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摘要: 运用离散小波阈值去噪原理对SHPB测试信号进行了处理,针对SHPB测试信号持时短、突变快等特性,并根据各小波基对信号的重构均方根误差,选择Symlets小波系中的小波基Sym5为适合SHPB测试信号小波分析的最佳小波基,并运用无偏估计程序SURE确定了各分解层的阈值。比较了小波阈值去噪与动态应变仪中常规低通滤波器去噪的信噪比和均方根误差,研究结果表明,相对于常规低通滤波器的去噪处理,离散小波变换不仅有良好的去噪效果,而且能得到更精确的重构信号,可以取代动态应变仪中的低通滤波器对SHPB测试信号进行去噪处理。Abstract: The discrete wavelet threshold method was used to denoise the SHPB testing signals containing the high-frequency noise. Aimed at the short-duration and abrupt change of non-stationary SHPB testing signals, the Sym5 wavelet basis was chosen as the optimal one which has the lowest root mean square error (RMSE) among various wavelet basis reconstruction for the processing of SHPB testing signals. The unbiased estimation procedure SURE was used to determine the threshold value for each decomposition level, the signal was decomposed to six levels with the threshold values of 0.119, 0.085, 0.089, 0.102, 0.118, 0.116 from level 1 to level 6 respectively. Signal-noise ratio (SNR) and RMSE of the signals denoised by the discrete wavelet transform were compared with those by the conventional low-pass filters in dynamic strain indicators. SNR of the signal denoised by the discrete wavelet transform is greater than that by the low-pass filter, and RMSE of the signal denoised by the discrete wavelet transform is smaller than that by the low-pass filter. The results show that discrete wavelet transform not only has favorable denoising effects, but also can get more accurate reconstruction signals, it can replace the low-pass filters in dynamic strain indicators for the SHPB testing signal denoising.
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