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Classification of wood species by neural network analysis of ultrasonic signals

机译:通过超声信号的神经网络分析对木材种类进行分类

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摘要

The passage of ultrasonic waves through an anisotropic inhomogeneous material such as wood involves complex interactions between the physical vibrations of the ultrasound and the elastic response of the wood. The initial ultrasound signal ismodified by the transmission medium in a way characteristic of the elastic anisotropy of the medium.The many species of wood have subtly different elastic responses. In this work the characteristic signals formed by these responses is examined. A neural network system is used to classify these signals in terms of species. The neural network is shown tohave a high success rate in identifying wood species from the ultrasonic trace. It is established that this identification is not possible using wave velocity or received signal amplitudes. The most appropriate propagation direction for speciesidentification is also considered.
机译:超声波通过各向异性的非均质材料(例如木材)的通道会涉及超声波的物理振动与木材的弹性响应之间的复杂相互作用。初始超声信号通过传输介质以介质的弹性各向异性的方式进行修改。许多木材具有不同的弹性响应。在这项工作中,检查了由这些响应形成的特征信号。神经网络系统用于根据种类对这些信号进行分类。该神经网络在从超声波痕迹中识别木材种类方面具有很高的成功率。已经确定使用波速或接收信号幅度不可能进行这种识别。还考虑了最适合物种识别的传播方向。

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