Open Access
Issue |
MATEC Web Conf.
Volume 309, 2020
2019 International Conference on Computer Science Communication and Network Security (CSCNS2019)
|
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Article Number | 03033 | |
Number of page(s) | 7 | |
Section | Smart Algorithms and Recognition | |
DOI | https://doi.org/10.1051/matecconf/202030903033 | |
Published online | 04 March 2020 |
- Guan Lili. Noise source identification and optimization of permanent magnet synchronous motor. Proceedings of the 14th Henan Auto Engineering Science and Technology Symposium, 2018, pp.380–382. (in Chinese) [Google Scholar]
- Lai Jianbin. Noise analysis and experimental study on electric vehicle driven motor. A Dissertation Submitted for the Degree of Master of Hefei University of Technology, 2018. (in Chinese) [Google Scholar]
- Wang Guangping. Application of Order Tracking Analysis in Identification of Electric Vehicle Interior Noise Resource. A Dissertation Submitted for the Degree of Master of Jiangsu University, 2011. (in Chinese) [Google Scholar]
- ZHANG Chengning, WANG Zaizhou, SONG Qiang. Research of noise source identification of traction motor system for electric vehicle based on microphone array. Proceedings of the CSEE, 2008, 28(30): 109–112. (in Chinese) [Google Scholar]
- Ko H S, Kim K J. Characterization of noise and vibration sources in interior permanent-magnet brushless DC motors [J], IEEE Transactions on Magnetics,2004,40(6):3482–3489. [CrossRef] [Google Scholar]
- Islam R, Husain I. Analytical Model for Predicting Noise and Vibration in Permanent-Magnet Synchronous Motors. IEEE Transactions on Industry Applications, 2010,46(6): 2346–2354. (in Chinese) [CrossRef] [Google Scholar]
- Song Zhihuan. Research on identification technology of electromagnetic vibration and noise source of permanent magnet synchronous motor (PMSM). A Dissertation Submitted for the Degree of Master of Shenyang University of Technology, 2010. (in Chinese) [Google Scholar]
- Huibinli, Mengxi Ning, Lei Hou, Tiangqi, Zhou. Experimental study on the noise identification of the turbocharger. Proceedings of the 3CA2011, 2011, pp.1–7 [Google Scholar]
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