基于二维提升整数小波的电能质量数据压缩技术

发布时间：2018-07-11 10:13

本文选题：电能质量 + 数据压缩　；参考：《兰州理工大学学报》2016年06期

【摘要】：为了更好地解决海量录波数据存储空间过大,数据传输效率低的问题,提出将二维提升小波、游程编码、哈夫曼编码相结合的数据压缩方法.首先将实时检测的一维电能质量数据按照周期截取,并依次排列形成二维的数据,对该数据进行二维提升小波分解得到低频系数和高频系数,然后对高频系数进行阈值量化,最后将量化后的数据与低频系数用零行程和哈夫曼进行编码,以进一步提高数据的压缩比.仿真实验结果表明,本文算法相比较传统的二维离散小波算法,能在压缩比提高一倍左右时将误差限制在很小的范围内.
[Abstract]:In order to solve the problem of too large storage space and low efficiency of data transmission, a data compression method combining 2-D lifting wavelet, run length coding and Huffman coding is proposed. First, the one dimensional power quality data detected in real time is intercepted according to the period, and then arranged in order to form two dimensional data. The data is decomposed into two dimensional lifting wavelet transform to obtain the low frequency coefficient and high frequency coefficient, then the threshold value of the high frequency coefficient is quantified. Finally, the quantized data and the low frequency coefficients are coded with zero stroke and Huffman to further improve the compression ratio of the data. The simulation results show that compared with the traditional two-dimensional discrete wavelet algorithm, the proposed algorithm can limit the error to a very small range when the compression ratio is doubled or so.
【作者单位】：兰州理工大学电气工程与信息工程学院;
【基金】：国家自然科学基金(51267011)
【分类号】：TM711

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