An Advanced Time-Frequency Domain Method for PD Extraction with Non-Intrusive Measurement
Partial discharge (PD) detection is an important
method to evaluate the insulation condition of metal-clad apparatus.
Non-intrusive sensors which are easy to install and have no
interruptions on operation are preferred in onsite PD detection.
However, it often lacks of accuracy due to the interferences in PD
signals. In this paper a novel PD extraction method that uses frequency
analysis and entropy based time-frequency (TF) analysis is introduced.
The repetitive pulses from convertor are first removed via frequency
analysis. Then, the relative entropy and relative peak-frequency of
each pulse (i.e. time-indexed vector TF spectrum) are calculated and
all pulses with similar parameters are grouped. According to the
characteristics of non-intrusive sensor and the frequency distribution
of PDs, the pulses of PD and interferences are separated. Finally the
PD signal and interferences are recovered via inverse TF transform.
The de-noised result of noisy PD data demonstrates that the
combination of frequency and time-frequency techniques can
discriminate PDs from interferences with various frequency
distributions.
[1] M. D. Judd, O. Farish, J. S. Pearson and B. F. Hampton, "Dielectric
windows for UHF partial discharge detection," IEEE Trans. Dielectrics
and Electrical Insulation, vol. 8, pp. 953-958, 2001.
[2] P. Brown, "Nonintrusive partial discharge measurements on high voltage
switchgear," in IEE Colloquium on Monitors and Condition Assessment
Equipment (Digest No. 1996/186), 1996, pp. 10/1-10/5.
[3] Y. Li, Y. Wang, G. Lu, J. Wang, and J. Xiong, "Simulation of transient
earth voltages aroused by partial discharge in switchgears," in 2010 Int.
Conf. High Voltage Engineering and Application (ICHVE), 2010, pp.
309-312.
[4] R. Bartnikas, "Partial discharges. Their mechanism, detection and
measurement," IEEE Trans. Dielectrics and Electrical Insulation, vol. 9,
pp. 763-808, 2002.
[5] C. Caironi, D. Brie, L. Durantay and A. Rezzoug, "Interest and utility of
time frequency and time scale transforms in the partial discharges
analysis," in Conf. Record of the 2002 IEEE Int. Symp. Electrical
Insulation, 2002, 2002, pp. 516-522.
[6] Y. H. M. Thayoob, Z. Zakaria, M. R. Samsudin, P. S. Ghosh, and M. L.
Chai, "Preprocessing of acoustic emission signals from partial discharge
in oil-pressboard insulation system," in 2010 IEEE Int. Conf. Power and
Energy (PECon), 2010, pp. 29-34.
[7] K. L. Wong, "Electromagnetic emission based monitoring technique for
polymer ZnO surge arresters," IEEE Trans. Dielectrics and Electrical
Insulation, vol. 13, pp. 181-190, 2006.
[8] A. Cavallini, A. Contin, G. C. Montanari and F. Puletti, "Advanced PD
inference in on-field measurements. Part I: Noise rejection," IEEE Trans.
Dielectrics and Electrical Insulation, vol. 10, pp. 216-224, Apr 2003.
[9] H. Zhang, T. R. Blackburn, B. T. Phung and D. Sen, "A novel wavelet
transform technique for on-line partial discharge measurements. Part 1:
WT de-noising algorithm," IEEE Trans. Dielectrics and Electrical
Insulation, vol. 14, pp. 3-14, Feb 2007.
[10] BSI, "High-Voltage Test Techniques - Partial Discharge Measurements,"
in IEC 60270, ed. London: European Committee for Electrotechnical
Standardization, 2001, p. 7.
[11] S. G. Mallat, "Time Meets Frequency," in A Wavelet Tour of Signal
Processing : The Sparse Way, Sparse ed Amsterdam ; Boston: Elsevier
/Academic Press, 2009, pp. 89-150.
[12] D. L. Donoho and I. M. Johnstone, "Ideal spatial adaptation by wavelet
shrinkage," Biometrika, vol. 81, pp. 425-455, Sep 1994.
[13] M. Misiti, Y. Misiti, G. Oppenheim and J.-M. Poggi. (1996). Wavelet
Toolbox for Use with MATLAB: User's Guide (1st ed.).
[14] S. Verd├║, S. W. McLaughlin and IEEE Information Theory Society.,
"Fifty Years of Shannon Theory," in Information theory 50 years of
discovery, ed New York: IEEE Press, 2000.
[1] M. D. Judd, O. Farish, J. S. Pearson and B. F. Hampton, "Dielectric
windows for UHF partial discharge detection," IEEE Trans. Dielectrics
and Electrical Insulation, vol. 8, pp. 953-958, 2001.
[2] P. Brown, "Nonintrusive partial discharge measurements on high voltage
switchgear," in IEE Colloquium on Monitors and Condition Assessment
Equipment (Digest No. 1996/186), 1996, pp. 10/1-10/5.
[3] Y. Li, Y. Wang, G. Lu, J. Wang, and J. Xiong, "Simulation of transient
earth voltages aroused by partial discharge in switchgears," in 2010 Int.
Conf. High Voltage Engineering and Application (ICHVE), 2010, pp.
309-312.
[4] R. Bartnikas, "Partial discharges. Their mechanism, detection and
measurement," IEEE Trans. Dielectrics and Electrical Insulation, vol. 9,
pp. 763-808, 2002.
[5] C. Caironi, D. Brie, L. Durantay and A. Rezzoug, "Interest and utility of
time frequency and time scale transforms in the partial discharges
analysis," in Conf. Record of the 2002 IEEE Int. Symp. Electrical
Insulation, 2002, 2002, pp. 516-522.
[6] Y. H. M. Thayoob, Z. Zakaria, M. R. Samsudin, P. S. Ghosh, and M. L.
Chai, "Preprocessing of acoustic emission signals from partial discharge
in oil-pressboard insulation system," in 2010 IEEE Int. Conf. Power and
Energy (PECon), 2010, pp. 29-34.
[7] K. L. Wong, "Electromagnetic emission based monitoring technique for
polymer ZnO surge arresters," IEEE Trans. Dielectrics and Electrical
Insulation, vol. 13, pp. 181-190, 2006.
[8] A. Cavallini, A. Contin, G. C. Montanari and F. Puletti, "Advanced PD
inference in on-field measurements. Part I: Noise rejection," IEEE Trans.
Dielectrics and Electrical Insulation, vol. 10, pp. 216-224, Apr 2003.
[9] H. Zhang, T. R. Blackburn, B. T. Phung and D. Sen, "A novel wavelet
transform technique for on-line partial discharge measurements. Part 1:
WT de-noising algorithm," IEEE Trans. Dielectrics and Electrical
Insulation, vol. 14, pp. 3-14, Feb 2007.
[10] BSI, "High-Voltage Test Techniques - Partial Discharge Measurements,"
in IEC 60270, ed. London: European Committee for Electrotechnical
Standardization, 2001, p. 7.
[11] S. G. Mallat, "Time Meets Frequency," in A Wavelet Tour of Signal
Processing : The Sparse Way, Sparse ed Amsterdam ; Boston: Elsevier
/Academic Press, 2009, pp. 89-150.
[12] D. L. Donoho and I. M. Johnstone, "Ideal spatial adaptation by wavelet
shrinkage," Biometrika, vol. 81, pp. 425-455, Sep 1994.
[13] M. Misiti, Y. Misiti, G. Oppenheim and J.-M. Poggi. (1996). Wavelet
Toolbox for Use with MATLAB: User's Guide (1st ed.).
[14] S. Verd├║, S. W. McLaughlin and IEEE Information Theory Society.,
"Fifty Years of Shannon Theory," in Information theory 50 years of
discovery, ed New York: IEEE Press, 2000.
@article{"International Journal of Electrical, Electronic and Communication Sciences:51135", author = "Guomin Luo and Daming Zhang and Yong Kwee Koh and Kim Teck Ng and Helmi Kurniawan and Weng Hoe Leong", title = "An Advanced Time-Frequency Domain Method for PD Extraction with Non-Intrusive Measurement", abstract = "Partial discharge (PD) detection is an important
method to evaluate the insulation condition of metal-clad apparatus.
Non-intrusive sensors which are easy to install and have no
interruptions on operation are preferred in onsite PD detection.
However, it often lacks of accuracy due to the interferences in PD
signals. In this paper a novel PD extraction method that uses frequency
analysis and entropy based time-frequency (TF) analysis is introduced.
The repetitive pulses from convertor are first removed via frequency
analysis. Then, the relative entropy and relative peak-frequency of
each pulse (i.e. time-indexed vector TF spectrum) are calculated and
all pulses with similar parameters are grouped. According to the
characteristics of non-intrusive sensor and the frequency distribution
of PDs, the pulses of PD and interferences are separated. Finally the
PD signal and interferences are recovered via inverse TF transform.
The de-noised result of noisy PD data demonstrates that the
combination of frequency and time-frequency techniques can
discriminate PDs from interferences with various frequency
distributions.", keywords = "Entropy, Fourier analysis, non-intrusive
measurement, time-frequency analysis, partial discharge", volume = "6", number = "2", pages = "160-7", }