信号处理和神经网络技术在多层介质超声表征中的应用

J. Rouvaen, K. Harrouche, M. Ourak, B. El Khaldi
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引用次数: 1

摘要

利用超声波表征多层介质的经典方法是使用脉冲状态下的飞行时间反射法或准连续波状态下的光谱学。我们的目标是研究数字信号处理的性能改进和神经网络方法。从层状介质的简单模型出发,计算了高频脉冲超声波的反射系数。从理论上研究了同态处理技术的应用,同时考虑了换能器的频率响应和整个测量系统的信噪比。然后考虑了神经网络,并表明它们在其他方法失败的情况下提供了有效的响应
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of signal processing and neural net techniques to ultrasonic characterization of multilayered media
The characterization of multilayered media using ultrasonic waves is classically performed using time of flight reflectometry in the pulsed regime or spectroscopy in the quasi-continuous wave regime. Our aim is to study the performances improvements given by numeric signal processing and neural nets methods. Starting from simple models for layered media, the reflection coefficient for high frequency pulsed ultrasonic waves is computed. The application of homomorphic processing techniques is studied theoretically, taking the transducer frequency response and the overall measurement system signal to noise ratio into account. Neural nets are then considered and it is shown that they provide a valid response in situations where other methods fail
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