小波神经网络在管道缺陷信号检测中的应用

Runjing Zhou, Fei Zhang
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引用次数: 0

摘要

针对长输管道缺陷检测信号的去噪问题,提出了基于小波神经网络的去噪方法,阐述了超声检测在长输管道中的应用。利用小波神经网络的自学习特性,减少了波损。该方法具有较好的效果,可以准确地获得缺陷的位置和幅度。这对超声检测的信号处理具有重要意义。
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 Detection for Pipeline Flaw Based on Wavelet Neural Network
Aiming at denoising to detection signal of the flaw in the long transporting pipe, the way of denoising based on wavelet neural network is present, and signal processing of ultrasonic detection application in long pipeline is described. Making use of self-learning characteristic of wavelet neural network, this way reduces wave loss. This method has the good effect and may acquire exact location and amplitude of the flaw. It is great significance for signal processing of ultrasonic detection.
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