摘要
断路器的故障诊断对岸电系统的稳定运行有重要意义。针对人工鱼群算法和其他智能算法在优化支持向量机参数时,存在易陷入局部最优、泛化能力差等问题,通过自适应调整步长和引入全局随机行为,提出基于改进人工鱼群算法优化支持向量机参数的故障诊断模型。将断路器合闸线圈电流信号中的时间和电流信号作为特征量,采用改进人工鱼群算法对支持向量机的参数寻优,以提升支持向量机的故障分类性能。仿真结果显示,该算法在样本数量小的情况下仍具有良好的分类性能,能够准确对断路器进行故障分类。
The fault diagnosis of the circuit breaker is of great significance to the stable operation of the shore power system.For the artificial fish swarm algorithm and other intelligent algorithms,when optimizing the parameters of support vector machine,there were problems such as easy to fall into local optimum and poor generalization ability.By adaptively adjusting the step size and introducing global random behavior,this paper proposed an improved artificial fish swarm algorithm to optimize the fault diagnosis model of the support vector machine parameters.To improve the fault classification performance of the support vector machine,the time and current signals extracted from the current signals of the circuit breaker closing coil were used as the characteristic variables,and the improved artificial fish swarm algorithm was adopted to optimize the parameters of the support vector machine.The simulation results show that this algorithm can accurately judge the fault type of the circuit breaker with good classification performance under the conditions of small quantity of samples.
作者
杨奕飞
焦文文
何祖军
张发平
郭江
YANG Yi-fei;JIAO Wen-wen;HE Zu-jun;ZHANG Fa-ping;GUO Jiang(School of Electronics and Information,Jiangsu University of Science and Technology,Zhenjiang 212003,China;Jiangsu Zhongzhi Marine Engineering Equipment Co.,Ltd,Zhenjiang 212000,China)
出处
《电工电气》
2019年第8期57-61,共5页
Electrotechnics Electric
基金
江苏省重点研发计划项目(BE2018109)
关键词
支持向量机
改进人工鱼群算法
岸电箱
断路器故障诊断
support vector machine
improved artificial fish swarm algorithm
shore power box
circuit breaker fault diagnosis
