Analysis of Acoustic Signal Based on Modified Ensemble Empirical Mode Decomposition

  • Sundeok Kwon
  • Sangjin Cho
Conference paper


Empirical mode decomposition (EMD) has been proposed recently as an adaptive time-frequency data analysis tool in the nonlinear and nonstationary signal processing research field. However, it has some drawbacks such as mode mixing, which is defined as a single intrinsic mode function (IMF) consisting of signals of widely disparate scales, and the prediction problem, which is intimately related to the end effects in the EMD. Although the ensemble EMD (EEMD), which overcomes these problems, can represent a major improvement of the EMD, this paper proposes a modified EEMD which includes the best IMF selection algorithm to analyze the acoustic signal. To evaluate the proposed method, it is applied to the vibration signal of an induction motor which has a bearing fault and musical percussion sound.


Acoustic signal processing Ensemble empirical mode decomposition Fault detection Intrinsic mode function IMF selection algorithm Musical instrument 



This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (NRF-2012R1A1B6002600).


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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Industry-Academy Cooperation FoundationYoungsan UniversityBusanSouth Korea
  2. 2.Automobile/Ship Electronics Convergence CenterUniversity of UlsanUlsanSouth Korea

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