在一个人工智能支持的监控平台的方向上,用于混凝土结构
Gloria Cosoli1, Maria Teresa Calcagni1, Giovanni Salerno1
1Department of Industrial Engineering and Mathematical Sciences, Università Politecnica delle Marche, 60131 Ancona, Italy.
Sensors (Basel, Switzerland)
|January 23, 2024
概括
这项研究表明,自传感混凝土梁可以监测地震地区的结构健康状况. 人工智能模型,特别是Prophet,可以准确预测电阻变化,提高结构健康监测 (SHM) 和维护预测.
科学领域:
- 材料科学 材料科学 材料科学
- 土木工程 土木工程是指土木工程.
- 结构健康监测 结构健康监测
背景情况:
- 结构健康监测 (SHM) 对于建筑环境中的地震风险管理至关重要.
- 人工智能 (AI) 提供了分析结构数据和启用早期警告的先进功能.
- 自传感材料,如混凝土,为综合结构监测提供了机会.
研究的目的:
- 评估在地震环境中用于SHM的自传感混凝土梁的潜力.
- 为了评估电阻与混凝土梁中的施加负荷之间的相关性.
- 为了比较基于AI (Prophet) 和统计 (ARIMA,SARIMAX) 的模型来预测电阻.
主要方法:
- 在受控负载条件下测试自传感混凝土梁.
- 测量混凝土样本内的电阻变化.
- 使用基于视觉的系统进行客观的裂评估.
- 应用Prophet,ARIMA和SARIMAX模型进行电阻预测.
主要成果:
- 在电阻的真实部分和应用负载之间发现了很高的相关性 (皮尔森的r>0.9),证实了混凝土的压力阻抗性质.
- 先知模型在预测电阻方面明显优于ARIMA和SARIMAX,平均绝对百分比误差 (MAPE) 低于1.00%.
结论:
- 自传感混凝土梁,加上基于视觉的系统和人工智能,为SHM提供了一个有前途的方法.
- 电阻监测有效地表明负载下的结构完整性.
- 人工智能驱动的预测模型,特别是Prophet,提高了用于地震应用的SHM系统的准确性和可靠性.
关键词:
人工智能的人工智能裂检测 裂检测 裂检测 裂检测早期预警的早期警告.电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电阻电电电电电电电电电监控 监控 监控 监控 监控 监控监控平台监控平台的监控平台.自觉感应混凝土自动感应视觉系统 视觉系统 视觉系统相关概念视频
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