Self-drilling micropiles (SDMs) are gaining popularity as bearing foundation elements, as this construction technique allows for considerable time and cost savings. However, the irregular geometry and variability in the bearing capacity present uncertainty and a significant risk that has limited SDM deployment. To date, no reliable technology has been used to measure the SDM geometry. This paper proposes a methodology that uses distributed fibre optics (DFO), heat conduction modelling and inverse analysis to measure the pile geometry, and could also be extended to assess its bearing capacity. The temperature distribution during cement hydration was measured using two DFO investigative technologies and was compared to traditional temperature measurements using point sensors. An inverse analysis of SDM geometry was subsequently carried out based on the DFO measurement of temperature, a finite-element heat conduction model and a calibration pile. Finally, the calculated pile geometry was compared to the geometry of an excavated pile in the uppermost part. The methodology presented here is not only intended as a tool for designing SDMs but can also be deployed as a structural health monitoring system to detect and monitor crack formation.

中文翻译：

---

使用分布式光纤传感器评估自钻微型桩几何形状的方法

自钻式微型桩 (SDM) 作为承载基础元件越来越受欢迎，因为这种施工技术可以节省大量时间和成本。然而，不规则的几何形状和承载能力的变化带来了不确定性和重大风险，限制了 SDM 的部署。迄今为止，还没有可靠的技术来测量 SDM 几何形状。本文提出了一种使用分布式光纤（DFO）、热传导建模和反演分析来测量桩几何形状的方法，并且还可以扩展到评估其承载能力。使用两种 DFO 研究技术测量水泥水化过程中的温度分布，并与使用点传感器的传统温度测量进行比较。随后基于 DFO 温度测量、有限元热传导模型和校准桩对 SDM 几何结构进行了反演分析。最后，将计算出的桩几何形状与最上部开挖桩的几何形状进行比较。这里介绍的方法不仅旨在作为设计 SDM 的工具，而且还可以部署为结构健康监测系统来检测和监测裂缝形成。