极地研究 ›› 2025, Vol. 37 ›› Issue (3): 532-540.DOI: 10.13679/j.jdyj.20230064

• 研究论文 • 上一篇    下一篇

中低频下海冰介电常数试验研究

张楠1, 常晓敏1左广宇2贾治学1窦银科2   

  1. 1太原理工大学水利科学与工程学院, 山西 太原 030024; 
    2太原理工大学电气与动力工程学院, 山西 太原 030024
  • 收稿日期:2023-10-23 修回日期:2024-01-15 出版日期:2025-09-30 发布日期:2025-09-25
  • 通讯作者: 张楠
  • 基金资助:
    国家重点研发项目和山西省应用基础研究计划

Experimental study of the brine ice dielectric constant at low and medium frequencies

ZHANG Nan1, CHANG Xiaomin1, ZUO Guangyu2, JIA Zhixue1, DOU Yinke2   

  1. 1College of Water Resources Science and Engineering, Taiyuan University of Technology, Taiyuan 030024, China; 
    2College of Electrical and Power Engineering, Taiyuan University of Technology, Taiyuan 030024, China
  • Received:2023-10-23 Revised:2024-01-15 Online:2025-09-30 Published:2025-09-25
  • Supported by:

摘要: 北极区域的海冰正在迅速消融,介电常数是关系海冰物理性质和遥感监测的重要参数。为了探究海冰介电性能与物理特性之间的关系,定量分析不同情况下影响海冰介电常数变化的主导因素,利用低温实验室模拟极区气温,在80 kHz~50 MHz频率范围内对不同盐度的人造海冰进行介电性能和物理特性测试,探究冰样温度由-45 ℃升至-15 ℃的过程中介电常数与频率、温度、盐度的变化关系,并利用相关分析方法研究不同因素对冰样介电常数的影响。结果表明,海冰的介电常数与温度、盐度呈正相关,温度每升高10 ℃介电常数约增加1.5;海冰的介电常数与频率呈负相关,盐度会影响介电常数随频率变化的速率,盐度越大,变化速率越小。最后利用试验结果建立纯冰及盐水冰介电常数预测模型, R2分别为0.75、0.68,P值分别为0.005、0.008,均方根误差分别为1.1、3.4,残差平方和分别为40、127,模型拟合效果较好,回归效果显著且满足精度要求。表明通过物理特性来反演极区海冰的介电常数具有可行性,有望通过海冰物理特性与介电性能的关系对极区海冰进行监测。

关键词: 盐水冰, 介电性能, 中低频, 物理性质, 预测模型, 北极海冰  

Abstract: Sea ice is melting rapidly in the Arctic region, and further monitoring of the ice situation in the polar region is critical. The dielectric constant is an important parameter for remote sensing monitoring of sea ice. This study utilizes a cryogenic laboratory to investigate the relationship between the dielectric and physical properties of sea ice and quantitatively analyze the dominant factors affecting changes in the dielectric constant of sea ice under different conditions. The air temperature of the polar region is simulated to test the dielectric and physical properties of artificially frozen brine ice within a frequency range of 80 kHz~50 MHz. The investigation is focused on changes in the dielectric constant of brine ice with frequency, ice temperature, and salinity with increasing temperature (from −45 ℃ to −15 ℃), and the effects of different factors on the dielectric constant are assessed using correlation analysis. The results show that the dielectric constant of brine ice is positively correlated with ice temperature and salinity, and increases by ~1.5 for every 10 ℃ increase in ice temperature. Furthermore, it is negatively correlated with frequency, with higher salinity lowering the rate of change. Finally, the test results are used to establish a dielectric constant prediction model for pure ice and brine ice, yielding R2 values of 0.75 and 0.68, P-values of 0.005 and 0.008, root mean square error values of 1.1 and 3.4, and residual sum of squares values of 40 and 127, respectively. The model fitting effect is improved, the regression effect is significant, and the accuracy requirements are met. This indicates that it is feasible to invert the dielectric constant of polar sea ice through physical properties, and that polar sea ice can be monitored via the relationship between its physical and dielectric properties.

Key words: saline ice, dielectric properties, low and medium frequencies, physical properties, predictive model, Arctic sea ice