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作 者:段雄英[1] 赵洋洋 陈艳霞 马畅 廖敏夫[1] DUAN Xiongying;ZHAO Yangyang;CHEN Yanxia;MA Chang;LIAO Minfu(School of Electrical Engineering,Dalian University of Technology,Liaoning Dalian 116024,China;State Grid Beijing Electric Power Research Institute,Beijing 100075,China)
机构地区:[1]大连理工大学电气工程学院,辽宁大连116024 [2]国网北京市电力公司电力科学研究院,北京100075
出 处:《高压电器》2020年第9期80-86,共7页High Voltage Apparatus
基 金:国家电网公司总部科技项目。
摘 要:电力系统中高压断路器普遍采用液压操动机构,其机械寿命是考核断路器可靠性和稳定性的基础,文中提出运用数据驱动方法建立退化过程与特征参量之间的数学映射关系,实现高压断路器液压操动机构的机械寿命预测。基于Hadoop+Spark大数据平台及其生态组件,将采集的数据存储在Hadoop分布式文件系统中,利用Spark运算框架处理数据,结合Spark ML机器学习库中的回归算法,训练模型并进行验证评估,从评估结果来看:文中创建的广义线性回归算法模型的均方根误差为52.96,R-平方系数为0.92,预测值和实际值偏差较小,拟合效果较好,相较于其他回归算法模型性能指标最优。最后得到最优模型及其参数,据此可确定对高压断路器维护检修的最佳时刻,对于切实保护高压断路器设备的运行可靠性、安全性和经济性具有重要的意义。The high-voltage circuit breakers generally use hydraulic operating mechanisms in power systems.The mechanical life is the basis for evaluating the reliability and stability of circuit breakers.In this paper,the data-driven method is proposed to establish the mathematical mapping relationship between the degradation process and the characteristic parameters.Realize the mechanical life prediction of the hydraulic operating mechanism of the high voltage circuit breaker.Based on Hadoop+Spark platform and its ecological components,the data is collected and stored in the distributed file system HDFS in Hadoop and the Spark computing framework is used to process the data.Combined with the regression algorithm in the Spark ML machine learning library,the model is trained and verified.From the evaluation results:The RMES of the model of generalized linear regression is 52.96,the R-square coefficient is 0.92,it shows the deviation between the predicted value and the actual value is small,and the fitting effect is better,which is the best compared with other regression algorithm models.Finally,the optimal model and its parameters are obtained.Based on this,the optimal time for maintenance and repair of the high-voltage circuit breaker is determined,which is of great significance for effectively protecting the operational reliability,safety and economy of the high-voltage circuit breaker.
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