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A New Zoning Method of Blasting Vibration Based on Energy Proportion and Its SVM Classification Models

机译:基于能量比例及其SVM分类模型的爆破振动的新分区方法

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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.
机译:爆破振动信号显示出明显的分区传播特性。由于不考虑地质和地形条件的具体影响,爆破振动的现有分区方法不能完全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的新分区方法,其中多分辨率小波分析后的低,介质和高频带中的能量比例用作区分爆破的不同特征的分区指数不同区域中的振动信号。基于所提出的分区方法,使用343组测量的爆破振动信号来培训和测试SVM分类模型,具有四种不同类型的内核功能。测试结果表明,基于能量比例的爆破振动的分区方法具有高可行性,灵活性和可靠性,并且具有RBF的SVM分类模型比具有爆破振动分区预测中的其他内核功能的模型具有更高的精度。

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