Analysis and Exploration for Automotive Engine Vibration Signal

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Abstract:

In Modern society, most of car engines are multi cylinder four stroke engines, rotate speed is an important parameter of the engine, engine running status is a comprehensive expression of engine operation condition. It is also the result of the interaction by the gas torque, load torque and inertia moment. So the speed measurement is of great significance. Car engine speed measurement method has a lot of kinds, this article is based on the vibration method to measure, different methods used in vibration signal acquisition, analysis, processing and implementation. The vibration of the automobile engine output signals are continuous changes over time, we can say is a continuous signal. The vibration of the automobile engine output signals are continuous changes over time, we can say at this time is a continuous signal, when we use vibration sensor to gather the signals, a certain number of sampling points that are in different time, same time interval the vibration data resulting from the sampling theorem. At this time we deal with discrete time signals [1, 3]. Because of various vibration interference, The useful information we want to extract has been hidden in a lot of vibration under the disturbance signal, therefore, we carried out on the vibration signal analysis and processing, converting vibration wave in the frequency domain analysis, combining the new method of machinery vibration signal feature extraction, using short time Fourier transform, multiple correlation theory and Hilbert Huang transform combined with the application, making us in post-processing can extract the characteristic signal under the strong noise background [4]. The original signal frequency is obtained, based on related formulas to calculate car engine speed.

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1230-1233

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September 2013

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© 2013 Trans Tech Publications Ltd. All Rights Reserved

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[1] Charles L. Phillips, John M. Parr, Eve A. Riskin: Signals, Systems, and Transforms, third ed., Bei Jing, (2006).

Google Scholar

[2] WenPing Ma, BingBing Li: Apply for Random Signals Analysis, Bei Jing, (2006).

Google Scholar

[3] JunLi Zheng, QiHeng Ying: Signals and System, Bei Jing, (2000).

Google Scholar

[4] JianWei Li, BaoJie Xu: Study on Hilbert-Huang transform in the analysis of non- stationary vibration signal, submitted to Journal of Mechanical Strength (2006).

Google Scholar

[5] Mallat: Singularity Detection and Processing with wavelet (Trans. Information Theory, 1992).

Google Scholar

[6] Alien J. B, R. Rahiner: A Unified Approach to short-time flourier analysis. Pro IEEE, Vol. 65 (1977), pp.1558-1564.

Google Scholar