基于python的应力波特征矩阵仿真程序的实现

Realization of stress wave characteristic matrix simulation program based on Python

本文实现了一种基于python的应力波特征矩阵仿真程序,通过程序构建了一个特征矩阵图像数据集——Eigen Matrix Net,以期能够解决通过卷积神经网络检测木材内部缺陷时样本量不足的问题。应用python内的wxpython、matplotlib等库实现了应力波特征矩阵仿真程序,并给出部分算法。根据图像数据集的深度学习结果显示,该程序生成的仿真数据能较好的代替真实数据,取得了满意的应用效果。

In this paper,a simulation program of stress wave characteristic matrix is implemented based on python,and a data set of characteristic matrix image,eigen matrix net,is constructed through the program,in order to solve the problem of insufficient sample size when detecting wood internal defects through convolutional neural network.In this paper,we use wxPython,Matplotlib and other libraries in Python to realize the simulation program of stress wave characteristic matrix,and give some algorithms and program codes.According to the deep learning result of image data set,the simulation data generated by the program can replace the real data better,and the application effect is satisfactory.