基于“多表合一”系统的智能表异常诊断及处理方法研究

摘要

文章在分析电、水、气智能表计故障诊断和实际消缺工作流程特点的基础上,提出了一种基于“多表合一”系统的智能表异常诊断和处理方法,该方法首先通过关联挖掘获取诊断规则,然后将监测的数据转换为事件元并进行规则匹配以获取诊断结果,最后通过现场排查确认并反馈诊断结果.该方法将异常诊断和消缺闭环管理结合起来,通过对诊断知识库的不断完善来提高异常诊断的准确性,充分发挥关联挖掘技术的优越性.%Based on analyzing the characteristics of fault diagnosis and practical elimination of smart electric,water and gas meter,an abnormity diagnosis and treatment method of smart meters based on association mining is proposed in this paper.Firstly,diagnosis rules are obtained through association mining by this method,the monitored data is then converted to event elements and the diagnostic results are obtained via a rule match.Finally,the diagnostic results are confirmed and feedback through the field investigation.The abnormity diagnosis and elimination of closedloop management are combined by the method,and the accuracy of the abnormity diagnosis is increased by improving the diagnosis knowledge base,and the superiority of the association mining technology is fully exerted.