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LabVIEW toolkits for output-only modal identification and long-term dynamic structural monitoring

机译:LabVIEW工具包,用于仅输出模式识别和长期动态结构监控

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摘要

This paper describes the development of computational tools for modal identification and long term dynamic monitoring in LabVIEW environment. These tools mainly consist of two individual toolkits for structural modal identification (SMI) and continuous monitoring (CSMI), respectively. The SMI toolkit implements the frequency domain Peak-Picking (PP) and Enhanced Frequency Domain Decomposition (EFDD) method, as well as the time domain Stochastic Subspace Identification (SSI) techniques. Based on this toolkit, the user can easily develop the whole process of structural modal identification by simply pushing buttons. The CSMI toolkit was conceived for continuous dynamic monitoring excluding manual interaction. It automatically searches the latest output measurements, detects maximum vibration amplitudes and makes statistical treatment of acceleration time series, generates waterfall plots for depicting the frequency component distribution and identifies modal parameters based on automated EFDD technique. The application of these tools is briefly described based on experimental data collected at Pinhao bridge and Coimbra footbridge.
机译:本文介绍了在LabVIEW环境中用于模式识别和长期动态监控的计算工具的开发。这些工具主要由两个分别用于结构模态识别(SMI)和连续监测(CSMI)的工具包组成。 SMI工具包实现了频域“峰值拾取”(PP)和增强型频域分解(EFDD)方法以及时域随机子空间识别(SSI)技术。基于该工具包,用户只需按一下按钮就可以轻松开发结构模态识别的整个过程。 CSMI工具包旨在用于连续动态监视,而无需手动交互。它会自动搜索最新的输出测量值,检测最大振动幅度,并对加速时间序列进行统计处理,生成瀑布图以描绘频率分量分布,并基于自动EFDD技术识别模式参数。根据在Pinhao桥和Coimbra人行桥上收集的实验数据简要描述了这些工具的应用。

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