Examination on the Denoising Methods for Electrical and Acoustic Emission Partial Discharge Signals in Oil
Abstract
Keywords
References
R. Hussein, K. B. Shaban, and A. H. El-Hag, “Denoising different types of acoustic partial discharge signals using power spectral subtraction,” Inst. Eng. Technol. High Volt., vol. 3, no. 1, pp. 44–50, 2018, doi: 10.1049/hve.2017.0119.
M. Ghorat, G. B. Gharehpetian, H. Latifi, and M. A. Hejazi, “A new partial discharge signal denoising algorithm based on adaptive dual-tree complex wavelet transform,” IEEE Trans. Instrum. Meas., vol. 67, no. 10, pp. 2262–2272, 2018, doi: 10.1109/TIM.2018.2816438.
Y. O. Shaker, “Detection of partial discharge acoustic emission in power transformer,” Int. J. Electr. Comput. Eng., vol. 9, no. 6, pp. 4573–4579, 2019, doi: 10.11591/ijece.v9i6.pp4573-4579.
S. Coenen, S. Kornhuber, A. Müller, and M. Beltle, “UHF and Acoustic Partial Discharge Localisation in Power Transformers,” XVI Int. Symp. High Volt. Eng. Hann. Ger. August 22-26, 2011, no. October 2014, p. D-015, 1-6, 2011.
N. A. Yusoff et al., “Denoising technique for partial discharge signal : A comparison performance between artificial neural network, fast fourier transform and discrete wavelet transform,” PECON 2016 - 2016 IEEE 6th Int. Conf. Power Energy, Conf. Proceeding, pp. 311–316, 2017, doi: 10.1109/PECON.2016.7951579.
G. Chen, J. Tao, Y. Ma, H. U. I. Fu, Y. Liu, and Z. Zhou, “On-site Portable Partial Discharge Detection Applied to Power Cables Using HFCT and UHF methods,” On-site Portable Partial Disch. Detect. Appl. to Power Cables Using HFCT UHF methods, vol. 15, pp. 83–90, 2016.
K. Zhou, M. Li, Y. Li, M. Xie, and Y. Huang, “An improved denoising method for partial discharge signals contaminated by white noise based on adaptive short-time singular value decomposition,” Energies, vol. 12, no. 18, 2019, doi: 10.3390/en12183465.
A. A. Soltani and A. El-Hag, “A new radial basis function neural network-based method for denoising of partial discharge signals,” Meas. J. Int. Meas. Confed., vol. 172, no. January, p. 108970, 2021, doi: 10.1016/j.measurement.2021.108970.
Y. Wang, P. Chen, Y. Zhao, and Y. Sun, “A Denoising Method for Mining Cable PD Signal Based on Genetic Algorithm Optimization of VMD and Wavelet Threshold,” Sensors, vol. 22, no. 23, 2022, doi: 10.3390/s22239386.
H. Janani, S. Shahabi, and B. Kordi, “Separation and Classification of Concurrent Partial Discharge Signals Using Statistical-Based Feature Analysis,” IEEE Trans. Dielectr. Electr. Insul., vol. 27, no. 6, pp. 1933–1941, 2020, doi: 10.1109/TDEI.2020.009043.
J. Rubio-Serrano, J. E. Posada, and J. A. Garcia-Souto, “Detection and location of acoustic and electric signals from partial discharges with an adaptative wavelet-filter denoising,” in Electrical Engineering and Applied Computing, Lecture Notes in Electrical Engineering, 2011, pp. 25–38. doi: 10.1007/978-94-007-1192-1_3.
H. Mohamed et al., “Partial discharge localization based on received signal strength,” ICAC 2017 - 2017 23rd IEEE Int. Conf. Autom. Comput. Addressing Glob. Challenges through Autom. Comput., no. September, pp. 7–8, 2017, doi: 10.23919/IConAC.2017.8082028.
R. Sarathi, P. D. Singh, and M. G. Danikas, “Characterization of partial discharges in transformer oil insulation under AC and DC voltage using acoustic emission technique,” J. Electr. Eng., vol. 58, no. 2, pp. 91–97, 2007.
R. Ghosh, B. Chatterjee, and S. Dalai, “A new method for the estimation of time difference of arrival for localization of partial discharge sources using acoustic detection technique,” in 2016 IEEE 7th Power India International Conference, PIICON 2016, Bikaner, India: IEEE, 2017, pp. 1–5. doi: 10.1109/POWERI.2016.8077180.
H. Dadashi Ilkhechi, M. H. Samimi, and R. Yousefvand, “Generation of acoustic phase-resolved partial discharge patterns by utilizing UHF signals,” Int. J. Electr. Power Energy Syst., vol. 113, no. January, pp. 906–915, 2019, doi: 10.1016/j.ijepes.2019.06.018.
M. S. A. Rahman, P. L. Lewin, and P. Rapisarda, “Autonomous localization of partial discharge sources within large transformer windings,” IEEE Trans. Dielectr. Electr. Insul., vol. 23, no. 2, pp. 1088–1098, 2016, doi: 10.1109/TDEI.2015.005070.
P. Kailasapathi and D. Sivakumar, “Analyzing Power Quality Disturbances Using Different Wavelet Families,” Glob. J. Engg. Appl. Sci. 2013 3, vol. 3, no. 1, pp. 8–13, 2013.
C. Boya, M. Ruiz-Llata, J. Posada, and J. A. Garcia-Souto, “Identification of multiple partial discharge sources using acoustic emission technique and blind source separation,” IEEE Trans. Dielectr. Electr. Insul., vol. 22, no. 3, pp. 1663–1673, 2015, doi: 10.1109/TDEI.2015.7116363.
T. Boczar, S. Borucki, A. Cichoń, and D. Zmarzły, “Application possibilities of artificial neural networks for recognizing partial discharges measured by the acoustic emission method,” IEEE Trans. Dielectr. Electr. Insul., vol. 16, no. 1, pp. 214–223, 2009, doi: 10.1109/TDEI.2009.4784570.
X. Zhou, C. Zhou, and I. J. Kemp, “An improved methodology for application of wavelet transform to partial discharge measurement denoising,” IEEE Trans. Dielectr. Electr. Insul., vol. 12, no. 3, pp. 586–594, 2005, doi: 10.1109/TDEI.2005.1453464.
E. Agletdinov, D. Merson, and A. Vinogradov, “A new method of low amplitude signal detection and its application in acoustic emission,” Appl. Sci., vol. 10, no. 1, pp. 1–14, 2020, doi: 10.3390/app10010073.
R. Hussein, K. B. Shaban, and A. H. El-Hag, “Wavelet Transform with Histogram-Based Threshold Estimation for Online Partial Discharge Signal Denoising,” IEEE Trans. Instrum. Meas., vol. 64, no. 12, pp. 3601–3614, 2015, doi: 10.1109/TIM.2015.2454651.
Q. Lin, F. Lyu, S. Yu, H. Xiao, and X. Li, “Optimized Denoising Method for Weak Acoustic Emission Signal in Partial Discharge Detection,” IEEE Trans. Dielectr. Electr. Insul., vol. 29, no. 4, pp. 1409–1416, Aug. 2022, doi: 10.1109/TDEI.2022.3183662.
R. Hussein, K. B. Shaban, and A. H. El-Hag, “Energy conservation-based thresholding for effective wavelet denoising of partial discharge signals,” IET Sci. Meas. Technol., vol. 10, no. 7, pp. 813–822, 2016, doi: 10.1049/iet-smt.2016.0168.
Y. Xie, J. Tang, and Q. Zhou, “Suppressing white-noise in partial discharge measurements part 2: the optimal de-noising scheme,” Eur. Trans. Electr. POWER 2010, vol. 20, no. June 2009, pp. 1–6, 2009, doi: 10.1002/etep.
D. Ambika and V. Radha, “A comparative study between Discrete Wavelet Transform and Linear Predictive Coding,” in Proceedings of the 2012 World Congress on Information and Communication Technologies, WICT 2012, 2012, pp. 965–969. doi: 10.1109/WICT.2012.6409214.
J. Baili, S. Lahouar, M. Hergli, I. L. Al-Qadi, and K. Besbes, “Experimental Study on the Partial Discharge Characteristics of Palm Oil and Coconut Oil based Al2O3 〖A1〗_2 O_3 Nanofluids in the Presence of Sodium Dodecyl Sulfate,” NDT&E Int., vol. 42, no. 8, pp. 696–703, 2009, doi: 10.1016/j.ndteint.2009.06.003.
J. Melchiorre, A. Manuello Bertetto, M. M. Rosso, and G. C. Marano, “Acoustic Emission and Artificial Intelligence Procedure for Crack Source Localization,” Sensors, vol. 23, no. 2, Jan. 2023, doi: 10.3390/s23020693.
B. Standard, “High-voltage test techniques - Partial discharge measurements,” Eur. Comm. Electrotech. Stand., no. 3rd Edition, 2000, doi: 10.1049/joe.2018.0172.
N. Pattanadech and M. Muhr, “Comments on PDIV testing procedure according to IEC 61294,” in 2017 IEEE 19th International Conference on Dielectric Liquids, (ICDL), Manchester, United Kingdom, 25-29 June, 2017, 2017, pp. 1–4. doi: 10.1109/ICDL.2017.8124658.
Hyrax Oils Sdn. Bhd., “Hyrax Hypertrans Transformer Oil (IEC 60296 :2020) –Edition 5,” Kuala Lumpur, 2020.
F. Sipahutar et al., “Ramp Rates Effect in Ramp Method for Partial Discharge Inception Voltage Measurement in Mineral Oil,” Procedia Technol., vol. 11, pp. 608–613, 2013, doi: 10.1016/j.protcy.2013.12.235.
N. A. Mohamad, N. Azis, J. Jasni, M. Zainal, A. Ab, and R. Yunus, “Experimental Study on the Partial Discharge Characteristics of Palm Oil and Coconut Oil based Al2O3 Nanofluids in the Presence of Sodium Dodecyl Sulfate,” pp. 1–19, 2021.
Y. W. Tang, C. C. Tai, C. C. Su, C. Y. Chen, and J. F. Chen, “A correlated empirical mode decomposition method for partial discharge signal denoising,” Meas. Sci. Technol., vol. 21, no. 8, 2010, doi: 10.1088/0957-0233/21/8/085106.
IEEE, “IEEE Guide for the Detection, Location and Interpretation of Sources of Acoustic Emissions from Electrical Discharges in Power Transformers and Power Reactors,” 2018. doi: 10.1109/IEEESTD.2019.8664690.
A. H. Mohd Hashim et al., “Partial Discharge Localization in Oil Through Acoustic Emission Technique Utilizing Fuzzy Logic,” IEEE Trans. Dielectr. Electr. Insul., vol. 29, no. 2, pp. 623–630, 2022, doi: 10.1109/TDEI.2022.3157911.
K. Ibrahim, R. M. Sharkawy, M. M. A. Salama, and R. Bartnikas, “Realization of Partial Discharge Signals in Transformer Oils Utilizing Advanced Computational Techniques,” 2012.
L. Litwin, “FIR and IIR digital filters,” IEEE Potentials, vol. 19, no. 4, pp. 28–31, 2000, doi: 10.1109/45.877863.
L. Song, “Position location of partial discharges in power transformers using fiber acoustic sensor arrays,” Opt. Eng., vol. 45, no. 11, p. 114401, 2006, doi: 10.1117/1.2390681.
M. Quizhpi-Cuesta, F. Gómez-Juca, W. Orozco-Tupacyupanqui, and F. Quizhpi-Palomeque, “An alternative method for Partial Discharges measurement using digital filters,” 2017 10th Int. Symp. Adv. Top. Electr. Eng. ATEE 2017, pp. 92–97, 2017, doi: 10.1109/ATEE.2017.7905172.
S. Sriram, S. Nitin, K. M. M. Prabhu, and M. J. Bastiaans, “Signal denoising techniques for partial discharge measurements,” IEEE Trans. Dielectr. Electr. Insul., vol. 12, no. 6, pp. 1182–1191, 2005, doi: 10.1109/TDEI.2005.1561798.
S. Chakraborty, “Advantages of Blackman Window over Hamming Window Method for designing FIR Filter,” Int. J. Comput. Sci. Eng. Technol., vol. 4, no. 08, pp. 1181–1189, 2013, [Online]. Available: http://ijcset.com/docs/IJCSET13-04-08-030.pdf
A. Swedan, A. H. El-Hag, and K. Assaleh, “Acoustic detection of partial discharge using signal processing and pattern recognition techniques,” Insight Non-Destructive Test. Cond. Monit., vol. 54, no. 12, pp. 667–672, 2012, doi: 10.1784/insi.2012.54.12.667.
M. Harbaji, K. Shaban, and A. El-Hag, “Classification of common partial discharge types in oil-paper insulation system using acoustic signals,” IEEE Trans. Dielectr. Electr. Insul., vol. 22, no. 3, pp. 1674–1683, 2015, doi: 10.1109/TDEI.2015.7116364.
Y. Xie, J. Tang, and Q. Zhou, “Suppressing white-noise in partial discharge measurements—part 1: construction of complex Daubechies wavelet and complex threshold,” Eur. Trans. Electr. POWER 2010, vol. 20, no. June 2009, pp. 800–810, 2009, doi: 10.1002/etep.
S. M. Joseph, F. S. A, and B. A. P, “Comparing Speech Compression Using Waveform Coding and Parametric Coding,” Int. J. Electron. Eng., vol. 3, no. 1, pp. 35–38, 2011.
W. Chen, “Importance Evaluation Method on the Fault Modes of Power Transformer Based on Trapezoidal Fuzzy Number,” no. Ii, pp. 5–6, 2012.
Y. V. Thien et al., “Investigation on the lightning breakdown voltage of Palm Oil and Coconut Oil under non-uniform field,” Conf. Proceeding - 2014 IEEE Int. Conf. Power Energy, PECon 2014, no. November, pp. 1–4, 2014, doi: 10.1109/PECON.2014.7062402.
B. Vigneshwaran, R. V. Maheswari, and P. Subburaj, “An Improved Threshold Estimation Technique for Partial Discharge Signal Denoising Using Wavelet Transform,” Proc. IEEE Int. Conf. Circuit, Power Comput. Technol. ICCPCT 2013, pp. 300–305, 2013, doi: 10.1109/ICCPCT.2013.6528823.
V. C. Thuc and H. S. Lee, “Partial Discharge (PD) Signal Detection and Isolation on High Voltage Equipment Using Improved Complete EEMD Method,” Energies, vol. 15, no. 16, Aug. 2022, doi: 10.3390/en15165819.
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