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Volume 11
Issue 7
10.3390/aerospace11070537
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Article

A Time Series Prediction-Based Method for Rotating Machinery Detection and Severity Assessment

by
Weirui Zhang
1,
Zeru Sun
2,
Dongxu Lv
3,
Yanfei Zuo
3,
Haihui Wang
1,* and
Rui Zhang
2,*
1
School of Mathematical Sciences, Beihang University, Beijing 102206, China
2
Aero Engine Academy of China, Beijing 101300, China
3
College of Mechanical and Electrical Engineering, Beijing University of Chemical Technology, Beijing 100029, China
*
Authors to whom correspondence should be addressed.
Aerospace 2024, 11(7), 537; https://doi.org/10.3390/aerospace11070537
Submission received: 6 May 2024 / Revised: 16 June 2024 / Accepted: 27 June 2024 / Published: 1 July 2024
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Abstract

Monitoring the condition of rotating machinery is critical in aerospace applications like aircraft engines and helicopter rotors. Faults in these components can lead to catastrophic outcomes, making early detection essential. This paper proposes a novel approach using vibration signals and time series prediction methods for fault detection in rotating aerospace machinery. By extracting relevant features from vibration signals and using prediction models, fault severity can be effectively quantified. Our experimental results show that the proposed method has potential in early fault detection and is applicable to various types of bearing faults and the different statuses of these faults under complex running conditions, achieving very good generalization ability.
Keywords: fault detection; fault severity estimation; time series prediction; vibration signal; aircraft engine fault detection; fault severity estimation; time series prediction; vibration signal; aircraft engine

Share and Cite

MDPI and ACS Style

Zhang, W.; Sun, Z.; Lv, D.; Zuo, Y.; Wang, H.; Zhang, R. A Time Series Prediction-Based Method for Rotating Machinery Detection and Severity Assessment. Aerospace 2024, 11, 537. https://doi.org/10.3390/aerospace11070537

AMA Style

Zhang W, Sun Z, Lv D, Zuo Y, Wang H, Zhang R. A Time Series Prediction-Based Method for Rotating Machinery Detection and Severity Assessment. Aerospace. 2024; 11(7):537. https://doi.org/10.3390/aerospace11070537

Chicago/Turabian Style

Zhang, Weirui, Zeru Sun, Dongxu Lv, Yanfei Zuo, Haihui Wang, and Rui Zhang. 2024. "A Time Series Prediction-Based Method for Rotating Machinery Detection and Severity Assessment" Aerospace 11, no. 7: 537. https://doi.org/10.3390/aerospace11070537

APA Style

Zhang, W., Sun, Z., Lv, D., Zuo, Y., Wang, H., & Zhang, R. (2024). A Time Series Prediction-Based Method for Rotating Machinery Detection and Severity Assessment. Aerospace, 11(7), 537. https://doi.org/10.3390/aerospace11070537

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