Yong Li - IEEE Xplore Author Profile
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Yong Li

Publications
3
Citations
1
Publications by Year
20232024
Co-Authors:
Show All Co-Authors (12)
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Yong Li

Affiliation

School of Mechanical and Electrical Engineering
China University of Mining and Technology
Xuzhou, China
School of Mines
China University of Mining and Technology
Xuzhou, China

Publication Topics

Biography

Yong Li received the B.S. and Ph.D. degrees from China University of Mining and Technology, Xuzhou, China, in 2015 and 2021, respectively. He is currently a Lecturer with the School of Mechanical and Electrical Engineering, China University of Mining and Technology. His research interests include vibration signal processing and fault diagnosis of large electromechanical equipment.(Based on document published on 6 September 2024).
Publications
3
Citations
1
Publications by Year
20232024
Co-Authors:
Show All Co-Authors (12)
Author's Published Works

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Weak Feature Extraction Method for Bearing Faults Under Low-Speed Heavy-Duty Conditions

Yong Li;Hongyao Zhang;Sencai Ma;Xin Li;Gang Cheng;Qiangling Yao;Chuanwei Zuo

IEEE Access
Year: 2024 | Volume: 12 | Journal Article |
Large electromechanical equipment typically operates under low-speed, heavy-duty conditions, significantly increasing the likelihood of bearing failures. The reduced speed diminishes the frequency of fault impacts per unit time, rendering them prone to being obscured within intricate vibration signals. To address this challenge, a novel fault weak feature extraction method is proposed for low-spee...Show More

Weak Feature Extraction Method for Bearing Faults Under Low-Speed Heavy-Duty Conditions

Yong Li;Hongyao Zhang;Sencai Ma;Xin Li;Gang Cheng;Qiangling Yao;Chuanwei Zuo

Year: 2024 | Volume: 12 | Journal Article |

An Intelligent Fault Detection Method of Industrial Gearboxes With Robustness One-Class Support Matrix Machine Toward Multisource Nonideal Data

Xin Li;Yong Li;Ke Yan;Lei Si;Haidong Shao

IEEE/ASME Transactions on Mechatronics
Year: 2024 | Volume: 29, Issue: 1 | Journal Article |
Cited by: Papers (1)
Various kinds of sensing data can be acquired for smart fault detection. Each signal source has spatial attributes and strong correlations exist between different data sources. However, most of the existing fault detection models are established in the vector domain, which would destroy the structure information embedded within multisource data. Besides, the nonideal data, especially strong-noise ...Show More

An Intelligent Fault Detection Method of Industrial Gearboxes With Robustness One-Class Support Matrix Machine Toward Multisource Nonideal Data

Xin Li;Yong Li;Ke Yan;Lei Si;Haidong Shao

Year: 2024 | Volume: 29, Issue: 1 | Journal Article |

Prior-weighted support matrix machine for mine gearbox fault diagnosis under mislabeled data

Xin Li;Xinhua Liu;Lei Si;Xiaoyu Zhou;Fan Jiang;Yong Li

2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)
Year: 2023 | Conference Paper |
The majority of present data-driven fault diagnosis methods for mine gearboxes are constructed in vector space, which fails to properly benefit from the structural information of 2D fault features like wavelet time-frequency images. Besides, the presence of mislabeled data can greatly impact the capability of fault diagnosis. Hence this article develops a prior-weighted support matrix machine (PWS...Show More

Prior-weighted support matrix machine for mine gearbox fault diagnosis under mislabeled data

Xin Li;Xinhua Liu;Lei Si;Xiaoyu Zhou;Fan Jiang;Yong Li

Year: 2023 | Conference Paper |

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