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基于AFSA-eCS混合算法的超磁致伸缩换能器输出特性分析

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超磁致伸缩换能器工作性能受到电-磁-机多场耦合的影响,常利用多场模型分析其非线性输出特性,而能否准确获取其多场耦合参数决定了模型的准确性,是换能器设计和优化的关键.鉴于换能器多场模型具有参数多、耦合强、参数辨识难等特点.该文提出基于改进人工鱼群和布谷鸟混合的超磁致伸缩换能器多场模型参数辨识方法.首先,考虑切割棒材涡流效应的影响,建立超磁致伸缩换能器电-磁-机多场耦合的综合电路模型,来实现超磁致伸缩换能器输出行为的模拟;其次,针对模型参数维度多、耦合强的问题,提出了改进的人工鱼群和布谷鸟混合算法(AFSA-eCS),该方法引入精英个体反向学习策略、动态步长和动态发现概率以强化局部精细化搜索能力;最后,基于实验平台验证了综合电路模型和AFSA-eCS的有效性.结果表明:AFSA-eCS相较于单一算法与遗传退火混合算法(GA-SA)收敛快、参数辨识精度高,基于所提算法和模型能够快速有效分析换能器不同工况下的输出特性.
Analysis of Output Characteristics of Giant Magnetostrictive Transducers Based on AFSA-eCS Hybrid Algorithm
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.

Giant magnetostrictive transducerparameter identificationcomprehensive circuit modelhybrid algorithm

高兵、吴泽伟、赵能桐、宁倩、杨文虎

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湖南大学电气与信息工程学院 长沙 410082

超磁致伸缩换能器 参数辨识 综合电路模型 混合算法

2025

电工技术学报
中国电工技术学会

电工技术学报

北大核心
影响因子:2.593
ISSN:1000-6753
年,卷(期):2025.40(2)