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Deployment optimization of wireless mesh networks in wind turbine condition monitoring system

机译:风力涡轮机状态监测系统无线网状网络的部署优化

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This study aims to propose a deployment optimization method based on IEEE 802.11 heterogeneous wireless mesh networks (WMNs) for the condition monitoring system (CMS) of wind turbines. This method can provide a flexible, low-cost, and easy-to-implement network framework for wind farms in harsh environments, thereby avoiding interference of the newly installed CMS on the communication network of the SCADA system. The K-medoids clustering algorithm transforms the continuous space location problem into the discrete space location problem. Moreover, the mesh client (MC) coverage and backbone network connectivity issues are considered to ensure that the generated candidate point set can meet the coverage and connectivity requirements without generating numerous redundant nodes. Firstly, according to the characteristics of the model, the K-medoids clustering algorithm is used to obtain a set of candidate points of mesh routers (MRs) that meet the coverage rate. Secondly, a reasonable connection algorithm is proposed according to the constraints, and the optimal deployment is selected from the candidate points. Thirdly, taking the number of hops from MR to MG and the priority of MC as the weight. The path planning with the least number of MRs and load balancing is obtained by constructing a minimum spanning tree (MST) based on the improved Kruskal algorithm. Finally, Multi-channel inter-frequency networking technology is adopted to reduce interference between co-channels and between adjacent channels. The result shows that the method proposed can minimize network operating costs, meet the capacity requirements of MC, and reduce link losses.
机译:本研究旨在提出基于IEEE 802.11异构无线网状网络(WMNS)的部署优化方法,用于风力涡轮机的状态监测系统(CMS)。该方法可以为恶劣环境提供灵活,低成本,易于实现的风电场网络框架,从而避免了新安装的CMS对SCADA系统的通信网络的干扰。 K-METOIDS聚类算法将连续空间位置问题转换为离散空间位置问题。此外,Mesh客户端(MC)覆盖和骨干网络连接问题被认为是确保所生成的候选点集可以满足覆盖和连接要求而不产生许多冗余节点。首先,根据模型的特征,k-myoids聚类算法用于获得满足覆盖率的网路由器(MRS)的一组候选点。其次,根据约束提出了合理的连接算法,并且从候选点中选择最佳部署。第三,从MR到MG的啤酒花数量和MC的优先级作为重量。通过基于改进的Kruskal算法构建最小生成树(MST)来获得具有最少数量的MRS和负载平衡的路径规划。最后,采用多通道间频率网络技术来减少共通道之间的干扰以及相邻信道之间的干扰。结果表明,所提出的方法可以最大限度地减少网络运营成本,满足MC的容量要求,减少链路损耗。

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