Lightning and Switching Overvoltage Identification Based on Singular Value Decomposition of Time-Frequency Matrix and Multi-Level Support Vector Machine
Bin Dai · Power System Technology · 2012
It is significant for improving and enhancing insulation coordination level of power system to identify lightning and switching surges.Based on singular value decomposition(SVD) of time-frequency matrix and support vector machine(SVM),a method to identify lightning and switching surges is proposed.Through applying wavelet decomposition to voltage signals a multi-scale time-frequency matrix is constructed,then this time-frequency matrix is decomposed by SVD and the signal components are decomposed into different time-frequency characteristic subspaces to attain singular spectrum of voltage signal,and characteristic quantities of singular spectrum are calculated and taken them as the input vectors of multilevel SVM to identify lightning and switching surges.Calculation results of five overvoltage signals measured in a certain substation show that the dimensionality of the extracted characteristic quantities is low and extracted characteristic quantities possess relative stability to electromagnetic disturbances in overvoltage signals;less training samples are needed for the proposed identification method that exists high recognition rate.Thus,using the proposed method,lightning and switching surges can be classified accurately.