Application of Pattern Recognition Techniques to non Invasive Insulation Monitoring

Bezerra, J. M. B.; Aquino, Ronaldo R. B. de; Oliveira, Josinaldo B. de; Silveira, Tatiana Maria Andrade da; Costa, Edson Guedes da; Neri, M.G.G.; Ferreira, Tarso Vilela; Dantas, J.L.P.; Mendonca, Pramila

doi:10.1109/elinsl.2008.4570287

Cited by 4 publications

(3 citation statements)

References 2 publications

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“…The present project was preliminarily submitted to studies and laboratory experiments that delineated the way to new researches [1]. Those previous studies were done between May 2006 and February 2008.…”

Section: Pilot Experimentsmentioning

confidence: 99%

“…ith the objective to prevent failures in electrical distribution systems, due to insulators problems, monitoring processes throughout visual inspections or special sensors are predictive actions of great value to trade companies and to the society in itself [1]. These failures cause interruptions in energy supply and must be avoided due to big disturbances caused by these kinds of occurrences.…”

Section: Introductionmentioning

confidence: 99%

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An experimental distribution line to develop a polymeric insulator monitoring system

Bezerra

Silva

Neto

et al. 2012

2012 Annual Report Conference on Electrical Insulation and Dielectric Phenomena

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Polymeric insulators used in 13.8 kV distribution network are presenting premature damage due to cavity inner dielectric. With the objective to develop a diagnostic process, it was constructed an experimental distribution line in Universidade Federal de Pernambuco (UFPE) campus. In this article it will be described this experimental line characteristics and performed studies to plan its construction.

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Section: Pilot Experimentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An experimental distribution line to develop a polymeric insulator monitoring system

Bezerra

Silva

Neto

et al. 2012

2012 Annual Report Conference on Electrical Insulation and Dielectric Phenomena

View full text Add to dashboard Cite

show abstract

“…Current pattern recognition methods have tended to use artificial intelligence, including expert systems, fuzzy theory, genetic algorithms, neural networks, and other methods. Among these methods, artificial neural networks have the unique capability of processing nonlinear information and distributed storage ways for information [5].…”

Section: The Classification and Recognition Of The Radial Basis Functmentioning

confidence: 99%

Study on the recognition method of airport perimeter intrusion incidents based on laser detection technology

Wu¹,

Wang²,

Wang³

2017

Turk J Elec Eng & Comp Sci

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Currently, detection technology is very important for airport perimeter security. When the perimeter is invaded or destroyed, the perimeter security alarm system can promptly alert personnel. In this paper, based on analysis and comparison of several detection technologies commonly used in airport perimeter security and according to the characteristics of airport perimeters and laser detection, an airport perimeter security alarm system based on laser detection is proposed. It analyzes factors that affect the performance of a laser alarm system, divides intrusions into six categories, estimates the different alarm thresholds by testing, and judges the intrusion category according to the number of blocked laser beams and the duration of the block. In order to improve the rapid response and the robustness of the system, it uses a pattern recognition method based on radial basis function neural network technology to train and learn different samples of intrusion categories, uses the classifier to determine the cluster center of each sample node, and uses the weights of the center variance and the weights of hidden nodes to establish the alarm curve of each intrusion category. Meanwhile, when the feature value of an intrusion sample is distributed along the classification boundary of two categories, it uses Bayes' theorem to calculate the probability of an invasive category to reduce the false alarm risk.According to sample testing, the above recognition method of airport intrusions based on laser detection technology effectively improves the intrusion detection probability.

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Thermography and artificial intelligence in transformer fault detection

2017

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Application of Pattern Recognition Techniques to non Invasive Insulation Monitoring

Cited by 4 publications

References 2 publications

An experimental distribution line to develop a polymeric insulator monitoring system

An experimental distribution line to develop a polymeric insulator monitoring system

Study on the recognition method of airport perimeter intrusion incidents based on laser detection technology

Thermography and artificial intelligence in transformer fault detection

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