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Independent Component Analysis in Frequency Domain and Its Application in Structural Vibration Signal Separation

机译:频域的独立分量分析及其在结构振动信号分离中的应用

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In structural vibration signals, many kinds of signals (such as sinusoidal signals and impulsive signals) are mixed together. Convolutive mixtures often take place in vibration signals. In order to separate effectively the useful signals from the signals mixed by noise, the paper firstly transforms time signals into frequency signals through FFT, then applies FastICA to separate the useful signals from mixed signals, transforms frequency signals into time signals through IFFT, finally accomplishes the separating of the useful signals and noise. Two different experiments have been done to separate the steel structural vibration signals generated by hammer and vibration exciter in laboratory. The experiments results show that the mixed signals can be separated successfully when the exciters and sensors are placed on the suitable locations.
机译:在结构振动信号中,将多种信号(例如正弦信号和脉冲信号)混合在一起。卷曲混合物通常在振动信号中进行。为了分离由噪声混合的信号的有效信号,本文首先将时间信号转换为通过FFT的频率信号,然后应用Fastica将有用信号与混合信号分开,通过IFFT将频率信号转换为时间信号,最终实现分离有用的信号和噪声。已经完成了两个不同的实验,以分离锤子和振动激励器中的钢结构振动信号在实验室中。实验结果表明,当励磁器和传感器放置在合适的位置时,可以成功分离混合信号。

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