| 基于PSO算法的MFF模型的参数辨识与优化 |
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| 引用本文： | 滕峰成,郝宇,林晓乐.基于PSO算法的MFF模型的参数辨识与优化[J].计量学报,2017,38(2). |
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| 作者姓名： | 滕峰成 郝宇 林晓乐 |
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| 作者单位： | 燕山大学 电气工程学院,河北 秦皇岛,066004 |
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| 摘 要： | 基于磁链理论和Monte-Carlo法,建立了磁流体薄膜(MFF)传感模型和MFF透射模型,分析了磁流体透射特性。采用粒子群算法对MFF透射模型进行了参数辨识,分析了群体数目、迭代次数、惯性权重、加速度因子等参数选值对算法运行结果的影响,并选取了最佳参数组合。搭建了MFF电流传感器实验平台,运用MFF透射模型对MFF电流传感器进行了仿真预测,分析了MFF厚度和粒子浓度对°MF下透射性的影响,实验及仿真结果表明该模型预测误差在2.3%以内,该MFF电流传感器的测量灵敏度达到12μW/A。
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| 关 键 词： | 计量学 磁流体薄膜 粒子群算法 电流传感器 透射模型 参数辨识 |
Parameter Identification and Optimization of the MFF Model Based on the Particle Swarm Optimization Algorithm |
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| TENG Feng-cheng,HAO Yu,LIN Xiao-le.Parameter Identification and Optimization of the MFF Model Based on the Particle Swarm Optimization Algorithm[J].Acta Metrologica Sinica,2017,38(2). |
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| Authors: | TENG Feng-cheng HAO Yu LIN Xiao-le |
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| Abstract: | Based on the flux theory and Monte-Carlo method, magnetic fluid transmission characteristics are analyzed and the magnetic fluid film (MFF) models of the transmittance and the sensor are established.Using PSO algorithm, the parameter identification of MFF transmission model is carried out.The influences of number of groups, iterations, inertia weight and acceleration factors on operating results of algorithm are analyzed, and the best combination of parameters is selected.The experiment platform of MFF current sensors is built, the impact of MFF transmission of the MFF thickness and particle concentration is analyzed.The results of experiment and simulation show that the predictive error of the model within 2.3% and the measurement sensitivity of the MFF current sensor reach 12 μW/A. |
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| Keywords: | metrology MFF PSO algorithm current sensor transmission model parameter identification |
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