破试验收集到24组爆破振动实测数据，以其中18组现场数据作为模型的学习样本对模型进行训练，建立与之相对应的判别函数，利用回代法进行误判率的回检，并用6组现场数据作为预测样本进行测试。结果表明：DDA模型回检误判率为5.6%，对影响因素的重要性进行加权的改进DDA模型回检误判率为0%，其判别结果与实际结果完全吻合。改进加权距离判别分析模型的算法简单、收敛速度快、预测精度高，为露天采矿爆破振动对边坡危害程度的判别提供了一种新思路。
关键字: 爆破振动；边坡危害；距离判别分析模型
（1. School of Civil and Resource Engineering, University of Science and Technology Beijing, Beijing 100083, China;
2. BaRun Mining Branch, Baotou Steel Union Co., Ltd., Baotou 014080, China）
Abstract:Aiming at the problem that there are many uncertain factors in the evaluation of mine slope stability by blasting vibration, the distance discriminant analysis theory was adopted and the weighted value of the model was improved to distinguish the importance of different parameters. The distance discriminant analysis model (DDA model) and the improved distance discriminant analysis model (improved DDA model) of slope hazards caused by blasting vibration in open-pit mining were established by selecting five influencing factors, namely, peak vibration velocity (horizontal and vertical), dominant vibration frequency (horizontal and vertical), and distance from blasting center as discriminant factors. The 24 groups of measured blasting vibration data were collected from 6 field blasting tests, 18 groups of which were used as the learning samples to train the model, and the corresponding discriminant function was established. The misjudgment rate was checked back by the back substitution method, and 6 groups of field data were used as the prediction samples for testing. The results show that the misdiagnosis rate of the DDA model is 5.6%, and the misdiagnosis rate of the improved DDA model weighted by the importance of influencing factors is 0%. The discriminant results of the improved weighted distance discriminant analysis model are completely consistent with the actual results. Because the algorithm is simple, the convergence speed is fast, and the prediction accuracy is high, the improved DDA model provides a new idea for the discrimination of the damage degree of the slope caused by blasting vibration in open-pit mining.
Key words: blasting vibration; slope failure; distance discriminant analysis model
