A. Moshrefi,
Volume 6, Issue 3 (9-2016)
Abstract
One of the factors that affects the efficiency and lifetime of spark ignited internal combustion engine is “knock”. Knock sensor is a commonly used to detect this phenomenon. However, noise, limits detection accuracy of this sensor. In this study, Empirical Mode Decomposition (EMD) method is introduced as a fully adaptive signal-based analysis. Then, based on weighting decompositions, a method for reducing knock signal noise to enhance detection accuracy of knock, has been proposed. Then, the presented method has been evaluated using recorded signals from four engine cylinders. Internal pressure of each cylinder were recorded and used as reference for knock detection. Test results verifies that knock detection accuracy improved by about 11.3%. The results of optimization method were consistent with our expectations and the weights of middle levels are higher than other levels, which means that the proposed method not only extracts the main frequencies of knock, but also assigns reasonable weights to them.
Amirhossein Moshrefi, Majid Shalchian,
Volume 8, Issue 3 (9-2018)
Abstract
Premature combustion that affects outputs, thermal efficiencies and lifetimes of internal combustion engine is called “knock effect”. However knock signal detection based on acoustic sensor is a challenging task due to existing of noise in the same frequency spectrum. Experimental results revealed that vibration signals, generated from knock, has certain frequencies related to vibration resonance modes of the combustion chamber. In this article, a new method for knock detection based on resonance frequency analysis of the knock sensor signal is introduced. More specifically at higher engine speed, where there is additional excitation of resonance frequencies, continuous wavelet transform has been proposed as an effective and applicative tool for knock detection and a formula for knock detection threshold based on this method is suggested. Measurement results demonstrate that this technique provide 15% higher accuracy in knock detection comparing to conventional method.
