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首页> 外文期刊>American journal of applied sciences >A Study of Fatigue Data Editing using the Short-Time Fourier Transform (STFT) | Science Publications
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A Study of Fatigue Data Editing using the Short-Time Fourier Transform (STFT) | Science Publications

机译：短时傅立叶变换（STFT）的疲劳数据编辑研究科学出版物

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> This study presents the development of the STFT-based fatigue data editing technique that will be used as a tool to accelerate for accelerating fatigue testing. This technique was performed by removing low amplitude cycles contained in the original signal in order to produce a shortened signal using the Short-Time Fourier Transform (STFT) parameter. The effectiveness of STFT power spectrum was validated using an SAE random fatigue data in order to indicate the relationship between STFT parameter and fatigue damage. The data was separated into two segments, i.e., damage and non-damage segments based on the 100% retention of the original fatigue damage. For the editing process, the STFT power spectrum distribution was used as the parameter to identify the damaged segment according to the power spectrum Cut-Off Level (COL). The low amplitude cycles with power spectrum lower than COL value were then removed from the original signal. Thus, a new edited signal was obtained which has retained almost 100% of the original fatigue damage and has equivalent signal statistic. The edited signal was found to be approximately 84% of the time duration of the original signal.
机译： >这项研究介绍了基于STFT的疲劳数据编辑技术的发展，该技术将用作加速疲劳测试的工具。通过使用短时傅立叶变换（STFT）参数删除原始信号中包含的低幅度循环以产生缩短的信号来执行此技术。为了表明STFT参数与疲劳损伤之间的关系，使用SAE随机疲劳数据验证了STFT功率谱的有效性。根据原始疲劳损坏的100％保留率，将数据分为两个部分，即损坏和非损坏部分。对于编辑过程，将STFT功率谱分布用作根据功率谱截止水平（COL）识别损坏段的参数。然后从原始信号中删除功率谱低于COL值的低幅度循环。因此，获得了新的编辑信号，该信号保留了几乎100％的原始疲劳损伤并具有等效的信号统计量。发现编辑后的信号大约是原始信号持续时间的84％。

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