动态测试信号模型及电能压缩感知测量方法
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摘要
首先建立了动态测试信号统一模型,并给出两种实现形式。将动态测试信号分解为稳态信号和动态本征信号,根据动态本征信号先验结构信息构造压缩感知(CS)测量矩阵,推导了动态测试信号CS间接测量模型,解决了动态电能量值溯源和准确测量的理论问题;提出了动态测试信号电能量值CS间接测量新方法,并建立了智能电能表动态误差测试系统。最后,实验验证和不确定度分析表明,CS间接测量方法能够测试不同条件下智能电能表的动态误差。
The unified model of dynamic test signal is established and two implementation forms of the unified model are given in this paper. Then, the dynamic test signal is decomposed the stable state signal and dynamic intrinsic signal; according to the prior structure information of the dynamic intrinsic signal, the compressed sensing(CS) measurement matrix is constructed. The CS indirect measurement model of the dynamic test signal is deduced, which solves the theoretical problems of traceability and accurate measurement of the dynamic electric energy value. Based on this, a new CS indirect measurement method of dynamic test signal electric energy value is proposed, and a dynamic error test system for smart energy meter is established. Finally, experiment verification and uncertainty analysis show that the CS indirect measurement method can test the dynamic errors of the smart energy meter under different measurement conditions.
The unified model of dynamic test signal is established and two implementation forms of the unified model are given in this paper. Then, the dynamic test signal is decomposed the stable state signal and dynamic intrinsic signal; according to the prior structure information of the dynamic intrinsic signal, the compressed sensing(CS) measurement matrix is constructed. The CS indirect measurement model of the dynamic test signal is deduced, which solves the theoretical problems of traceability and accurate measurement of the dynamic electric energy value. Based on this, a new CS indirect measurement method of dynamic test signal electric energy value is proposed, and a dynamic error test system for smart energy meter is established. Finally, experiment verification and uncertainty analysis show that the CS indirect measurement method can test the dynamic errors of the smart energy meter under different measurement conditions.
引文
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[17] 赵鑫,李东新.高斯随机观测矩阵的改进[J]. 国外电子测量技术, 2017, 36(5):25- 29.ZHAO X, LI D X. Improvement of Gauss random measurement matrix[J]. Foreign Electronic Measurement Technology, 2017, 36(5):25- 29.
[18] DAVENPORT M A, BOUFOUNOS P T, WAKIN M B. Signal processing with compressive measurements[J]. IEEE Journal of Selected Topics Signal Processing, 2010, 4(2): 445- 460.
[19] 袁太文,谢永乐,毕东杰. 非均匀磁共振压缩成像的交替方向乘子法[J]. 仪器仪表学报,2018,39(3): 223- 230.YUAN T W, XIE Y L, BI D J. Alternating direction method of multipliers for non-uniform MR compressive imaging[J]. Chinese Journal of Scientific Instrument, 2018, 39(3): 223- 230.
[20] DU Z H, CHEN X F, ZHANG H, et al. Feature Identification with compressive measurements for machine fault diagnosis[J]. IEEE Transaction on Instrumentation and Measurement, 2016, 65(5): 977-987.
[21] 张男,龚磊,翟旭平. M2M通信系统下基于压缩感知的多用户检测技术[J].电子测量技术,2018,41(15): 72-77.ZHANG N, GONG L, ZHAI X P. Compressive sensing-based multi-user detection for M2M communication[J]. Electronic Measurement Technology, 2018,41(15): 72-77.
[22] 史洪印,贾宝京,齐兆龙. 基于压缩感知的非均匀脉冲 SAR 欺骗性干扰抑制方法[J]. 仪器仪表学报, 2016, 37(3):525- 532.SHI H Y, JIA B J, QI ZH L. Novel non-uniform pulse SAR deception jamming suppressing method based on compressive sensing[J]. Chinese Journal of Scientific Instrument, 2016, 37(3):525- 532.
[23] 沈跃,丁灵卫,吴翃轩,等.回溯自适应匹配追踪电能质量信号重构方法[J]. 电子测量与仪器学报, 2017, 31(5): 731-738.SHEN Y, DING L W, WU H X, et al. Power quality signal reconstruction of backtracking-based self-adaptive matching pursuit method[J]. Electronic Measurement and Instrumentation, 2017, 31(5): 731-738.
[2] 王项南,张原飞,夏海南,等. 我国自主研发潮流能发电装置的现场测试与评价分析[J]. 仪器仪表学报, 2018, 39(7): 226- 234.WANG X N, ZHANG Y F, XIA H N. Field test and evaluation of self-developed tidal power generation device [J]. Chinese Journal of Scientific Instrument, 2018, 39(7): 226- 234.
[3] PETERSEN H M, KOCH R G, SWART P H, et al. Modelling arc furnace flicker and investigating compensation techniques[C]. Industry Applications Conference, 1995: 1733-1740.
[4] 张淑清,宿新爽,陈荣飞,等.基于变分模态分解和 FABP 的短期电力负荷预测[J]. 仪器仪表学报, 2018, 39(4): 67-73.ZHANG S Q, SU X SH, CHEN R F, et al. Short-term load forecasting based on the VMD and FABP[J]. Chinese Journal of Scientific Instrument, 2018, 39(4): 67-73.
[5] HU Y, YUAN Y, CHEN ZH F, et al. Research on the calculation of the influence of arc furnace reactive impact loads on power system and the method of compensation[C]. Conference Proceedings IPEC, 2010: 1052-1055.
[6] 向世强,唐求,宋鹏,等. 非线性负荷电能计量方法研究[J].电子测量与仪器学报,2018,32(4):181-186.XIANG SH Q, TANG Q, SONG P, et al. Research on nonlinear load energy measurement method[J]. Journal of Electronic Measurement and Instrumentation, 2018,32(4): 181-186.
[7] DOMIJAN A, EMBRIZ-SANTANDER E, et al. Watthour meter accuracy under controlled unbalanced harmonic voltage and current conditions[J]. IEEE Transactions on Power Delivery, 1996, 11(1): 64-70.
[8] LU Z L, SO E. A proposal for verifying the performance specifications of certain functions of smart meters in distribution power line networks[C]. IEEE CPEM, 2010: 271- 272.
[9] 李世松, 赵伟. 基于DDS信号发生器的智能电表动态测量功能评估方法初探[J]. 电测与仪表, 2010, 47(10):1- 5,20.LI SH S, ZHAO W. A method for dynamic measurement capabilities evaluation of smart meter based on dds signal generator[J]. Electrical Measurement & Instrumentation, 2010,47(10):1- 5,20.
[10] 王学伟,温丽丽,贾晓璐,等.智能电能表动态误差的OOK激励测试方法[J].电力自动化设备,2014,34(9):143-147.WANG X W,WEN L L,JIA X L,et al.OOK-driven dynamic error measurement of smart energy meter[J].Electric Power Automation Equipment,2014,34(9):143-147.
[11] 王学伟,董晓璇,王琳,等.m序列伪随机动态测试信号建模与压缩检测方法[J].电力自动化设备,2017,37(2):145-150.WANG X W,DONG X X,WANG L,et al.Modeling of m-sequence pseudo-random dynamic test signal and compressive measurement method[J].Electric Power Automation Equipment,2017,37(2):145-150.
[12] ANDREA B, GIOVANNI B, et al. Electrical energy metering: Some challenges of the European directive on measuring instruments (MID)[J]. Measurement, 2013, 46(9):3347-3354.
[13] 郑荐中,陆祖良,李敏. 电能表动态特性实验研究[J]. 电测与仪表,2011,48(3):1-7.ZHENG J ZH, LU Z L, LI M. Experimental research for dynamic characteristic of electrical energy meter[J]. Electrical & Instrumentation, 2011, 48(3): 1-7.
[14] WANG X W, CHEN J X, YUAN R M, et al. OOK power model based dynamic error testing for smart electricity meter[J]. Measurement Science and Technology,2017, 28(2): 025015.
[15] DONOHO D L. Compressed sensing[J]. IEEE Transactions on Information Theory,2006, 52(4): 1289-1306.
[16] 王学伟, 崔广伟, 王琳,等. 基于平衡Gold序列的压缩感知测量矩阵的构造[J]. 仪器仪表学报, 2014, 35(1):97-102.WANG X W, CUI G W, WANG L, et al. Construction of measurement matrix in compressed sensing based on balanced Gold sequence[J]. Chinese Journal of Scientific Instrument,2014, 35(1): 97-102.
[17] 赵鑫,李东新.高斯随机观测矩阵的改进[J]. 国外电子测量技术, 2017, 36(5):25- 29.ZHAO X, LI D X. Improvement of Gauss random measurement matrix[J]. Foreign Electronic Measurement Technology, 2017, 36(5):25- 29.
[18] DAVENPORT M A, BOUFOUNOS P T, WAKIN M B. Signal processing with compressive measurements[J]. IEEE Journal of Selected Topics Signal Processing, 2010, 4(2): 445- 460.
[19] 袁太文,谢永乐,毕东杰. 非均匀磁共振压缩成像的交替方向乘子法[J]. 仪器仪表学报,2018,39(3): 223- 230.YUAN T W, XIE Y L, BI D J. Alternating direction method of multipliers for non-uniform MR compressive imaging[J]. Chinese Journal of Scientific Instrument, 2018, 39(3): 223- 230.
[20] DU Z H, CHEN X F, ZHANG H, et al. Feature Identification with compressive measurements for machine fault diagnosis[J]. IEEE Transaction on Instrumentation and Measurement, 2016, 65(5): 977-987.
[21] 张男,龚磊,翟旭平. M2M通信系统下基于压缩感知的多用户检测技术[J].电子测量技术,2018,41(15): 72-77.ZHANG N, GONG L, ZHAI X P. Compressive sensing-based multi-user detection for M2M communication[J]. Electronic Measurement Technology, 2018,41(15): 72-77.
[22] 史洪印,贾宝京,齐兆龙. 基于压缩感知的非均匀脉冲 SAR 欺骗性干扰抑制方法[J]. 仪器仪表学报, 2016, 37(3):525- 532.SHI H Y, JIA B J, QI ZH L. Novel non-uniform pulse SAR deception jamming suppressing method based on compressive sensing[J]. Chinese Journal of Scientific Instrument, 2016, 37(3):525- 532.
[23] 沈跃,丁灵卫,吴翃轩,等.回溯自适应匹配追踪电能质量信号重构方法[J]. 电子测量与仪器学报, 2017, 31(5): 731-738.SHEN Y, DING L W, WU H X, et al. Power quality signal reconstruction of backtracking-based self-adaptive matching pursuit method[J]. Electronic Measurement and Instrumentation, 2017, 31(5): 731-738.