[an error occurred while processing this directive]
 
       首 页  |  期刊介绍  |  编委会  |  投稿指南  |  期刊订阅  |  广告合作  |  留言板  |  联系我们 |  English
现代隧道技术 2016, Vol. 53 Issue (4) :84-89    DOI:
分析与计算 最新目录 | 下期目录 | 过刊浏览 | 高级检索 << [an error occurred while processing this directive] | [an error occurred while processing this directive] >>
基于小波变换与卡尔曼滤波结合的 GM(1, 1)模型在高铁隧道沉降变形分析中的应用
(1 广西空间信息与测绘重点实验室,桂林 541004; 2 桂林理工大学测绘地理信息学院,桂林 541004;3 桂林理工大学广西矿冶与环境科学实验中心, 桂林 541004; 4 广西壮族自治区测绘地理信息产品质量检验站, 南宁 530023)
Application of Wavelet Transform and Kalman Filtering Based GM(1,1) Model in Analyzing Settlement Deformation of High-Speed Railway Tunnels
(1 Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin 541004; 2 College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004; 3 Guangxi Scientific Experiment Center of Mining, Metallurgy and Environment, Guilin University of Technology, Guilin 541004; 4 Guangxi Zhuang Autonomous Region Surveying and Mapping Geographic Information Product Quality Inspection Station, Nanning 530023)
Download: PDF (1909KB)   HTML (1KB)   Export: BibTeX or EndNote (RIS)      Supporting Info
摘要 高铁隧道的变形量较小, 但受随机噪声的干扰较大, 使得监测得到的沉降曲线不能反映实际的沉降情况。鉴于此, 文章提出了基于小波变换与卡尔曼滤波相结合的 RLG降噪方法, 该方法既有小波变换的去相关作用和多分辨分析功能, 又有卡尔曼滤波对未知信号的线性无偏最小方差估计的特点。采用 GM (1, 1)预测模型对降噪后的数据进行分析, 得到的结论是: 基于小波变换与卡尔曼滤波相结合的 GM(1, 1)模型的精度较基于卡尔曼滤波的GM(1, 1)模型的精度高, 可有效地运用于高铁隧道沉降分析中。
Service
把本文推荐给朋友
加入我的书架
加入引用管理器
Email Alert
RSS
作者相关文章
高 红 1
3
4 文鸿雁 1
2
3 李运健 4 聂光裕 1
3 杨 志 1
2
关键词隧道沉降 变形分析 小波变换 卡尔曼滤波 GM(1   1)模型     
Abstract: Although the settlement deformation of high-speed railway tunnels is not high, it is possible that a settle? ment curve may not reflect actual settlement deformation due to random noise interference. An RLG denoising method combining a wavelet transform with a Kalman filter is put forward that has the functions of noise-related interference removal and multiple resolution analysis by wavelet transform, and also has the advantages of linear unbiased minimum variance estimation to unknown signals by Kalman filtering. By applying the GM(1,1) model to analyze the data after denoising, it is detemined that the GM(1,1) model combining the wavelet transform and Kalman filtering is higher in precision than that of the GM(1,1) model based only on Kalman filtering and can be used for settlement analysis in high-speed railway tunnels.
KeywordsTunnel settlement,   Deformation analysis,   Wavelet transform,   Kalman filtering,   GM(1,1) model     
基金资助:

基金项目: 国家自然科学基金项目(41461089); 广西 “八桂学者” 岗位专项经费资助项目; 广西空间信息与测绘重点实验室项目(151400702,140452402); 广西自然科学基金项目(2014GXNSFAA118288) ;广西矿冶与环境科学实验中心资助课题(KH2012ZD004); 广西空间信息与测绘重点实验室开放基金项目 (13-051-14-20) ( . YCSZ2014151, YCSZ2012083) .

作者简介: 作者简介: 高 红(1990-), 男, 研究生, 从事变形监测与数据处理工作, E-mail: 827086139@qq.com. 通讯作者: 文鸿雁 (1963-), 男, 教授, 博士, 从事精密工程测量与专题信息系统研究工作, E-mail:glitewhy@163.com.
引用本文:   
高 红 1, 3, 4 文鸿雁 1等 .基于小波变换与卡尔曼滤波结合的 GM(1, 1)模型在高铁隧道沉降变形分析中的应用[J]  现代隧道技术, 2016,V53(4): 84-89
GAO Hong- 1, 3, 4 Wen-Hong-Yan- 1 etc .Application of Wavelet Transform and Kalman Filtering Based GM(1,1) Model in Analyzing Settlement Deformation of High-Speed Railway Tunnels[J]  MODERN TUNNELLING TECHNOLOGY, 2016,V53(4): 84-89
链接本文:  
http://www.xdsdjs.com/CN/      或     http://www.xdsdjs.com/CN/Y2016/V53/I4/84
 
没有本文参考文献
Copyright 2010 by 现代隧道技术