服役条件下取向硅钢磁致伸缩模型的研究

doi:10.19595/j.cnki.1000-6753.tces.191224

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Abstract Magnetostrictive effect of silicon steel is the main source of vibration noise for power equipment such as transformers. In order to establish the magnetostrictive model for silicon steel, the magnetic domain rotation characteristics were considered and the related parameter k₁ was added in the J-A model. Then, the magnetostrictive model of oriented silicon was established by combing the improved J-A model with the quadratic domain rotation model. The parameters in the model were extracted using the particle swarm optimization algorithm(PSO). Considering the working condition of power transformers, the magnetostrictive properties of oriented silicon steel were analyzed under ideal sine, harmonics and DC bias, respectively. The results showed that the magnetostrictive curves calculated by the model under the different conditions were in good agreement with the experimentally measured data. Therefore, the magnetostrictive model proposed in the paper can be used to simulate the magnetostrictive properties of oriented silicon steel under service conditions.

Key words： J-A model oriented silicon steel magnetostrictive model service condition particle swarm optimization algorithm(PSO)

Received: 26 September 2019

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TM401+.1

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	Zhu Lihua
	Li Jingjing
	Zhu Jianguo

Cite this article:

Zhu Lihua,Li Jingjing,Zhu Jianguo. Research on Magnetostrictive Model for Oriented Silicon Steel under Service Conditions[J]. Transactions of China Electrotechnical Society, 2020, 35(19): 4131-4138.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.191224 OR https://dgjsxb.ces-transaction.com/EN/Y2020/V35/I19/4131

[1] 李长云, 郝爱东, 娄禹. 直流偏磁条件下电力变压器振动特性研究进展[J]. 电力自动化设备, 2018, 38(6): 215-223.
Li Changyun, Hao Aidong, Lou Yu.Research progress on vibration characteristics of power transformers under DC bias conditions[J]. Electric Power Automation Equipment, 2018, 38(6): 215-223.
[2] Jiles D C.Theory of the magnetomechanical effect[J]. Journal of Physics D: Applied Physics, 1999, 28(8): 1537.
[3] Sablikm, Jiles D C. Coupled magnetoelastic theory of magnetic and magnetostrictive hysteresis[J]. IEEE Transactions on Magnetics, 1993, 29(3):2113-2123.
[4] Hristoforou E.Magnetostrictive delay lines: engineering theory and sensing applications[J]. Measurement Science & Technology, 2003, 14(2): R15-R47.
[5] Adly A A, Mayergoyz I D, Bergqvist A .Preisach modeling of magnetostrictive hysteresis[J]. Journal of Applied Physics, 1991, 69(8): 5777-5779.
[6] 张黎, 王国政, 董攀婷, 等. 基于磁致伸缩本征特性的晶粒取向性变压器铁心振动模型[J]. 中国电机工程学报, 2016, 36(14): 3990-4000.
Zhang Li, Wang Guozheng, Dong Panting, et al.Core-oriented transformer core vibration model based on magnetostrictive intrinsic property[J]. Proceedings of the CSEE, 2016, 36(14): 3990-4000.
[7] Foster S L, Reiplinger E. Charcteristics and control of transformer sound[J]. IEEE Transactions on Power Apparatus and Systems, 1981, PAS-100(3): 1072-1077.
[8] 顾晓安, 曾进, 沈荣瀛. 正弦电磁场中铁磁材料数学模型[J]. 应用数学和力学, 2004, 25(9): 974-982.
Gu Xiaoan, Zeng Jin, Shen Rongying.Mathematical model of ferromagnetic materials in sinusoidal electromagnetic field[J]. Applied Mathematics and Mechanics, 2004, 25(9): 974-982.
[9] 祝丽花, 杨庆新, 闫荣格, 等. 考虑磁致伸缩效应电力变压器振动噪声的研究[J].电工技术学报, 2013, 28(4): 1-6,19.
Zhu Lihua, Yang Qingxin, Yan Rongge, et al.Study on vibration and noise of power transformer considering magnetostrictive effect[J]. Transactions of China Electrotechnical Society, 2013, 28(4): 1-6, 19.
[10] Hilgert T, Vandevelde L, Melkebeek J.Neural- network-based model for dynamic hysteresis in the magnetostriction of electrical steel under sinusoidal induction[J]. IEEE Transactions on Magnetics, 2007, 43(8): 3462-3466.
[11] Li Q, Wang X, Zhang L, et al.Modelling methodology for transformer core vibrations based on the magnetostrictive properties[J]. IET Electric Power Applications, 2012, 6(9): 604.
[12] Jiles David C.Introduction to magnetism and magnetic materials[M]. Boca Raton: CRC Pr I LIc, 1998.
[13] Lee E W.Magnetostriction and magnetomechanical effects[J]. Reports on Progress in Physics, 1955, DOI:10.1088/0034-4885/18/1/305.
[14] 李长云, 刘亚魁. 直流偏磁条件下变压器铁心磁化特性的Jiles-Atherton修正模型[J]. 电工技术学报, 2017, 32(19): 193-201.
Li Changyun, Liu Yakui.Jiles-Atherton correction model of magnetization characteristics of transformer core under DC bias[J]. Transactions of China Electrotechnical Society, 2017, 32(19): 193-201.
[15] 王旭, 张艳丽, 唐伟, 等.旋转磁化下逆矢量Jiles-Atherton磁滞模型改进[J]. 电工技术学报, 2018, 33(增刊2): 257-262.
Wang Xu, Zhang Yanli, Tang Wei, et al.Improvement of inverse vector Jiles-Atherton hysteresis model under rotational magnetization[J]. Transactions of China Electrotechnical Society, 2018, 33(S2): 257-262.
[16] Li Yang, Zhu Lihua, Zhu Jianguo.Core loss calculation based on finite-element method with Jiles-Atherton dynamic hysteresis model[J]. IEEE Transactions on Magnetics, 2018, 54(3): 1-5.
[17] Jiles D C, Thoelke J B, Devine M K.Numerical determination of hysteresis parameters for the modeling of magnetic properties using the theory of ferromagnetic hysteresis[J]. IEEE Transactions on Magnetics, 1992, 28(1): 27-35.
[18] 程声烽, 程小华, 杨露. 基于改进粒子群算法的小波神经网络在变压器故障诊断中的应用[J]. 电力系统保护与控制, 2014, 42(19): 37-42.
Cheng Shengfeng, Cheng Xiaohua, Yang Lu.Application of wavelet neural network based on improved particle swarm optimization in transformer fault diagnosis[J]. Power System Protection and Control, 2014, 42(19): 37-42.
[19] 刘任, 李琳, 王亚琦, 等. 基于随机性与确定性混合优化算法的Jiles-Atherton磁滞模型参数提取[J]. 电工技术学报, 2019, 34(11): 2260-2268.
Liu Ren, Li Lin, Wang Yaqi, et al.Parameter extraction of Jiles-Atherton hysteresis model based on hybrid optimization algorithm of randomness and determinism[J]. Transactions of China Electrotechnical Society, 2019, 34(11): 2260-2268.