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Frequency slice wavelet transform for transient vibration response analysis

机译:频率切片小波变换用于瞬态振动响应分析

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摘要

This paper introduces a new kind of time-frequency signal analysis method, called frequency slice wavelet transform (FSWT), by means of extension of short-time Fourier transform (STFT) defined directly in frequency domain. The original signal can be decomposed by frequency slice function (FSF), which is similar with the wavelet base but can be designed very freely. At the same time, the original signal can be reconstructed by a FSWT representation in an easy way without the strict limitation of wavelet theory. Some new characteristics of its time-frequency window will be shown. Due to these features, FSWT is more flexible to fit ever-changing signals, and convenient to analyze and control in application. Next, the frequency resolution ratio of signal and Dirac function, etc., are employed to study FSWT, and to select a new scale parameter. The new scale is a good balance factor between time and frequency resolution. Moreover a fast discrete algorithm of FSWT is completed. Its application is focused on transient vibration signal analysis in this paper. FSWT can not only individually represent each modal signal in frequency domain, but also correctly show its details in time domain. FSWT helps to discover some new features of the experimental signal obtained from a small laboratory bridge monitoring system. By using FSWT, the filtering under high noise, and the segmenting of signal with high damping and close modes of frequency, will be discussed. Finally, the summary shows that this paper will be able to provide a more available tool for signal analyzing simultaneously in time-frequency domain, and further to refine the wavelet theory.
机译:通过扩展直接在频域中定义的短时傅立叶变换(STFT),本文介绍了一种新的时频信号分析方法,称为频率切片小波变换(FSWT)。原始信号可以通过频率切片函数(FSF)进行分解,该函数与小波基相似,但是可以非常自由地设计。同时,可以通过FSWT表示轻松地重建原始信号,而不必严格限制小波理论。将显示其时频窗口的一些新特性。由于这些功能,FSWT可以更灵活地适应不断变化的信号,并在应用中方便分析和控制。接下来,利用信号的频率分辨率和Dirac函数等研究FSWT,并选择新的比例参数。新的刻度是时间和频率分辨率之间的良好平衡因素。此外,完成了FSWT的快速离散算法。本文的应用主要针对瞬态振动信号分析。 FSWT不仅可以在频域中单独表示每个模态信号,而且可以在时域中正确显示其详细信息。 FSWT有助于发现从小型实验室桥梁监控系统获得的实验信号的一些新功能。通过使用FSWT,将讨论高噪声下的滤波以及具有高阻尼和频率接近模式的信号分割。最后,总结表明,本文将能够为时频域中的信号同时分析提供更多可用的工具,并进一步完善小波理论。

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