Separation of combustion noise and piston-slap in diesel engine—Part I: Separation of combustion noise and piston-slap in diesel engine by cyclic Wiener filtering

The main purpose of this study is to characterize the relative noise given out by a diesel engine, around the Top Dead Centre (TDC) by quantifying the proportions of “mechanical noise” originating mainly from piston-slap on the one hand and ‘thermal noise” originating from combustion on the other ha...

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Bibliographic Details
Published in:Mechanical systems and signal processing 2005-11, Vol.19 (6), p.1209-1217
Main Authors: Badaoui, M. El, Danière, J., Guillet, F., Servière, C.
Format: Article
Language:English
Subjects:
Acoustics
Applied sciences
Blind source separation
Combustion noise
Computer Science
Cyclic Wiener filter
Engineering Sciences
Engines and turbines
Exact sciences and technology
Fundamental areas of phenomenology (including applications)
Internal combustion engines: gazoline engine, diesel engines, etc
Mechanical engineering. Machine design
Physics
Piston-slap
Signal and Image Processing
Structural acoustics and vibration
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Summary:The main purpose of this study is to characterize the relative noise given out by a diesel engine, around the Top Dead Centre (TDC) by quantifying the proportions of “mechanical noise” originating mainly from piston-slap on the one hand and ‘thermal noise” originating from combustion on the other hand. Two different approaches are described here to solve this problem. In the first part of the paper, the cylinder pressure is measured and used as a reference in order to reconstruct the thermal noise. Next, we propose a method based on applying a cyclic Wiener filter to the measured cylinder pressure in order to separate the noises of mechanical and thermal origins. The final result is to reduce the engine resulting noise. The second part of the paper is devoted to blind source separation (BSS) methods applied on signals issued from accelerometers placed on one of the cylinders. It develops a BSS method based on a convolutive model of non-stationary mixtures and introduces a new method based on the joint diagonalization of time varying spectral matrices of the observations. Both methods are then applied to real data and the estimated sources are finally validated by several physical arguments.
ISSN:0888-3270
1096-1216
DOI:10.1016/j.ymssp.2005.08.010