基于HHT的航空直流串行电弧特征提取方法
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摘要
由于飞机内部布线空间有限、电弧故障存在发生时间地点随机以及特征不明显等问题,导致检测困难。本文基于航空270V高压直流(HVDC)系统开展直流串行电弧故障特征提取方法研究,采用希尔伯特黄变换(HHT)提取电弧电流交流分量的时域和频域特征量。选择HHT的固有模态函数IMF5瞬时幅值的峰峰值和标准差作为识别电弧故障的时域特征,与原始信号中提取的时域特征量对比,正常和电弧特征量的区分度更大;选择HHT的固有模态函数IMF1+IMF2、一定频带范围内的瞬时幅值计算得到的谐波功率和作为区分正常和电弧情况的频域特征量。与常用的快速傅里叶变换(FFT)方法相比,HHT三维时频谱能够反映信号的局部特征,HHT方法计算得到的正常和电弧特征量之间的区分度更大,电弧和正常特征量的比值最高可达346。基于HHT的电弧故障特征提取方法能够更好地区分正常和电弧情况,有助于提高电弧故障的检测率,降低虚警率,具有重要的工程应用价值。
Due to the limited space inside the aircraft,the arbitrariness of the arc fault in time and space,and the nonobviousness of characteristics,it is difficult to detect the DC arc fault occurred in aircrafts.To solve the problem,this paper studies the characteristics extraction method of DC arc fault based on the aircraft 270 VHigh VoHage Direct Current(HVDC)system.The Hilbert-Huang Transform(HHT)is used to extract the time domain and frequency domain characteristics of current's AC component.The peak-to-peak value and standard deviation of the instantaneous amplitude of the IMF5 of HHT are selected as the time domain characteristics of the arc fault.Compared with the time domain characteristics of the original signal,the discrimination between the normal and the arc characteristic is more significant.The sum of harmonic power in a certain range,calculated by the IMF1+IMF2 is selected as the characteristic of frequency domain.Compared with the traditional FFT method,the time-frequency spectrum of HHT method can reflect the partial characteristics of the signal.The difference between the normal and arc characteristics calculated by the HHT method is more significant,and the ratio of the arc fault and the normal characteristics can be up to 346.The HHT method can better distinguish between normal and arc fault states,and improve the rate of arc fault detection and reduce the rate of false alarm,showing high values for engineering application.
Due to the limited space inside the aircraft,the arbitrariness of the arc fault in time and space,and the nonobviousness of characteristics,it is difficult to detect the DC arc fault occurred in aircrafts.To solve the problem,this paper studies the characteristics extraction method of DC arc fault based on the aircraft 270 VHigh VoHage Direct Current(HVDC)system.The Hilbert-Huang Transform(HHT)is used to extract the time domain and frequency domain characteristics of current's AC component.The peak-to-peak value and standard deviation of the instantaneous amplitude of the IMF5 of HHT are selected as the time domain characteristics of the arc fault.Compared with the time domain characteristics of the original signal,the discrimination between the normal and the arc characteristic is more significant.The sum of harmonic power in a certain range,calculated by the IMF1+IMF2 is selected as the characteristic of frequency domain.Compared with the traditional FFT method,the time-frequency spectrum of HHT method can reflect the partial characteristics of the signal.The difference between the normal and arc characteristics calculated by the HHT method is more significant,and the ratio of the arc fault and the normal characteristics can be up to 346.The HHT method can better distinguish between normal and arc fault states,and improve the rate of arc fault detection and reduce the rate of false alarm,showing high values for engineering application.
引文
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[14]林方圆,苏建徽,赖纪东.光伏系统直流故障电弧识别方法研究[J].电工电能新技术,2015,34(12):7-13.LIN F Y,SU J H,LAI J D.Research on DC fault arc identification method for photovoltaic system[J].Advanced Technology of Electrical Engineering and Energy,2015,34(12):7-13(in Chinese).
[15] YAO X,HERRERA L,WANG J.A series DC arc faultdetection method and hardware implementation[C]∥2013Twenty-Eighth Annual IEEE Applied Power Electronics Conference and Exposition(APEC).Piscataway,NJ:IEEE Press,2013,2444-2449.
[16] JOHNSON J,KUSZMAUL S,BOWER W,et al.Using PV module and line frequency response data to create robust arc fault detectors[C]∥26th European Photovoltaic Solar Energy Conference and Exhibition, Eastleigh:COPE Press,2011:3745-3750.
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[18]李成业.基于HHT的二滩拱坝工作性态识别及其“拍振”机理研究[D].天津:天津大学,2010:25-29.LI C Y.Study on working state identification and beat vibration of ertan arch dam based on Hilbert-Huang Transform[D].Tianjin:Tianjin University,2010:25-29(in Chinese).
[19] US-ANSI.Standard for satety for arc-fault circuit-interrupters:UL 1699[S].Washington,D.C.:AVSI,1999.
[20]谭善文,秦树人,汤宝平.Hilbert-Huang变换的滤波特性及其应用[J].重庆大学学报,2004(2):9-12.TAN S W,QIN S R,TANG B P.The filtering character of Hilbert-Huang transform and its application[J].Journal of Chongqing University,2004(2):9-12(in Chinese).
[21]王慧.HHT方法及其若干应用研究[D].合肥:合肥工业大学,2009:21-25.WANG H.Research on the HHT method and its applications[D].Hefei:Hefei University of Technology,2009:21-25(in Chinese).
[22] ZHANG Y J,WANG L.The research on characteristics of DC arc fault based on HHT[C]∥2017IEEE International Conference on Prognostics and Health Management(ICPHM).Piscataway,NJ:IEEE Press,2017:130-134.
[23] YAO X,HERRERA L,HUANG Y,et al.The detection of DC arc fault:Experimental study and fault recognition[C]∥Applied Power Electronics Conference and Exposition(APEC),2012Twenty-Seventh Annual IEEE.Piscataway,NJ:IEEE Press,2012:1720-1727.
[24]王尧,李阳,葛磊蛟,等.基于滑动离散傅里叶变换的串联直流电弧故障识别[J].电工技术学报,2017,32(19):118-124.WANG Y,LI Y,GE L J,et al.A series DC arcing fault recognition method based on sliding discrete Fourier transform[J].Transactions of China Electrotechnical Society,2017,32(19):118-124(in Chinese).
[2]王其平.电器电弧理论[M].北京:机械工业出版社,1991:1-18.WANG Q P.Electric arc theory[M].Beijing:China Machine Press,1991:1-18(in Chinese).
[3] NAIDU M,THOMAS J S,SURESH G.Arc fault detection schemes for an automotive 42V wire harness[C]//2005SAE World Congress.Warrendale,PA:SAE International,2005:1-11.
[4] SEO G S,BAE H,CHO B H.Arc protection scheme for DC distribution systems with photovoltaic generation[C]∥International Conference on Renewable Energy Research and Applications(ICRERA).Piscataway,NJ:IEEE Press,2012:1-5.
[5] LIU Y,JI S C,WANG J,et al.Study on characteristics and detection of DC arc fault in power electronics system[C]∥2012IEEE International Conference on Condition Monitoring and Diagnosis.Piscataway,NJ:IEEE Press,2012:1043-1046.
[6] YAO X,JI S C,HERRATA L,et al.DC arc fault:Characteristic study and fault recognition[C]∥1st International Conference on Electric power Equipment-Switching Technology(ICEPE-ST).Piscataway,NJ:IEEE Press,2011:387-390.
[7] YAO X,HERRATA L,HUANG Y,et al.The detection of DC arc fault:Experimental study and fault recognition[C]∥IEEE Applied Power Electronics Conference&Exposition.Piscataway,NJ:IEEE Press,2012:1720-1727.
[8] ROZMAN G I,SWENSON J C.SSPC for parallel arc fault detection in DC power system:US, US2011/0299201A1[P].2011-12-08.
[9] GRASSETTI R,OTTOBONI R,ROSSI M.A novel algorithm for the parallel arc fault identification in DC aircraft power plants[C]∥IEEE International Instrumentation and Measurement Technology Conference(I2MTC).Piscataway,NJ:IEEE Press,2012:148-153.
[10] SHEKHAR L,MACKAY L,RAMREZ-ELIZONDO L,et al.Experimental design of a series arc load side detection algorithm for DC microgrid protection[C]∥2016International Symposium on Power Electronics,Electrical Drives,Automation and Motion(SPEEDAM).Piscataway,NJ:IEEE Press,2016:343-347.
[11] MOMOH J A,BUTTON R.Design and analysis of aerospace DC arcing faults using fast fourier transformation and artificial neural network[C]∥IEEE Power Engineering Society General Meeting.Piscataway, NJ:IEEE Press,2003:788-793.
[12] SPYKER R,SCHWEICKART D L,HORWATH J C,et al.An evaluation of diagnostic techniques relevant to arcing fault current interrupters for direct current power systems in future aircraft[C]∥Proceedings Electrical Insulation Conference and Electrical Manufacturing Expo.Piscataway,NJ:IEEE Press,2005:146-150.
[13] OHTA Y,ISODA H.Arc detecting device and aircraft equipped therewith:U.S.Patent,8093904[P].2012-1-10.
[14]林方圆,苏建徽,赖纪东.光伏系统直流故障电弧识别方法研究[J].电工电能新技术,2015,34(12):7-13.LIN F Y,SU J H,LAI J D.Research on DC fault arc identification method for photovoltaic system[J].Advanced Technology of Electrical Engineering and Energy,2015,34(12):7-13(in Chinese).
[15] YAO X,HERRERA L,WANG J.A series DC arc faultdetection method and hardware implementation[C]∥2013Twenty-Eighth Annual IEEE Applied Power Electronics Conference and Exposition(APEC).Piscataway,NJ:IEEE Press,2013,2444-2449.
[16] JOHNSON J,KUSZMAUL S,BOWER W,et al.Using PV module and line frequency response data to create robust arc fault detectors[C]∥26th European Photovoltaic Solar Energy Conference and Exhibition, Eastleigh:COPE Press,2011:3745-3750.
[17] HUANG N E,SHE N Z,LONG S R,et al.The wmpirical mode decomposition and the spedrum for non-linear and non-stationary time series analysis[J].Proceeding of the Society,1998,454:903-905.
[18]李成业.基于HHT的二滩拱坝工作性态识别及其“拍振”机理研究[D].天津:天津大学,2010:25-29.LI C Y.Study on working state identification and beat vibration of ertan arch dam based on Hilbert-Huang Transform[D].Tianjin:Tianjin University,2010:25-29(in Chinese).
[19] US-ANSI.Standard for satety for arc-fault circuit-interrupters:UL 1699[S].Washington,D.C.:AVSI,1999.
[20]谭善文,秦树人,汤宝平.Hilbert-Huang变换的滤波特性及其应用[J].重庆大学学报,2004(2):9-12.TAN S W,QIN S R,TANG B P.The filtering character of Hilbert-Huang transform and its application[J].Journal of Chongqing University,2004(2):9-12(in Chinese).
[21]王慧.HHT方法及其若干应用研究[D].合肥:合肥工业大学,2009:21-25.WANG H.Research on the HHT method and its applications[D].Hefei:Hefei University of Technology,2009:21-25(in Chinese).
[22] ZHANG Y J,WANG L.The research on characteristics of DC arc fault based on HHT[C]∥2017IEEE International Conference on Prognostics and Health Management(ICPHM).Piscataway,NJ:IEEE Press,2017:130-134.
[23] YAO X,HERRERA L,HUANG Y,et al.The detection of DC arc fault:Experimental study and fault recognition[C]∥Applied Power Electronics Conference and Exposition(APEC),2012Twenty-Seventh Annual IEEE.Piscataway,NJ:IEEE Press,2012:1720-1727.
[24]王尧,李阳,葛磊蛟,等.基于滑动离散傅里叶变换的串联直流电弧故障识别[J].电工技术学报,2017,32(19):118-124.WANG Y,LI Y,GE L J,et al.A series DC arcing fault recognition method based on sliding discrete Fourier transform[J].Transactions of China Electrotechnical Society,2017,32(19):118-124(in Chinese).