prof.dr.ir. T. Tinga (Tiedo)

Full Professor Dynamics based Maintenance

About Me

Tiedo Tinga (1973) is a professor in Dynamics based Maintenance at the faculty of Engineering Technology, with a background in Materials Science and Mechanical Engineering. His research focuses on the detection and prediction of failures in systems, with the aim of developing smart maintenance concepts, like Predictive Maintenance. The is achieved by combining the Physics of Failure, thorough understanding of the (dynamic) system behaviour and advanced (condition) monitoring techniques, as well as data science and artificial intelligence. 


Engineering & Materials Science
Fatigue Damage
Predictive Maintenance
Structural Health Monitoring
Physics & Astronomy

Ancillary Activities

  • Nederlandse Defensie Academie
    Professor Life Cycle Management
  • NLR (Netherlands Aerospace Center)
    Adviescommissie Aerospace Vehicles NLR
  • Consultinga
    Incidenteel verzorgen van lezingen en/of advies


Mostafa, N. (2024). Utilizing the system instantaneous frequency for the structural health monitoring of bridges. [PhD Thesis - Research UT, graduation UT, University of Twente]. University of Twente. https://doi.org/10.3990/1.9789036560382
Homborg, A. M., Mol, J. M. C. , & Tinga, T. (2024). Corrosion classification through deep learning of electrochemical noise time-frequency transient information. Engineering applications of artificial intelligence, 133, 1-9. Article 108044. Advance online publication. https://doi.org/10.1016/j.engappai.2024.108044
Meghoe, A. A. , Loendersloot, R. , & Tinga, T. (2023). Selection of a suitable wear model for implementation in a generic rail damage function. 1-16. Paper presented at Railway Engineering 2023, Edinburgh, United Kingdom.
Ribeiro Marinho, N. , Loendersloot, R. , Tinga, T., Grooteman, F., & Wiegman, J. W. (2023). A Comparison of Optical Sensing Systems with Piezo-Electric Sensors for Impact Identification of Composite Plates. In S. Farhangdoust, A. Guemes, & F.-K. Chang (Eds.), Proceedings of the 14th International Workshop on Structural Health Monitoring 2023: Designing SHM for Sustainability, Maintainability, and Reliability (pp. 1127-1133). DEStech Publications, Inc.
Tinga, T., Homborg, A. M. , & Rijsdijk, C. (2023). Data-driven maintenance of military systems: Potential and challenges. In P. B. M. J. Pijpers, M. Voskuijl, & R. Beeres (Eds.), Towards a data-driven military: A multidisciplinary perspective (pp. 73-96). Leiden University Press. https://doi.org/10.24415/9789087284084

UT Research Information System

Contact Details

Visiting Address

University of Twente
Drienerlolaan 5
7522 NB Enschede
The Netherlands

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Mailing Address

University of Twente
P.O. Box 217
7500 AE Enschede
The Netherlands