数据与知识融合的电能表故障关联模型研究

当前各地积累了大量因故障拆回的电能表,但拆回表的价值尚未充分发掘。本文利用拆回表信息构建从“电能表故障现象”到“元器件故障”的关联模型给出了建立该模型的完整流程。首先对拆回表进行开盖检视,记录初步结果并进行数据筛分、清洗,获得故障现象与元器件故障之间的直接与间接关系;其次对于直接关系采用统计方法建模,对于间接关系则以层次分析法为桥梁进行建模,最终获得完整关联模型。本文还给出了该模型的应用实例与数据更新方法。通过实验证明了该方法有效性,所提方法可用于指导电能表的维护检修及生产流程改进。

Research on Electric Energy Meter Fault Correlation Model Based on Data and Knowledge Fusion

At present, a large number of electric energy meters removed due to faults have accumulated in various places, but the value of the removed meters has not been fully explored. This paper uses the information of the dismantled meter to build a correlation model from "electric energy meter failure phenomenon" to "component failure", and gives the complete process of establishing the model. First, open the cover and inspect the dismantling table, record the preliminary results, and perform data screening and cleaning to obtain the direct and indirect relationship between the failure phenomenon and component failure. Secondly, statistical methods are used to model the direct relationship, and the bridge is modeled by the analytic hierarchy process. Finally the complete association model is obtained. This paper also gives the application example and data update method of the model. The effectiveness of the method is proved by experiments, and the proposed method can be used to guide the maintenance and repair of the electric energy meter and the improvement of the production process.