F. Molinaro et F. Castanie, SIGNAL-PROCESSING PATTERN-CLASSIFICATION TECHNIQUES TO IMPROVE KNOCK DETECTION IN SPARK-IGNITION ENGINES, Mechanical systems and signal processing, 9(1), 1995, pp. 51-62
The aim of this paper is to illustrate the contribution of signal proc
essing pattern recognition techniques to the resolution of a physical
problem: entire knock detection. Knock is an abnormal combustion of sp
ark ignition in automotive engines. Classical detectors use the energy
of engine vibration in order to detect it. Unfortunately, detection b
ecomes erroneous at high speeds when noise level increases.-Pattern re
cognition techniques allow the determination of optimal parameters and
methods for knock recognition: cepstral coefficients and amplitude hi
stograms improve knock recognition at 5500 rpm and for other speeds. A
comparison between five speeds using the conventional detector and th
e new detector shows that the latter clearly outperforms the former. T
he method used here of knock detection can be used in several other ap
plications e.g. gear default detection and axle fissure.