Theory-inspired machine learning—towards a synergy between knowledge and data JG Hoffer, AB Ofner, FM Rohrhofer, M Lovrić, R Kern, S Lindstaedt, ... Welding in the World 66 (7), 1291-1304, 2022 | 22 | 2022 |
Detection of knocking combustion using the continuous wavelet transformation and a convolutional neural network A Kefalas, AB Ofner, G Pirker, S Posch, BC Geiger, A Wimmer Energies 14 (2), 439, 2021 | 21 | 2021 |
Knock Detection in Combustion Engine Time Series Using a Theory-Guided 1D Convolutional Neural Network Approach AB Ofner, A Kefalas, S Posch, BC Geiger IEEE/ASME Transactions on Mechatronics 27 (5), 4101-4111, 2022 | 18 | 2022 |
In-cylinder pressure reconstruction from engine block vibrations via a branched convolutional neural network AB Ofner, A Kefalas, S Posch, G Pirker, BC Geiger Mechanical Systems and Signal Processing 183, 109640, 2023 | 10 | 2023 |
Estimation of Combustion Parameters from Engine Vibrations Based on Discrete Wavelet Transform and Gradient Boosting A Kefalas, AB Ofner, G Pirker, S Posch, BC Geiger, A Wimmer Sensors 22 (11), 4235, 2022 | 9 | 2022 |
Modeling Cycle-to-Cycle Variations of a Spark-Ignited Gas Engine Using Artificial Flow Fields Generated by a Variational Autoencoder S Posch, C Gößnitzer, AB Ofner, G Pirker, A Wimmer Energies 15 (7), 2325, 2022 | 7 | 2022 |
A Comparison of Virtual Sensors for Combustion Parameter Prediction of Gas Engines Based on Knock Sensor Signals A Kefalas, A Ofner, S Posch, G Pirker, C Gößnitzer, B Geiger, A Wimmer SAE Technical Paper, 2023 | 1 | 2023 |
Virtual Sensors in Small Engines–Previous Successes and Promising Future Use Cases AB Ofner, B Geiger, S Posch, M Neumayer, J Sjoblom, S Schmidt SAE Technical Paper, 2023 | | 2023 |