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作 者:李朋 LI Peng(State Grid Taixing Power Supply Company Engineering Technology Center.Taixing 225400,China)
机构地区:[1]国网泰兴市供电公司工程技术中心,江苏泰兴225400
出 处:《通信电源技术》2024年第9期34-36,共3页Telecom Power Technology
摘 要:文章提出一种基于无线通信和机器学习的智能系统解决方案。该系统通过部署无线传感器网络实现配电网的实时监测,采用改进的支持向量机(Support Vector Machine,SVM)算法进行故障检测,引入阻抗法实现精确的故障定位。搭建一个高度仿真的实验平台,对系统的传输性能、检测精度及定位误差等指标进行了全面评估。实验结果表明,该系统能够在低信噪比环境下实现高精度的故障检测与定位,为配电自动化提供新的解决思路。The article proposes an intelligent system solution based on wireless communication and machine learning.The system realizes real-time monitoring of distribution networks by deploying wireless sensor networks,adopts an improved Support Vector Machine(SVM)algorithm for fault detection,and introduces the impedance method to realize accurate fault localization.A highly simulated experimental platform is built to comprehensively evaluate the system’s transmission performance,detection accuracy and localization error.The experimental results show that the system is capable of realizing high-precision fault detection and localization in a low signal-to-noise ratio environment,providing a new solution idea for power distribution automation.
分 类 号:TM73[电气工程—电力系统及自动化]
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