基于变分模态分解的变压器有载分接开关振动信号去噪分析
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摘要
针对变压器有载分接开关振动信号中的环境噪声影响后续特征提取与识别的问题,提出了基于变分模态分解(Variational Mode Decomposition,VMD)与小波包阈值的去噪算法。首先对信号进行VMD分解,得到一系列窄带、中心频率区分度较好的模态分量。然后对各模态分量分别进行小波包阈值处理,利用均方根误差、信噪比及平滑度构成的复合评价指标确定最佳分解层数,得到最优的去噪效果。最后重构得到去噪后的振动信号。在变压器有载分接开关模拟试验平台上进行试验,并对采集的振动信号进行去噪分析,结果表明该方法的效果优于常用的去噪方法。
Aiming at the problem that the subsequent feature extraction and recognition of vibration signal of transformer on-load tap-changer are affected by the environmental noise,the de-noising method based on the variational mode decomposition (VMD) and the wavelet packet threshold algorithm is proposed in this paper. Firstly,the vibration signal is decomposed by VMD method into a series of modal components with narrow band and distinguishing center frequency. Then,the modal components are processed by the wavelet packet threshold algorithm separately,and a composite evaluation index constituted by root-mean-square error,signal-to-noise ratio and smoothness is used to determine the optimal wavelet decomposition level in order to obtain the best de-noising result. Finally the signal is restructured to get the de-noised vibration signal. An experiment is conducted on the transformer on-load tap-changer simulation experimental platform and the de-noising analysis on the collected vibration signal is processed,which shows the effect of the proposed method is better than that of several common de-noising methods.
Aiming at the problem that the subsequent feature extraction and recognition of vibration signal of transformer on-load tap-changer are affected by the environmental noise,the de-noising method based on the variational mode decomposition (VMD) and the wavelet packet threshold algorithm is proposed in this paper. Firstly,the vibration signal is decomposed by VMD method into a series of modal components with narrow band and distinguishing center frequency. Then,the modal components are processed by the wavelet packet threshold algorithm separately,and a composite evaluation index constituted by root-mean-square error,signal-to-noise ratio and smoothness is used to determine the optimal wavelet decomposition level in order to obtain the best de-noising result. Finally the signal is restructured to get the de-noised vibration signal. An experiment is conducted on the transformer on-load tap-changer simulation experimental platform and the de-noising analysis on the collected vibration signal is processed,which shows the effect of the proposed method is better than that of several common de-noising methods.
引文
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[2]王春亮,李凯,马宏忠,等.基于WP_SVD降噪的OLTC振动信号特征识别[J].电力系统及其自动化学报,2012,24(5):36-41.Wang Chunliang,Li Kai,Ma Hongzhong,et al.Feature Recognition of OLTC Vibration Signal Based on WP_SVD De-noising Method[J].Proceedings of the CSU-EPSA,2012,24(5):36-41.
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[8]王立东,张凯,王良润.改进小波阈值算法在电机振动信号降噪中的应用[J].电子技术应用,2015,41(5):77-80.Wang Lidong,Zhang Kai,Wang Liangrun.Improved wavelet threshold algorithm application in motor vibration signal denoising[J].Application of Electronic Technique,2015,41(5):77-80.
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[14]叶昱媛,沙浩源,梁君涵,等.基于小波包能量的断路器操作机构缺陷诊断技术研究[J].电力工程技术,2018,37(4):71-77.Ye Yuyuan,Sha Haoyuan,Liang Junhan,et al.Defect Diagnosis Technology of Operating Mechanism of Circuit Breakers Based on Wavelet Packet Energy[J].Electric Power Engineering Technology,2018,37(4):71-77.
[15]陶珂,朱建军.多指标融合的小波去噪最佳分解尺度选择方法[J].测绘学报,2012,41(5):749-755.Tao Ke,Zhu Jianjun.A Hybrid Indicator for Determining the Best Decomposition Scale of Wavelet Denoising[J].Acta Geodaetica et Cartographica Sinica,2012,41(5):749-755.
[16]朱建军,章浙涛,匡翠林,等.一种可靠的小波去噪质量评价指标[J].武汉大学学报(信息科学版),2015,40(5):688-694.Zhu Jianjun,Zhang Zhetao,Kuang Cuilin,et al.A Reliable Evaluation Indicator of Wavelet De-noising[J].Geomatics and Information Science of Wuhan University,2015,40(5):688-694.
[17]尹晖,朱锋.时序数据去噪中的小波策略及评价指标[J].武汉大学学报(信息科学版),2012,37(11):1374-1377.Yin Hui,Zhu Feng.Wavelet Strategies and Evaluation Indicator in Time Series Data Denoising[J].Geomatics and Information Science of Wuhan University,2012,37(11):1374-1377.
[18]门宝辉,赵燮京,梁川.基于变异系数权重的水质评价属性识别模型[J].郑州大学学报(理学版),2003,35(3):86-89.Men Baohui,Zhao Xiejing,Liang Chuan.Attribute Recognition Model for Evaluating Water Quality[J].Journal of Zhengzhou University,2003,35(3):86-89.
[2]王春亮,李凯,马宏忠,等.基于WP_SVD降噪的OLTC振动信号特征识别[J].电力系统及其自动化学报,2012,24(5):36-41.Wang Chunliang,Li Kai,Ma Hongzhong,et al.Feature Recognition of OLTC Vibration Signal Based on WP_SVD De-noising Method[J].Proceedings of the CSU-EPSA,2012,24(5):36-41.
[3]陈涛涛,华晓珠,陆金.变压器噪声有源控制技术新方法研究[J].电力工程技术,2015,34(4):44-47.Chen Taotao,Hua Xiaozhu,Lu Jin.Research on Active Noise Reduction Technology for Transformers[J].Electric Power Engineering Technology,2015,34(4):44-47.
[4]张伟政,施琳琛,汲胜昌,等.小波奇异性检测诊断有载分接开关故障[J].高电压技术,2006,32(7):49-53.Zhang Weizheng,Shi Linchen,Ji Shengchang,et al.Wavelet Singularity Detection Used for Fault Diagnosis of On-load Tap Changers[J].High Voltage Engineering,2006,32(7):49-53.
[5]章浙涛,朱建军,匡翠林,等.不同噪声下几种滤波方法的比较研究及改进[J].大地测量与地球动力学,2014,34(1):127-130.Zhang Zhetao,Zhu Jianjun,Kuang Cuilin,et al.Comparative Study And Improvement on Several De-noising Methods for Different Noise[J].Journal of Geodesy and Geodynamics,2014,34(1):127-130.
[6]刘明才.小波分析及其应用[M].清华大学出版社,2013.
[7]李红延,周云龙,田峰,等.一种新的小波自适应阈值函数振动信号去噪算法[J].仪器仪表学报,2015,36(10):2200-2206.Li Hongyan,Zhou Yunlong,Tian Feng,et al.Wavelet-based vibration signal de-noising algorithm with a new adaptive threshold function[J].Chinese Journal of Scientific Instrument,2015,36(10):2200-2206.
[8]王立东,张凯,王良润.改进小波阈值算法在电机振动信号降噪中的应用[J].电子技术应用,2015,41(5):77-80.Wang Lidong,Zhang Kai,Wang Liangrun.Improved wavelet threshold algorithm application in motor vibration signal denoising[J].Application of Electronic Technique,2015,41(5):77-80.
[9]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[J].Proceedings Mathematical Physical&Engineering Sciences,1998,454(1971):903-995.
[10]李琳,张永祥,刘树勇.改进EMD-小波分析的转子振动信号去噪方法[J].噪声与振动控制,2015,35(2):170-174.
[11]Dragomiretskiy K,Zosso D.Variational Mode Decomposition[J].IEEETransactions on Signal Processing,2014,62(3):531-544.
[12]Nocedal J,Wright S J.Numerical Optimization[M].科学出版社,2006.
[13]潘泉,孟晋丽,张磊,等.小波滤波方法及应用[J].电子与信息学报,2007,29(1):236-242.Pan Quan,Meng Jinli,Zhang Lei,et al.Wavelet Filtering Method and Its Application[J].Journal of Electronics&Information Technology,2007,29(1):236-242.
[14]叶昱媛,沙浩源,梁君涵,等.基于小波包能量的断路器操作机构缺陷诊断技术研究[J].电力工程技术,2018,37(4):71-77.Ye Yuyuan,Sha Haoyuan,Liang Junhan,et al.Defect Diagnosis Technology of Operating Mechanism of Circuit Breakers Based on Wavelet Packet Energy[J].Electric Power Engineering Technology,2018,37(4):71-77.
[15]陶珂,朱建军.多指标融合的小波去噪最佳分解尺度选择方法[J].测绘学报,2012,41(5):749-755.Tao Ke,Zhu Jianjun.A Hybrid Indicator for Determining the Best Decomposition Scale of Wavelet Denoising[J].Acta Geodaetica et Cartographica Sinica,2012,41(5):749-755.
[16]朱建军,章浙涛,匡翠林,等.一种可靠的小波去噪质量评价指标[J].武汉大学学报(信息科学版),2015,40(5):688-694.Zhu Jianjun,Zhang Zhetao,Kuang Cuilin,et al.A Reliable Evaluation Indicator of Wavelet De-noising[J].Geomatics and Information Science of Wuhan University,2015,40(5):688-694.
[17]尹晖,朱锋.时序数据去噪中的小波策略及评价指标[J].武汉大学学报(信息科学版),2012,37(11):1374-1377.Yin Hui,Zhu Feng.Wavelet Strategies and Evaluation Indicator in Time Series Data Denoising[J].Geomatics and Information Science of Wuhan University,2012,37(11):1374-1377.
[18]门宝辉,赵燮京,梁川.基于变异系数权重的水质评价属性识别模型[J].郑州大学学报(理学版),2003,35(3):86-89.Men Baohui,Zhao Xiejing,Liang Chuan.Attribute Recognition Model for Evaluating Water Quality[J].Journal of Zhengzhou University,2003,35(3):86-89.