基于AFSA-eCS混合算法的超磁致伸缩换能器输出特性分析

doi:10.19595/j.cnki.1000-6753.tces.240043

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Abstract The multi-field coupling of electricity, magnetism, and mechanics affects the working performance of giant magnetostrictive transducers. A multi-field coupling model is often used to analyze the nonlinear output characteristics, and its parameters determine the model's accuracy. The model has many key parameters with strong coupling, and the relationship between parameters in different working conditions is complex. Nowadays, artificial intelligence algorithms, such as particle swarm optimization and other single algorithms, are often combined to obtain parameters, which can easily lead to problems such as low identification accuracy, falling into local optima, and low stability. This paper constructs a comprehensive circuit model of the transducer considering the eddy current effect of bar cutting. An improved hybrid algorithm of artificial fish swarm and cuckoo search algorithm is used to identify the model.
Firstly, the equivalent eddy current factor is calculated. An equivalent circuit for a magnetostrictive transducer's magnetic circuit, considering the non-uniform cutting of GMM rods, is constructed. Secondly, the classic JA hysteresis model is used to describe the magnetization process of the GMM rod, and the strain of the GMM rod is calculated using a stress-corrected secondary domain transition model to achieve the magneto-mechanical coupling process of the transducer. Then, a single-degree-of-freedom vibration model is used to describe the actual output displacement of the transducer radiation head. Finally, the artificial fish swarm algorithm with strong global searching ability and the cuckoo search algorithm with strong fine-grained searching ability are integrated. Thus, hybrid algorithms are introduced into parameter identification of transducer models to achieve fast, accurate, and stable extraction of model parameters.
In addition, a prototype of a giant magnetostrictive transducer is produced, and an output displacement testing platform is built. The proposed algorithm has significant advantages in curve fitting accuracy, identification speed, and stability, with a curve fitting error of only 4.86%. Then, the measured displacement curves at different frequencies show that considering the eddy current factor in non-uniform cut bars is essential for effectively analyzing the output characteristics of transducers. The output displacement curves of the transducer are analyzed under different prestress and bias magnetic fields. The proposed method provides an excellent prediction of the experimental results, indicating that the method can effectively track the actual output characteristics of transducers under different working conditions.
The following conclusions can be drawn. (1) In identifying transducer parameters, the proposed algorithm has higher identification accuracy, faster speed, and more robuststability than single algorithms and GA-SA hybrid algorithms. (2) Compared with the models with and without the eddy current factor, the importance of calculating the eddy current factor is demonstrated. (3) The output characteristics of transducers under different prestressed and biased magnetic field conditions can be effectively simulated using the proposed algorithm, and the optimal working point of transducers can be tracked, supporting the optimization design of transducers.

Key words： Giant magnetostrictive transducer parameter identification comprehensive circuit model hybrid algorithm

Received: 06 January 2024

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TN712+.2

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	Gao Bing
	Wu Zewei
	Zhao Nengtong
	Ning Qian
	Yang Wenhu

Cite this article:

Gao Bing,Wu Zewei,Zhao Nengtong等. Analysis of Output Characteristics of Giant Magnetostrictive Transducers Based on AFSA-eCS Hybrid Algorithm[J]. Transactions of China Electrotechnical Society, 2025, 40(2): 346-357.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.240043 OR https://dgjsxb.ces-transaction.com/EN/Y2025/V40/I2/346

[1] 黄文美, 刘泽群, 郭万里, 等. 磁致伸缩振动能量收集器的全耦合非线性等效电路模型[J]. 电工技术学报, 2023, 38(15): 4076-4086.
Huang Wenmei, Liu Zequn, Guo Wanli, et al.Fully coupled nonlinear equivalent circuit model for mag- netostrictive vibration energy harvester[J]. Transa- ctions of China Electrotechnical Society, 2023, 38(15): 4076-4086.
[2] Huang Wenmei, Li Yafang, Weng Ling, et al.Multifield coupling model with dynamic losses for giant magnetostrictive transducer[J]. IEEE Transa- ctions on Applied Superconductivity, 2016, 26(4): 4900805.
[3] Xu Qingsong.Robust impedance control of a compliant microgripper for high-speed position/force regulation[J]. IEEE Transactions on Industrial Elec- tronics, 2015, 62(2): 1201-1209.
[4] Nouicer A, Nouicer E, Feliachi M.A neural network for incorporating the thermal effect on the magnetic hysteresis of the 3F3 material using the Jiles-Atherton model[J]. Journal of Magnetism and Magnetic Materials, 2015, 373: 240-243.
[5] 宁倩, 李桥, 高兵, 等. 电-磁-机-声多场边界下的超磁致伸缩Ⅳ型弯张换能器设计方法[J]. 电工技术学报, 2023, 38(12): 3112-3121.
Ning Qian, Li Qiao, Gao Bing, et al.Design of giant magnetostrictive class Ⅳ flextensional transducer under electrical-magnetic-mechanical-acoustic multi- field boundaries[J]. Transactions of China Electro- technical Society, 2023, 38(12): 3112-3121.
[6] Zhao Nengtong, Gao Bing, Yang Wenhu, et al.Design of underwater magnetostrictive longitudinal- type transducers with circuit model considering eddy currents and multi-rod structure[J]. Applied Acoustics, 2023, 202: 109112.
[7] Yang Guozhe, Zhang Yu, Liu Huifang, et al.Study on eddy current loss characteristics of precision giant magnetostrictive actuator considering magnetic field distribution[J]. International Journal of Nanomanufa- cturing, 2019, 15(4): 343.
[8] Niu Muqing, Yang Bintang, Yang Yikun, et al.Dynamic modelling of magnetostrictive actuator with fully coupled magneto-mechanical effects and various eddy-current losses[J]. Sensors and Actuators A: Physical, 2017, 258: 163-173.
[9] Liu Yongguang, Gao Xiaohui, Li Yunlong.Giant magnetostrictive actuator nonlinear dynamic Jiles- Atherton model[J]. Sensors and Actuators A: Physical, 2016, 250: 7-14.
[10] Zheng Jiaju, Cao Shuying, Wang Hongli, et al.Hybrid genetic algorithms for parameter identification of a hysteresis model of magnetostrictive actuators[J]. Neurocomputing, 2007, 70(4/5/6): 749-761.
[11] Calkins F T, Smith R C, Flatau A B.Energy-based hysteresis model for magnetostrictive transducers[J]. IEEE Transactions on Magnetics, 2000, 36(2): 429-439.
[12] 曹淑瑛, 王博文, 郑加驹, 等. 应用混合遗传算法的超磁致伸缩致动器磁滞模型的参数辨识[J]. 中国电机工程学报, 2004, 24(10): 127-132.
Cao Shuying, Wang Bowen, Zheng Jiaju, et al.Parameter identification of hysteretic model for ginat magnetostrictive actuator using hybrid genetic algo- rithm[J]. Proceedings of the CSEE, 2004, 24(10): 127-132.
[13] Li Huiqi, Li Qingfeng, Zhang Junjie.Calculation of Jiles-Atherton hysteresis model’s parameters using mix of chaos optimization algorithm and simulated annealing algorithm[C]//2009 International Con- ference on Microwave Technology and Computational Electromagnetics (ICMTCE 2009), Beijing, 2009: 471-474.
[14] 杨理华, 李践飞, 吴海平, 等. 超磁致伸缩作动器非线性模型辨识研究[J]. 振动与冲击, 2015, 34(18): 142-146, 194.
Yang Lihua, Li Jianfei, Wu Haiping, et al.Parameter identification of nonlinear model of giant mag- netostrictive actuator[J]. Journal of Vibration and Shock, 2015, 34(18): 142-146, 194.
[15] Tian Jing, Zhang Jifeng, Li Boxiao.Parameter identi- fication of Bouc-Wen dynamic model for mag- netorheological shimmy damper based on improved simulated annealing algorithm[J]. The Journal of Engineering, 2020, 2020(14): 970-975.
[16] Yang Yikun, Yang Bintang, Niu Muqing.Parameter identification of Jiles-Atherton model for mag- netostrictive actuator using hybrid niching coral reefs optimization algorithm[J]. Sensors and Actuators A: Physical, 2017, 261: 184-195.
[17] 黄文美, 郭萍萍, 郭万里, 等. 直流偏置对磁致伸缩材料高频动态损耗及磁特性的影响分析[J]. 电工技术学报, 2022, 37(22): 5765-5775.
Huang Wenmei, Guo Pingping, Guo Wanli, et al.Impact analysis of DC bias on high-frequency dynamic loss and magnetic characteristics for magnetostrictive materials[J]. Transactions of China Electrotechnical Society, 2022, 37(22): 5765-5775.
[18] Li Husheng, Gao Bing, Yang Mingzhi, et al.Development of a comprehensive dynamic model for giant magnetostrictive transducers considering bias magnetic field[J]. IEEE Sensors Journal, 2024, 24(7): 10257-10269.
[19] 赵志刚, 马习纹, 姬俊安. 基于AFSA与PSO混合算法的J-A动态磁滞模型参数辨识及验证[J]. 仪器仪表学报, 2020, 41(1): 26-34.
Zhao Zhigang, Ma Xiwen, Ji Jun’an.Parameter identification and verification of J-A dynamic hysteresis model based on hybrid algorithms of AFSA and PSO[J]. Chinese Journal of Scientific Instrument, 2020, 41(1): 26-34.
[20] 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 for Jiles-Atherton hysteresis model based on the hybrid technique of stochastic and deter- ministic optimization algorithm[J]. Transactions of China Electrotechnical Society, 2019, 34(11): 2260-2268.
[21] Deng Jia.Study on the giant magnetostrictive materials with actuator displacement model parameter identification[J]. Advanced Materials Research, 2013, 830: 37-40.
[22] Dozor D M, Engel B B, Kiley J E.Modeling, optimization, and control of magnetostrictive high force-to-mass ratio reaction mass actuators[C]//SPIE Proceedings", "Smart Structures and Materials 1997: Industrial and Commercial Applications of Smart Structures Technologies, San Diego, CA, 1997.