The blasting vibration signals show obvious zoning propagation characteristics. Because of not considering the specific influences of geological and topographical conditions, the existing zoning methods of blasting vibration cannot fully describe the internal details of blasting vibration signals. Therefore, a new zoning method of blasting vibration based on energy proportion was proposed in this paper, in which the energy proportion in low, medium, and high frequency bands after multiresolution wavelet analysis is used as the zoning index to distinguish the different characteristics of blasting vibration signals in different zones. Based on the proposed zoning method, 343 sets of measured blasting vibration signals were used to train and test the SVM classification models with four different types of kernel functions. The testing results demonstrate that the zoning method of blasting vibration based on energy proportion has high feasibility, flexibility, and reliability, and the SVM classification models with RBF have higher accuracy than models with other kernel functions in blasting vibration zoning prediction.

中文翻译：

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基于能量比例的爆破振动分区方法及其支持向量机分类模型

爆破振动信号具有明显的分区传播特征。由于没有考虑地质和地形条件的特定影响，现有的爆破振动分区方法无法充分描述爆破振动信号的内部细节。因此，本文提出了一种基于能量比例的爆破振动分区方法，该方法将多分辨率小波分析后的低，中，高频段的能量比例作为分区指标，以区分爆破的不同特征。不同区域的振动信号。基于所提出的分区方法，使用343组测得的爆破振动信号来训练和测试具有四种不同类型核函数的SVM分类模型。