基于自适应加权系数的智能表计使用寿命预测方法
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通讯作者:

王军(1973),男,工程硕士,工程师,主要从事智能用电技术研究;Email:29986595@qq.com

中图分类号:

TM93

基金项目:

许继集团科技项目(2017G37)


An intelligent meter life prediction method based on adaptive weighting coefficient
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    摘要:

    传统的基于威布尔分布拟合的方法,没有考虑智能表计内部不同的电路模块受不同的外部应力影响的差异性,忽略不同应力影响因子对智能表计寿命的影响。因此,该文提出一种基于自适应加权系数的智能表计使用寿命预测方法,实现基于表计整机预测算法的改进。该方法从产品故障历史数据着手,建立应力与历史原始失效率之间的关系,分别获取基于历史原始失效率的应力调整系数K和加权系数R,并利用该2个系数调整预测失效率以提高预测准确性。算例表明,所提方法可减少批次电能表剩余寿命误判率,提高预测准确度。工程应用中,所提方法可提供参考信息便于提前制定电能表采购计划进行批次轮换,避免出现大规模的电能表故障。

    Abstract:

    The traditional method is based on Weibull distribution fitting, which does not consider the difference of different circuit modules in the smart meter affected by different external stress, and lacks the influence of different stress factors on the life of the smart meter. So, an intelligent meter life prediction method based on adaptive weighting coefficient is proposed in the paper, which realizes an improvement of the whole meter prediction algorithm . This method starts from the historical data of product failure, finds out the relationship between the stress and the historical original failure rate, and obtains the stress adjustment coefficient K and the weighting coefficient R based on the historical original failure rate respectively. The stress adjustment coefficient K and the weighting coefficient R is utilized to modify the obtained predicted failure rate and achieve higher accuracy. The case study shows that this method can reduce the miscalculation rate of remaining life of batch electric energy meters, In the actual application process, the proposed method can provide the useful information for purchasing electric energy meters in advance for batch rotation, and avoid largescale failure of electric energy meters.

    参考文献
    [1] 杜孟珂,任燕峰,刘金涛,等.电力市场环境下发输电组合系统可靠性评估[J].电力科学与技术学报,2019,34(4):2128.DU Mengke,REN Yanfeng,LIU Jintao,et al.Reliability evaluation of generation and transmission composite in power market environment [J].Journal of Power Science and Technology,2019,34(4):2128.
    [2] 王艳荣.基于可靠性分析的剩余寿命评估方法研究[D].西安:西安电子科技大学,2015.
    [3] 蔚德申,王景芹,王丽,等.基于灰色理论的低压断路器寿命预测模型的研究[J].电力科学与技术学报,2019,34(4):3541.WEI Deshen,WANG Jingqin,WANG Li,et al.Research on life prediction model of lowvoltage circuit breaker based on grey theory [J].Journal of electric power science and technology,2019,34(4):3541.
    [4] 徐晴,沈秋英,郭兴昕,等.基于多元线性回归分析的计量资产寿命预测与评价方法研究[J].电测与仪表,2014,51(11):1317.XU Qing,SHEN Qiuying,GUO Xingxin,et al.Study on the lifetime prediction and evaluation of metering assets based on the multivariate linear regression analysis[J].Electrical Measurement and Instrument,2014,51(11):1317.
    [5] 刘勇,荣雪琴,卜树坡.基于Weibull分布的智能电能表寿命预计[J].电测与仪表,2019,56(3):148152.LIU Yong,RONG Xueqin,BU Shupo.Life expectancy of smart meter based on Weibull distribution[J].Electric Measurement and Instrument,2019,56(3):156160.
    [6] 孙国玺,张清华,文成林,等.基于随机退化数据建模的设备剩余寿命自适应预测方法[J].电子学报,2015,43(6):11191126.SUN Guoxi,ZHNG Qinghua,WEN Chenglin,et al.A stochastic degradation modeling based adaptive prognostic approach for equipment[J].Journal of Electronics,2015,43(6):11191126.
    [7] 韩志远,王广健,张晓静,等.基于故障模型的大型变压器故障综合诊断方法与应用[J].华电技术,2018,40(10):2226+77.HAN Zhiyuan,WANG Guangjian,ZHANG Xiaojing,et al.Application of large transformer comprehensive fault diagnosis based on fault model[J].Huadian Technology,2018,40(10):2226+77.
    [8] 彭宝华,周经伦,孙权,等.基于退化与寿命数据融合的产品剩余寿命预测[J].系统工程与电子技术,2011,33(5):10731078.PENG Baohua,ZHOU Jinglun,SUN Quan,et al.Residual lifetime prediction of products based on fusion of degradation data and lifetime data [J].Systems Engineering and Electronics,2011,33(5):10731078.
    [9] 章江铭,姚力,沈建良,等.基于现场可靠性数据和组合应力寿命模型的电能表寿命预判[J].浙江电力,2019,38(7):8185.ZHANG Jiangming,YAO Li,SHEN Jianliang,et al.Life prediction of electric energy meter based on field reliability data and combined stress life model [J].Zhejiang Electric Power,2019,38(7):8185.
    [10] 李莉,熊炜,赵艺杰,等.基于模糊遗传算法的输电线路故障混合威布尔分布模型[J].电力科学与技术学报,2018,33(1):6066.LI Li,XIONG Wei,ZHAO Yijie,et al.Mixed Weibull distribution model of transmission line fault based on fuzzy genetic algorithm [J].Journal of Electric Power Science and Technology,2018,33(1):6066.
    [11] 包振华,张姝.基于指数威布尔分布的组合统计模型[J].统计与决策,2018,34(1):1013.BAO Zhenhua,ZHANG Shu.Combined statistical model based on exponential Weibull distribution [J].Statistics & Decision,2018,34(1):1013.
    [12] 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):2832.XU Jintao,FENG Xingle,ZHAO Feng.Study on intelligent electric energy meter reliability prediction[J].Smart Power,2018,46(4):2832.
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王 军,李 飞,华 隽,等.基于自适应加权系数的智能表计使用寿命预测方法[J].电力科学与技术学报,2020,35(3):99-106.
WANG Jun, LI Fei, HUA Jun, et al. An intelligent meter life prediction method based on adaptive weighting coefficient[J]. Journal of Electric Power Science and Technology,2020,35(3):99-106.

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  • 在线发布日期: 2020-09-14
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