A Study on the Decay Process in the Time-Frequency-Dependent Combustion-Noise-Generation Model for Diesel Engines

2019-32-0512

01/24/2020

Features
Event
Small Engine Technology Conference & Exposition
Authors Abstract
Content
We experimentally investigated the process of decay of engine noise from a single-cylinder diesel engine considering the time-frequency-dependent combustion-noise-generation model. In this model, the vibration energy of each frequency component is assumed to accumulate in the engine structure excited by the combustion impact during the combustion period in a cycle and decay over time, and the combustion noise is assumed to radiate from the engine surface. We used wavelet transform analysis as a time-frequency analysis of the sound pressure to obtain the decay rate, c, of the engine noise power. In order to investigate the dependence of the decay rate, c, on the sound-source location, we placed eight microphones in different positions near the engine. In order to investigate the dependence of the decay rate on the maximum in-cylinder pressure rise, we conducted experiments under three different operating conditions. The shape of the temporal variation of the engine-noise power depended on the sound-source location while the value of the engine noise power depended on the maximum in-cylinder pressure rise. Based on the time-frequency-dependent combustion-noise-generation model, we obtained the engine-noise decay rate, c, as the absolute value of the time differentials of the natural logarithm of the combustion noise power by line approximation. The results show that the decay rate, c, depends on the sound source location while it is almost independent of the maximum in-cylinder pressure rise.
Meta TagsDetails
DOI
https://doi.org/10.4271/2019-32-0512
Pages
8
Citation
Oguchi, H., and Mikami, M., "A Study on the Decay Process in the Time-Frequency-Dependent Combustion-Noise-Generation Model for Diesel Engines," SAE Technical Paper 2019-32-0512, 2020, https://doi.org/10.4271/2019-32-0512.
Additional Details
Publisher
Published
Jan 24, 2020
Product Code
2019-32-0512
Content Type
Technical Paper
Language
English