Wavelet-based de-noising for PD online measurement of transformers

被引：0
|
作者：
Li, J [1 ]
Wang, YY [1 ]
Du, L [1 ]
Jin, ZR [1 ]
Yang, Y [1 ]
机构：
[1] Chongqing Univ, Minist Educ, Key Lab High Voltage Engn & Elect New Technol, Chongqing 400044, Peoples R China
来源：
CONFERENCE RECORD OF THE 2004 IEEE INTERNATIONAL SYMPOSIUM ON ELECTRICAL INSULATION | 2004年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The method based on thresholding and shrinking empirical wavelet coefficients is introduced in this paper for de-noising PD signals. Because the wavelet-based de-noising can not give a satisfied results while PD pulse amplitude is the same as or less than that of discrete spectral interferences (DSI), the wavelet combined with 2nd order lattice infinite impulse response (IIR) notch filter is proposed to enhance the signal-to-noise ratio (SNR) of signal detected by PD online measurement system of transformers. We present the results from simulations and real data examples.
引用
收藏
页码：54 / 57
页数：4
相关论文
共 50 条
  • [21] Improved 3-D Wavelet-based De-noising of fMRI data
    Khullar, Siddharth
    Michael, Andrew M.
    Correa, Nicolle
    Adali, Tulay
    Baum, Stefi A.
    Calhoun, Vince D.
    MEDICAL IMAGING 2011: IMAGE PROCESSING, 2011, 7962
  • [22] Real-time Traffic Data De-noising Based on Wavelet De-noising
    Xiao Qian
    Li Yingchao
    Wu Shuwei
    Zhao Zhipeng
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON CIVIL, TRANSPORTATION AND ENVIRONMENT, 2016, 78 : 1366 - 1369
  • [23] Wavelet Based De-noising of Pulse Signal
    Guo, Rui
    Wang, Yiqin
    Yan, Jianjun
    Li, Fufeng
    Yan, Haixia
    2008 IEEE INTERNATIONAL SYMPOSIUM ON IT IN MEDICINE AND EDUCATION, VOLS 1 AND 2, PROCEEDINGS, 2008, : 617 - +
  • [24] Adaptive wavelet based spatially de-noising
    Pan, Q
    Zhang, L
    Zhang, HC
    Dai, GZ
    ICSP '98: 1998 FOURTH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, PROCEEDINGS, VOLS I AND II, 1998, : 486 - 489
  • [25] Wavelet-based de-noising in groundwater quality and quantity prediction by an artificial neural network
    Vousoughi, Farnaz Daneshvar
    WATER SUPPLY, 2023, 23 (03) : 1333 - 1348
  • [26] Improving de-noising by coefficient de-noising and dyadic wavelet transform
    Zhu, HL
    Kwok, JI
    Qu, LS
    16TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL II, PROCEEDINGS, 2002, : 273 - 276
  • [27] Optimum Wavelet Bases Selection for Wavelet Based De-Noising In Partial Discharge Measurement
    Ray, Partha
    Basuray, Arijit
    Maitra, Ashok Kumar
    2013 IEEE CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES (ICT 2013), 2013, : 1110 - 1113
  • [28] Wavelet Based ECG Signal De-noising
    Sawant, Chitrangi
    Patil, Harishchandra T.
    2014 FIRST INTERNATIONAL CONFERENCE ON NETWORKS & SOFT COMPUTING (ICNSC), 2014, : 20 - 24
  • [29] EEG De-noising Based on Wavelet Transformation
    Yu, Lanlan
    2009 3RD INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICAL ENGINEERING, VOLS 1-11, 2009, : 2539 - 2542
  • [30] Wavelet-based vibration signal de-noising algorithm with a new adaptive threshold function
    Li, Hongyan
    Zhou, Yunlong
    Tian, Feng
    Li, Song
    Sun, Tianbao
    Yi Qi Yi Biao Xue Bao/Chinese Journal of Scientific Instrument, 2015, 36 (10): : 2200 - 2206
12345