一种基于Morlet小波系数谱的提取计算算法

T. E. Putra, S. Abdullah, M. Nuawi
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引用次数: 1

摘要

讨论了Morlet小波在生成新编辑信号中的有效性。基于Morlet小波系数幅度级对122.4 s SAESUS应变信号进行编辑。去除小波系数幅值低于截断电平(Cut Off level, COL)的片段。对提取的疲劳损伤片段进行保留和拼接,得到新的编辑信号。所有信号的信号统计参数和疲劳损伤值应尽可能准确。从分析中,选择25,000µo作为最佳COL值,因为该电平不会改变信号的行为。这个值使长度减少了14%,而疲劳损伤只减少了6.1%。这表明Morlet小波可以在不改变主历史的情况下成功地对原始信号进行压缩。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An extraction computational algorithm based on the Morlet wavelet coefficient spectrum
This paper discussed on the effectiveness of the Morlet wavelet to generate new edited signal. The 122.4 second SAESUS strain signal was edited based on the Morlet wavelet coefficient amplitude level. Segments with wavelet coefficient amplitude level lower than Cut Off Level (COL) were removed. Furthermore, extracted fatigue damaged segments were retained and then were joined in order to gain new edited signal. The signal statistical parameter and fatigue damaging values should be as accurate as possible for all signals. From the analysis, the 25,000 µɛ was selected to be the optimum COL value since the level did not change the signal behaviour. This value gave a 14 % reduction in length with only 6.1 % reduction in the fatigue damage. This indicated that the Morlet wavelet can be successfully applied to compress the original signal without changing the main history as well.
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