为比较基于Shannon熵准则的最优小波包基信号去噪算法的优越性,采用延期时间分别为22 ms、45 ms和75 ms高精度雷管进行台阶爆破试验,对监测的振动信号分别用基于小波变换去噪算法和基于Shannon熵准则的最优小波包基信号去噪算法进行对比并计算2者方法的峰值信噪比.结果表明:基于Shannon熵准则的最优小波包基信号去噪算法提高了信噪比,能够识别高精度雷管爆破振动信号随药量增加和延期时间不同而产生的速度峰值变化,具有较强的信噪分离能力和良好的去噪性能,达到了很好的去噪效果.%For comparing the advantage of de-noising with best wavelet packet basis on Shannon entropy, the blast experiments with delay time of 22 ms、45 ms and 75 ms were done. The wavelet transformation and the best wavelet packet basis on Shannon entropy were used to de-noising the blasting vibration signal,then calculate the peak signal to noise ratio ( PSNR) separately. The results show that the de-noising way of best wavelet packet basis on Shannon entropy has a good de-noising performance, and can recognize and determine the changes of peak velocity from the high precision blasting vibration signal as the charge mass added,and achieves a good de-noising result.
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