Title :
Hybrid algorithm for traction transformer differential protection based on intrinsic mode function energy entropy and correlation dimension
Author :
Xingjun Tian ; Yunhua Li ; Xiaqing Li
Author_Institution :
Sch. of Autom. Sci. & Electr. Eng., Beihang Univ., Beijing, China
Abstract :
This study addresses fault identification in differential protection of a V/x-type traction transformer used in a high-speed railway. To quickly and accurately identify an internal short circuit in a traction transformer, a hybrid algorithm is developed that combines intrinsic mode function (IMF) energy entropy with the correlation dimension from chaos theory. IMF energy entropy and correlation dimension are sufficiently fast and sensitive to reflect the dynamic changes in the differential-current signal from the traction transformer using different metrics; thus, this hybrid method can effectively identify an internal short circuit and magnetising inrush. Real-time simulations and actual measurements of faults illustrate the validity of the proposed method.
Keywords :
chaos; correlation methods; differential transformers; entropy; fault diagnosis; magnetisation; power transformer protection; railway electrification; traction; IMF; V-x-type traction transformer differential protection; chaos theory; correlation dimension; differential-current signal; fault identification; fault measurement; high- speed railway; internal short circuit; intrinsic mode function energy entropy; magnetising inrush;
Journal_Title :
Generation, Transmission & Distribution, IET
DOI :
10.1049/iet-gtd.2012.0653