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文章摘要
基于BP神经网络的智能台区识别方法研究
Research on the Intelligent Transformer Area Recognition MethodBased on BP Neural Network
Received:August 04, 2015  Revised:August 04, 2015
DOI:
中文关键词: 台区识别  电力载波  信号品质  BP神经网络
英文关键词: transformer  area recognition, power  line carrier, signal  quality, BP  neural network
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目,61202369);上海市自然科学基金(14ZR1417400);上海市科技创新行动计划地方院校能力建设项目(13160500900);上海市教育委员会科研创新项目(12ZZ176,13YZ102)
Author NameAffiliationE-mail
Li Ya* College of Electronics and Information Engineering,Shanghai University of Electric Power dqly2013@126.com 
Jiang Wei College of Electronics and Information Engineering,Shanghai University of Electric Power  
Fan Rusen State Grid Shanghai Qingpu Power Supply Company fanrusen107@163.com 
Yang Junjie College of Electronics and Information Engineering,Shanghai University of Electric Power  
Song Tao College of Electronics and Information Engineering,Shanghai University of Electric Power  
Zhao Qinxue College of Electronics and Information Engineering,Shanghai University of Electric Power  
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中文摘要:
      为方便普查用户台区和相位信息,特别是解决跨台区用户信息识别难题,提出一种基于BP神经网络的智能台区用户信息识别方法并研制了该系统。系统由识别器和手持器两部分组成,通信方式采用电力载波通信技术,对于垮台区用户,依据系统和已识别用户之间的通信信号品质,选取隐藏层节点数为6的前向BP神经网络作为跨台区用户识别模型进行识别。MATLAB仿真和实际测试结果表明:该方法可有效解决跨台区通信串扰难题,能够智能识别用户台区和相位信息,同时具有识别准确性高、容差性能较好的优点,对提高台区用户信息识别准确性,减少工作量降低成本,具有重要意义。
英文摘要:
      For the convenience of census the transformer area and the phase information, especially to solve the user information of across the transformer area identifying problems, we put forward a kind of intelligent transformer area of the users information recognition method based on BP neural network and developed the system. This system consists of identifier and handheld devices, the communication used power line carrier communication technology. For the across transformer area, according to the communication signal quality between the system and the recognized user, we selected the forward BP neural network with the hidden layer nodes is 6 as the across the transformer area model to recognize. The MATLAB simulation and actual test results show that this method not only can effectively solve the cross transformer area communication crosstalk problems but also can intelligently identify the user transformer area and the phase information, and also with the advantages of high identification accuracy, higher tolerance performance, these to improve the accuracy of the transformer area and the phase information, reduce the workload and to reduce cost are have a great significance.
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