The relationships between the grain size of ferromagnetic material and the strength and waveform characteristic parameters of Barkhausen noise (BN) were studied.
研究了铁磁材料的晶粒度与巴克豪森噪声的强度和波形特征参数之间的关系。
Finally using the neural network method to extract the wear particle image waveform characteristic and realize automatically distinguishing the wear particle image.
最后使用神经网络方法提取磨粒图像波形特征并且实现磨粒图像的自动识别。
First reflection waveform characteristic parameters that exhibit lithologic variation are determined by defining geological characters of seismic horizon with the aid of waveform analysis.
首先利用波形分解确定地震反射层的地质属性，找出能反映岩性变化的反射波波形特征参数；
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