基于信息融合的矿用电缆状态检修方法
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摘要
针对矿用电缆单一参数在线监测方法准确度低、多参数监测方法未根据专家经验进行权重分配并进行信息融合等问题,提出了基于信息融合的矿用电缆状态检修方法。通过多个分布式传感器实时监测电缆运行时的表面温度、护套接地电流、局部放电量,根据模糊理论对多源信息进行初步融合诊断,将融合结果作为D-S证据理论的识别框架和证据体;根据专家经验确定各运行参数的权重,结合初步诊断结果,确定证据理论的合理信度函数分配值,根据信度最大准则判断被测电缆的工作状态。实例分析结果验证了该方法能有效融合处理矿用电缆的多源信息,提高故障诊断的准确性。
In view of problems of low accuracy of online monitoring method of mine cable using single parameter,and that monitoring method using multi-parameter does not carry out weight distribution and information fusion based on expert experience,a mine cable state maintenance method based on information fusion was proposed.Distributed sensors are used to real-timely monitor surface temperature,grounding current of cable sheath and partial discharge during cable operation.Preliminary fusion diagnosis for multi-source information is carried out according to fuzzy theory.The fusion results are used as identification framework and evidence body of D-S evidence theory.The weight of each operating parameter is determined based on expert experience,and reasonable reliability function allocation value of the evidence theory is determined combined with the preliminary diagnosis results,then the working state of the tested cable is judged according to the maximum reliability criterion.The example analysis result proves that the method can effectively integrate multi-source information of mine cable and improve accuracy of fault diagnosis.
In view of problems of low accuracy of online monitoring method of mine cable using single parameter,and that monitoring method using multi-parameter does not carry out weight distribution and information fusion based on expert experience,a mine cable state maintenance method based on information fusion was proposed.Distributed sensors are used to real-timely monitor surface temperature,grounding current of cable sheath and partial discharge during cable operation.Preliminary fusion diagnosis for multi-source information is carried out according to fuzzy theory.The fusion results are used as identification framework and evidence body of D-S evidence theory.The weight of each operating parameter is determined based on expert experience,and reasonable reliability function allocation value of the evidence theory is determined combined with the preliminary diagnosis results,then the working state of the tested cable is judged according to the maximum reliability criterion.The example analysis result proves that the method can effectively integrate multi-source information of mine cable and improve accuracy of fault diagnosis.
引文
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[13]龚瑞昆,马亮,赵延军,等.基于量子神经网络信息融合的变压器故障诊断[J].电力系统保护与控制,2011,39(23):79-84.GONG Ruikun,MA Liang,ZHAO Yanjun,et al.Fault diagnosis for power transformer based on quantum neural network information fusion[J].Power System Protection and Control,2011,39(23):79-84.
[14]夏向阳,张琦,李明德,等.证据理论与模糊理论集成的XLPE电缆绝缘状态评估研究[J].电力系统保护与控制,2014,42(20):13-18.XIA Xiangyang,ZHANG Qi,LI Mingde,et al.Research on insulation assessment of XLPE cables based on evidence and fuzzy theory integrated method[J].Power System Protection and Control,2014,42(20):13-18.
[15]敖蕾蕾,王慧芳,张弛,等.基于D-S证据理论的输变电设备状态检修多目标群决策[J].电网技术,2014,38(6):1627-1633.AO Leilei,WANG Huifang,ZHANG Chi,et al.Multi-objective and group decision-making research based on D-S evidence theory in condition-based maintenance for transmission and transformation equipment[J].Power System Technology,2014,38(6):1627-1633.
[16]符杨,江玉蓉,崔椿洪,等.基于模糊数学和概率论的变压器故障诊断[J].高电压技术,2008,34(5):1040-1044.FU Yang,JIANG Yurong,CUI Chunhong,et al.Fuzzy theory and probability reasoning applied for identifying power transformer fault[J].High Voltage Engineering,2008,34(5):1040-1044.
[17]张文元,赵卫国,晋涛,等.多神经网络与证据理论的变压器故障诊断方法[J].高压电器,2018,54(8):207-211.ZHANG Wenyuan,ZHAO Weiguo,JIN Tao,et al.Fault diagnosis method of transformer based on multi-neural network and evidence theory[J].High Voltage Apparatus,2018,54(8):207-211.
[18]廖瑞金,孟繁津,周年荣,等.基于集对分析和证据理论融合的变压器内绝缘状态评估方法[J].高电压技术,2014,40(2):474-481.LIAO Ruijin,MENG Fanjin,ZHOU Nianrong,et al.Assessment strategy for inner insulation condition of power transformer based on set-pair analysis and evidential reasoning decision-making[J].High Voltage Engineering,2014,40(2):474-481.
[2]朱德恒,严璋,谈克雄,等.电气设备状态监测与故障诊断技术[M].北京:中国电力出版社,2009.
[3]郭创新,高振兴,张金江,等.基于物联网技术的输变电设备状态监测与检修资产管理[J].电力科学与技术学报,2010,25(4):36-41.GUO Chuangxin,GAO Zhenxing,ZHANG Jinjiang,et al.IOT based transmission and transformation equipment monitoring and maintenance assets management[J].Journal of Electric Power Science and Technology,2010,25(4):36-41.
[4]王慧芳,杨荷娟,何奔腾,等.输变电设备状态故障率模型改进分析[J].电力系统自动化,2011,35(16):27-31.WANG Huifang,YANG Hejuan,HE Benteng,et al.Improvement of state failure rate model for power transmission and transforming equipment[J].Automation of Electric Power Systems,2011,35(16):27-31.
[5]张怀宇,朱松林,张扬,等.输变电设备状态检修技术体系研究与实施[J].电网技术,2009,33(13):70-73.ZHANG Huaiyu,ZHU Songlin,ZHANG Yang,et al.Research and implementation of condition-based maintenance technology system for power transmission and distribution equipments[J].Power System Technology,2009,33(13):70-73.
[6]邱伟豪,阳林,郝艳捧,等.XLPE电缆内置分布式光纤的温度监测试验[J].广东电力,2018,31(8):175-181.QIU Weihao,YANG Lin,HAO Yanpeng,et al.Temperature monitoring experiment for XLPE builtin distributed optical fiber[J].Guangdong Electric Power,2018,31(8):175-181.
[7]阳林,史尊伟,黄吉超,等.基于BOTDR分布式光纤传感技术的架空线路温度检测现场试验研究[J].高电压技术,2015,41(3):925-930.YANG Lin,SHI Zunwei,HUANG Jichao,et al.Field test research on temperature detection of overhead transmission line based on BOTDR distributed fiber sensing technology[J].High Voltage Engineering,2015,41(3):925-930.
[8]张潇,王彦文,赵永梅,等.矿用高压电缆绝缘在线监测方法[J].工矿自动化,2017,43(4):60-63.ZHANG Xiao,WANG Yanwen,ZHAO Yongmei,et al.Online monitoring method of mine-used high voltage cable insulation[J].Industry and Mine Automation,2017,43(4):60-63.
[9]杨静,朱晓岭,董翔,等.基于护层电流的高压电缆故障在线监测和诊断[J].高电压技术,2016,42(11):3616-3625.YANG Jing,ZHU Xiaoling,DONG Xiang,et al.On-line monitoring and diagnosis of HV cable faults based on sheath currents[J].High Voltage Engineering,2016,42(11):3616-3625.
[10]侯淞学,彭涛,王雪,等.井下高压电缆局部放电及其传播特性研究[J].煤炭技术,2018,37(3):203-205.HOU Songxue,PENG Tao,WANG Xue,et al.Study on partial discharge and propagation characteristics of underground high voltage cable[J].Coal Technology,2018,37(3):203-205.
[11]万志强,宋建成,雷志鹏,等.矿用干式变压器绝缘在线监测及故障诊断预警系统研制[J].工矿自动化,2013,39(10):1-5.WAN Zhiqiang,SONG Jiancheng,LEI Zhipeng,et al.Development of system of on-line monitoring,fault diagnosis and prewarning for insulation of mine-used dry-type transformer[J].Industry and Mine Automation,2013,39(10):1-5.
[12]MARZINOTTO M,MAZZANTI G.The feasibility of cable sheath fault detection by monitoring sheathto-ground currents at the ends of cross-bonding sections[J].IEEE Transactions on Industry Applications,2015,51(6):5376-5384.
[13]龚瑞昆,马亮,赵延军,等.基于量子神经网络信息融合的变压器故障诊断[J].电力系统保护与控制,2011,39(23):79-84.GONG Ruikun,MA Liang,ZHAO Yanjun,et al.Fault diagnosis for power transformer based on quantum neural network information fusion[J].Power System Protection and Control,2011,39(23):79-84.
[14]夏向阳,张琦,李明德,等.证据理论与模糊理论集成的XLPE电缆绝缘状态评估研究[J].电力系统保护与控制,2014,42(20):13-18.XIA Xiangyang,ZHANG Qi,LI Mingde,et al.Research on insulation assessment of XLPE cables based on evidence and fuzzy theory integrated method[J].Power System Protection and Control,2014,42(20):13-18.
[15]敖蕾蕾,王慧芳,张弛,等.基于D-S证据理论的输变电设备状态检修多目标群决策[J].电网技术,2014,38(6):1627-1633.AO Leilei,WANG Huifang,ZHANG Chi,et al.Multi-objective and group decision-making research based on D-S evidence theory in condition-based maintenance for transmission and transformation equipment[J].Power System Technology,2014,38(6):1627-1633.
[16]符杨,江玉蓉,崔椿洪,等.基于模糊数学和概率论的变压器故障诊断[J].高电压技术,2008,34(5):1040-1044.FU Yang,JIANG Yurong,CUI Chunhong,et al.Fuzzy theory and probability reasoning applied for identifying power transformer fault[J].High Voltage Engineering,2008,34(5):1040-1044.
[17]张文元,赵卫国,晋涛,等.多神经网络与证据理论的变压器故障诊断方法[J].高压电器,2018,54(8):207-211.ZHANG Wenyuan,ZHAO Weiguo,JIN Tao,et al.Fault diagnosis method of transformer based on multi-neural network and evidence theory[J].High Voltage Apparatus,2018,54(8):207-211.
[18]廖瑞金,孟繁津,周年荣,等.基于集对分析和证据理论融合的变压器内绝缘状态评估方法[J].高电压技术,2014,40(2):474-481.LIAO Ruijin,MENG Fanjin,ZHOU Nianrong,et al.Assessment strategy for inner insulation condition of power transformer based on set-pair analysis and evidential reasoning decision-making[J].High Voltage Engineering,2014,40(2):474-481.