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文章摘要
基于多应力影响威布尔分布模型的电能表寿命预判及验证
Life Prediction and Verification of Energy Meter Based on Multi-stress Influence Weibull Distribution Model
Received:April 26, 2020  Revised:April 26, 2020
DOI:10.19753/j.issn1001-1390.2021.05.029
中文关键词: 多应力模型  威布尔分布  电能表  失效率  寿命预判
英文关键词: multi-stress  model, Weibull  distribution, electric  energy meter, failure  rate, life  prediction
基金项目:国网浙江省电力有限公司科技项目
Author NameAffiliationE-mail
Zhang Jiangming* State Grid Zhejiang Marketing Service Center Metrology Center zjming@zju.edu.cn 
Yao Li State Grid Zhejiang Marketing Service Center Metrology Center yl0571@139.com 
Xu Tao State Grid Zhejiang Marketing Service Center Metrology Center xutao@zj.sgcc.com.cn 
Lu Chunguang State Grid Zhejiang Marketing Service Center Metrology Center zjdl_lcg@163.com 
Liu Wei State Grid Zhejiang Marketing Service Center Metrology Center lwei0714@163.com 
Zhou You State Grid Zhejiang Marketing Service Center Metrology Center 4656684@qq.com 
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中文摘要:
      通常,不同故障模式的失效分布特征不同,诱发其失效的应力类型和退化过程也各有差异。本文提出了一种基于多应力影响威布尔分布模型的电能表寿命预判方法,应力类型主要包括环境应力及电应力。利用电能表实测历史故障数据建立各故障模式失效率威布尔分布模型,进而针对主要影响应力类型,建立影响应力与各故障模式失效率之间的模型,并计算影响系数,通过调整各故障模式的预测阶段失效率,获得整体电能表的近期寿命。经现场实际电能表故障数据验证,表明该方法可有效预判电能表寿命,为电能表状态更换、故障预警提供技术支撑。
英文摘要:
      Generally, the failure distribution characteristics of different failure modes are different, and the stress types and degradation processes that induce their failures also differ. This paper proposes a method for predicting the life of electric energy meter based on Multi-stress influence Weibull distribution model. The stress types mainly include environmental stress and electrical stress. Using historical fault data of electric energy meter to establish Weibull distribution model of failure rate of each failure mode, and then for the main types of influence stress, establish a model between the influence stress and failure rate of each failure mode, and calculate the influence coefficient. The short-term life of the overall energy meter is obtained by adjusting the failure rate at the predicted stage of each failure mode. By verifying the field actual energy meter fault data, showing that the method can effectively predict the life of the energy meter, and provide technical support for energy meter status replacement, and fault early warning.
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