Comparative Study on Reliability Prediction Standard for Intelligent Meter
XIE Xin1, WANG Li-min2, ZHANG Hong-yu2, CHEN Feng-kai3, ZHOU Shao-yuan2, HONG Tao1
1.China Jiliang University, Hangzhou, Zhejiang 310018, China
2.Zhejiang Institute of Metrology, Hangzhou, Zhejiang 310016, China
3.Huali Technology Co. LTD,Hangzhou, Zhejiang 311100, China
Abstract：As the main device for collecting electricity, the high reliability and long life of smart meter are particularly important.Reliability prediction is an effective means to quantitatively evaluate the reliability of smart meters and also provides a reference for the design improvement of smart meters.The key to carry out the prediction is the selection of reliability standard. The principle, process, advantages and disadvantages of the commonly used prediction standard are introduced.Three standards were selected to predict the reliability of a single-phase fee-controlled watt-hour meter. Through comprehensive analysis and comparison, the failure rate of GJB/Z299C was nearly twice higher than that of other standards.
1 邱忠梅. 基于LabVIEW平台的新型电能表可靠性寿命预估软件设计与应用［D］. 南京:南京师范大学, 2014.
2 袁金灿. 智能电能表可靠性预计技术的研究及软件开发［D］. 北京:华北电力大学, 2012.
3 郎干勇, 李香, 徐振伟. 智能电表可靠性预计方法研究［J］. 电子制作, 2017, (1): 97-98. LangG Y, liX, XuZ W. Research on Reliability Prediction Methods of Smart Meters［J］. Electronic production, 2017(01): 97-98.
4 纪静. 基于SR-332的电子设备失效率灵敏度分析［J］. 产业与科技论坛, 2018, 17(1): 49-51. JiJ. Sensitivity Analysis of Failure Rate of Electronic Equipment Based on SR-332［J］. Industry and Technology Forum, 2018, 17(1): 49-51.
5 郭青龙. 电子式电能表可靠性预计方法研究及应用［D］. 南京:南京师范大学, 2013.
6 Meghan Elizabeth Kallman, FrickelScott. Nested logics and smart meter adoption: Institutional processes and organizational change in the diffusion of smart meters in the United States［J］. Energy Research & Social Science, 2019, 57.
7 朱自伟. 智能电能表可靠性研究与分析［D］. 西安:长安大学, 2019.
8 朱志勇. 嵌入式系统的可靠性方法和流程探讨［J］. 新型工业化, 2018, 8(7): 73-77. ZhuZ Y. Discussion on Reliability Method and Process of Embedded System［J］. New industrialization, 2018, 8(7): 73-77.
9 徐锦涛, 冯兴乐, 赵峰. 智能电表可靠性预计技术研究［J］. 智慧电力, 2018, 46(4): 28-32. Xu J T, Feng X L, Zhao F, Research on Reliability Prediction Technology of Smart Meters［J］. Smart Power, 2018, 46(4): 28-32.
10 韩志强, 周碧红, 佘寻峰. 我国电能表行业发展趋势预估［J］. 上海计量测试, 2018, 45(S1): 11-14. HanZ Q, ZhouB H, YuX F. Development Trend Forecast of China’s Electric Energy Meter Industry［J］. Shanghai Metrology Test, 2018, 45(S1): 11-14.
11 杨洪旗, 刘少卿, 黄进永. 智能电能表的可靠性预计方法研究［J］. 电子产品可靠性与环境试验, 2016, 34(3): 65-71. YangH Q, LiuS Q, HuangJ Y. Research onReliability Prediction Methods of Smart Energy Meters［J］. Electronic product reliability and environmental test, 2016, 34(3): 65-71.
12 李海霞. 产品可靠性预计方法应用［J］. 科学技术创新, 2019, (8): 43-44. LiH X. Application of Product Reliability Prediction Methods［J］. Scientific and technological innovation, 2019, (8): 43-44.
13 YangZ, ChenY X, LiY F,et al. Smart electricity meter reliability prediction based on accelerated degradation testing and modeling［J］. International Journal of Electrical Power and Energy Systems, 2014, 56:209-219.
2019, Vol. 40 
