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Simon Pfingstl
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Improving production efficiency with a digital twin based on anomaly detection
J Trauer, S Pfingstl, M Finsterer, M Zimmermann
Sustainability 13 (18), 10155, 2021
262021
On integrating prior knowledge into Gaussian processes for prognostic health monitoring
S Pfingstl, M Zimmermann
Mechanical Systems and Signal Processing 171, 108917, 2022
172022
On the potential of extending aircraft service time using load monitoring
S Pfingstl, D Steinweg, M Zimmermann, M Hornung
Journal of Aircraft 59 (2), 377-385, 2022
92022
Crack detection zones: Computation and validation
S Pfingstl, M Steiner, O Tusch, M Zimmermann
Sensors 20 (9), 2568, 2020
92020
Warped Gaussian processes for predicting the degradation of aerospace structures
S Pfingstl, C Braun, A Nasrollahi, FK Chang, M Zimmermann
Structural Health Monitoring 22 (4), 2531-2546, 2023
52023
Reinforcement learning for structural health monitoring based on inspection data
S Pfingstl, YN Schoebel, M Zimmermann
8th Asia-Pacific Workshop on Structural Health Monitoring, 203-210, 2021
52021
Strain-based structural health monitoring: computing regions for critical crack detection
S Pfingstl, M Zimmermann
Structural Health Monitoring 2019, 2019
52019
Estimation of composite laminate ply angles using an inverse Bayesian approach based on surrogate models
M Franz, S Pfingstl, M Zimmermann, S Wartzack
Proceedings of the Design Society 2, 1569-1578, 2022
22022
Warped Gaussian processes for prognostic health monitoring
S Pfingstl, C Braun, M Zimmermann
STRUCTURAL HEALTH MONITORING 2021, 2021
22021
Comparison of error measures and machine learning methods for strain-based structural health monitoring
S Pfingstl, O Tusch, M Zimmermann
STRUCTURAL HEALTH MONITORING 2021, 2021
22021
Predicting Crack Growth and Fatigue Life with Surrogate Models
S Pfingstl, JI Rios, H Baier, M Zimmermann
arXiv preprint arXiv:2008.02324, 2020
22020
On the potential of extending aircraft service time using a fatigue damage index
S Pfingstl, D Steinweg, M Zimmermann, M Hornung
arXiv preprint arXiv:2008.03138, 2020
12020
Gaussian Processes for Prognostics
SB Pfingstl
Technische Universität München, 2023
2023
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Articles 1–13