The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Fault Diagnosis of Motor Bearing Based on Speed Signal Kurtosis Spectrum Analysis
Abstract
Bearing failure is one of the most common types of motor faults. For the electrical diagnostic methods of permanent magnet synchronous motor(PMSM) bearing faults, the existing literatures are mostly based on the motor current signal, but subject to the limitations of sampling frequency and other factors, the current method can guarantee the analysis effect only through external signal acquisition such as oscilloscope. Considering the relatively high resolution of encoder in PMSM, proposed a diagnosis method based on motor speed with kurtosis spectrum analysis which can promote the impact component extraction to improve the signal-to-noise ratio(SNR). Compared with current method, it can promote diagnosis stability and reduce costs. In this paper, the integrated model of motor and bearing is constructed, then the simulation experiment is carried out based on the speed method. Experiments based on speed and current signals are carried out to make comparison, and the mature vibration method is used as reference. The results show that although the speed method is affected by the speed domain and load torque, the diagnostic strategy combining the rotational speed signal and the kurtosis spectrum can basically reach the effect of vibration method and has a good full-speed versatility, which is obviously better than the current signal.
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In [139], kurtosis spectrum analysis of the speed signal can achieve similar results to the vibration method for bearing fault detection over a wide range of PMSM motor speeds.
“The study showed that the kurtosis spectrum analysis of the speed signal can achieve similar results to those obtained for the vibration method.”
From Fault Diagnosis and Fault-Tolerant Control of PMSM Drives–State of the Art and Future Challenges (2022) · cites this paper as [139]
Citations
Cites
Robust Diagnosis of Rolling Element Bearings Based on Classification Techniques
Cococcioni, M., Lazzerini, B., & Volpi, S. L. (2012) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2012.2231084 · Cited by 82
Daviu, J. A. A., Aviyente, S., Strangas, E. G., & Riera‐Guasp, M. (2012) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2012.2198659 · Cited by 77
Trajin, B., Régnier, J., & Faucher, J. (2010) · IET Electric Power Applications · doi:10.1049/iet-epa.2009.0040 · Cited by 56
Chen, Z. (2012) · Journal of Mechanical Engineering · doi:10.3901/jme.2012.21.084 · Cited by 27
He, Q., Ren, X., Jiang, G., et al. (2014) · Insight - Non-Destructive Testing and Condition Monitoring · doi:10.1784/insi.2014.56.6.326 · Cited by 10
Flagged first, then by citations
Research works printed but not linked: 10
- h, 2013, Gear tooth surface damage fault detection using induction machine electrical signature analysis[C], 9th IEEE International Symposium on Diagnostics for Electric Machines Power Electronics and Drives (SDEMPED), 358
- h, 2013, A time-domain fault detection method based on an electrical machine stator current measurement for planetary gear-sets[C], IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM), 1631
- xiaotao, 2014, Fault Diagnosis of Acoustic Emission in Rolling Bearing Based on SVD and Fast Kurtogram Algorithm[J], Vibration and shock, 33, 101
- m, 2012, Load torque signature analysis: an alternative to MCSA to detect faults in motor driven loads[C], IEEE Energy Conversion Congress and Exposition (ECCE), 4029
- zheng, 2014, Sliding-mode variable structure control with integral action for permanent magnet synchronous motor[J], Proceedings of the CSEE, 34, 431
- yan, 2014, A method for fault diagnosis of induction motors based on spectral Kurtosis[J], Transactions of China Electrotechnical Society, 29, 189
- dongdong, 2017, Fault Detection of Planetary Gearbox of Wind Turbine Based on Adaptive EMMD and Hierarchical Fractal Dimensions[J], Transactions of China Electrotechnical Society, 32, 236
- jun, 2013, An overview of condition monitoring and fault diagnostic for wind energy conversion system[J], Transactions of China Electrotechnical Society, 28, 261
- ming, 2018, Fault Diagnosis of Gear Fault Based on Bit Field Motion Error Observer[J], Transactions of China Electrotechnical Society, 33, 1285
- ming, 2016, Review of gear fault diagnosis methods based on motor drive system[J], Transactions of China Electrotechnical Society, 31, 58
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Fault Diagnosis and Fault-Tolerant Control of PMSM Drives–State of the Art and Future Challenges
Orlowska-Kowalska, T., Wolkiewicz, M., Pietrzak, P., Skowron, M., Ewert, P., Tarchala, G., Krzysztofiak, M., & Kowalski, C. T. (2022) · IEEE Access · doi:10.1109/access.2022.3180153 · Cited by 328
Ewert, P., Orlowska-Kowalska, T., & Jankowska, K. (2021) · Energies · doi:10.3390/en14030712 · Cited by 48
Metadata
- Authors
- Ren, B., Yang, M., Chai, N., Li, Y., & Xu, D.
- Affiliations
- Harbin Institute of Technology (CN)
- Venue
- 2019 22nd International Conference on Electrical Machines and Systems (ICEMS)
- Publisher
- IEEE
- Published
- 2019-08
- Pages
- 1-6
- OpenAlex
- W2993509335
- Cited by
- 15
- References
- 5
- Citations by year
- 2025: 4 · 2024: 4 · 2023: 3 · 2022: 3 · 2021: 1
- FWCI
- 1.55
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Conference on Electrical Machines and Systems (ICEMS) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Machine Fault Diagnosis Techniques
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Electric Motor Design and Analysis
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Sensorless Control of Electric Motors
- Keywords
- motor bearing fault diagnosis, permanent magnet synchronous motor, signal-to-noise ratio improvement, vibration fault diagnosis
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