FPGA realization of wavelet transform for detection of electric power system disturbances

Abstract

Realization of wavelet transform on field-programmable gate array (FPGA) device for the detection of power system disturbances is proposed in this paper. This approach provides an integral signal-processing paradigm, where its embedded wavelet basis serves as a window function to monitor the signal variations very efficiently. By using this technique, the time information and frequency information can be unified as a visualization scheme, facilitating the supervision of electric power signals. To improve its computation performance, the proposed method starts with the software simulation of wavelet transform in order to formulate the mathematical model. This is followed by the circuit synthesis and timing analysis for the validation of the designated circuit. Then, the designated portfolio can be programmed into the FPGA chip through the download cable. And the completed prototype will be tested through software-generated signals and utility-sampled signals, in which test scenarios covering several kinds of electric power quality disturbances are examined thoroughly. From the test results, they support the practicality and advantages of the proposed method for the applications.Index Terms-Disturbances, field-programmable gate array (FPGA), wavelet transform.

Expert System for Power Quality Disturbance Classifier

“…At the end of the first level of signal decomposition, the resulting vectors and are the level 1 wavelet coefficients of approximation and of detail, respectively. In fact, for the first level, these wavelet coefficients are called and , respectively, as stated in (3) and (4) [11] (3) 4In the same manner, the calculation of the subsequent approximated and the detailed version associated with the level 2 is based on the level 1 wavelet coefficient of approximation . The process iterates, always adopting the " " level wavelet coefficient of approximation to calculate the " " level approximated and detailed wavelet coefficients.…”

“…Over the last ten years a number of different approaches to the PQ disturbance analysis using intelligent methods were suggested. In one of the research [3], DWT is employed to detect PQ disturbances. This approach unifies time and frequency information and provides an integral signal-processing paradigm, where its embedded wavelet basis serves as a window function to monitor the signal variations efficiently.…”

Field Programmable Gate Array Applications—A Scientometric Review

“…These have been implemented for image processing [527,1582,1583], pattern recognition [476,1584], real-time processing [671,1477,1585], melanoma cancer detection [510,511,1586,1587], speech recognition [1587,1588] and so forth. Digital signal processing techniques implementations in FPGAs covers FFT [537,[1589][1590][1591][1592][1593], DWT [597,[1594][1595][1596][1597], time-to-digital converters [1598][1599][1600][1601][1602], DCT [580,[1603][1604][1605] and digital filters like FIR filter [56,612,[1606][1607][1608], Kalman filter [620,[1609][1610][1611], median filter [1612,1613], LMS [1614]…”

Discriminação em tempo real de sinais de peixes elétricos pulsadores usando FPGAs

“…Apesar de não conhecermos nenhum trabalho a respeito da implementação desse tipo de transformada wavelet em FPGAs, outras famílias são largamente abordadas na literatura. [85][86][87][88][89][90][91] Porém, como toda transformada wavelet é composta essencialmente pelas mesmas operações básicas de aplicação de um conjunto de filtros de resposta ao impulso finita, podemos adaptar facilmente as mesmas arquiteturas atualmente descritas na literatura.…”