基于小波分析与高斯基函数的高速公路路堑水平位移数据分析研究  

Study on the horizontal displacement of highway cutting based on wavelet analysis and Gaussian function

作　　者：梁永平 王江荣 Liang Yongping;Wang Jiangrong(School of Civil Engineering,Lanzhou Petrochemical University of Vocational Technology,Lanzhou 730060,China;College of Information Processing and Control Engineering,Lanzhou Petrochemical University of Vocational Technology,Lanzhou 730060,China)

机构地区：[1]兰州石化职业技术大学土木工程学院,兰州730060 [2]兰州石化职业技术大学信息处理与控制工程学院,兰州730060

出　　处：《工程勘察》2021年第12期43-46,共4页Geotechnical Investigation & Surveying

基　　金：2020年度甘肃省高等学校创新基金项目(甘教技[2020]6号)(2019A-196);2019年兰州市科技发展指导性计划项目(兰科字[2020]38号)(2019-ZD-163);2019年省级大学生创新创业训练计划立项项目(甘教高[2019]7号)“三维激光扫描技术监测结构形变适用性问题研究”(创新训练项目)。

摘　　要：针对高速公路施工中路堑水平位移影响因素多,"噪声"明显的特点,利用小波变换原理和高斯基函数线性叠加的特点,构建了一种基于小波分析与高斯基函数的数据分析与动态预测模型。通过对历史实测数据进行小波分解消噪来提取路堑变形真实数据,利用高斯基函数模型实现了位移变形的超前预测。研究表明,提出的以小波原理进行监测数据消噪,通过将变形影响因素进行线性叠加构建高斯函数来拟合预测变化趋势的方法具有较好拟合优度值和较高预测精度的特点,对于同类工程监测数据处理具有较好的借鉴意义。In view of the influence factors on horizontal displacements in highway cutting construction, "noise" is obvious. A data analysis and dynamic prediction model is established based on wavelet analysis and Gaussian function. The real data of road cutting deformation are extracted by wavelet decomposition and de-noising of historical measured data. The results show that the proposed method uses wavelet principle to monitor data de-noising, and constructs Gaussian function by linear superposition of deformation influencing factors to fit and predict the change trend. It has the characteristics of good fit and high prediction accuracy, and has a good reference significance for similar engineering monitoring data processing.

关 键 词：水平位移 小波原理 高斯基函数 线性叠加 精度 

分 类 号：O141.4[理学—数学]