摘要
不同类型的电缆PD(局部放电),其相位谱图和统计参数存在差异。个别故障间的差异较小,模式识别难度大,为此提出了一种基于Fuzzy-ART(模糊自适应共振理论)的电缆PD模式识别方法。设置了4种电缆人工缺陷并通过实验对该方法进行验证,结果表明,Fuzzy-ART神经网络具有快速、稳定的学习和分类能力,不仅能对已知的电缆PD进行模式识别,而且能够有效识别未知电缆PD模式,具有广泛的适用性。
The phase spectrum and statistical parameters of different types of cable partial discharge(PD)are different.Since the difference between individual faults is slight,pattern recognition is difficult.Therefore,a pattern recognition method of cable PD based on fuzzy adaptive resonance theory(Fuzzy-ART)is proposed.Four kinds of artificial defects are set up,and the method is verified by experiments.The experimental results show that the Fuzzy-ART neural network is capable of fast and stable learning and classification.It can not only recognize the known cable PD pattern but also recognize the unknown cable PD fault pattern effectively.It is widely applicable to cable PD pattern recognition.
作者
舒锦宏
徐灵江
吕延春
段文华
钟守平
SHU Jinhong;XU Lingjiang;LYU Yanchun;DUAN Wenhua;ZHONG Shouping(Jinshuitan Hydropower Plant of State Grid Zhejiang Electric Power Co.,Ltd.,Lishui Zhejiang 323000,China;State Grid Zhejiang Electric Power Co.,Ltd.,Hangzhou 310007,China;Nanjing NR Electric Co.,Ltd.,Nanjing 211102,China)
出处
《浙江电力》
2021年第11期10-15,共6页
Zhejiang Electric Power
基金
国网浙江省电力有限公司科技项目(5211JS19001B)。
