基于自适应变分模态分解的电力系统机电振荡特征提取
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摘要
针对电力系统非线性、非平稳机电振荡信号特征参数提取困难的问题,提出了一种基于自适应变分模态分解(adaptive variational mode decomposition,AVMD)和Hilbert变换的电力系统机电振荡特征参数提取方法。自适应变分模态分解方法是一种非递归式算法,通过约束变分模型的构建及求解,从而获取频率成分固定的振荡分量,且抗噪性能较好。首先根据窗口傅立叶变换频谱分布确定变分模态分解算法的分解模态数,然后利用自适应变分模态分解算法获取各有限带宽固有模态分量,最后通过Hilbert变换提取振荡特征参数。仿真分析及实测数据计算结果表明了所提方法的可行性及有效性。
Owing to difficulty in extracting electromechanical oscillation modes from non-stationary and nonlinear oscillation signals, a novel method based on adaptive variational mode decomposition(AVMD) and Hilbert transform was proposed. The AVMD method is a non-recursive algorithm. Avariational model is constructed, and then used to search the optimal solution of the variational model iteratively and sifted modal responses with fixed frequencies. Also it has good noise robustness. Firstly, the decomposition modal number of VMD algorithm is determined according to the window Fourier transform(WFT) spectrum analysis, then the band-limited intrinsic mode functions are obtained with VMD. Finally, Hilbert transform was employed to extract oscillation characteristic parameters. Effectiveness and feasibility of the proposed method is confirmed by the results of simulation and measured data.
Owing to difficulty in extracting electromechanical oscillation modes from non-stationary and nonlinear oscillation signals, a novel method based on adaptive variational mode decomposition(AVMD) and Hilbert transform was proposed. The AVMD method is a non-recursive algorithm. Avariational model is constructed, and then used to search the optimal solution of the variational model iteratively and sifted modal responses with fixed frequencies. Also it has good noise robustness. Firstly, the decomposition modal number of VMD algorithm is determined according to the window Fourier transform(WFT) spectrum analysis, then the band-limited intrinsic mode functions are obtained with VMD. Finally, Hilbert transform was employed to extract oscillation characteristic parameters. Effectiveness and feasibility of the proposed method is confirmed by the results of simulation and measured data.
引文
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[16]杨华,陈云良,徐永,等.基于VMD-HHT方法的水电机组启动过渡过程振动信号分析研究[J].工程科学与技术,2017,49(2):92-99.Yang Hua,Chen Yunliang,Xu Yong,et al.Analysis of the hydropower unit vibration signal in the start transient process based on VMD-HHT method[J].Advanced Engineering Sciences,2017,49(2):92-99(in Chinese).
[17]唐贵基,王晓龙.参数优化变分模态分解方法在滚动轴承早期故障诊断中的应用[J].西安交通大学学报,2015,49(5):73-81.Tang Guigeng, Wang Xiaolong.Parameter optimized variational mode decomposition method with application to incipient fault diagnosis of rolling bearing[J].Journal of Xi’an JiaoTong University,2015,49(5):73-81(in Chinese).
[18]朱永利,贾亚飞,王刘旺,等.基于改进变分模态分解和Hilbert变换的变压器局部放电信号特征提取及分类[J].电工技术学报,2017,32(9):221-235.Zhu Yongli,JiaYafei,Wang Liuwang,et al.Feature extraction and classification on partial discharge signals of power transformers based onimprovedvariationalmodedecompositionandHilbert transform[J].Transactions of China Electrotechnical Society,2017,32(9):221-235(in Chinese).
[19]Messina AR, Vitttal V. Nonlinear, non-stationaryanalysis of inter-areaoscillationsvia Hilbertspectral analysis[J]. IEEE Transactions on Power Systems,2006,21(3):1234-1241.
[2]Kundar P.Power system stability and control[M].New York,NY,USA:McG raw-Hill,1994.
[3]段刚,严亚勤,谢晓冬,等.广域相量测量技术发展现状与展望[J].电力系统自动化,2015,39(1):73-80.Duan Gang,Yan Yaqin,XieXiaodong,et al.Development status quo and tendency of wide area phasormeasuring technology[J].Electric Power Automation Equipment,2015,39(1):73-80(in Chinese).
[4]Hauer J F,Demeure C J,Scharf L L.Initial results in Prony analysis ofpowersystemresponsesignals[J].IEEETransactionsonPower Systems,1990,5(1):80-89.
[5]孙英云,游亚雄,侯建兰,等.基于差分正交匹配追踪和Prony算法的低频振荡模态辨识[J].电力系统自动化,2015,39(10):69-74.SunYingyun, YouYaxiong, HouJianlan. Identificationof low-frequencyoscillationmodebasedondifferenceorthogonal matching pursuit and Prony algorithm[J].Electric Power??Automation Equipment,2015,39(10):69-74(in Chinese).
[6]赵礼杰.基于EMD的Prony算法在低频振荡模态参数辨识中的应用[J].电力系统保护与控制,2009,37(23):9-14.ZhaoLijie.ApplicationofPronyalgorithmbasedonEMDfor identifying model parameters of low-frequency oscillations[J].Power System Protection and Control,2009,37(23):9-14(in Chinese).
[7]蔡国伟,杨德友,张俊丰,等.基于实测信号的电力系统的低频振荡模态辨识[J].电网技术,2011,35(1):59-65.CaiGuowei,Yang Deyou,Zhang Junfeng,et al.Mode identification ofpowersystemlow-frequencyoscillationbasedonmeasured signal[J].Power System Technology,2011,35(1):59-65(in Chinese).
[8]李玲,李天云,黄绍平,等.基于随机子空间的同步电机参数高精度辨识新方法[J].电网技术,2011,35(7):156-160.LiLing,LiTianyun,HuangShaoping,etal.Ahigh-precision approachtoidentifysynchronousgeneratorparametersbasedon stochasticsubspaceidentification[J].PowerSystemTechnology,2011,35(7):156-160(in Chinese).
[9]李天云,高磊,赵妍.基于HHT的电力系统低频振荡分析[J].中国电机工程学报,2006,26(14):24-30.LiTianyun, GaoLei, ZhaoYan. Analysisoflowfrequency oscillations using HHT method[J].Proceedings of the CSEE,2006,26(14):24-30(in Chinese).
[10]杨德昌,Rehtanz C,李勇,等.基于改进希尔伯特-黄变换算法的电力系统低频振荡分析[J].中国电机工程学报,2011,31(10):102-108.YangDechang,RehtanzC,LiYong,etal.Researchingonlow frequencyoscillationinpowersystembasedonimprovedHHT algorithm[J].Proceedings of the CSEE,2011,31(10):102-108(in Chinese).
[11]张杨,刘志刚.EEMD在电能质量扰动检测中的应用[J].电力自动化设备,2011,31(12):86-91.ZhangYang,LiuZhigang.ApplicationofEEMDinpowerquality disturbancedetection[J].ElectricPowerAutomationEquipment,2011,31(12):86-91(in Chinese).
[12]于静文,薛蕙,温渤婴.基于卡尔曼滤波的电能质量分析方法综述[J].电网技术,2010,34(2):97-103.Yu Jingwen,XueHui,Wen Boying.A survey on Kalmanfilering based methods for power quality analysis[J].Power System Technology,2010,34(2):97-103(in Chinese).
[13]李志农,朱明,褚福磊,等.基于经验小波变换的机械故障诊断方法研究[J].仪器仪表学报,2014,35(11):2423-2432.Li Zhinong,Zhu Ming,Chu Fulei,et al.Mechanical fault diagnosis method based on empirical wavelet transform[J].Chinese Journal of Scientific Instrument,2014,35(11):2423-2432(in Chinese).
[14]Dragomiretskiy K, Zosso D. Variationalmode decomposition[J].IEEE Transactions on Signal Processing,2014,62(3):531-544.
[15]Zipeng Li,Jinglong Chen,Yangyang Zi.Idependence-oriented VMD toidentify faultfeature forwheelsetbearing faultdiagn osisofhigh speedlocomotive[J].MechanicalSystemsandSignal Proccessing,2017,85(1):512-529.
[16]杨华,陈云良,徐永,等.基于VMD-HHT方法的水电机组启动过渡过程振动信号分析研究[J].工程科学与技术,2017,49(2):92-99.Yang Hua,Chen Yunliang,Xu Yong,et al.Analysis of the hydropower unit vibration signal in the start transient process based on VMD-HHT method[J].Advanced Engineering Sciences,2017,49(2):92-99(in Chinese).
[17]唐贵基,王晓龙.参数优化变分模态分解方法在滚动轴承早期故障诊断中的应用[J].西安交通大学学报,2015,49(5):73-81.Tang Guigeng, Wang Xiaolong.Parameter optimized variational mode decomposition method with application to incipient fault diagnosis of rolling bearing[J].Journal of Xi’an JiaoTong University,2015,49(5):73-81(in Chinese).
[18]朱永利,贾亚飞,王刘旺,等.基于改进变分模态分解和Hilbert变换的变压器局部放电信号特征提取及分类[J].电工技术学报,2017,32(9):221-235.Zhu Yongli,JiaYafei,Wang Liuwang,et al.Feature extraction and classification on partial discharge signals of power transformers based onimprovedvariationalmodedecompositionandHilbert transform[J].Transactions of China Electrotechnical Society,2017,32(9):221-235(in Chinese).
[19]Messina AR, Vitttal V. Nonlinear, non-stationaryanalysis of inter-areaoscillationsvia Hilbertspectral analysis[J]. IEEE Transactions on Power Systems,2006,21(3):1234-1241.