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作 者:赵铭滕 朱永利[1] Zhao Mingteng;Zhu Yongli(School of Control and Computer Engineering,North China Electric Power University,Baoding 071003,Hebei,China)
机构地区:[1]华北电力大学控制与计算机工程学院,河北保定071003
出 处:《计算机应用与软件》2022年第2期44-48,共5页Computer Applications and Software
基 金:国家自然科学基金项目(51677072);中央高校基本科研业务费专项资金项目(2018QN078)。
摘 要:随着局部放电数据增多,为了提高放电数据的参数提取和模式构造的效率,将放电数据参数分析与Storm相结合,设计并使用Storm平台下双阈值过滤参数提取算法。该算法在框架组件中分别对各个阶段进行编程实现,通过数据流连通,将其产生的任务提交至集群完成,有效提取基本参数并且绘制图谱。实验结果表明,该算法与Storm框架结合具有低延迟和高吞吐量,能够提高处理效率。With the increasing of the partial discharge data,in order to improve the efficiency of parameter extraction and pattern construction of discharge data,the discharge data parameter analysis is combined with Storm,and a dual threshold filtering parameter extraction algorithm under the Storm platform was designed and used.The algorithm implemented the programming of each phase in the framework component.The data flow was connected,and the tasks were submitted to the cluster for completion.The basic parameters were effectively extracted and the map was drawn.Experimental results show that the algorithm combined with the Storm framework has low latency and high throughput,which can improve processing efficiency.
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