Performance, cost, and risk
What are the performance, cost, and risk impacts of implementing this product?
- Performance: Enables evaluating the performance of any emerging sensor system for impact monitoring systems and allowing for the implementation of new sensor technologies, optimize sensor networks for accurate and cost-effective identification of (barely visible) impact; enables estimation of the impact energy and hence estimation of severity of impact and necessity of inspection. Using Physics-Informed Neural Networks.
- Cost: If not available already, the required sensors need to be purchased and installed, as well as the required computational power and software for training and using the Physics-Informed Neural Networks.
- Risk: Only tested in aerospace environments.
Implementation requirements
What capabilities would a business/organization/institution need to have to implement this product?
- Processes: Impact data on representative structures.
- Resources: Piezoelectric or Fibre Bragg Grating sensors.
- Competences: Knowledge of the advantages and shortcomings of different types of sensors; knowledge and expertise on structural behaviour under impact loading and on data-science methods such as Neural Networks.
- Technologies: Physics-Informed Neural Networks (or similar hybrid methods).
Related works
- Marinho et al. (2022). A Comparison of Optical Sensing Systems with Piezo-Electric Sensors for Impact Identification of Composite Plates.
- Loendersloot et al. (2022). Impact Damage Identification on Composite Structures.
- Bezes et al. (2024). Validation of an Abaqus impact wave propagation model.
- Marinho et al. (2024). Impact Identification Method for Structural Health Monitoring of Stiffened Composite Panels using Passive Sensing Systems.
- Marinho et al. (2025). Evaluating sensor performance for impact identification in composites: a comprehensive comparison of FBGs with PZTs.
Contact information
For further inquiries regarding this product, feel free to get in touch with:
- Frank Grooteman, NLR. Frank [dot] Grooteman [at] nlr [dot] nl
- Richard Loendersloot, University of Twente. r [dot] loendersloot [at] utwente [dot] nl
- Natalia Ribeiro Marinho, University of Twente. n [dot] ribeiromarinho [at] utwente [dot] nl
- Tiedo Tinga, University of Twente. t [dot] tinga [at] utwente [dot] nl
