NDLI: Intelligent System for Detecting Failures in the Switching of Isolators in Power Substations

Content Provider	IEEE Xplore Digital Library
Author	Lambert-Torres, G. Carrasco, A.C. da Silva, L.E.B. Coutinho, M.P. Santo, D.E.
Copyright Year	2008
Description	Author affiliation: Fed. Univ. at Itajuba, Itajuba (Lambert-Torres, G.; Carrasco, A.C.; da Silva, L.E.B.; Coutinho, M.P.) \|\| Neoenergia Group, Iberdrola, Recife (Santo, D.E.)
Abstract	The purpose of this paper is to present the development of a system capable of detecting incipient malfunction and also verify the correct operation of opening and closing of high voltage switches thru digital analysis of the torque curve supplied by the drive engine during the maneuvers of the switch, surpassing the difficulties involved with the direct monitoring of the contacts. This system will be based on the use of dedicated devices to the digital signals processing (DSP's) associated to the algorithms of artificial neural networks, for pattern recognitions of recurrent malfunction during the maneuvers of the high voltage switches. The signals to be processed by the DSP will be the values of the torque of the drive engine, calculated by the immediate values of the electric power supplied. The real-time analysis of the curve of the torque supplied by the engine during the operations of opening and closing will make possible for an indirect monitoring of the position of the main contacts of the high power switch, increasing the trustworthiness of the electrical system's operation. The information supplied by the detection system of malfunction will allow a more efficient preventive maintenance of the switches, based on the indication of misaligned or broken components in the mechanical system of power switch.
Starting Page	1
Ending Page	6
File Size	2307120
Page Count	6
File Format	PDF
ISBN	9781424417636
DOI	10.1109/ICPST.2008.4745369
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-12
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent systems Isolators Substations Switches Torque Engines Digital signal processing Voltage Monitoring Contacts Power Equipment Neural Networks Data Mining Intelligent Systems Power Substation
Content Type	Text
Resource Type	Article

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