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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  3/2019 - 6

Spectral Subband Centroid Energy Vectors Algorithm and Artificial Neural Networks for Acoustic Emission Pattern Classification

FLORENTINO, M. T. B. See more information about FLORENTINO, M. T. B. on SCOPUS See more information about FLORENTINO, M. T. B. on IEEExplore See more information about FLORENTINO, M. T. B. on Web of Science, Da COSTA, E. G. See more information about  Da COSTA, E. G. on SCOPUS See more information about  Da COSTA, E. G. on SCOPUS See more information about Da COSTA, E. G. on Web of Science, FERREIRA, T. V. See more information about  FERREIRA, T. V. on SCOPUS See more information about  FERREIRA, T. V. on SCOPUS See more information about FERREIRA, T. V. on Web of Science, GERMANO, A. D. See more information about GERMANO, A. D. on SCOPUS See more information about GERMANO, A. D. on SCOPUS See more information about GERMANO, A. D. on Web of Science
 
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Download PDF pdficon (837 KB) | Citation | Downloads: 77 | Views: 96

Author keywords
acoustic emission, artificial neural networks, condition monitoring, corona, insulators

References keywords
power(10), insulators(9), networks(7), insulation(7), systems(6), partial(6), neural(6), acoustic(6), outdoor(5), speech(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2019-08-31
Volume 19, Issue 3, Year 2019, On page(s): 49 - 56
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.03006
Web of Science Accession Number: 000486574100006
SCOPUS ID: 85072171267

Abstract
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This work proposes and evaluates a methodology for monitoring and diagnosis of polymeric insulators in operation based on the parameterization of acoustic emissions (AE) created by corona and electrical surface discharges. The parameterization was performed with the use of the spectral subband centroid energy vectors (SSCEV) algorithm, which compresses the frequency spectrum and presents the results of the AE energies in several frequency bands. Thus, it was possible to calculate the dominant acoustic emission frequencies. This parameter was used as reference for an operating point of the insulators and, therefore, it was used to classify them. This classification was correlated to the classification obtained by visual inspection in the laboratory, where the insulators were divided into three distinct classes: clean, polluted and damaged. Aiming to insert an aid to the decision-making, this work still proposes the use of artificial neural networks (ANN) for pattern recognition. In this way, we performed a sensitivity analysis of the parameters that influence the SSCEV and ANN, in order to obtain the values and configurations with higher performance. The use of Levenberg-Marquardt training algorithm has proved to be more suitable, since it showed hit rates and convergence up to 97.66 percent and 70 epochs, respectively.


References | Cited By  «-- Click to see who has cited this paper

[1] Gubanski, S. M. Dernfalk, A., Andersson J., Hillborg, H. "Diagnostic Methods for Outdoor Polymeric Insulators." IEEE Trans. Dielectrics and Electrical Insulation, vol. 14, n. 5, pp. 1065-1080, 2007.
[CrossRef] [Web of Science Times Cited 81]


[2] Cigre Working Group B2.21, "Assessment of in-service Composite Insulators by using Diagnostic Tools.", Electra, vol. 269, pp. 29-31, 2013.

[3] Al-Geelani, N. A., Piah, M. A. M., Bashir, N. "A Review on Hybrid Wavelet Regrouping Particle Swarm Optimization Neural Networks for Characterization of Partial Discharge Acoustic Signals." Renewable and Sustainable Energy Reviews, vol. 45, pp. 20-35, 2015.
[CrossRef]


[4] Herrera-Viedma, E., Lopez-Herrera, A. G. "A Review on Information Accessing Systems Based on Fuzzy Linguistic Modelling," Int. Journal of Computational Intelligence Systems, vol. 3, n. 4, pp. 420-437, 2010.
[CrossRef]


[5] Pozna, C., Precup, R., Tar, J. K., Skrjanc, I., Preitl, S. "New results in modelling derived from Bayesian filtering," Knowledge-Based Systems, vol. 23, n. 2, 2010, pp. 182-194.
[CrossRef] [Web of Science Times Cited 17]


[6] Takacs, A., Kovacs, L., Rudas, I. J., Precup, R., Haidegger, T. "Models for Force Control in Telesurgical Robot Systems," Acta Polytechnica Hungarica, vol. 12, n. 8, 2015, pp. 95-114.
[CrossRef]


[7] Ruiz-Rangel, J., Hernandez, C. J. A., Gonzalez, L. M., Molinares, D. J. "ERNEAD: Training of Artificial Neural Networks Based on a Genetic Algorithm and Finite Automata Theory," Int. Journal of Artificial Intelligence, vol. 16, n. 1, 2018, pp 214-253.

[8] Gorur, R. S., Cherney, E. A., Burnham, J. T. Outdoor insulators, 1st ed. Phoenix: Ravi S. Gorur Inc., 1999.

[9] Vosloo, W. L., Macey, R. E., Tourreil, C. The Practical Guide to High Voltage Insulators. South Africa: Crown Publications cc, vol. 3, pp. 220, 2006.

[10] Ramirez, C., Moore, P. J. "Identification of surface discharges over new and aged polymeric chain insulators using a non invasive method", In: IEEE Proc. 41st Int. Universities Power Eng. Conf., 2006. pp. 903-906.
[CrossRef] [Web of Science Times Cited 4]


[11] Ferreira, T. V., Germano, A. D., Costa, E. G. "Ultrasound and Artificial Intelligence Applied to the Pollution Estimation in Insulations." IEEE Trans. Power Delivery, vol. 12, pp. 583-589, 2012.
[CrossRef] [Web of Science Times Cited 9]


[12] Menon. R., Kolambekar, S., Buch, N. J., Ramamoorty, M. "Correlation of acoustic emission method and electrical method for detection of partial discharges in transformers," in Proc. IEEE 7th Int. Conf. Solid Dielectrics, pp. 299-302, Jun. 2001.
[CrossRef] [Web of Science Times Cited 5]


[13] Muniraj, C., Chandrasekar, S. "Condition Monitoring of Outdoor Polymeric Insulators Using Wavelets and ANFIS", In: IEEE Int. Conf. on Power and Energy, Kuala Lumpur, 2010, pp. 346-351.
[CrossRef]


[14] Nyamupangedengu, C., Luhlanga, L. P., Letlape T. "Acoustic and HF Detection of Defects on Porcelain Pin Insulators", In: IEEE Power Eng. Society Conf. and Expo. in Africa, Johannesburg, 2007.
[CrossRef]


[15] Shurrab, I. Y., El-Hag, A., Assaleh, K., Ghunem, R. "Partial Discharge On-Line Monitoring of Outdoor Insulators", In: IEEE Int. Symp. on Electrical Insulation, San Juan, 2012, pp. 391-394.
[CrossRef]


[16] Gorur, R. S., Chang, J. W., Amburgey, O. G. "Surface hydrophobicity of polymers used for outdoor insulation", IEEE Trans. Power Delivery, vol. 5, n. 4, pp. 1923-1933, 1990.
[CrossRef] [Web of Science Times Cited 72]


[17] Huang, C. M., Huang, Y. C. "A novel approach to real-time economic emission power dispatch", IEEE Trans. Power Systems, vol. 18, n. 1, 2003, pp. 288-294,
[CrossRef] [Web of Science Times Cited 31]


[18] Kreuger, F. H., Gulski, E., Krivda, A. "Classification of partial discharges", IEEE Trans. Electrical Insulation, vol. 28, n. 6, 1993. pp. 917-931.
[CrossRef] [Web of Science Times Cited 170]


[19] Ferreira, T. V., Germano, A. D., Silva, K. M., Costa, E. G. "Ultra-sound and Artificial Intelligence Applied to the Diagnosis of Insulations in the Field." High Voltage Engineering, vol. 38, n. 8, pp. 20061-20066, 2012.

[20] Harrold, R. T. "Acoustic Waveguides for Sensing and Locating Electrical Discharges in High Voltage Power Transformers and other Apparatus." IEEE Trans. Power Apparatus and Systems, vol. 98, n. 2, pp. 449-457, 1979.
[CrossRef] [Web of Science Times Cited 16]


[21] Lundgaard, L. E. "Partial Discharge XIII: acoustic partial discharge detection-fundamental considerations." IEEE Electrical Insulation Magazine, vol. 8, pp. 25-31, 1992.
[CrossRef]


[22] Abdel-Salam, M., Abdel-Sattar, S., Sayed, Y., Ghally, M. "Early Detection of Weak Point in MEEC Distribution System." In: Industry Applications Conf. Record of the 2001 IEEE, 2001, Chicago. vol. 4, pp. 2541-2545.
[CrossRef]


[23] Rocha, P. H. V., Fontgalland, G. "Measuring the radiation bands of overhead power lines glass insulators". Proc. of the IEEE 2014 Int. Conf. Antenna Measurements & Applications. France, 2014.
[CrossRef]


[24] Dawson, G. A., Richards, C. N., Krider, E. P., Uman, M. A. "The Acoustic Output of a Long Spark". Journal of Geophysical Research, vol. 73, pp. 815-816, 1968.
[CrossRef]


[25] Harrold, R. T. "Acoustical Technology Applications in Electrical Insulation and Dielectrics." IEEE Trans. Electrical Insulation, vol. 20, n. 1, pp. 3-19, 1985.
[CrossRef] [Web of Science Times Cited 36]


[26] Gajic, B., Paliwal, K. K. "Speech Parametrization for Automatic Speech Recognition in Noisy Conditions," in: Proc. Norwegian Symp. Signal Processing, Trondheim, 2001.

[27] Paliwal, K. K. "Spectral Subband Centroid Features for Speech Recognition," in: Int. Conf. Acoustics, Speech and Signal Processing, Seattle, vol. 2, pp. 617-620, 1998.
[CrossRef]


[28] McCulloch, W. S., Pitts, W. "A Logical Calculus of the Ideas Immanent in Nervous Activity." Bulletin of Mathematical Biophysics, vol. 5, pp. 115-133, 1943.
[CrossRef]


[29] Haykin, S. O. Neural Networks and Learning Machines. 3. ed. New Jersey: Pearson Prentice Hall, 2008.

[30] Rosenblatt, F. "The Perceptron: A probabilistic model for information storage and organization in the brain," Psychological Review, vol. 65, pp. 386-408.
[CrossRef]


[31] Riedmiller, M., Braun, H. "RPROP - A Fast Adaptive Learning Algorithm", In: Int. Symp. Computer and Information Science, 1993.
[CrossRef]


[32] Hagan, M. T, Menhaj, M. B. "Training Feedforward Networks with the Marquardt Algorithm," IEEE Trans. Neural Networks, vol. 5, pp. 989-993, 1994.
[CrossRef] [Web of Science Times Cited 3881]


[33] Bishop, C. M. Neural Networks for Pattern Recognition. Clarendon Press, Oxford. 1995.

[34] Kalman, B. L., Kwasny, S. C. "Why tanh: choosing a sigmoidal function." In: Int. Joint Conf. Neural Networks, 1992, Baltimore. vol. 2, pp. 578 - 581.
[CrossRef]




References Weight

Web of Science® Citations for all references: 4,322 TCR
SCOPUS® Citations for all references: 0

Web of Science® Average Citations per reference: 123 ACR
SCOPUS® Average Citations per reference: 0

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2019-10-14 21:29 in 171 seconds.




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