基于小波熵时间序列的碳纤维t梁空气夹杂物空间定位

Spyridon Brouzas, I. Georgiou
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引用次数: 0

摘要

本文介绍了一种基于振动的小波熵时间序列方法,并对其进行了实验验证。对试件冲击激励后得到的振动信号进行小波变换,并结合香农信息熵来量化信号的无序趋势。定义了小波熵、小波熵时间序列等概念,并应用于结构健康监测。通过实验和计算验证了该方法的科学性。小波熵时间序列能够识别信号复杂性中的模式,使该方法适用于无损检测范围之外的其他信号处理应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatial Localization of Air Inclusions in Carbon Fiber T-Beam, by Use of Wavelet Entropy Time Series From Hammer Tap Test
In this paper, a vibration-based method, called wavelet entropy time series, for non-destructive testing of carbon fiber specimens is introduced and demonstrated experimentally. The wavelet transform of vibration signals, acquired after an impact excitation of the specimen, is combined with Shannon’s informational entropy to quantify a trend in the disorder of the signal. Notions such as wavelet entropy, wavelet entropy time series are defined and utilized to assist in structural health monitoring. The scientific merit of the method was investigated both experimentally and computationally. Wavelet entropy time series was able to identify patterns in the complexity of signals making the method suitable for other signal processing applications, outside the scope of non-destructive testing.
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