A Real-Time Power Quality Disturbances Classification Using Hybrid Method Based on S-Transform and Dynamics
- 31 May 2013
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Instrumentation and Measurement
- Vol. 62 (9), 2465-2475
- https://doi.org/10.1109/tim.2013.2258761
Abstract
This paper proposes a real-time power quality disturbances (PQDs) classification by using a hybrid method (HM) based on S-transform (ST) and dynamics (Dyn). Classification accuracy and run time are mainly considered in our work. The HM firstly uses Dyn to identify the location of the signal components in the frequency spectrum yielded by Fourier transform, and uses inverse Fourier transform to only some of the signal components. Then features from Fourier transform, ST, and Dyn are selected, and a decision tree is used to classify the types of PQD. In order to reduce the influence of Heisenberg' s uncertainty, we proposed that different signal components are windowed by different Gaussian windows, which brings better adaption and flexibility. By the HM, run time of the application has been greatly reduced with satisfactory classification accuracy. Finally, a DSP-FPGA based hardware platform is adopted to test the run time and correctness of the proposed method under real standard signals. Field signal tests have also presented. Both simulations and experiments validate the feasibility of the new method.Keywords
This publication has 22 references indexed in Scilit:
- Classification of power system disturbances using linear Kalman filter and fuzzy-expert systemInternational Journal of Electrical Power & Energy Systems, 2012
- Effective Voltage Flicker Calculation Based on Multiresolution S-TransformIEEE Transactions on Power Delivery, 2012
- A real-time classification method of power quality disturbancesElectric Power Systems Research, 2011
- Fast Tracking of Power Quality Disturbance Signals Using an Optimized Unscented FilterIEEE Transactions on Instrumentation and Measurement, 2009
- Optimal feature selection for classification of power quality disturbances using wavelet packet-based fuzzy k-nearest neighbour algorithmIET Generation, Transmission & Distribution, 2009
- Power Quality Disturbance Classification Using Fuzzy C-Means Algorithm and Adaptive Particle Swarm OptimizationIEEE Transactions on Industrial Electronics, 2008
- PQ Monitoring System for Real-Time Detection and Classification of Disturbances in a Single-Phase Power SystemIEEE Transactions on Instrumentation and Measurement, 2008
- Hybrid S-Transform and Kalman Filtering Approach for Detection and Measurement of Short Duration Disturbances in Power NetworksIEEE Transactions on Instrumentation and Measurement, 2004
- A scalable PQ event identification systemIEEE Transactions on Power Delivery, 2000
- New measure of contrast: the dynamicsPublished by SPIE-Intl Soc Optical Eng ,1992