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Andreas B. Ofner
Andreas B. Ofner
Researcher, Know Center Research GmbH
Verified email at know-center.at
Title
Cited by
Cited by
Year
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
252022
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
222021
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
192022
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
112022
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
102023
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
72022
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
12023
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
12023
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