基于小波与谱分析的大坝变形预报模型

李双平; 张斌

doi:10.11779/CJGE201502024

基于小波与谱分析的大坝变形预报模型 English Version

李双平^{1, 2},
张斌²

1. 武汉大学测绘学院,湖北武汉 430079; 2. 长江勘测规划设计研究有限责任公司,湖北武汉 430010

基金项目: “十二五”国家科技支撑计划（2011BAB10B07）

详细信息

作者简介:
李双平（1974- ）,男,博士研究生,主要从事水利水电工程安全监测方面的研究工作。E-mail: cjwjcgs_lsp@126.com。

中图分类号: TU47
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出版历程
- 收稿日期: 2014-05-19
- 发布日期: 2015-03-01

Forecast model for dam deformation based on wavelet and spectral analysis

LI Shuang-ping^{1, 2},
ZHANG Bin²

1. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China; 2. Changjiang Institute of Surveying, Planning, Design and Research, Changjiang Spatial Information Technology Engineering Co., Ltd., Wuhan 430010, China

摘要

摘要: 传统大坝变形回归分析模型不具备降噪功能,同时人为拟定环境量周期项,存在一定的不足,对此,引入小波与谱分析方法,提出了基于小波与谱分析的大坝变形预报模型,以提高预报精度。首先对实测的位移数据进行分段三次Hermite插值,获取均匀采样数据;然后对采样数据进行小波分解,做降噪处理;最后通过谱分析,根据功率谱图,确定位移量的主要周期项,结合传统回归方法构建合理的拟合模型,实现大坝变形的预报。以2010年三峡大坝175 m蓄水后的实测数据为样本,采用文中方法对大坝变形值预报,结果表明预报精度较高,新方法对提高大坝安全评估和类似变形分析有重要价值。
- 大坝变形 /
- 均匀采用 /
- 小波 /
- 谱分析 /
- 预报
Abstract: The traditional regression model for dam deformation is not equipped with denoising function, and has certain defects because the cycle items of environment are artificially determined. In order to improve the accuracy of the model forecast, the method of wavelet and spectral analysis is used, and a forecast model is proposed. The new method uses the observed data interpolated by the piecewise cubic Hermite polynomial to get the uniform sampling data. Then the noise of the uniform sampling data is reduced by the wavelet transform. Finaly, the dominant periodic terms of the data are found by using the spectrual analysis. Combining the traditional regression model, the appropriate model is established. On this basis, the deformation of Three Gorges Dam with impoundment of 175 m is predicted. The calculated results show that the proposed new method can effectively forecast the dam deformation with high precision and has the reference value for dam safety evaluation and similar deformation analysis.
- dam deformation /
- uniform sampling /
- wavelet /
- spectral analysis /
- forecast

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参考文献(15)

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