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Multiresolution nonsynchronous entropy: Measurement approach for synchronous series analysis and feature extraction of rotating machinery

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  • Zhao, Yanqing
  • Chang, Lyu
  • Dai, Jianguo
  • Jiang, Hailin
  • Wang, Hualing

Abstract

Entropy methods have widely been used to extract features for fault diagnosis. However, the existing entropy methods cannot extract fault features reliably. To address this issue, we proposed a synchronous series analysis method, namely nonsynchronous entropy (NSyncEn), based on a novel phase space reconstruction strategy. The reconstructed phase space can adapt to the rotational speed of rotating machinery. The NSyncEn's superiority is verified via the simulated synchronous series and the other five existing entropy methods. To better extract features, we further extended NSyncEn into multiresolution analysis by using multiple time lags of the phase space, called multiresolution nonsynchronous entropy (MNSyncEn). Numerical and real-world milling processes assess the MNSyncEn performance in feature extraction. Numerical and experimental results demonstrate that MNSyncEn performs better feature extraction than the existing MDivEn, MSampEn, MFuzzEn, MAppEn, and MPermEn.

Suggested Citation

  • Zhao, Yanqing & Chang, Lyu & Dai, Jianguo & Jiang, Hailin & Wang, Hualing, 2024. "Multiresolution nonsynchronous entropy: Measurement approach for synchronous series analysis and feature extraction of rotating machinery," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
  • Handle: RePEc:eee:chsofr:v:181:y:2024:i:c:s0960077924002327
    DOI: 10.1016/j.chaos.2024.114680
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    References listed on IDEAS

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    1. Jiejunyi Liang & Jian-Hua Zhong & Zhi-Xin Yang, 2017. "Correlated EEMD and Effective Feature Extraction for Both Periodic and Irregular Faults Diagnosis in Rotating Machinery," Energies, MDPI, vol. 10(10), pages 1-14, October.
    2. Wang, Cheng-Chi, 2007. "Bifurcation analysis of an aerodynamic journal bearing system considering the effect of stationary herringbone grooves," Chaos, Solitons & Fractals, Elsevier, vol. 33(5), pages 1532-1545.
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