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An extraction computational algorithm based on the Morlet wavelet coefficient spectrum

机译:基于Morlet小波系数谱的提取计算算法。

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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.
机译:本文讨论了Morlet小波产生新的编辑信号的有效性。根据Morlet小波系数振幅水平编辑122.4秒的SAESUS应变信号。去除小波系数幅度水平低于截止水平(COL)的线段。此外,保留提取的疲劳损伤段,然后将其合并以获得新的编辑信号。对于所有信号,信号统计参数和疲劳破坏值应尽可能准确。从分析中,选择25,000 µl作为最佳COL值,因为该水平不会改变信号行为。该值使长度减少14%,而疲劳损伤仅减少6.1%。这表明Morlet小波可以成功地应用于压缩原始信号,而无需更改主要历史记录。

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