基于K聚类算法的露天矿微波网络参数优化

    Optimization of microwave network parameters in open-pit mines based on K-clustering algorithm

    • 摘要: 由于露天矿的电流聚集效应,使得不同区域的微波网络参数产生显著差异,造成微波信号在传输过程中的传输路径和角度出现偏差,导致通信信号频谱波动剧烈。因此,提出基于K聚类算法的露天矿微波网络参数优化方法。分析露天矿微波网络架构发现优化信号波长、各终端站间的距离、天线高度等参数,构建数字微波通信主架构,计算调整终端站微波收发装置天线垂直距离,确保微波信号在传输过程中保持最佳的传输路径和角度。将露天矿不同区域微波网络各终端站间的距离、天线高度及信号波长作为待优化的参数集,利用K聚类算法对海量参数数据集进行聚类处理,通过欧氏距离确定不同参数间的距离,由此得到不同区域的最优参数结果。实验结果显示,不同的K值对聚类效果略有影响,当K值设定为4时,轮廓系数达到最高值,参数聚类结果最优;微波网络参数优化后,通信信号频谱平稳均匀,信号质量得到全面提升。

       

      Abstract: Due to the current accumulation effect in open-pit mines, there are significant differences in microwave network parameters in different regions, resulting in deviations in the transmission path and angle of microwave signals during transmission, leading to severe spectral fluctuations in communication signals. Therefore, a parameter optimization method for microwave networks in open-pit mines based on K-clustering algorithm is proposed. Analyzing the microwave network architecture of open-pit mines, it is found that optimization parameters such as signal wavelength, distance between terminal stations, and antenna height can construct a digital microwave communication main architecture, calculate and adjust the vertical distance of the terminal station microwave transceiver antenna, and ensure that the microwave signal maintains the optimal transmission path and angle during transmission. The distance, antenna height, and signal wavelength between different terminal stations of the microwave network in different areas of the open-pit mine are taken as the parameter sets to be optimized. The K-clustering algorithm is used to cluster the massive parameter dataset, and the Euclidean distance is used to determine the distance between different parameters, thereby obtaining the optimal parameter results for different areas. The experimental results show that different K values have a slight impact on the clustering effect. When the K value is set to 4, the contour coefficient reaches the highest value and the parameter clustering result is optimal. After optimizing the parameters of the microwave network, the communication signal spectrum is stable and uniform, and the signal quality is comprehensively improved.

       

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