TY - CONF
T1 - Fault diagnosis in power lines using Hilbert transform and fuzzy classifier
AU - Rivera-Calle, F. M.
AU - Minchala-Ávila, L. I.
AU - Montesdeoca-Contreras, J. C.
AU - Morales-Garcia, J. A.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - © 2015 IEEE. Early detection of faults in power lines allows improve the service quality and therefore a reduction in high operating costs that a failure of this type implies. This paper describes a method used to determine the type of failure occurs in a three-phase over time, using tools as Hilbert transform and fuzzy classifier for successful detection is done. The algorithm developed uses each of the power lines phases which are analyzed in its angle of coverage and its variation in time, after this analysis the results classified by a classifier Fuzzy c-means. This classifier makes groups of fault data and no-fault data. The results show a high performance in classified values near to zero as correct.
AB - © 2015 IEEE. Early detection of faults in power lines allows improve the service quality and therefore a reduction in high operating costs that a failure of this type implies. This paper describes a method used to determine the type of failure occurs in a three-phase over time, using tools as Hilbert transform and fuzzy classifier for successful detection is done. The algorithm developed uses each of the power lines phases which are analyzed in its angle of coverage and its variation in time, after this analysis the results classified by a classifier Fuzzy c-means. This classifier makes groups of fault data and no-fault data. The results show a high performance in classified values near to zero as correct.
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U2 - 10.1109/ESARS.2015.7101420
DO - 10.1109/ESARS.2015.7101420
M3 - Paper
T2 - Electrical Systems for Aircraft, Railway and Ship Propulsion, ESARS
Y2 - 1 January 2015
ER -