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用改进小波阈值分析法处理场地微动数据
引用本文:董连成,刘娟,胡新福,李广影,黄学欣.用改进小波阈值分析法处理场地微动数据[J].黑龙江科技学院学报,2013(3):289-292.
作者姓名:董连成  刘娟  胡新福  李广影  黄学欣
作者单位:黑龙江科技大学建筑工程学院;中国科学院寒区旱区环境与工程研究所冻土工程国家重点实验室
基金项目:中国科学院冻土工程国家重点实验室开放基金课题(SKLFSE201103);黑龙江省自然科学基金项目(E201227);黑龙江省教育厅科学技术研究面上项目(12511486;11551442)
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。

关 键 词:小波阈值  微动数据  滤波  功率谱

Microtremors records processing with improving wavelet thresholding
DONG Liancheng,LIU Juan,HU Xinfu,LI Guangying,HUANG Xuexin.Microtremors records processing with improving wavelet thresholding[J].Journal of Heilongjiang Institute of Science and Technology,2013(3):289-292.
Authors:DONG Liancheng  LIU Juan  HU Xinfu  LI Guangying  HUANG Xuexin
Institution:1(1.School of Civil Engineering,Heilongjiang Institute of Science & Technology,Harbin 150022,China; 2.State Key Laboratory of Frozen Soil Engineering,Cold & Arid Regions Environmental & Engineering Research Institute,Chinese Academy of Sciences,Lanzhou 730000,China)
Abstract: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 set- tlement, this paper, based on the wavelet analysis theory, proposes an improved wavelet threshold de- noising 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, a- chieving denoising process of the revised data by the combination of the improved wavelet threshold de- noising 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 conven- tional wavelet de-noising method, a better agreement with actual measurement data, and a better engi- neering application prospect.
Keywords:wavelet threshold  fretting data  filtering  power spectrum
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