用改进小波阈值分析法处理场地微动数据
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摘要
针对场地土层监测数据受工程施工及气候变化等诸多外界因素的影响而出现土层结构判断失准的情况,基于小波分析理论,提出一种改进小波阈值去噪方法,用于处理青藏高原实测微动数据。首先采用基线校正法对原始监测数据进行调零,然后通过改进小波阈值分析法和传统滤波法分别对校正后的数据去噪处理,最后通过功率谱分析验证改进阈值小波分析法的滤波效果。对比结果表明:改进小波阈值分析法去噪效果优于传统滤波法,且与实测数据吻合较好,具有工程应用前景。
Aimed at overcoming the inaccurate judgment of soil layer structure due to the negative effect of engineering construction and weather variations in the case of monitoring data of foundation settlement,this paper,based on the wavelet analysis theory,proposes an improved wavelet threshold denoising method to deal with micro records by actual measurement from Qinghai-Tibet Plateau.The method involves obtaining the zero alignment of original monitoring data by using baseline correction method,achieving denoising process of the revised data by the combination of the improved wavelet threshold denoising method and traditional wavelet denoising method,and verifying the filtering effect produced by the improved wavelet threshold denoising method,based on power spectrum analysis.The results show that the improved wavelet threshold denoising method demonstrates a better denoising effect than does conventional wavelet de-noising method,a better agreement with actual measurement data,and a better engineering application prospect.
Aimed at overcoming the inaccurate judgment of soil layer structure due to the negative effect of engineering construction and weather variations in the case of monitoring data of foundation settlement,this paper,based on the wavelet analysis theory,proposes an improved wavelet threshold denoising method to deal with micro records by actual measurement from Qinghai-Tibet Plateau.The method involves obtaining the zero alignment of original monitoring data by using baseline correction method,achieving denoising process of the revised data by the combination of the improved wavelet threshold denoising method and traditional wavelet denoising method,and verifying the filtering effect produced by the improved wavelet threshold denoising method,based on power spectrum analysis.The results show that the improved wavelet threshold denoising method demonstrates a better denoising effect than does conventional wavelet de-noising method,a better agreement with actual measurement data,and a better engineering application prospect.
引文
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[2]王荫江.小波分析瑞利波测试中的应用[D].南京:河海大学,2006:26-52.
[3]李长冬,唐辉明,胡斌,等.小波分析和RBF神经网络在地基沉降预测中的应用研究[J].岩土力学,2008,29(7):1917-1922.
[4]姜绍辉.小波变换及在提高地震资料信噪比中的应用[D].青岛:中国海洋大学,2005:21-30.
[5]陈宪麦,王澜,陶夏新,等.基于小波分析理论的轨道不平顺分析[J].铁道工程学报,2008(1):57-61.
[6]李薇,张文,郑妍.基于改进的小波阈值的电能质量信号去噪[J].应用科技,2012(2):15-18.
[7]王大巍.一种改进的小波阈值去噪算法研究[J].硅谷,2012(5):36-38.
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