FPGA Applications in Discrete Wavelet Transform and Real-Time Monitoring of Voltage Sag

• Main Authors: Ming Hung Hu, 胡名宏
• Other Authors: Wen Ren Yang
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/33220935463715059189

碩士 === 國立彰化師範大學 === 電機工程學系 === 97 === With rapid development of technology, accurate equipment or operation of production line machine that worked for a long time, that power quality requirement for more stringent, and the interference event in the power quality monitoring have become relatively more important, therefore the analysis of power quality measurement and analysis necessary to be more efficient. The references in the power quality research, the digital signal processing methods for the use of discrete wavelet transform, and its analysis in a serial input signal to input the discrete wavelet transformation, and to calculate the average power. When the voltage interfere with the event occurred , the signal power will change. In the analysis of discrete signal processing, as point by point approach, but real-time monitoring system can not use this signal processing approach. Therefore in this paper proposes the sub-signal processing methods, when the signal input to its temporary buffer, and as the signals at zero-crossover point to carry out the sub-signal input to the DWT, and to calculation of their average range. From the average value of each interval, to observe high-frequency signal and low-frequency signal changes; again its power as a characteristic value, using probability neural network to identification and classification, in order to achieve real-time monitoring system; and its architecture the use of the state controller, multiplexer, demultiplexer, a group of high-pass filter and six groups of low-pass filter, and analysis wavelet coefficients and of interval power. In this paper, analytical methods for the use of Matlab simulation of discrete wavelet filters, and Quartus II and DSPBuilder as a hardware description language design and downloaded to the FPGA hardware board to carry out analysis and the use of RAM on-board to analysis of data storage, and then using Matlab to carry out neural network simulation of probability in order to achieve the power quality monitoring system of measurement.