Misalignment fault detection of magnetic suspension multi-span rotors based on improved adaptive notch filter
Aiming at misalignment vibration of magnetic suspension multi-span rotors coupling, a rotor misalignment fault detection method based on improved adaptive notch filter is proposed. First, a coupling misalignment dynamic model and a magnetic suspension multi-span rotors model were established, and the force analysis was carried out. Second, aiming at the problem of insufficient frequency recognition accuracy of traditional adaptive notch filter algorithm for signals containing direct current components, an improved adaptive notch filter algorithm is adopted. The improved adaptive notch filter algorithm with the same detection accuracy results in faster computation speed compared with fast Fourier transform, and does not require data caching. And the improved adaptive notch filter algorithm was simulated for detecting double and triple frequencies with varying amplitudes in rotor vibration displacement signals. Finally, experimental verification was conducted. The simulation and experimental results show that the misalignment fault detection method based on improved adaptive notch filter not only has high accuracy and small steady-state error, but also has fast convergence speed, and can achieve fault detection within 0.2 s.
Authors
- Song Zhu (ORCID: https://orcid.org/0000-0001-5228-9406)
- Shigang She
- Xudong Guan (ORCID: https://orcid.org/0000-0001-7453-5540)
- Hui Li (ORCID: https://orcid.org/0000-0003-0386-1300)
- Zhiwei Lu (ORCID: https://orcid.org/0000-0002-7878-8278)
- Tong Liu (ORCID: https://orcid.org/0009-0008-3205-3074)
Institutions
- Ford Motor Company (United States) (US)
- China University of Mining and Technology (CN)
- Ningbo City College of Vocational Technology (CN)
- Changzhou University (CN)
Publication Details
- Journal
- Journal of Vibration and Control
- Published
- 2025-11-11
- DOI
- https://doi.org/10.1177/10775463251397323
- Primary Topic
- Magnetic Bearings and Levitation Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 0.00