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The Noise Reduction of Structural Multichannel Signals Based on Independent Component Analysis

机译:基于独立分量分析的结构多通道信号降噪

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In practice, there are various noises mixed into structural vibration signals and the useful signals maybe covered up by noise. Independent component analysis (ICA) is one kind of effectual signal processing technology. Using of this method, the multichannel signals can be separated into some independent components. Because noise and vibration signal are statistical independent to each other, the ICA method is introduced to denoise the structural vibration signals. A noise channel is added to amplify the sensor signals to satisfy the calculation condition of ICA. Because the noise is unknown, the usual method simulating noises by numerical dummy channel needs to adjust the noise type unceasingly to obtain the perfect denoising effect. In this paper, an actual testing noise channel substitutes for the simulating channel. In the laboratory, a sensor, static relatively to the ground, is placed outside the vibration structure and regarded as noise channel. The signals of vibration experiment are processed by ICA. The effect of noise reduction compared with wavelet is satisfied and the denoised signals do not change its dynamic characteristic.
机译:在实践中,有各种噪声混入结构振动信号,并且可以通过噪声覆盖有用的信号。独立分量分析(ICA)是一种有效的信号处理技术。使用这种方法,多通道信号可以分成一些独立的组件。因为噪声和振动信号彼此独立于统计,所以引入ICA方法以使结构振动信号代替。添加噪声通道以放大传感器信号以满足ICA的计算条件。由于噪声未知,通常使用数值虚拟通道模拟噪声的方法需要不断调整噪声类型以获得完美的去噪效果。在本文中,实际测试噪声信道替换为模拟通道。在实验室中,传感器,相对接地的静态放置在振动结构之外并被视为噪声通道。振动实验信号由ICA加工。满足与小波相比的降噪效果,并且去噪信号不会改变其动态特性。

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