摘要
输电线路绝缘故障时常发生,严重影响电力正常供应,造成巨大的经济损失。在此背景下,为在故障发生后更快检测出故障,针对模糊理论、灰色聚类、神经网络三种算法造成系统延迟时间长的问题,设计一种基于组合决策树的输电线路绝缘故障检测系统。该系统最大特点在于将组合决策树替代模糊理论、灰色聚类、神经网络三种算法,应用在输电线路绝缘故障检测系统当中。组合决策树在保证检测准确性的前提下,运算更为简便,占用系统更少内存,加快系统运行速度,使得系统检测的延迟时间短,达到了本次系统研究的预期目标。
Insulation faults of transmission lines often occur,which seriously affect the normal supply of power and cause huge economic losses. In this context,in order to detect faults more quickly after faults occur,a transmission line insulation fault detection system based on combinatorial decision tree is designed to solve the problem of long delay time caused by three algorithms: fuzzy theory,grey clustering and neural network. The greatest feature of the system is that the combination decision tree is used in the transmission line insulation fault detection system instead of the three algorithms of fuzzy theory,grey clustering and neural network. On the premise of guaranteeing the accuracy of detection,the combined decision tree has the advantages of simpler operation,less memory occupied and faster running speed,which shortens the delay time of system detection and achieves the expected goal of this system research.
作者
郑海
张超
杨玺
ZHENG Hai;ZHANG Chao;YANG Xi(Guangdong Power Grid Co.,Ltd.,Jiangmen Power Supply Bureau,Jiangmen 529000,China)
出处
《电子设计工程》
2020年第11期166-169,174,共5页
Electronic Design Engineering
基金
广东电网有限责任公司科技项目资助(GDKJXM20180012)
2017年广东省教育厅重点平台和重大科研项目(2017GKTSCX042)。
关键词
组合决策树
输电线路
绝缘故障
检测系统
combinatorial decision tree
transmission line
insulation fault
detection system