DSP-FPGA Based Real-time Power Quality Disturbances Classifier

This paper describes an real-time classification method of power quality (PQ) disturbances based on DSP-FPGA. The proposed method simultaneously uses the results obtained in the application of a series of RMS values and the discrete Fourier transform to the power signal waveform. A series of RMS values are used for estimation of the time-related parameters of the PQ disturbances and the discrete Fourier transform is used for confirmation of the frequency-related parameters of the PQ disturbances. Without adding the computational burden, both the elementary parameters of the power signal and the type of PQ disturbance are obtained easily. A simple and effective methodology for classification of nine typical kinds of PQ disturbances is proposed in this paper. Five distinguished time-frequency statistical features of each type of PQ disturbances are extracted. Using a rule-based decision tree (RBDT), the PQ disturbances pattern can be recognized easily and there is no need to use other complicated classifiers. Finally, the method is also tested using both simulated disturbances and disturbances measured using an initial development instrument. Different experimental results show the good performance of this proposed approach. Real-time calculating time based on DSP is also taken into consideration to show the effectiveness of the proposed method.