Innovative multi-setup modal analysis using random decrement technique: a novel approach for enhanced structural characterization

A. Sabamehr, Nima Amani, Ashutosh Bagchi
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Abstract

PurposeThis paper introduces a novel multi-setup merging method and assesses its performance using simulated response data from a Finite Element (FE) model of a five-storey frame and experimental data from a cantilever beam tested in a laboratory setting.Design/methodology/approachIn the research conducted at the Central Building Research Institute (CBRI) in Roorkee, India, a cantilever beam was examined in a laboratory setting. The study successfully extracted the modal properties of the multi-storey building using the merging technique. Identified frequencies and mode shapes provide valuable insights into the building's dynamic behavior, which is essential for structural analysis and assessment. The sensor layout and data merging approach allowed for the capture of relevant vibration modes despite the limited number of sensors, demonstrating the effectiveness of the methodology.FindingsThe results show that reducing the number of sensors can impact the accuracy of the mode shapes. It is recommended to use a minimum of 8 sensor locations (every two floors) for the building under study to obtain reliable benchmark results for further evaluation, periodic monitoring, and damage identification.Originality/valueThe results demonstrate that the developed algorithm can improve the system identification process and streamline data handling. Furthermore, the proposed method is successfully applied to analyze the modal properties of a multi-storey building.
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使用随机递减技术的创新型多设置模态分析:增强结构特性的新方法
本文介绍了一种新颖的多设置合并方法,并使用五层框架有限元(FE)模型的模拟响应数据和在实验室测试的悬臂梁的实验数据评估了该方法的性能。研究利用合并技术成功提取了多层建筑的模态特性。识别出的频率和模态振型为了解建筑物的动态行为提供了宝贵的信息,这对结构分析和评估至关重要。尽管传感器数量有限,但传感器布局和数据合并方法仍能捕捉到相关的振动模式,证明了该方法的有效性。建议对所研究的建筑物至少使用 8 个传感器位置(每两层),以获得可靠的基准结果,用于进一步评估、定期监测和损坏识别。此外,所提出的方法还成功地应用于分析多层建筑的模态特性。
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