Noise Source Separation of an Internal Combustion Engine Based on a Single-Channel Algorithm
The separation and identification technology of noise sources is the focus and hot spot in the field of internal combustion engine noise research. Combustion noise and piston slap noise are the main noise sources of an internal combustion engine. However, both combustion noise and piston slap noise...
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Hindawi Limited
2019-01-01
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Series: | Shock and Vibration |
Online Access: | http://dx.doi.org/10.1155/2019/1283263 |
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doaj-826096897cc14623b40bae9da85db5692020-11-25T02:03:07ZengHindawi LimitedShock and Vibration1070-96221875-92032019-01-01201910.1155/2019/12832631283263Noise Source Separation of an Internal Combustion Engine Based on a Single-Channel AlgorithmJiachi Yao0Yang Xiang1Sichong Qian2Shuai Wang3School of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, ChinaSchool of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, ChinaSchool of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, ChinaSchool of Energy and Power Engineering, Wuhan University of Technology, Wuhan 430063, ChinaThe separation and identification technology of noise sources is the focus and hot spot in the field of internal combustion engine noise research. Combustion noise and piston slap noise are the main noise sources of an internal combustion engine. However, both combustion noise and piston slap noise occur almost at the top dead center. They mix in the time domain and frequency domain. It is difficult to accurately and effectively separate them. A single-channel algorithm which combines time-varying filtering-based empirical mode decomposition (TVF-EMD) and robust independent component analysis (RobustICA) methods is proposed to separate them. Firstly, the TVF-EMD method is utilized to decompose the single-channel noise signal into several intrinsic mode functions (IMFs). Then, the RobustICA method is applied to extract the independent components. Finally, related prior knowledge and time-frequency analysis are employed to identify noise sources. Furthermore, the spectral filtering method and the calculation method of piston slap noise based on the dynamic model are further carried out to verify separation results. The simulation and experimental research results show the effectiveness of the proposed method.http://dx.doi.org/10.1155/2019/1283263 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jiachi Yao Yang Xiang Sichong Qian Shuai Wang |
spellingShingle |
Jiachi Yao Yang Xiang Sichong Qian Shuai Wang Noise Source Separation of an Internal Combustion Engine Based on a Single-Channel Algorithm Shock and Vibration |
author_facet |
Jiachi Yao Yang Xiang Sichong Qian Shuai Wang |
author_sort |
Jiachi Yao |
title |
Noise Source Separation of an Internal Combustion Engine Based on a Single-Channel Algorithm |
title_short |
Noise Source Separation of an Internal Combustion Engine Based on a Single-Channel Algorithm |
title_full |
Noise Source Separation of an Internal Combustion Engine Based on a Single-Channel Algorithm |
title_fullStr |
Noise Source Separation of an Internal Combustion Engine Based on a Single-Channel Algorithm |
title_full_unstemmed |
Noise Source Separation of an Internal Combustion Engine Based on a Single-Channel Algorithm |
title_sort |
noise source separation of an internal combustion engine based on a single-channel algorithm |
publisher |
Hindawi Limited |
series |
Shock and Vibration |
issn |
1070-9622 1875-9203 |
publishDate |
2019-01-01 |
description |
The separation and identification technology of noise sources is the focus and hot spot in the field of internal combustion engine noise research. Combustion noise and piston slap noise are the main noise sources of an internal combustion engine. However, both combustion noise and piston slap noise occur almost at the top dead center. They mix in the time domain and frequency domain. It is difficult to accurately and effectively separate them. A single-channel algorithm which combines time-varying filtering-based empirical mode decomposition (TVF-EMD) and robust independent component analysis (RobustICA) methods is proposed to separate them. Firstly, the TVF-EMD method is utilized to decompose the single-channel noise signal into several intrinsic mode functions (IMFs). Then, the RobustICA method is applied to extract the independent components. Finally, related prior knowledge and time-frequency analysis are employed to identify noise sources. Furthermore, the spectral filtering method and the calculation method of piston slap noise based on the dynamic model are further carried out to verify separation results. The simulation and experimental research results show the effectiveness of the proposed method. |
url |
http://dx.doi.org/10.1155/2019/1283263 |
work_keys_str_mv |
AT jiachiyao noisesourceseparationofaninternalcombustionenginebasedonasinglechannelalgorithm AT yangxiang noisesourceseparationofaninternalcombustionenginebasedonasinglechannelalgorithm AT sichongqian noisesourceseparationofaninternalcombustionenginebasedonasinglechannelalgorithm AT shuaiwang noisesourceseparationofaninternalcombustionenginebasedonasinglechannelalgorithm |
_version_ |
1724949406612979712 |