International Conference on Gears 2025

Produktbeschreibung

Content (Auszug)

Foreword 1
AI and digitalization – Impact on the future of gears
Powered by AI – Leading the future of drive technology 3
J. Reimann, J. Zundel, T. Sadek, Flender GmbH, Bocholt
AI/ML-accelerated gear durability analysis within gear design
optimization
AI/ML-accelerated gear durability analysis within gear design optimization 7
M. Vivet, D. Park, A. Scheuer, Siemens Digital Industries Software, Leuven, Belgium
Condition monitoring using AI
Early Detection of Critical Operating Conditions in Journal Bearings of
Gearboxes Using Acoustic Emission and Machine Learning 25
F. Wirsing, A. Saleh, G. Jacobs, D. Bosse, F. König, B. Lehmann, B. Klinghart,
Institut für Maschinenelemente und Systementwicklung, RWTH Aachen University,
Schinkelstraße 10, 52062 Aachen
Condition Monitoring and Remaining Useful Lifetime Prediction of a Worm
Gear based on Simulative, Lazy Learning, and Deep Learning Methods 45
F. Heiland, J. Schilling, R. Kollert, M. Götz, A. Keller, D. Katava, P. Rettenmeier,
M. Werschler, IMS Gear SE & Co. KGaA, Donaueschingen
Tooth root carrying capacity
Tooth root strength of different quenched and tempered steels for
induction-hardened planetary pinions in wind turbine gearboxes 59
S. Hendricks1,2, C. Westphal1,2, M. Davidovic1,2, T. Bergs2,3,
1Laboratory for Machine Tools and Production Engineering (WZL) of RWTH
Aachen University, Aachen, Germany;
²Manufacturing Technology Institute MTI of RWTH Aachen University, Aachen, Germany;
3Fraunhofer-Institute for Production Technology IPT, Aachen, Germany Planetary gears: NVH
Noise Reduction of two-stage Planetary Gear Set based on Multi-body
Dynamics and Modal Acoustic Transfer Vector Simulations 71
D. J. Min, H. Yoo, Hyundai Mobis, Yongin-si, Republic of Korea
Advancements in tooth root strength
Size influence on tooth root strength based on testing and simulation 87
J. Meis, N. Lukaschik, Flender GmbH, Bocholt
Gear analysis & simulation
Virtual Optimization of Gearbox Oiling – How Reliable are the Results? 105
M. Reichl, K. Schierl, AVL Deutschland GmbH, München
Detailed and efficient transient simulations of wave gears 115
H. Grillenberger, H. Golbach, M. Kittsteiner, V. Makhavikou,
Schaeffler Technologies AG & Co KG, Herzogenaurach, Germany;
L. Ronchiato, R. G. Parker, Redpoint Vibration, Reno, NV, USA
Advancements in NVH Simulation
Efficient simulation procedure for NVH evaluation of bevel gear sets 123
F. Rudolph, J. Kunert, SEW-EURODRIVE GmbH & Co KG, Bruchsal
Frequency Response Analysis of Drivetrains based on an Iterative
Approach for Efficient Prediction of System Responses 133
S. Ebrahimi, S. Beermann, KISSsoft AG., Bubikon, Switzerland;
A. Möstl, KUMERA Antriebstechnik GmbH, Graz, Austria
Holistic and statistical approach to the impact of manufacturing deviations
on the transmission error, structural vibrations and the acoustic behavior
of gearboxes 147
D. Tazir, FVA-GmbH, Frankfurt; D. Werner, AVL Deutschland GmbH, München;
B. Abert, FVA-GmbH, München Efficiency and friction
A New Approach to Friction Calculation of Internal Gears 167
C. Paschold, T. Lohner, K. Stahl, Technical University of Munich, School of Engineering
and Design, Department of Mechanical Engineering, Gear Research Center (FZG),
Garching, Germany
Proposal of Low Friction Loss Gear Surface Based on Correlation Map
between Surface Roughness and Friction Coefficient 175
Y. Shishihara, Y. Otaki, H. Maki, JTEKT Corporation, Osaka,
Japan; A. Hase, Saitama Institute of Technology, Saitama, Japan
Quantitative Analysis of Churning in Dip-Lubricated Gearboxes
Through Computer Vision Techniques 189
B. Cardozo, R. Rego, R. Metzger, Aeronautics Institute of Technology,
São José dos Campos, Brazil
Damage detection
Electric Impedance-Based Detection of Surface Deviations in
Helical Gear Meshes 207
M. Hausmann, E. Kirchner, Fachgebiet für Produktentwicklung und
Maschinenelemente, TU Darmstadt, Germany
Gear Damage Detection in Planetary Gearboxes 233
L. Merkle, L. Binanzer, M. Dazer, University of Stuttgart, Institute of Machine
Components, Stuttgart, Germany
Tooth flank load capacity
Micropitting behavior of spur gears in eDrives with a holistic thermal
management 239
M. Yilmaz, B. Heine, F. Zerulli, J. König, D. Fuchs, ZF Friedrichshafen AG,
Friedrichshafen, Germany

Keywords: Künstliche Intelligenz, Digitalisierung, Früherkennung von kritischen Betriebsbedingungen, verbleibende nützliche Lebensdauer Vorhersage, Planetengetriebe, Effizienz und Friktion, Schaden Untersuchung, AI, digitalization, condition momitoring, tooth root carying capacity, remaing useful lifetime prediction, planetry gears, efficiency and friction, damage detection