Knock probability determination employing convolutional neural network and IGTD algorithm

M Hosseini, I Chitsaz - Energy, 2023 - Elsevier
This study presents a novel method based on the convolutional neural network to evaluate
knock probability. In this way, lots of data sets are extracted from the real driving conditions …

[HTML][HTML] Experimental study on hydro-thermal behavior of journal bearing oil film profile in a slow speed diesel engine

NA Marey, WM El‑Maghlany, M Fayed - Alexandria Engineering Journal, 2023 - Elsevier
Utilizing universal journal bearing test rig, the performance of a heavy-loaded main journal
bearing has been investigated based on tracing operational behavior of oil film temperature …

Knock detection in combustion engine time series using a theory-guided 1-D convolutional neural network approach

AB Ofner, A Kefalas, S Posch… - … /ASME Transactions on …, 2022 - ieeexplore.ieee.org
This article introduces a method for the detection of knock occurrences in an internal
combustion engine (ICE) using a 1-D convolutional neural network trained on in-cylinder …

Knock detection in spark ignited heavy duty engines: An application of machine learning techniques with various knock sensor locations

A Aramburu, C Guido, P Bares, B Pla, P Napolitano… - Measurement, 2024 - Elsevier
Knock detection is critical to engine control as it prevents damage and ensures optimal
performance. However, it still presents significant challenges, particularly in alternative …

In-cylinder pressure reconstruction from engine block vibrations via a branched convolutional neural network

AB Ofner, A Kefalas, S Posch, G Pirker… - Mechanical Systems and …, 2023 - Elsevier
We introduce a novel approach to reconstructing the in-cylinder pressure trace from
vibration signals recorded with common knock sensors. The proposed methodology is …

Deep learning for knock occurrence prediction in SI engines

H Tajima, T Tomidokoro, T Yokomori - Energies, 2022 - mdpi.com
This research aims to predict knock occurrences by deep learning using in-cylinder pressure
history from experiments and to elucidate the period in pressure history that is most …

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… - Sensors, 2022 - mdpi.com
An optimal control of the combustion process of an engine ensures lower emissions and fuel
consumption plus high efficiencies. Combustion parameters such as the peak firing pressure …

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, 2022 - mdpi.com
A deeper understanding of the physical nature of cycle-to-cycle variations (CCV) in internal
combustion engines (ICE) as well as reliable simulation strategies to predict these CCV are …

Machine Learning Approaches for Predicting Ignition Delay in Combustion Processes: A Comprehensive Review

M Molana, S Darougheh, A Biglar… - Industrial & …, 2024 - ACS Publications
This review explores machine learning approaches for predicting ignition delay in
combustion processes. Ignition delay is a vital parameter in optimizing the engine design …

Data-driven anomaly detection of engine knock based on automotive ecu

LT Francis, VE Pierozan, G Gracioli… - 2022 XII Brazilian …, 2022 - ieeexplore.ieee.org
In the automotive industry, the study of internal combustion engines (ICE) has massively
been studied to identify the occurrence of some failures, such as engine knock [1],[2]. The …