摘要
为了提高高压断路器故障诊断的正确率,采用动态调整交叉概率和突变概率的策略对遗传算法进行改进,采用改进遗传算法对支持向量机进行参数优化,建立了基于改进遗传算法优化支持向量机的断路器故障诊断模型,采用实际断路器运行数据进行算法分析,并与其他断路器故障诊断方法对比,结果表明,IGA-SVM模型的综合正确率为97.5%,优于其他方法,验证了本文方法的正确性和实用性。
In order to improve the accuracy of highvoltage circuit breaker fault diagnosis,the strategy of dynami cally adjusting the crossover probability and mutation probability is adopted to improve the genetic algorithm,and the improved genetic algorithm is used to optimize the parameters of support vector machineA circuit breaker fault diagnosis model based on improved genetic algorithm optimized support vector machine is establishedThe algorithm is analyzed by using the actual circuit breaker operation data,and compared with other circuit breaker fault diagno sis methods,The results show that the comprehensive accuracy of IGASVM model is 975%,which is better than other methods,and verifies the correctness and practicality of this method.
作者
龙紫筠
曾小兰
阮绍炯
谭锦雄
LONG Zijun;ZENG Xiaolan;RUAN Shaojiong;TAN Jinxiong(Jiangmen Daguangming Electric Power Design CoLtd.,Jiangmen 529000,China)
出处
《电气开关》
2023年第4期66-70,共5页
Electric Switchgear
关键词
断路器
故障诊断
改进遗传算法
支持向量机
circuit breaker
fault diagnosis
improved genetic algorithm
support vector machine
