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 …
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
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 …
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
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 …
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
Knock detection is critical to engine control as it prevents damage and ensures optimal
performance. However, it still presents significant challenges, particularly in alternative …
performance. However, it still presents significant challenges, particularly in alternative …
In-cylinder pressure reconstruction from engine block vibrations via a branched convolutional neural network
We introduce a novel approach to reconstructing the in-cylinder pressure trace from
vibration signals recorded with common knock sensors. The proposed methodology is …
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 …
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
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 …
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
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 …
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
This review explores machine learning approaches for predicting ignition delay in
combustion processes. Ignition delay is a vital parameter in optimizing the engine design …
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 …
been studied to identify the occurrence of some failures, such as engine knock [1],[2]. The …