Normalized Embedded Zero-tree Wavelet Coding Applied in Tracking DC Arc Furnace Characteristics Considering Data Compression

摘要

The application of data compression technique using the normalized embedded zero-tree wavelet (NEZW) coding is presented for the long-duration monitoring of a DC electric arc furnace, where voltage fluctuation and loading fluctuation are critical and stochastic load characteristics. While keep enough stochastic load information, it is desired to reduce data size in long duration recording of voltage and current waveforms. The effects of multi-resolution analysis levels and threshold values in the NEZW coding are investigated. From the calculation results of field measurement data, the NEZW coding almost preserves the values of voltage fluctuation and power quantities. For storage of the field measurement voltage and current waveforms, the NEZW coding can not only greatly reduce data size, but it also can preserve sufficient load information.