首页|EEMD-小波在高边坡变形信息提取中的应用研究

EEMD-小波在高边坡变形信息提取中的应用研究

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针对高边坡变形呈现非平稳性及数据"噪声"多源的问题，提出了一种定向滤波的变形信息提取方法。首先，利用集合经验模态分解方法分解变形时序数据，结合定量分析法判别模态分量信号频段;然后，对高频模态分量中的"噪声"利用小波函数进行"靶向"消噪处理，并对趋势项进行傅里叶级数拟合;最后，重构高边坡变形分析模型，实现真实变形量的提取。结果表明，对比分析各项检验指标，通过"靶向"消噪，各高频模态分量消噪效果明显，重构后的集合经验模态分解(Ensemble Empirical Mode Decomposition，EEMD)-小波高边坡变形分析模型较原始形变和其他模型在精度指标方面提升显著，该方法可用于高边坡的变形预测分析和真实变形量提取。
Application of EEMD-wavelet in extracting deformation information of high slopes
Aiming at the problems of non-stationary deformation of high slope and multiple sources of data"noise",a directional filtering method for deformation information extraction is proposed in this paper.Firstly,the Ensemble Empirical Mode Decomposition(EEMD)is used to decompose the deformation time series data,and the frequency band of the modal component is identified by combining the cumulative mean and the energy value of two quantitative analysis methods.The"noise"in the high-frequency modal component is denoised by the wavelet function.After the wavelet denoising,the orthodoxy and correlation coefficient indexes of the high-frequency modal component are improved significantly.To overcome the defect that the residual terms of EEMD decomposition can not accurately reflect the trend of deformation,Fourier series fitting is carried out on the trend term.Then the filtered high-frequency modal component,other modal components,and fitting trend item are superimposed to reconstruct the deformation analysis model of a high slope,realizing the extraction of the real deformation.By comparing the constructed EEMD-wavelet model with the other four different models through various inspection indexes,it can be concluded that the noise reduction effect of the high slope deformation time series data is obvious through"targeted",and the noise reduction effect of each high-frequency modal component is obvious.Compared with the original deformation and other models,the accuracy index of the reconstructed analysis model of high slope deformation is improved significantly.The constructed EEMD-wavelet model makes full use of the advantages of the component model,overcomes the defects of the single model,and shows a good ability to extract the deformation information of a high slope.This method can be used to predict the deformation of high slopes and extract the real deformation.

public safetydeformationEnsemble Empirical Mode Decomposition(EEMD)-waveletintrinsic mode functionmodel reconstructionaccuracyinformation extraction

梁永平、李盛、赖国泉

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兰州石化职业技术大学土木工程学院,兰州 730060

兰州交通大学土木工程学院,兰州 730050

中铁西北科学研究院有限公司,兰州 730000

公共安全 变形 集合经验模态分解(EEMD)-小波 模态分量 模型重构 精度 信息提取

国家自然科学基金项目甘肃省教育厅高校教师创新基金项目兰州市科技发展指导性计划项目

518680412023B-2802022-5-4

2024

10.13637/j.issn.1009-6094.2023.0416

安全与环境学报
北京理工大学 中国环境科学学会 中国职业安全健康协会

安全与环境学报

CSTPCD北大核心
影响因子：0.943
ISSN：1009-6094
年,卷(期)：2024.24(3)
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