评价砌体结构爆破振动破坏效应的突变级数法

为了研究爆破振动对砌体结构破坏效应的评价与预测问题,提出基于突变级数法的方案。考虑爆破振动、建筑施工、砌体结构和建设场地等4个方面的属性,选用振幅、主频率、主频率持时、施工质量、灰缝强度、圈梁构造柱、房屋高度、屋盖形式、砖墙面积率以及场地条件等10个参数,建立了砌体结构爆破振动破坏效应评价的递阶层次指标体系;选用28组现场实测数据作为训练样本,建立突变级数判据,从而建立了砌体结构爆破振动破坏效应评价和预测的突变级数法;选用24组现场实测数据作为测试样本,以检验模型的可行性和可靠性。研究表明,突变级数法的评价结果与实际情况吻合,其中,12组测试样本的评价结果与模糊神经网络、Fisher判别分析法和支持向量机法等的评价结果一致。

Evaluation of masonry structure destructive effect under blasting vibration based on catastrophe progression method

To study the evaluation and prediction of the destructive effect on masonry structure under blasting vibration,a catastrophe progression method was proposed. Four characteristics of blasting vibration, construction quality, masonry structure, and construction site were taken into account, and 10 parameters were selected as the discriminant factors,including blasting vibration amplitude, dominant frequency, dominant frequency duration, construction quality,joint mortar intensity, collar beam structure, house height, roof forms, brick vall ratio, and site conditions. Then,the hierarchical index system for destructive effect evaluation of masonry structure under blasting vibration was put forward. 28 measured data in site were selected as the training samples to present the catastrophe progression recognition criteria, and catastrophe progression method for evaluation and prediction on the destructive effect of masonry structure under blasting vibration was constructed. An additional 24 measured data in site were selected as the testing samples, and evaluated to verify the feasibility and reliability of the catastrophe progression method. The study indicates that the results evaluated by the proposed method are the same as the practical situation, and that those of the 12 samples of the selected training samples agrees well with those of the fuzzy neural network, Fisher discriminant analysis method, and support vector machine method.