Research On Application Method For Reliability Prediction Of Intelligent Electric Energy Meter Based On Failure Rate Level

The intelligent electric energy meter is responsible for the important social service function,which has the characteristics of large installation and wide distribution.If the reliability is not high during the long term operation,it will not only cause the replacement due to quality problems,but also lead to time-consuming,laborious and easy to cause electricity safety problems.Reliability prediction is an indispensable technical means to make decision design,improve design and ensure that the product meets the requirements of reliability index.With the rapid development of intelligent and digital instruments and instruments,the functions of the intelligent electric energy meter are constantly improved.the traditional manual prediction method has not been able to meet the actual needs of the project.There is a high failure rate in the field and the components that can not find the data in the manual,and the process is cumbersome,which makes it difficult to predict the work.In view of the difference between the reliability prediction manual and the field use,the reliability prediction method combined with the field data is proposed.Different prediction methods are applied according to the different failure rate levels of the components,and the corresponding reliability prediction model is established.Conventional components are estimated by the traditional IEC62059/61709 manual.And the key components with high failure rate are used to evaluate the reliability through the failure data.The use of components counting method is expected to simplify the prediction process for the high reliability and large number of components,so as to simplify the prediction process and improve the application.Through the collection,processing and analysis of the field data of a large number of intelligent electric energy meters.we find common failure modes,cause of failure and key components that affect the reliability level of the whole machine.Based on the probability estimation method,the fault interval time distribution model of key components is fitted,parameter estimation and hypothesis test,and the field work failure rate is obtained.Finally,the reliability prediction is carried out on the CHINT's DTZY666 as an example.The prediction result is compared with the real life of the field data evaluation and the GJB/Z299 C manual prediction result,which verifies the applicability of the research method in this paper.