Diesel engine air tightness feature recognition based on multi-scale analysis

Xiaojie Song; Wei Liu; Boxue Tan

doi:10.1117/12.2021214

Translator Disclaimer

13 March 2013 Diesel engine air tightness feature recognition based on multi-scale analysis

Xiaojie Song; Wei Liu; Boxue Tan

Author Affiliations +

Proceedings Volume 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies; 87842C (2013) https://doi.org/10.1117/12.2021214
Event: Fifth International Conference on Machine Vision (ICMV 12), 2012, Wuhan, China

Abstract

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.

Citation Download Citation

Xiaojie Song, Wei Liu, and Boxue Tan "Diesel engine air tightness feature recognition based on multi-scale analysis", Proc. SPIE 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies, 87842C (13 March 2013); https://doi.org/10.1117/12.2021214

ACCESS THE FULL ARTICLE