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爆破震动测试得到的数据常常具有较大的离散性,采用剔除错误数据和小波降噪对爆破震动检测数据进行预处理,以标准残差平方和作为爆破振动实测数据与萨道夫斯基公式拟合值偏差大小的判断依据,应用小波降噪对实测数据进行处理的方法,优化了粒子群算法对萨道夫斯基公式中的k和α的回归分析。研究结果表明,小波降噪和粒子群优化算法结合使用,能够较真实地反映爆破震动测试的真实情况,从而提高了对爆破震动测试模拟的精度。研究结果对爆破振动测试理论和工程实践具有一定的参考价值。
The data obtained by blasting vibration test often have large discreteness. The detection data of blasting vibration are preprocessed by eliminating error data and wavelet denoising. The standard residual square sum is used as the data of blasting vibration to fit with the Sadowssky equation Based on the judgment of the value of the deviation, the method of using the wavelet denoising to process the measured data, and the regression analysis of k and α in the Sadovski’s formula are optimized. The results show that the combination of wavelet denoising and particle swarm optimization algorithm can reflect the real situation of blasting vibration test more accurately, and improve the accuracy of blasting vibration test simulation. The research results have certain reference value to blasting vibration test theory and engineering practice.