Faults’ Diagnosis of Time-Varying Rotational Speed Machinery Based on Vibration and Acoustic Signals Features Extraction, and Machine Learning Methods-Reference-Cited by-同舟云学术

Faults’ Diagnosis of Time-Varying Rotational Speed Machinery Based on Vibration and Acoustic Signals Features Extraction, and Machine Learning Methods

Published:2022-09-21 Issue: Volume: Page:
ISSN:2523-3920
Container-title:Journal of Vibration Engineering & Technologies
language:en
Short-container-title:J. Vib. Eng. Technol.

Author:

Bettahar Toufik^ORCID,Chemseddine Rahmoune,Benazzouz Djamel

Publisher

Springer Science and Business Media LLC

Subject

Microbiology (medical),Immunology,Immunology and Allergy

Link

https://link.springer.com/content/pdf/10.1007/s42417-022-00705-7.pdf

Reference34 articles.

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3. Xu J, Ding X, Gong Y, Wu N, Yan H (2022) Rotor imbalance detection and quantification in wind turbines via vibration analysis. Wind Eng 46(1):3–11. https://doi.org/10.1177/0309524X21999841

4. Glowacz A, Tadeusiewicz R, Legutko S, Caesarendra W, Irfan M, Liu H, Brumercik F, Gutten M, Sułowicz M, Antonino-Daviu JA, Sarkodie-Gyan T, Fracz P, Kumar A, Xiang J (2021) Fault diagnosis of angle grinders and electric impact drills using acoustic signals. Appl Acoust 179:108070. https://doi.org/10.1016/j.apacoust.2021.108070

5. Świercz M (2015) Signal processing methods for fault diagnostics in engineering systems. Sign Process Symp (SPSympo) 2015:1–6. https://doi.org/10.1109/SPS.2015.7168303

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