变分模态提取引导的桥梁自动异步运行模态分析

IF 5.1 2区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Tao Chen, Xiao-Mei Yang, Shu-Han Yang, Xiao-Jun Yao, Yong-Xiang Zheng
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引用次数: 0

摘要

结构模态参数是监测桥梁状态的关键。运行模态分析(OMA)由于只需要多个传感器的振动测量,在基于振动的桥梁结构健康监测中受到了广泛的关注。在监视过程中,这些测量中经常出现轻微的不同步。将经典的OMA方法,如自然激励技术(NExT)与特征系统实现算法(ERA)相结合,应用于异步振动测量会导致模态参数的显著误差。为了解决这一问题,本研究提出了一种基于模态保证准则(MAC)的时间同步技术,以生成可靠的模态识别同步振动测量。基于mac的方法利用了模态分量的比例性,只能检测单自由度信号之间的非同步问题。采用变分模态提取(VME)技术将桥梁振动测量数据迭代分解为SDOF分量。VME技术消除了在许多信号分解技术中需要人为地预先定义模式数的需要。在时间同步之后,采用基于next - era的自动OMA方法进行模态识别。通过公路桥梁有限元模型的振动测量和实际桥梁的现场监测数据,验证了该方法的有效性。结果表明,即使存在模态节点现象,该方法也能成功地同步振动信号并识别模态振型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Variational Mode Extraction-Guided Automated Asynchronous Operational Modal Analysis for Bridges

Variational Mode Extraction-Guided Automated Asynchronous Operational Modal Analysis for Bridges

Structural modal parameters are crucial for monitoring the condition of bridges. Operational modal analysis (OMA) has garnered great attention in vibration-based structural health monitoring of bridges because it only requires vibration measurements from multiple sensors. Slight asynchronization often occurs in these measurements during the monitoring process. Applying classical OMA methods, such as the natural excitation technique (NExT) combined with the eigensystem realization algorithm (ERA), to asynchronous vibration measurements can lead to significant errors in modal parameters. To address this issue, this study proposes a modal assurance criterion (MAC)-based time synchronization technique to generate reliable synchronous vibration measurements for modal identification. The MAC-based method takes advantage of the proportionality of modal components and is only capable of detecting nonsynchronized issues between single-degree-of-freedom (SDOF) signals. A variational mode extraction (VME) technique is employed to iteratively decompose bridge vibration measurements into SDOF components. The VME technique eliminates the need for artificially predefining the number of modes, which was required in many signal decomposition techniques. After time synchronization, the proposed method employs the NExT–ERA-based automatic OMA method for modal identification. The effectiveness of the proposed method is demonstrated using vibration measurements from both the finite element model of a highway bridge and field monitoring data from an actual bridge. The results show that the proposed method successfully synchronizes vibration signals and identifies mode shapes, even in the presence of modal node phenomena.

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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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