Discrimination of power transformer inrush and internal fault current using time to time transform and fault classification using fuzzy clustering

Maǧallaẗ al-abḥāṯ al-handasiyyaẗ

关键词: Inrush current;    internal fault current;    parseval’s theorem;    fault classification;    TT-transform;    fuzzy clustering and wavelet transform.;   

DOI  :  

来源: DOAJ

【 摘 要 】

A new approach is attempted for the differential protection of power transformer using advanced signal processing such as time to time transform along with Fuzzy clustering technique. The time-time representation is derived from inverse Fourier transform of S-transform, a method of representation of real time series as a set of complex, time local spectra. Here, TT-transform used to generate time-time TT contour) from the samples of differential current. Parseval’s theorem extracts the features like energy and standard deviations. Later these features are used as inputs to the Fuzzy clustering to distinguish inrush current, external fault current and internal fault current. Simulation of the fault (with and without noise) was done using MATLAB/SIMULINK software taking 2 cycles of data from each 400 samples. The advantage of the proposed algorithm provides accurate results even in the presence of noise inputs (energy and standard deviations).

【 授权许可】

Unknown