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为解决经典经验模态分解(empirical mode decomposition,EMD)滤波算法在低信噪比环境下滤波效果不佳的问题,提出了一种改进的EMD滤波算法。利用FFT对信号进行简单的频谱分析,若其中含有高频噪声,则对信号经EMD分解后得到的一阶本征模态函数(intrinsic mode function,IMF)分量做剔除处理;若信号中含有白噪声及毛刺干扰,则向经典EMD滤波算法中添加变尺度因子,然后对信号进行EMD滤波,在算法最后一次迭代时再将一阶IMF剔除。仿真试验结果表明,改进的EMD滤波算法在低信噪比环境下有较小的均方误差值,滤波效果较好。
In order to solve the problem that the empirical mode decomposition (EMD) filtering algorithm has poor filtering effect in low signal-to-noise ratio environment, an improved EMD filtering algorithm is proposed. If the signal contains high-frequency noise, the first-order intrinsic mode function (IMF) component obtained after the signal is decomposed by EMD is removed; if the signal contains white Noise and glitch interference, the variable scaling factor is added to the classical EMD filtering algorithm, and then the signal is EMD-filtered, and then the first-order IMF is eliminated at the last iteration of the algorithm. The simulation results show that the improved EMD filtering algorithm has a smaller mean square error in low signal-to-noise ratio environment and the filtering effect is better.