{"title":"LabVIEW with Fuzzy Logic Controller Simulation Panel for Condition Monitoring of Oil and Dry Type Transformer","authors":"N. A. Muhamad, S.A.M. Ali","volume":20,"journal":"International Journal of Electrical and Computer Engineering","pagesStart":1685,"pagesEnd":1692,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/5002","abstract":"Condition monitoring of electrical power equipment\r\nhas attracted considerable attention for many years. The aim of this\r\npaper is to use Labview with Fuzzy Logic controller to build a\r\nsimulation system to diagnose transformer faults and monitor its\r\ncondition. The front panel of the system was designed using\r\nLabVIEW to enable computer to act as customer-designed\r\ninstrument. The dissolved gas-in-oil analysis (DGA) method was\r\nused as technique for oil type transformer diagnosis; meanwhile\r\nterminal voltages and currents analysis method was used for dry type\r\ntransformer. Fuzzy Logic was used as expert system that assesses all\r\ninformation keyed in at the front panel to diagnose and predict the\r\ncondition of the transformer. The outcome of the Fuzzy Logic\r\ninterpretation will be displayed at front panel of LabVIEW to show\r\nthe user the conditions of the transformer at any time.","references":"[1] Arshad M, I.S.M., Power Transformer Critical Diagnostics for\r\nReliability and Life Extension. CCECE 2004-CCGEI 2004, 2004: p.\r\n625-628.\r\n[2] Gockenbach E, W.P., Borsi H, Monitoring and Diagnostic System for\r\nDry-Transformers. IEEE 7th International Conference on Solid\r\nDielectric Eindhoven the Netherlands, 2001: p. 291-294.\r\n[3] Song Y.H, A.T.J., Application of Fuzzy Logic in Power System: Part 2\r\nComparison and integration with expert systems, neural networks and\r\ngenetic algorithms. Power Engineering Journal, 1998: p. 219-222.\r\n[4] Song Y.H, A.T.J., Application of Fuzzy Logic in Power System: Part 1\r\nGeneral Introduction to Fuzzy Logic. Power Engineering Journal, 1997.\r\n11(5): p. 219-222.\r\n[5] Huang Y.C, Y.H.T., Huang C.L, Developing a New Transformer Fault\r\nDiagnosis System through Evolutionary Fuzzy Logic. IEEE Transaction\r\non Power Delivery, 1997. 12(2): p. 761-767.\r\n[6] Saleh S.A, R.M.A., Modeling and Protection of a Three-Phase\r\nTransformer Using Wavelet Packet Transform. IEEE Transaction on\r\nPower Delivery, 2005. 20(2): p. 1273-1282.\r\n[7] Zhang G, L.Y.S., Ibuka S, Yasuoka K, Isihi S., Application of Fuzzy\r\nData Processing for Fault Diagnosis for Power Transformer. High\r\nVoltage Engineering Symposium, 1999. -(467): p. 160-163.\r\n[8] Kim J.W, P.B.K., Jeong S.C, Kim S.W, Park P.G, Fault Diagnosis of a\r\nPower Transformer Using an Improved Frequency-Response Analysis.\r\nIEEE Transaction on Power Delivery, 2005. 20(1): p. 169-178.\r\n[9] Higa, M.L.T., D.M; Lord, S.M.;, An Introduction to LabVIEW Exercise\r\nfor An Electronic Class. 32nd Annual Frontiers in Education 2002, FIE\r\n2002, 2002. 1: p. 6-9.\r\n[10] Fountain, T., Software advances in measurement and instrumentation.\r\nIEE Colloquium on Software Instrumentation - Software Components,,\r\n2004: p. 1-45.\r\n[11] Karen L. B.P, B.M., Mausavi M.J, Peter P.B, Experimental Investigation\r\nof Internal Short Circuit Fault Leading to Advanced Incipient Behavior\r\nand Failure of Distribution Transformer. IEEE Trans., 2004.\r\n[12] Dr. Sarma S, K.G.N.S., ANN Approach For Condition Monitoring of\r\nPower Transformer Using DGA. IEEE International Conference, 2004:\r\np. 444-447.\r\n[13] Islam S.M, W.T., Ledwich G., A Novel Fuzzy Logic Approach to\r\nTransformer Faults Diagnosis. IEEE Transaction on Dielectric and\r\nElectrical Insulation, 2000. 7(2): p. 177-186.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 20, 2008"}