使用惯性无线传感器和并行训练模型评估建筑物的双轴倾斜
Luis Pastor Sánchez-Fernández1, Luis Alejandro Sánchez-Pérez2, José Juan Carbajal-Hernández1
1Instituto Politécnico Nacional, Centro de Investigación en Computación, Juan de Dios Bátiz Ave., México City 07738, Mexico.
Sensors (Basel, Switzerland)
|June 10, 2023
概括
这项研究引入了一种新的双轴倾斜评估,用于使用MEMS惯性传感器和先进算法的建筑物. 该系统可以实时监测结构倾斜,这对于检测诸如差异性土壤沉积等问题至关重要.
科学领域:
- 结构工程 结构工程
- 地质技术工程 地质技术工程
- 传感器技术 传感器技术
背景情况:
- 微电机系统 (MEMS) 传感器在结构健康监测中提供了多功能应用.
- 当前的实时监控系统往往受到成本和信号处理挑战的限制,尤其是在杂的加速数据方面.
- 准确处理静态加速度变化是测量双轴倾斜和结构模式的关键.
研究的目的:
- 开发和验证使用MEMS惯性传感器对建筑物的双轴倾斜评估系统.
- 解决结构倾斜监测的高效信号处理方面的研究缺口.
- 允许实时同时监督结构倾向及其严重程度.
主要方法:
- 利用惯性传感器,Wi-Fi Xbee和互联网连接来实现实时数据采集.
- 开发了两种专用算法,连续进行数值重复,以处理引力加速信号.
- 使用一个并行训练模型与神经模型连接,用于识别和分类18种倾斜模式及其严重程度.
主要成果:
- 开发的算法显著改善了重力加速信号的处理.
- 倾斜模式是通过计算生成的,考虑到差异化定居点和地震事件.
- 监控软件实现了0.1°的分辨率,分类器在实验室测试中显示了>95%的精度,回忆,F1分数和准确性.
结论:
- 拟议的双轴倾斜评估系统有效地实时监测结构倾斜.
- 先进的信号处理算法和神经模型提供准确的倾斜模式和严重程度的分类.
- 该系统是监督建筑物的结构健康的可行解决方案,特别是在易受差异性土壤沉积的城市地区.
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