基于 DVMD-VDR 的堤坝结构振动特性分析

IF 3.6 2区 工程技术 Q1 ENGINEERING, CIVIL Journal of Civil Structural Health Monitoring Pub Date : 2024-03-23 DOI:10.1007/s13349-024-00782-0
Jianwei Zhang, Zhirui Li, Qi Jiang, Jinlin Huang, Kelei Cao
{"title":"基于 DVMD-VDR 的堤坝结构振动特性分析","authors":"Jianwei Zhang, Zhirui Li, Qi Jiang, Jinlin Huang, Kelei Cao","doi":"10.1007/s13349-024-00782-0","DOIUrl":null,"url":null,"abstract":"<p>Aiming at the problem that earth-rock dam structure is susceptible to non-stationary signal interference in the process of collecting vibration information, this paper proposes a feature information extraction method based on the fusion of Dispersion Entropy Variational Mode Decomposition (DVMD) and Variance Dedication Rate (VDR) improved by Dispersion Entropy. First, multi-channel vibration signals are dynamically fused using the variance dedication rate to extract the complete vibration information of the dam body; then the entropy value of each modal component (Intrinsic Mode Function) under different decomposition layers is calculated by using Dispersion Entropy, and the entropy turning point is selected to determine the number of decomposition modes of DVMD, to compensate for the insufficiency of blind selection of decomposition modes in Variational Mode Decomposition. The entropy value turning point is selected to determine the number of decomposition modes of DVMD, which can make up for the deficiency of blindly selecting decomposition modes in Variational Mode Decomposition. To verify the accuracy and effectiveness of the method in this paper, three groups of simulated signals are constructed for numerical simulation, and it is found that its noise reduction effect is better than that of digital filtering, wavelet thresholding and Improved Variational Mode Decomposition, and the signal feature information can be effectively extracted. Combining the measured data of the embankment dam of HeLong dam site under the excitation of natural environment, the operational characteristic information of the dam body is analyzed and compared with the finite element simulation results, and the study shows that the DVMD–VDR method can efficiently extract the complete vibration characteristic information of the structure, which has a good engineering practicability, and it can provide the basis for the on-line monitoring of the structural operational status of the embankment dam.</p>","PeriodicalId":48582,"journal":{"name":"Journal of Civil Structural Health Monitoring","volume":"28 1","pages":""},"PeriodicalIF":3.6000,"publicationDate":"2024-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analysis of structural vibration characteristics of embankment dam based on DVMD–VDR\",\"authors\":\"Jianwei Zhang, Zhirui Li, Qi Jiang, Jinlin Huang, Kelei Cao\",\"doi\":\"10.1007/s13349-024-00782-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Aiming at the problem that earth-rock dam structure is susceptible to non-stationary signal interference in the process of collecting vibration information, this paper proposes a feature information extraction method based on the fusion of Dispersion Entropy Variational Mode Decomposition (DVMD) and Variance Dedication Rate (VDR) improved by Dispersion Entropy. First, multi-channel vibration signals are dynamically fused using the variance dedication rate to extract the complete vibration information of the dam body; then the entropy value of each modal component (Intrinsic Mode Function) under different decomposition layers is calculated by using Dispersion Entropy, and the entropy turning point is selected to determine the number of decomposition modes of DVMD, to compensate for the insufficiency of blind selection of decomposition modes in Variational Mode Decomposition. The entropy value turning point is selected to determine the number of decomposition modes of DVMD, which can make up for the deficiency of blindly selecting decomposition modes in Variational Mode Decomposition. To verify the accuracy and effectiveness of the method in this paper, three groups of simulated signals are constructed for numerical simulation, and it is found that its noise reduction effect is better than that of digital filtering, wavelet thresholding and Improved Variational Mode Decomposition, and the signal feature information can be effectively extracted. Combining the measured data of the embankment dam of HeLong dam site under the excitation of natural environment, the operational characteristic information of the dam body is analyzed and compared with the finite element simulation results, and the study shows that the DVMD–VDR method can efficiently extract the complete vibration characteristic information of the structure, which has a good engineering practicability, and it can provide the basis for the on-line monitoring of the structural operational status of the embankment dam.</p>\",\"PeriodicalId\":48582,\"journal\":{\"name\":\"Journal of Civil Structural Health Monitoring\",\"volume\":\"28 1\",\"pages\":\"\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-03-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Civil Structural Health Monitoring\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s13349-024-00782-0\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Civil Structural Health Monitoring","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s13349-024-00782-0","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0

摘要

针对土石坝结构在振动信息采集过程中易受非稳态信号干扰的问题,本文提出了一种基于频散熵变异模态分解(DVMD)和频散熵改进的方差奉献率(VDR)融合的特征信息提取方法。首先,利用方差奉献率对多通道振动信号进行动态融合,提取完整的坝体振动信息;然后,利用离散熵计算不同分解层下各模态分量(本征模态函数)的熵值,并选择熵值转折点确定 DVMD 的分解模态数,以弥补变模态分解法盲目选择分解模态的不足。选择熵值转折点来确定 DVMD 的分解模式数,可以弥补变量模式分解中盲目选择分解模式的不足。为验证本文方法的准确性和有效性,构建了三组模拟信号进行数值模拟,发现其降噪效果优于数字滤波、小波阈值法和改进变分模式分解法,并能有效提取信号特征信息。结合贺龙坝址堤坝在自然环境激励下的实测数据,分析了坝体的运行特征信息,并与有限元模拟结果进行了对比,研究表明 DVMD-VDR 方法能有效提取结构的完整振动特征信息,具有较好的工程实用性,可为堤坝结构运行状态的在线监测提供依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Analysis of structural vibration characteristics of embankment dam based on DVMD–VDR

Aiming at the problem that earth-rock dam structure is susceptible to non-stationary signal interference in the process of collecting vibration information, this paper proposes a feature information extraction method based on the fusion of Dispersion Entropy Variational Mode Decomposition (DVMD) and Variance Dedication Rate (VDR) improved by Dispersion Entropy. First, multi-channel vibration signals are dynamically fused using the variance dedication rate to extract the complete vibration information of the dam body; then the entropy value of each modal component (Intrinsic Mode Function) under different decomposition layers is calculated by using Dispersion Entropy, and the entropy turning point is selected to determine the number of decomposition modes of DVMD, to compensate for the insufficiency of blind selection of decomposition modes in Variational Mode Decomposition. The entropy value turning point is selected to determine the number of decomposition modes of DVMD, which can make up for the deficiency of blindly selecting decomposition modes in Variational Mode Decomposition. To verify the accuracy and effectiveness of the method in this paper, three groups of simulated signals are constructed for numerical simulation, and it is found that its noise reduction effect is better than that of digital filtering, wavelet thresholding and Improved Variational Mode Decomposition, and the signal feature information can be effectively extracted. Combining the measured data of the embankment dam of HeLong dam site under the excitation of natural environment, the operational characteristic information of the dam body is analyzed and compared with the finite element simulation results, and the study shows that the DVMD–VDR method can efficiently extract the complete vibration characteristic information of the structure, which has a good engineering practicability, and it can provide the basis for the on-line monitoring of the structural operational status of the embankment dam.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Civil Structural Health Monitoring
Journal of Civil Structural Health Monitoring Engineering-Safety, Risk, Reliability and Quality
CiteScore
8.10
自引率
11.40%
发文量
105
期刊介绍: The Journal of Civil Structural Health Monitoring (JCSHM) publishes articles to advance the understanding and the application of health monitoring methods for the condition assessment and management of civil infrastructure systems. JCSHM serves as a focal point for sharing knowledge and experience in technologies impacting the discipline of Civionics and Civil Structural Health Monitoring, especially in terms of load capacity ratings and service life estimation.
期刊最新文献
Development and implementation of medium-fidelity physics-based model for hybrid digital twin-based damage identification of piping structures Innovated bridge health diagnosis model using bridge critical frequency ratio R–C–C fusion classifier for automatic damage detection of heritage building using 3D laser scanning An AIoT system for real-time monitoring and forecasting of railway temperature Environmental effects on the experimental modal parameters of masonry buildings: experiences from the Italian Seismic Observatory of Structures (OSS) network
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1