1 - 5 out of 5Page size: 20
Publications
2025
- E-pub ahead of print
Comparing Gaussian process enhanced grey-box approaches to detect damage in unknown environmental conditions due to climate change
Möller, S., Jonscher, C., Grießmann, T. & Rolfes, R., 2025, (E-pub ahead of print) In: Structural health monitoring.Research output: Contribution to journal › Article › Research › peer review
2023
- Published
Evaluation of machine learning techniques for structural health monitoring using ultrasonic guided waves under varying temperature conditions
Abbassi, A., Römgens, N., Tritschel, F. F., Penner, N. & Rolfes, R., Mar 2023, In: Structural health monitoring. 22, 2, p. 1308-1325 18 p.Research output: Contribution to journal › Article › Research › peer review
2020
- Published
Combination of damage feature decisions with adaptive boosting for improving the detection performance of a structural health monitoring framework: Validation on an operating wind turbine
Tsiapoki, S., Bahrami, O., Häckell, M. W., Lynch, J. P. & Rolfes, R., 13 Mar 2020, In: Structural health monitoring. 20, 2, p. 637-660 24 p.Research output: Contribution to journal › Article › Research › peer review
2017
- Published
A two-step approach to damage localization at supporting structures of offshore wind turbines
Schröder, K., Gebhardt, C. G. & Rolfes, R., 29 Nov 2017, In: Structural health monitoring. 17, 5, p. 1313-1330 18 p.Research output: Contribution to journal › Article › Research
- Published
Damage and ice detection on wind turbine rotor blades using a three-tier modular structural health monitoring framework
Tsiapoki, S., Häckell, M. W., Grießmann, T. & Rolfes, R., 11 Oct 2017, In: Structural health monitoring. 17, 5, p. 1289-1312 24 p.Research output: Contribution to journal › Article › Research