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Signal-noise separation of sensor signal based on variational mode decomposition

机译:基于变分模式分解的传感器信号的信号噪声分离

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For the problem of strong noisy interference in the data acquisition of the micro electro mechanical system (MEMS) hydrophone, signal-noise separation of the MEMS hydrophone receiving signal make use of the variational mode decomposition (VMD), which is a completely non-recursive variational method. The frequency of the signal is segmented by the default parameters, then the center frequency and the intrinsic mode function (IMF) are obtained. Firstly, the empirical mode decomposition (EMD), the ensemble empirical mode decomposition (EEMD) and the VMD are regarded as a bandpass filter, respectively. And the simulation signal of different signal-to-noise ratio is going to be denoised. According to the denoising effect and performance index, the experiment shows that the denoising effect of the VMD is much better than the previous two methods. Secondly, the VMD is applied to the Fenji experimental data of the North University of China in the lake trial. Finally, the results show that the VMD is one of the best estimation algorithms of MEMS hydrophone original signal.
机译:对于对微电机系统(MEMS)水听器的数据采集的强烈干扰的问题,MEMS Hydophy接收信号的信号噪声分离利用变分模式分解(VMD),这是一个完全非递归的变分法。通过默认参数分段信号的频率,然后获得中心频率和内部模式功能(IMF)。首先,经验模式分解(EMD),集合经验模式分解(EEMD)和VMD分别被视为带通滤波器。并且,不同信噪比的模拟信号将被剥夺。根据去噪效果和性能指标,实验表明,VMD的去噪效果远远优于前两种方法。其次,VMD适用于中国北部湖北审判的汾吉实验数据。最后,结果表明,VMD是MEMS Hydrophate原始信号的最佳估计算法之一。

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