基于动态自由能磁滞模型的GMM-FBG电流传感器磁滞建模与参数辨识

滕峰成; 杨雪璠; 吕登岩; 叶文昊

doi:10.3969/j.issn.1000-1158.2022.04.13

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计量学报 ›› 2022, Vol. 43 ›› Issue (4) : 513-520. DOI: 10.3969/j.issn.1000-1158.2022.04.13

电磁学计量

基于动态自由能磁滞模型的GMM-FBG电流传感器磁滞建模与参数辨识

滕峰成,杨雪璠,吕登岩,叶文昊

作者信息 +

Hysteresis Modeling and Parameter Identification of GMM-FBG Current Sensor Based on Dynamic Free Energy Hysteresis Model

TENG Feng-cheng,YANG Xue-fan,LÜ Deng-yan,YE Wen-hao

Author information +

文章历史 +

摘要

为解决GMM-FBG电流传感器中存在的磁滞非线性和涡流损失问题,提出了一种耦合涡流损失模型的动态自由能磁滞模型,采用非线性遗传算法对该模型进行参数辨识和优化,提高了模型在工频下对磁滞曲线的预测精度。搭建了GMM-FBG电流传感器实验平台,利用所建的磁滞模型对传感系统进行建模补偿和实验验证。实验结果表明该模型能够较好地预测工频下传感器中的动态磁滞非线性,模型的预测误差在3.6%以内,电流测量灵敏度可达到0.069nm/A。

Abstract

In order to solve the hysteresis nonlinearity and eddy current loss problems in GMM-FBG current sensor, a dynamic free energy hysteresis model of coupled eddy current loss model was proposed, and nonlinear genetic algorithm was used to identify and optimize the parameters of the model, which improved the prediction accuracy of the model to the hysteresis curve at power frequency. A GMM-FBG current sensor experimental platform was built, and the hysteresis model was used to compensate the sensor system and verify the sensor system. The experimental results showed that the model can well predict the dynamic hysteresis nonlinearity of the sensor under power frequency, the prediction error of the model is within 3.6%, and the sensitivity of current measurement can reach 0.069nm/A.

导出引用

滕峰成,杨雪璠,吕登岩,叶文昊. 基于动态自由能磁滞模型的GMM-FBG电流传感器磁滞建模与参数辨识[J]. 计量学报. 2022, 43(4): 513-520 https://doi.org/10.3969/j.issn.1000-1158.2022.04.13

TENG Feng-cheng,YANG Xue-fan,Lü Deng-yan,YE Wen-hao. Hysteresis Modeling and Parameter Identification of GMM-FBG Current Sensor Based on Dynamic Free Energy Hysteresis Model[J]. Acta Metrologica Sinica. 2022, 43(4): 513-520 https://doi.org/10.3969/j.issn.1000-1158.2022.04.13

中图分类号： TB97

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