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本文将信号处理领域的经验模式分解算法应用于变形信息的提取中,通过引入阈值函数,建立了基于经验模式分解的尺度阈值滤波模型,采用优化模型确定了经验模式分解的次数。分别通过模拟试验和实测数据与小波阈值法和多项式拟合法进行了比对,分析表明:在低噪声情况下,三种方法都有一定的滤波效果;在高噪声情况下,经验模式分解的尺度阈值滤波法具有与小波阈值去噪法相等的精度,而且瞬时强噪声识别能力更好,优于多项式拟合法。
In this paper, the empirical mode decomposition algorithm in the field of signal processing is applied to the extraction of deformation information. Based on the threshold function, a threshold threshold filtering model based on empirical mode decomposition is established. The optimal model is used to determine the number of empirical mode decomposition. The simulation results show that the three methods have some filtering effects under low noise conditions. In the case of high noise, the scale of empirical mode decomposition The threshold filtering method has the same accuracy as the wavelet threshold denoising method, and the instantaneous strong noise recognition ability is better than the polynomial fitting method.