A simple method,based on harmonic wavelet analysis is proposed for the decomposition of a given energy bounded signal into a periodic signal and a pulse.Alike a denoising method,the first part signal it might represen...A simple method,based on harmonic wavelet analysis is proposed for the decomposition of a given energy bounded signal into a periodic signal and a pulse.Alike a denoising method,the first part signal it might represent a smooth periodic function while the pulse is a singular unpredicted perturbation (taken as a fault).It will be shown that,under some general conditions,by a simple projection into two disjoint space of functions we can easily separate the periodic component of the signal from the fault (represented by the singular pulse).展开更多
This paper presents an approach for shunt faults detection and classification in transmission line using Support Vector Machine （SVM）. The paper compares between using three line post-fault current samples for one-h...This paper presents an approach for shunt faults detection and classification in transmission line using Support Vector Machine （SVM）. The paper compares between using three line post-fault current samples for one-half cycle and one-fourth cycle from the inception of the fault as inputs for SVM. Two SVMs are used, first SVMabc is used for faulty phase detection and second SVMg is used for ground detection. SVMs with polynomial kernel with different degrees are used to obtain the best classification score. The classification test results show that the proposed method is accurate and reliable.展开更多
文摘A simple method,based on harmonic wavelet analysis is proposed for the decomposition of a given energy bounded signal into a periodic signal and a pulse.Alike a denoising method,the first part signal it might represent a smooth periodic function while the pulse is a singular unpredicted perturbation (taken as a fault).It will be shown that,under some general conditions,by a simple projection into two disjoint space of functions we can easily separate the periodic component of the signal from the fault (represented by the singular pulse).
文摘This paper presents an approach for shunt faults detection and classification in transmission line using Support Vector Machine （SVM）. The paper compares between using three line post-fault current samples for one-half cycle and one-fourth cycle from the inception of the fault as inputs for SVM. Two SVMs are used, first SVMabc is used for faulty phase detection and second SVMg is used for ground detection. SVMs with polynomial kernel with different degrees are used to obtain the best classification score. The classification test results show that the proposed method is accurate and reliable.
