Diesel Engine Air Tightness Feature Recognition Based on Multi-scale Analysis

摘要

Cylinder air tightness is an important indicator to the comprehensive performance of internal combustion engine. It can be got the low-frequency and high-frequency signals of the starting voltage waveform using multi-scale analysis method and by binary discrete wavelet transform with the Mallat algorithm. The experiment results show that the working conditions of diesel engine starting process can be shown from the low-frequency signals, and the main frequency distribution can be recognised from the high frequency partial. This algorithm can effectively identify signal characteristics, and provide a reliable basis for signal feature recognition.