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Robust and Efficient Synchronization for Structural Health Monitoring Data with Arbitrary Time Lags

Engineering Structures(2025)SCI 2区

Tongji Univ

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Abstract
With the advancement of structural health monitoring (SHM) technology, operational modal analysis (OMA) has played an indispensable role in finite-element model updating, damage detection, and wind resistance design. As a result of combined factors such as sensor errors and equipment failures, multiple-channel response signals often exhibit slight or significant asynchrony, leading to unforeseeable uncertainty and phase deviation during OMA. Additionally, both clock-based wireless sensor networks and cable-based wired SHM systems cannot guarantee complete data synchronization. This paper presents a novel approach for detecting and synchronizing SHM data with arbitrary time lags in the post-processing stage. The approach focuses on phase variations across multiple modes and converts time lags into phase period differences within a specified bandwidth. To improve the accuracy and automation of frequency-domain analysis, the variational mode extraction (VME) algorithm is employed in the study, which provides a robust solution by extracting fundamental mode components. The feasibility is validated utilizing a linear time-invariant simulation system with non-proportional damping. Finally, the proposed approach is implemented in the SHM system with actual time lags at the Shanghai Tower, the tallest building in China. The relative time lags between vibration response channels are successfully estimated, revealing that the data asynchronization of channels can be attributed to the misaligned timestamps between data acquisition substations. This finding mitigates current challenges in estimating the mode shape of the Shanghai Tower and assists in reducing uncertainty during the OMA process.
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Key words
Structural health monitoring,Time lag,Data synchronization,Phase deviation,VME algorithm,Shanghai Tower
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要点】:本文提出了一种新颖的方法,用于检测和同步具有任意时间延迟的结构健康监测数据,通过将时间延迟转换为特定带宽内的相位周期差异,有效解决了操作模态分析中的不确定性问题。

方法】:研究采用变分模式提取(VME)算法,专注于多个模式间的相位变化,将时间延迟转换为相位周期差异,从而提高频率域分析的准确性和自动化水平。

实验】:通过线性时不变模拟系统验证了方法的可行性,并在上海中心大厦的结构健康监测系统中实际应用,成功估计了振动响应通道间的相对时间延迟,证实了该方法能够有效减小操作模态分析过程中的不确定性。