The HyTowering project aimed to investigate the structural behaviour of onshore wind turbine towers and foundations under defined static, cyclic and dynamic loads, with a particular focus on segmental concrete towers that use dry‑joint construction. In these towers, the concrete rings are stacked and connected solely by external pretension, and the transfer of shear forces and torsional moments across the joint relies on friction as long as the joint is sufficiently compressed. When the joint reaches its load‑bearing limit and begins to open, existing models predict a dramatic drop in shear transfer. To monitor this critical behaviour, the project developed a photogrammetric monitoring system capable of detecting and localising strain changes and joint opening in real time.
The technical work began with a requirements study (AP 1) that defined the measurement objectives for validating static design models, especially the load at which the dry joint starts to gape. The team evaluated commercial photogrammetry software and a custom image‑correlation tool, ultimately selecting digital image correlation (DIC) as the most suitable method for the civil‑engineering context. DIC was adapted from its typical use in machine‑tool steel components to concrete, enabling the detection of micrometre‑level deformations. The system was integrated with camera hardware, lighting, and a data‑transfer pipeline to form a stand‑alone monitoring unit. Automated measurement routines were implemented, allowing continuous data acquisition, real‑time image processing, and live visualisation of deformation fields. Alarm thresholds were defined to trigger alerts when joint opening or crack initiation exceeded predefined limits.
Experimental validation (AP 5) involved static bending, torsion, and cyclic loading tests on tower specimens. The DIC system successfully captured the onset of joint opening and crack development, with deformation measurements in the micrometre range. The automated workflow reduced manual effort and increased measurement repeatability. The project also explored the influence of lighting, camera distance, and image resolution on measurement accuracy, establishing guidelines for optimal field deployment. The results demonstrate that the photogrammetric system can reliably monitor critical joint states and could be incorporated into a digital twin framework for real‑time structural health assessment of wind turbines and other civil‑engineering structures.
The project ran from January 2018 to December 2021 and was funded by the German Federal Ministry for Economic Affairs and Climate Action through the Jülich Research Center. The main partner was MKP GmbH, a company specialising in construction monitoring, which led the development of the DIC software and hardware integration. The Leibniz University Hannover’s Institute for Massive Construction (IFMA) contributed expertise in structural testing and data analysis. The project was managed by the Jülich Research Center, which coordinated the work packages, handled the funding, and facilitated the extension of the project timeline to compensate for COVID‑19 restrictions on test‑center access. The collaboration combined academic research, industrial application, and practical testing to deliver a monitoring solution that is ready for deployment in wind‑energy and broader civil‑engineering contexts.