周涛,彭勇,施佩克,等. 移动基站共址高压输电铁塔的电磁场分布特性分析与预测[J]. 电波科学学报,2021,36(4):637-644. DOI: 10.13443/j.cjors.2020062401
      引用本文: 周涛,彭勇,施佩克,等. 移动基站共址高压输电铁塔的电磁场分布特性分析与预测[J]. 电波科学学报,2021,36(4):637-644. DOI: 10.13443/j.cjors.2020062401
      ZHOU T, PENG Y, SHI P K, et al. Analysis and prediction of electromagnetic field distribution characteristics for mobile base station co-located with high voltage transmission tower[J]. Chinese journal of radio science,2021,36(4):637-644. (in Chinese). DOI: 10.13443/j.cjors.2020062401
      Citation: ZHOU T, PENG Y, SHI P K, et al. Analysis and prediction of electromagnetic field distribution characteristics for mobile base station co-located with high voltage transmission tower[J]. Chinese journal of radio science,2021,36(4):637-644. (in Chinese). DOI: 10.13443/j.cjors.2020062401

      移动基站共址高压输电铁塔的电磁场分布特性分析与预测

      Analysis and prediction of electromagnetic field distribution characteristics for mobile base station co-located with high voltage transmission tower

      • 摘要: 为了明确移动基站架设在高压输电铁塔上对电力运检人员的电磁辐射影响,对移动基站共址高压输电铁塔的电磁场分布特性进行了研究. 在4G基站共址220 kV高压输电铁塔的真实场景下开展了电磁场强度测量,获得了铁塔周围地面区域和铁塔内部垂直方向上的场强测量数据;基于射线追踪仿真,在实测验证的基础上,全面分析了移动基站共址高压输电铁塔的电磁场分布特性,并根据实测和仿真结果提出了强中弱场区划分方法;将径向基函数(radial basis function, RBF)神经网络应用于场强预测,建立了电磁场分布特性预测模型. 结果表明所提出的模型能够较为准确地实现移动基站共址高压输电铁塔场景下的场强预测,可为移动基站共址高压输电铁塔的安全运检工作提供参考.

         

        Abstract: In order to understand the impact of electromagnetic radiation on power inspectors who work on a high voltage transmission tower equipped with a mobile base station, we investigate the electromagnetic field distribution characteristics of the mobile base station co-located with high voltage transmission tower. Electromagnetic field intensity measurements in the realistic scenario of 4G base station co-located with 220 kV high-voltage transmission tower are performed, and field intensity measurement data in the ground area around the tower and in the vertical direction inside the tower are acquired. Based on the ray tracing simulation and depending on experimental verification, the electromagnetic field distribution characteristics of mobile base station co-located with high-voltage transmission tower are comprehensively analyzed. According to the measurement and simulation results, a method for partitioning strong, middle and weak field intensity areas is proposed. Finally, the radial basis function neural network is applied to the field strength prediction, and a prediction model for electromagnetic field distribution characteristics is established. These results can provide a reference for the safe operation and inspection in the scenario of mobile base station co-located with high voltage transmission tower.

         

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