Reliability Assessment of Relay Protection Devices Based on Weibull Distribution and Iterative Maximum Likelihood Estimation

doi:10.16628/j.cnki.2095-8188.2022.11.011

Abstract

Abstract:

Aiming at the reliability assessment of relay protection devices with small samples and censored data,an iterative maximum likelihood estimation method based on two-parameter Weibull distribution is proposed.The field operation data of the protective relays is collected,the two-parameter Weibull distribution is used for reliability modeling,and the iterative maximum likelihood estimation method is used to estimate the parameters of the Weibull distribution model.Finally,the reliability function,cumulative failure distribution function,failure density function and failure rate function of relay protection device life distribution are obtained.The simulation results show that the reliability indexes of the relay protection device calculated by the proposed method are basically consistent with the actual engineering application experience values,which can proved the assessment method has high accuracy and practicability.

Key words: relay protection device, reliability assessment, Weibull distribution, iterative maximum likelihood estimation

CLC Number:

TM774

WANG Jingjing, SUN Zhixuan. Reliability Assessment of Relay Protection Devices Based on Weibull Distribution and Iterative Maximum Likelihood Estimation[J]. LOW VOLTAGE APPARATUS, 2022, 0(11): 63-68.

Figures/Tables 8

References 25

[1]	王嘉琦, 徐岩, 彭雅楠, 等. 基于灰色-三参数威布尔分布模型的继电保护装置可靠性参数估计[J]. 电网技术, 2019, 43(4):1354-1360.
[2]	王佳炜, 王召斌, 黄周霖. 继电器寿命预测方法综述[J]. 电器与能效管理技术, 2018(4):1-5,12.
[3]	叶远波, 刘宏君, 张兆云, 等. 基于广域信息的继电保护实时评价研究[J]. 电力系统保护与控制, 2021, 49(13):150-157.
[4]	戴志辉, 李芷筠, 焦彦军, 等. 基于BP神经网络的小样本失效数据下继电保护可靠性评估[J]. 电力自动化设备, 2014, 34(11):129-134.
[5]	李维燕, 王召斌, 王占, 等. 电磁继电器贮存失效分析及小子样零失效可靠性分析综述[J]. 电器与能效管理技术, 2019(15):65-70.
[6]	薛安成, 罗麟, 景琦, 等. 基于Markov模型的高压输电线继电保护装置风险评估[J]. 电网技术, 2014, 38(7):1995-2000.
[7]	叶远波, 刘宏君, 黄太贵, 等. 变电站继电保护设备状态检修可靠性分析方法研究[J]. 电力系统保护与控制, 2021, 49(10):170-177.
[8]	戴志辉, 王增平. 继电保护可靠性研究综述[J]. 电力系统保护与控制, 2010, 38(15):160-167.
[9]	DAI Z, WANG Z. Protection Dynamic Reliability Analysis System Based on 3RF Technique[J]. IEEE Transactions on Power Systems, 2011, 26(3):1137-1144. doi: 10.1109/TPWRS.2010.2100413
[10]	李浩, 林湘宁, 喻锟, 等. 基于连续时间马尔可夫链的继电保护装置动作行为预测模型[J]. 中国电机工程学报, 2018, 38(增刊1):121-128.
[11]	王玉财, 吕飞鹏, 何奎. 满足可靠性要求的继电保护装置预防检修模型[J]. 电力系统保护与控制, 2016, 44(10):49-53.
[12]	WANG J, YIN H. Failure rate prediction model of substation equipment based on Weibull distribution and time series analysis[J]. IEEE Access, 2019, 7:85298-85309. doi: 10.1109/ACCESS.2019.2926159
[13]	ZHOU P, ZHOU M, XIE Y, et al. Research of risk assessment reliability of relay protection based on three-parameter Weibull distribution[J]. Industry and Mine Automation, 2016(8):60-65.
[14]	徐岩, 白静, 戴志辉. 一种基于威布尔分布的继电保护装置可靠性分析的新方法[J]. 华北电力大学学报:自然科学版, 2012, 39(4):15-19.
[15]	LI T, GRIFFITHS W D, CHEN J. Weibull modulus estimated by the non-linear least squares method:A solution to deviation occurring in traditional Weibull estimation[J]. Metallurgical and Materials Transactions A, 2017, 48(11):5516-5528. doi: 10.1007/s11661-017-4294-4
[16]	陈勇, 李胜男, 张丽, 等. 基于改进平均秩次法的保护装置可靠性评估[J]. 电力系统保护与控制, 2020, 48(2):165-171.
[17]	DAVIES I J. Confidence limits for Weibull parameters estimated using linear least squares analysis[J]. Journal of the European Ceramic Society, 2017, 37(15):5057-5064. doi: 10.1016/j.jeurceramsoc.2017.05.051
[18]	DONG L, LU Z, ZHOU J. Nonlinear least squares estimation for parameters of mixed Weibull distributions by using particle swarm optimization.[J]. Journal Of Nanjing University Of Aeronautics & Astronautics, 2019, 7(5):139-146.
[19]	JIA X, XI G G, NADARAJAH S. Correction factor for unbiased estimation of Weibull modulus by the linear least squares method[J]. Metallurgical and Materials Transactions,A.Physical Metallurgy and Materials Science, 2019(6):2991-3001.
[20]	陈康宁, 王召斌, 李朕, 等. 继电器贮存可靠性评估与寿命试验方法综述[J]. 电器与能效管理技术, 2020(12):1-6.
[21]	王晓剑, 徐喆, 徐俊元, 等. 一种电磁继电器寿命评估的新方法[J]. 电器与能效管理技术, 2018(4):66-71.
[22]	金少华, 陆俭国, 李志刚, 等. 一种关于电工产品平均寿命的评估方法[J]. 低压电器, 2005(11):3-5.
[23]	高僮, 周莽, 孙树学, 等. 基于改进果蝇优化算法的电力设备故障率预测[J]. 电器与能效管理技术, 2017(21):28-34.
[24]	朱旭晴, 梁慧敏, 张家赫, 等. 电磁继电器触簧系统关键装配参数退化建模与可靠性评估[J]. 电器与能效管理技术, 2020(4):1-6.
[25]	张赛鹏, 冯世涛, 赵春明, 等. 基于威布尔分布和蒙特卡洛法的高压隔离开关可靠性研究[J]. 高压电器, 2021, 57(6):86-93.

退出序号	t	退出序号	t	退出序号	t
1	3.052 6	11	13.173 1	21	21.375 8
2	4.797 7	12	13.941 6	22	21.375 8+
3	6.099 5	13	14.708 9	23	21.375 8+
4	7.205 0	14	15.479 5	24	21.375 8+
5	8.196 4	15	16.257 7	25	21.375 8+
6	9.113 5	16	17.048 1	26	21.375 8+
7	9.979 3	17	17.855 5	27	21.375 8+
8	10.808 8	18	18.685 2	28	21.375 8+
9	11.612 6	19	19.543 3	29	21.375 8+
10	12.398 5	20	20.437 2	30	21.375 8+

退出序号	t	退出序号	t	退出序号	t
1	3.052 6	11	12.398 5	21	19.543 3
2	4.797 7	12	13.173 1	22	20.437 2
3	6.099 5	13	13.941 6	23	21.375 8
4	7.205 0	14	14.708 9	24	22.370 7
5	7.205 0+	15	15.479 5	25	23.436 9
6	8.196 4	16	16.257 7	26	23.436 9+
7	9.113 5	17	16.257 7+	27	23.436 9+
8	9.979 3	18	17.855 5	28	23.436 9+
9	10.808 8	19	18.685 2	29	23.436 9+
10	11.612 6	20	18.685 2+	30	23.436 9+

数据	参数估计结果		误差
数据	β	η	Δβ	Δη
表1	2.147 0	19.661 1	0.147 0	-0.338 9
表2	2.195 8	19.337 5	0.195 8	-0.662 5

参数估计方法	参数估计结果		误差
参数估计方法	β	η	Δβ	Δη
平均秩次法	1.032 6	28.471 6	-0.967 4	8.471 6
迭代极大似	1.681 5	19.992 5	-0.318 5	-0.007 5
然估计法	1.681 5	19.992 5	-0.318 5	-0.007 5

故障次序	运行时间/h	退出模式	备注
1	25 560	故障退出	—
2	31 848	故障退出	—
3	36 648	故障退出	—
4	43 104	故障退出	—
5	46 872	故障退出	—
6	49 656	故障退出	—
7	51 864	故障退出	—
8	55 608	故障退出	—
9	60 624	故障退出	—
10~30	70 128	正常退出	共21个