Abstract
The phenomenon of knock is an abnormal combustion occurring in spark-ignition (SI) engines and forms a barrier that prevents an increase in thermal efficiency while simultaneously reducing CO2 emissions. Since knocking combustion is highly stochastic, a cyclic analysis of in-cylinder pressure is necessary. In this study we propose an approach for efficient and robust detection and identification of knocking combustion in three different internal combustion engines. The proposed methodology includes a signal processing technique, called continuous wavelet transformation (CWT), which provides a simultaneous analysis of the in-cylinder pressure traces in the time and frequency domains with coefficients. These coefficients serve as input for a convolutional neural network (CNN) which extracts distinctive features and performs an image recognition task in order to distinguish between non-knock and knock. The results revealed the following: (i) The CWT delivered a stable and effective feature space with the coefficients that represents the unique time-frequency pattern of each individual in-cylinder pressure cycle; (ii) the proposed approach was superior to the state-of-the-art threshold value exceeded (TVE) method with a maximum amplitude pressure oscillation (MAPO) criterion improving the overall accuracy by 6.15 percentage points (up to 92.62%); and (iii) The CWT + CNN method does not require calibrating threshold values for different engines or operating conditions as long as enough and diverse data is used to train the neural network.
Highlights
An important topic related to spark-ignition (SI) engine combustion has been the characterization of engine knock
Keras callbacks were used for adaptive regulation of the learning rate, which reduce it to half of the actual rate when a plateau of test loss value was reached with a patience of 2 epochs
This study provides an appropriate case for applying new deep learning techniques and investigating whether these neural networks are capable of grasping human criteria for detecting knocking combustion
Summary
An important topic related to spark-ignition (SI) engine combustion has been the characterization of engine knock. Two ways of achieving these objectives are to downsize and pressure charge the engine or to increase the compression ratio. Both approaches provoke engine knock [1]. Chemical reactions and subsequent heat release create a shock wave called detonation These detonations have high velocity flame propagation which can reach or even exceed values of 1000 m/s due to the high speed of sound of the gas. The sudden release of high amounts of chemical energy results in an increase in pressure and temperature with high amplitude shock waves. This causes the high-frequency noise after which the phenomenon is named. An increase in air pollution, a decrease in efficiency, a rise in fuel consumption and a source of noise can be expected [4]
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