- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
The data compression techniques are used to enhance the storage capability of electric power quality instruments in monitoring distorted waveforms of electric arc furnaces. Both voltage flicker in voltage waveforms and harmonic components in current waveforms are major disturbances. The compression approaches by multiresolution analysis developed from the discrete wavelet transform with threshold coding and vector quantization coding are compared. The results from spectrum analysis show high compression ratios while keep low information loss. The error levels between original and reconstructed waveforms are discussed. Field measured waveforms from arc furnace loads are used to show the goodness of the data compression techniques. From the calculation results, the reconstructed voltage waveforms using threshold coding almost keep the same voltage flicker values. However, the vector quantization coding is better for harmonic distorted current waveforms. Thereafter, in the practical application of data compression for arc furnace loads, the threshold coding is used for recording voltage waveforms, and vector quantization coding for current waveforms. For the field measurement voltage and current waveforms, this method can reduce data memory size to 15.11% and 24.51%, respectively, while keep power quality characteristics. This paper provides a good approach to longtime electric power quality tracking of disturbing loads.