作者：卢鹏宇1,2, 刘宏勋1,2
作者单位：1. 河北工业大学电气工程学院 省部共建电工装备可靠性与智能化国家重点实验室，天津 300130;
2. 河北工业大学电气工程学院 河北省电磁场与电器可靠性重点实验室，天津 300130
关键词：电能质量;自适应噪声总体平均经验模态分解;排列熵;非抽样小波变换;LabVIEW
摘要：
针对电网电能质量检测和噪声污染问题，结合自适应噪声总体平均经验模态分解(CEEMDAN)、排列熵(PE)、基于非抽样小波变换(UWT)的小波阈值降噪和希尔伯特黄变换(HHT)，提出基于CEEMDAN-UWT降噪的暂态电能质量检测方法。CEEMDAN将扰动信号分解成具有单分量特征的固有模态函数组，应用UWT阈值降噪处理PE筛选出的含噪分量，重构后获得最终的降噪信号，接着通过HHT获得其扰动特征信息。在LabVIEW环境下独立实现此方法并进行仿真，结果验证方法的有效性。最后以PXI设备为基础开发基于LabVIEW的检测装置，可为现代电能质量检测仪器和系统的开发提供新思路。
Transient power quality detection method based on CEEMDAN-UWT denoising
LU Pengyu1,2, LIU Hongxun1,2
1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China;
2. Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China
Abstract: Aiming at power quality detection and noise pollution, in combination with complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN), permutation entropy(PE), wavelet threshold denoising based on undecimated wavelet transform(UWT) and Hilbert-Huang transform(HHT), a transient power quality detection method based on CEEMDAN-UWT denoising is proposed. CEEMDAN decomposes the disturbance signal into a series of intrinsic mode function with single-component characteristics, UWT denoising is used to deal with the noise components screened out by PE and reconstruction to obtain the original signal after denoising, the Hilbert-Huang transform is used to get the characteristic information. The method is implemented in LabVIEW and simulated independently, the results verify the effectiveness of the method. Finally, on the basis of PXI equipment, a detection device based on LabVIEW is built, which provides a new idea for the development of power quality detection instrument and system.
Keywords: power quality;complete ensemble empirical mode decomposition with adaptive noise;permutation entropy;undecimated wavelet transform;LabVIEW
2020, 46(7):60-67 收稿日期: 2019-10-21;收到修改稿日期: 2019-12-28
基金项目:
作者简介: 卢鹏宇(1993-),男,天津市人,硕士研究生,专业方向为电力系统自动化
参考文献
[1] 胡雷, 陈湘波, 熊魁, 等. 基于改进HHT的电能质量扰动检测方法[J]. 电测与仪表, 2018, 55(21): 105-111
[2] HUANG N E, SHEN Z, LONG S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[C]//Proc Roy Soc Lond A, 1998: 903-995.
[3] WU Z H, HUANG N E. Ensemble empirical mode decom- position: a noise-assisted data analysis method[J]. Advances in Adaptive Data Analysis, 2009, 1(1): 1-41
[4] YEH J R, SHIEH J S, HUANG N E. Complementary ensemble empirical mode decomposition: a novel noise enhanced data analysis method[J]. Advances in Adaptive Data Analysis, 2010, 2(2): 135-156
[5] TORRES M E, COLOMINAS M A, SCHLOTTHAUER G, et al. A complete ensemble empirical mode decomposition with adaptive noise[C]//IEEE International Conference on Acoustics, Speech, and Signal Processing, 2011.
[6] 任子晖, 成江洋, 邢强, 等. 基于CEEMDAN与Teager能量算子的谐波检测方法[J]. 电力系统保护与控制, 2017, 45(9): 56-62
[7] 吴新忠, 邢强, 周涛, 等. 基于CEEMD与改进Prony的谐波检测方法[J]. 电测与仪表, 2017, 54(10): 80-86
[8] 张建文, 刘洋, 张大朋, 等. 基于CEEMDAN与小波自适应阈值的去噪新方法[J]. 电测与仪表, 2018, 55(10): 14-18, 33
[9] BANDT C, BEMD P. Permutation entropy: a natural complexity measure for time series[J]. Physical Review Letters, 2002, 88(17): 174102
[10] 吴新忠, 邢强, 渠虎, 等. CEEMD在电能质量扰动检测中的应用[J]. 电力系统保护与控制, 2017, 45(3): 48-55
[11] 万书亭, 吕路勇, 何玉灵. 基于提升模式非抽样小波变换的滚动轴承故障诊断方法研究[J]. 振动与冲击, 2009, 28(1): 170-173, 204
[12] 甄杰. 基于小波分析的导气槽尺寸检测方法研究[D]. 重庆: 重庆大学, 2015.
[13] 汪雪元, 何剑锋, 吴光明. 改进小波阈值函数法平滑X射线荧光光谱[J]. 核电子学与探测技术, 2018, 38(5): 719-724
[14] 郑近德, 程军圣, 杨宇. 改进的EEMD算法及其应用研究[J]. 振动与冲击, 2013, 32(21): 21-26, 46
[15] 陶顺, 徐永海, 齐林海. 现代电能质量检测技术[M]. 北京: 中国电力出版社, 2015.
