Occhipinti Giuseppe, Lo Iacono Francesco, Tusa Giuseppina, Costanza Antonio, Fertitta Gioacchino, Lodato Luigi, Macaluso Francesco, Martino Claudio, Mugnos Giuseppe, Oliva Maria, Storni Daniele, Alessandroni Gianni, Navarra Giacomo, Patanè Domenico
Istituto Nazionale di Geofisica e Vulcanologia-Osservatorio Etneo, 95125 Catania, Italy.
Department of Engineering and Architecture, University of Enna "Kore", 94100 Enna, Italy.
Sensors (Basel). 2025 Feb 8;25(4):1010. doi: 10.3390/s25041010.
This study presents the results of an experimental investigation conducted on a 2:3 scale model of a two-story stone masonry building. We tested the model on the UniKORE L.E.D.A. lab shake table, simulating the Mw 6.3 earthquake ground motion that struck L'Aquila, Italy, on 6 April 2009, with progressively increasing peak acceleration levels. We installed a network of accelerometric sensors on the model to capture its structural behaviour under seismic excitation. Medium-to lower-cost MEMS accelerometers (classes A and B) were compared with traditional piezoelectric sensors commonly used in Structural Health Monitoring (SHM). The experiment assessed the structural performance and damage progression of masonry buildings subjected to realistic earthquake inputs. Additionally, the collected data provided valuable insights into the effectiveness of different sensor types and configurations in detecting key vibrational and failure patterns. All the sensors were able to accurately measure the dynamic response during seismic excitation. However, not all of them were suitable for Operational Modal Analysis (OMA) in noisy environments, where their self-noise represents a crucial factor. This suggests that the self-noise of MEMS accelerometers must be less than 1 µg/√Hz, or preferably below 0.5 µg/√Hz, to obtain good results from the OMA. Therefore, we recommend ultra-low-noise sensors for detecting differences in the structural behaviour before and after seismic events. Our findings provide valuable insights into the seismic vulnerability of masonry structures and the effectiveness of sensors in detecting damage. The management of buildings in earthquake-prone areas can benefit from these specifications.
本研究展示了对一座两层石砌建筑2:3比例模型进行实验研究的结果。我们在UniKORE L.E.D.A.实验室振动台上对该模型进行测试,模拟了2009年4月6日袭击意大利拉奎拉的Mw 6.3级地震地面运动,并逐步提高峰值加速度水平。我们在模型上安装了加速度传感器网络,以捕捉其在地震激励下的结构行为。将中低成本的MEMS加速度计(A类和B类)与结构健康监测(SHM)中常用的传统压电传感器进行了比较。该实验评估了砖石建筑在实际地震输入下的结构性能和损伤发展情况。此外,收集的数据为不同传感器类型和配置在检测关键振动和破坏模式方面的有效性提供了有价值的见解。所有传感器都能够准确测量地震激励期间的动态响应。然而,并非所有传感器都适用于噪声环境下的运行模态分析(OMA),在这种环境中,它们的自噪声是一个关键因素。这表明,MEMS加速度计的自噪声必须小于1 µg/√Hz,或最好低于0.5 µg/√Hz,才能从OMA中获得良好结果。因此,我们建议使用超低噪声传感器来检测地震事件前后结构行为的差异。我们的研究结果为砖石结构的地震脆弱性以及传感器在检测损伤方面的有效性提供了有价值的见解。地震多发地区的建筑物管理可以从这些规范中受益。