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基于无线传感器网络的电气故障点定位仿真 被引量:1

Simulation of Electrical Fault Point Location Based on Wireless Sensor Network
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摘要 由于电网结构中的电气设备及输电线寿命有限,若运维不及时,电气故障会严重影响电网的稳定运行,因此,实现故障快速自动定位是降低故障影响程度和避免电力损失的关键途径之一。提出无线传感器网络的电气故障点定位方法。引入无线传感器网络,根据节点覆盖度和能量均衡,优化部署无线传感器网络节点,完成电气设备的故障信息的采集。采用小波包和支持向量机对故障信息去噪,最后在二进制粒子群算法中输入去噪后的故障信息,实现电气故障点的定位。仿真结果表明,提出方法定位电网故障时所需的训练时间更短,且误识率低于1%,识别率高达98%,输出的电气故障信号定位幅值波形图与实际情况一致,实验结果验证了上述方法的应用性能良好,具有较高研究价值。 Due to a limited service life,it is necessary to maintain the electrical equipment and transmission lines in the power grid structure timely.Therefore,rapid automatic fault location is one of the ways to reduce the impact of fault and avoid power loss.In this paper,a method of electrical fault location for wireless sensor networks was pro-posed.Firstly,a wireless sensor network was introduced.Secondly,the deployment of wireless sensor network nodes was optimized according to node coverage and energy balance,and then the collection of fault information of electrical equipment was completed.On this basis,wavelet packet and support vector machine were used to remove the noise form fault information.Finally,the denoised fault information was input into the binary particle swarm optimization al-gorithm to locate the electrical fault.Following conclusions can be drawn from simulation results.The proposed method needs less training time when locating power grid faults is shorter;The error recognition rate is as high as 98%,and less than 1%;The amplitude waveform of electrical fault signal location is consistent with the actual situa-tion.The experimental result also proves the good application performance and high research value of the method.
作者 张迪 韩铮 王雪丽 ZHANG Di;HAN Zheng;WANG Xue-li(School of Physics and Intelligent Manufacturing Engineering,Chifeng University,Chifeng Inner Mongolia 024000,China;Intelligent Information Processing Technology and Systems Laboratory,Tiangong University,Tianjin 300387,China)
出处 《计算机仿真》 北大核心 2023年第11期86-90,共5页 Computer Simulation
关键词 无线传感器网络 节点优化部署 数据去噪 二进制粒子群算法 电气故障点定位 Wireless sensor network Optimization and deployment of nodes Data denoising Binary particle swarm algorithm Electrical fault location
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