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基于引导波和稀疏的贝叶斯学习的护柱的深度检测

Jiewen Bai¹, Qiangqiang Han¹, Zijian Wang¹

¹Key Laboratory of C & PC Structures Ministry of Education, National and Local Unified Engineering Research Center for Basalt Fiber Production and Application Technology, Southeast University, Nanjing 211189, China.

|February 20, 2026

概括

这项研究引入了一种使用传感器和Sparse贝叶斯学习的新方法,以准确测量护后埋葬深度. 这通过克服冲击回声方法的局限性来改善高速公路基础设施的维护.

科学领域:

土木工程土木工程是指土木工程.
地质技术工程地质技术工程
非破坏性测试是指非破坏性测试.

背景情况:

护站对于道路安全至关重要,防止车道交叉并减少死亡事故.
准确测量护后的埋葬深度至关重要,特别是在硬土壤条件下.
传统的深度探测冲击回声方法由于不受控制的频率和波浪分散而缺乏准确性.

研究的目的:

开发一种更准确的方法来检测护后的埋葬深度.
克服冲击回声方法的局限性,特别是在频率控制和波浪分散方面.
提高高速公路基础设施维护的可靠性.

主要方法:

利用传感器激发引导波,取代了传统的冲击.
开发了一种基于Sparse贝叶斯学习的自动识别方法来处理引导波信号.
采用贝叶斯模型,使用多个传感器对进行深度测定,而不需要先前的材料或波速知识.

主要成果:

在模拟中获得了3.23%的平均相对误差.
在实验和实地测试中显示了8.43%的平均相对误差.
成功补偿引导波分散,并确定了底部回声.

结论:

拟议的基于传感器的方法与Sparse贝叶斯学习为护后埋葬深度检测提供了更好的准确性.
这种技术通过提供可靠的埋葬深度测量,提高了高速公路基础设施的维护.
贝叶斯模型有效地确定埋葬深度,而不需要先前了解土壤特性或波速.

关键词:

贝叶斯的推理是贝叶斯的推理.护柱护柱的位置导向波浪的导向波浪是一种指导波浪.很少有贝叶斯式学习.

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