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The Measurement and Elimination of Mode Splitting: From the Perspective of the Partly Ensemble Empirical Mode Decomposition

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  • Bin Liu
  • Peng Zheng
  • Qilin Dai
  • Zhongli Zhou

Abstract

The problems of mode mixing, mode splitting, and pseudocomponents caused by intermittence or white noise signals during empirical mode decomposition (EMD) are difficult to resolve. The partly ensemble EMD (PEEMD) method is introduced first. The PEEMD method can eliminate mode mixing via the permutation entropy (PE) of the intrinsic mode functions (IMFs). Then, bilateral permutation entropy (BPE) of the IMFs is proposed as a means to detect and eliminate mode splitting by means of the reconstructed signals in the PEEMD. Moreover, known ingredient component signals are comparatively designed to verify that the PEEMD method can effectively detect and progressively address the problem of mode splitting to some degree and generate IMFs with better performance. The microseismic signal is applied to prove, by means of spectral analysis, that this method is effective.

Suggested Citation

  • Bin Liu & Peng Zheng & Qilin Dai & Zhongli Zhou, 2018. "The Measurement and Elimination of Mode Splitting: From the Perspective of the Partly Ensemble Empirical Mode Decomposition," Complexity, Hindawi, vol. 2018, pages 1-10, November.
    • Handle: RePEc:hin:complx:4230649
    DOI: 10.1155/2018/4230649
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    Cited by:

    1. Hui Li & Fan Li & Rong Jia & Fang Zhai & Liang Bai & Xingqi Luo, 2021. "Research on the Fault Feature Extraction of Rolling Bearings Based on SGMD-CS and the AdaBoost Framework," Energies, MDPI, vol. 14(6), pages 1-19, March.

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