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浙江大学学报(工学版)
J4  2012, Vol. 46 Issue (5): 954-960    DOI: 10.3785/j.issn.1008-973X.2012.05.029
    
Studying noise contributions of IC engine via MEEMD method
ZHENG Xu, HAO Zhi-yong, JIN Yang, LU Zhao-gang
Department of Energy Engineering, Zhejiang University, Hangzhou 310027, China
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Abstract  

A novel adaptive signal analysis method-modified ensemble empirical mode decomposition (MEEMD) was proposed in this paper to study the noise contribution of IC engine's vibration components. The advantages of MEEMD method over empirical mode decomposition (EMD) and ensemble empirical mode decomposition (EEMD) methods were obtained by simulation analysis. The results indicate that MEEMD method not only overcomes the disadvantage of mode mixing problem, but also restrains the white noise residue and mode splitting problem. The MEEMD method was used to study the noise contributions of IC engine's vibration components and identify the dominant noise sources. A four-cylinder IC engine was used for the experiment. The vibration and near-field noise signals were both decomposed by MEEMD method, and the time-frequency representations of the intrinsic mode functions (IMFs) were obtained by time-frequency analysis method. The results show that the noise contributions of different vibration components can be obtained, and the vibration sources which generate the dominant noise components can be identified．

Published: 01 May 2012
CLC:  TK 421  
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Cite this article:

ZHENG Xu, HAO Zhi-yong, JIN Yang, LU Zhao-gang. Studying noise contributions of IC engine via MEEMD method. J4, 2012, 46(5): 954-960.

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http://www.zjujournals.com/eng/10.3785/j.issn.1008-973X.2012.05.029     OR     http://www.zjujournals.com/eng/Y2012/V46/I5/954


基于MEEMD的内燃机辐射噪声贡献

为了研究内燃机振动成分对噪声的贡献,提出一种改进的集总平均经验模态分解（MEEMD）方法.通过仿真试验,对比MEEMD与传统经验模态分解（EMD）和集总平均经验模态分解（EEMD）的结果.结果表明,MEEMD是一种更为优秀的自适应信号模态分解方法,不仅能够抑制模态混叠问题,而且能够解决模态分裂等问题.采用MEEMD方法对内燃机振动成分对辐射噪声的贡献进行研究,以一个4缸4冲程内燃机为例,对标定工况下的缸盖罩振动信号和缸盖罩近场噪声信号进行MEEMD分解,并对分解得到的本征模态函数（IMF）进行时频分析,研究对辐射噪声贡献大的振动成分的来源.研究结果表明,通过MEEMD方法能够得到对内燃机辐射噪声贡献大的振动成分,并且准确确定其来源.

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