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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:实际上,结构振动信号中混入了各种噪声,有用的信号可能会被噪声掩盖。独立分量分析(ICA)是一种有效的信号处理技术。使用此方法,可以将多通道信号分离为一些独立的分量。由于噪声和振动信号在统计上是相互独立的,因此引入ICA方法对结构振动信号进行消噪。添加了噪声通道以放大传感器信号以满足ICA的计算条件。由于噪声是未知的,因此通常采用数字虚拟通道模拟噪声的方法需要不断调整噪声类型以获得理想的去噪效果。在本文中,一个实际的测试噪声通道替代了模拟通道。在实验室中,相对于地面静止的传感器放置在振动结构的外部,并被视为噪声通道。振动实验的信号由ICA处理。与小波相比,降噪效果令人满意,去噪后的信号不会改变其动态特性。

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