Innovative Approach to Dam Deformation Analysis: Integration of VMD, Fractal Theory, and WOA-DELM

IF 4.6 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY Structural Control & Health Monitoring Pub Date : 2024-05-20 DOI:10.1155/2024/1710019
Bin Ou, Caiyi Zhang, Bo Xu, Shuyan Fu, Zhenyu Liu, Kui Wang
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Abstract

This paper introduces a novel and comprehensive model for the analysis of dam deformation trends, integrating the variational mode decomposition (VMD) method, fractal theory, and the whale optimization algorithm (WOA) to refine the deep extreme learning machine (DELM) model. This integration allows for a meticulous denoising process through VMD, effectively isolating pertinent signal characteristics from noise and measurement interference. Following this, fractal theory is utilized to conduct an in-depth qualitative analysis of the denoised data, capturing intricate patterns within the deformation trends. The model further evolves with the application of WOA to optimize the DELM model, thereby facilitating an integrated approach that merges qualitative insights with quantitative analysis. The efficacy of this advanced model is demonstrated through a case study, highlighting its capability to deliver accurate and reliable predictions that are in harmony with practical engineering scenarios. This research not only offers a robust framework for analyzing dam deformation trends but also sets a new standard in the field, providing a new solution for assessing structural integrity in hydrological engineering.

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大坝变形分析的创新方法:整合 VMD、分形理论和 WOA-DELM
本文介绍了一种用于分析大坝变形趋势的新型综合模型,该模型综合了变模分解(VMD)方法、分形理论和鲸鱼优化算法(WOA),以完善深度极端学习机(DELM)模型。这种整合通过 VMD 实现了细致的去噪过程,有效地将相关信号特征从噪声和测量干扰中分离出来。随后,利用分形理论对去噪数据进行深入的定性分析,捕捉变形趋势中错综复杂的模式。通过应用 WOA 来优化 DELM 模型,该模型得到进一步发展,从而促进了定性分析与定量分析相结合的综合方法。这一先进模型的功效通过一个案例研究得以展示,突出了其提供与实际工程场景相一致的准确可靠预测的能力。这项研究不仅为分析大坝变形趋势提供了一个稳健的框架,还为该领域设定了一个新标准,为评估水文工程中的结构完整性提供了一个新的解决方案。
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来源期刊
Structural Control & Health Monitoring
Structural Control & Health Monitoring 工程技术-工程:土木
CiteScore
9.50
自引率
13.00%
发文量
234
审稿时长
8 months
期刊介绍: The Journal Structural Control and Health Monitoring encompasses all theoretical and technological aspects of structural control, structural health monitoring theory and smart materials and structures. The journal focuses on aerospace, civil, infrastructure and mechanical engineering applications. Original contributions based on analytical, computational and experimental methods are solicited in three main areas: monitoring, control, and smart materials and structures, covering subjects such as system identification, health monitoring, health diagnostics, multi-functional materials, signal processing, sensor technology, passive, active and semi active control schemes and implementations, shape memory alloys, piezoelectrics and mechatronics. Also of interest are actuator design, dynamic systems, dynamic stability, artificial intelligence tools, data acquisition, wireless communications, measurements, MEMS/NEMS sensors for local damage detection, optical fibre sensors for health monitoring, remote control of monitoring systems, sensor-logger combinations for mobile applications, corrosion sensors, scour indicators and experimental techniques.
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