基于综合健康指数的设备状态评估
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摘要
将健康指数作为表征设备整体健康状态优劣的指标,构建了设备健康状态的综合评估模型。在利用设备多个特征参数变化来反映设备运行状态的基础上,参照电力设备健康状况老化公式,提出了一个变量健康因子对设备运行状态健康指数进行修正。为综合考虑设备特征参数的重要程度,结合序关系法和熵权法改进了特征参数权重值的计算方式,使得设备健康状态综合评估体系的建立更加合理。最后,建立一种基于时间序列分析的非线性关系模型来拟合设备综合健康指数的变化趋势,评估未来健康状态并预测维护时间节点。利用该评估模型对某制氧厂的空压机进行了实例分析,结果表明该模型具有一定的有效性与合理性。
The health index is used to indicate the overall health status of the equipment, based on which a comprehensive evaluation model is constructed. A variable health factor is proposed to revise the health index of the equipment according to the aging formula of the power equipment health condition and multiple characteristic parameters of the equipment that reflect the operating state of the equipment. In order to comprehensively consider the importance of equipment characteristic parameters, the combination of the order relation method and the entropy weight method is utilized for the calculation method of the weight value of the feature parameter, which leads to more reasonable establishment of the comprehensive evaluation system of the equipment health condition. Finally, a nonlinear relation model based on time series analysis is developed to fit the trend comprehensive health index of the equipment, evaluate the future health status and predict the maintenance time node. This model is used to analyze the air compressor of an oxygen plant, and the results show that the model is effective and reasonable.
The health index is used to indicate the overall health status of the equipment, based on which a comprehensive evaluation model is constructed. A variable health factor is proposed to revise the health index of the equipment according to the aging formula of the power equipment health condition and multiple characteristic parameters of the equipment that reflect the operating state of the equipment. In order to comprehensively consider the importance of equipment characteristic parameters, the combination of the order relation method and the entropy weight method is utilized for the calculation method of the weight value of the feature parameter, which leads to more reasonable establishment of the comprehensive evaluation system of the equipment health condition. Finally, a nonlinear relation model based on time series analysis is developed to fit the trend comprehensive health index of the equipment, evaluate the future health status and predict the maintenance time node. This model is used to analyze the air compressor of an oxygen plant, and the results show that the model is effective and reasonable.
引文
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[2]苗红霞,萧旋旋,江冰.基于信息融合的预装式变电站健康状态评估[J].电力系统保护与控制,2017,45(14):85-91.MIAO Hongxia,XIAO Xuanxuan,JIANG Bing.State evaluation of prefabricated substation based on information fusion[J].Power System Protection and Control,2017,45(14):85-91.
[3]史常凯,宁昕,孙智涛,等.基于设备实时健康指数的配电网风险量化评估[J].高电压技术,2018,44(2):534-540.SHI Changkai,NING Xin,SUN Zhitao,et al.Quantitative risk assessment of distribution network based on real-time health index of equipment[J].High Voltage Engineering,2018,44(2):534-540.
[4]周莉梅,马钊,盛万兴.现代配电网健康指数理论最新研究进展[J].供用电,2016,33(1):3-7.ZHOU Limei,MA Zhao,SHENG Wanxing.Recent development of health index theory for modern distribution network[J].Distribution&Utilization,2016,33(1):3-7.
[5]国连玉,李可军,梁永亮,等.基于灰色模糊综合评判的高压断路器状态评估[J].电力自动化设备,2014,34(11):161-167.GUO Lianyu,LI Kejun,LIANG Yongliang,et al.HVcircuit breaker state assessment based on gray-fuzzy comprehensive evaluation[J].Electric Power Automation Equipment,2014,34(11):161-167.
[6]李丹.考虑退化隐式马尔可夫过程的设备状态诊断研究[D].重庆:重庆大学,2016.LI Dan.Research on machinery diagnosis based on deteriorating hidden Markov Process[D].Chongqing:Chongqing University,2016.
[7]张友强,寇凌峰,盛万兴,等.配电变压器运行状态评估的大数据分析方法[J].电网技术,2016,40(3):768-773.ZHANG Youqiang,KOU Lingfeng,SHENG Wanxing,et al.Big data analytical method for operating state assessment of distribution transformer[J].Power System Technology,2016,40(3):768-773.
[8]万凌云,王主丁,庞祥璐,等.中压配电网可靠性评估参数收集及其规划应用[J].供用电,2017,34(6):38-43.WAN Lingyun,WANG Zhuding,PANG Xianglu,et al.Parameter collection and planning application of medium voltage distribution system reliability assessment[J].Distribution&Utilization,2017,34(6):38-43.
[9]周名煜,谢宁,王承民.基于灵敏度和灰色关联度的配电网运行方式变权重评估方法[J].电力系统保护与控制,2017,45(13):130-137.ZHOU Mingyu,XIE Ning,WANG Chengmin.Variable weight evaluation method of distribution network operation mode based on sensitivity and grey correlation[J].Power System Protection and Control,2017,45(13):130-137.
[10]郭亚军.综合评价理论、方法及应用[M].北京:科学出版社,2007.
[11]翟章良,周力行.基于状态量权重的变压器状态评价系统研制[J].智慧电力,2018,46(9):88-94.ZHAI Zhangliang,ZHOU Lixing.Development of transformer state evaluation system based on state quantity weight[J].Smart Power,2018,46(9):88-94.
[12]马纪,刘希喆.基于序关系-熵权法的低压配网台区健康状态评估[J].电力系统保护与控制,2017,45(6):87-93.MA Ji,LIU Xizhe.Evaluation of health status of lowvoltage distribution network based on order relationentropy weight method[J].Power System Protection and Control,2017,45(6):87-93.
[13]田成来,田旻双,熊亚骁,等.基于熵权法的农村低压台区典型问题评估研究[J].供用电,2018,35(7):54-58.TIAN Chenglai,TIAN Minshuang,XIONG Yaxiao,et al.Research on assessment of typical problems in rural distribution transformers based on entropy weight method[J].Distribution&Utilization,2018,35(7):54-58.
[14]周正,雷玲,吴汉彬,等.基于多指标综合法的核心骨干网架生存性评估研究[J].智慧电力,2018,46(6):1-6,33.ZHOU Zheng,LEI Ling,WU Hanbin,et al.Study on survivability evaluation of core backbone network based on multiple indexes synthesis method[J].Smart Power,2018,46(6):1-6,33.
[15]卫泽晨,赵凤展,王佳惠,等.网格化中低压智能配电网评价指标体系与方法[J].电网技术,2016,40(1):249-255.WEI Zechen,ZHAO Fengzhan,WANG Jiahui,et al.Gridding evaluation index system and method of MV and LV intelligent distribution network[J].Power System Technology,2016,40(1):249-255.
[16]KHODAPARAST J,KHEDERZADEH M.Least square and Kalman based methods for dynamic phasor estimation:a review[J].Protection and Control of Modern Power Systems,2017,2(2):1-18.DOI:10.1186/s41601-016-0032-y.
[17]张彦如,耿梦晓.基于健康指数的设备运行状态评价与预测[J].合肥工业大学学报(自然科学版),2015,38(10):1318-1323.ZHANG Yanru,GENG Mengxiao.Equipment comprehensive health status evaluation and prediction based on health index[J].Journal of Hefei University of Technology(Natural Science Edition),2015,38(10):1318-1323.
[18]GOPAKUMAR P,MALLIKAJUNA B,REDDY M J B,et al.Remote monitoring system for real time detection and classification of transmission line faults in a power grid using PMU measurements[J].Protection and Control of Modern Power Systems,2018,3(3):159-168.DOI:10.1186/s41601-018-0089-x.
[19]李辉,胡姚刚,唐显虎,等.并网风电机组在线运行状态评估方法[J].中国电机工程学报,2010,30(33):103-109.LI Hui,HU Yaogang,TANG Xianhu,et al.Method for on-line operating conditions assessment for a grid-connected wind turbine generator system[J].Proceedings of the CSEE,2010,30(33):103-109.
[20]蔡红飞.电力变压器剩余技术寿命的综合评估[D].郑州:郑州大学,2012.CAI Hongfei.Comprehensive assessment of the power transformer remaining life[D].Zhengzhou:Zhengzhou University,2012.
[21]LI E W,SONG B.Transformer health status evaluation model based on multi-feature factors[C]//International Conference on Power System Technology,October 20-22,2014,Chengdu,China:1417-1422.
[22]廖雯竹.基于设备衰退机制的预知性维护策略及生产排程集成研究[D].上海:上海交通大学,2011.LIAO Wenzhu.Research of predictive maintenance policy and integrated production scheduling model based on machine degradation[D].Shanghai:Shanghai Jiaotong University,2011.