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

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

Chaos, Solitons & Fractals, 2024, vol. 181, issue C

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.

Keywords: Fault diagnosis; Feature extraction; Multiresolution nonsynchronous entropy (MNSyncEn); Phase space reconstruction; Synchronous series (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:181:y:2024:i:c:s0960077924002327

DOI: 10.1016/j.chaos.2024.114680

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