二维离散小波变换电能质量数据压缩算法

摘要

This paper proposed combination of Self-Adaptive Frequency Statistic Compression ( SAFSC ) and Self-Adaptive Energy Threshold ( SAET ) to compress the power quality data which has raised a high requirement on the compression ratio and the quality of reconstruction. Firstly, one-dimensional power quality data were mapped into two-dimensional matrix and the boundary of the matrix was extended. Then two-dimensional discrete wavelet transform was implemented. On the basis of bitmap compression algorithm, loseless compression of low frequency data was realized based on the balance of the decrease in data volume and the increase in flags. The threshold was determined automatically according to the percentage of energy that all parts account for. Compression of high frequency data was realized by using a modified sparse matrix represented by list of 3-tuples. Respectively, SAFSC and SAET were used to compress coefficients of low and high frequency. The results indicate that the proposed method ensures the quality of reconstruction as well as increases the compression ratio greatly.%针对电能质量数据压缩对压缩比和重构质量要求高的问题，提出了低频自适应统频位图无损压缩、高频自适应能量阈值相结合的方法。首先将一维电能质量数据映射为二维矩阵，其次对二维矩阵进行边界延拓，再进行二维离散小波变换。在位图压缩算法基础上，权衡压缩后数据的减少量和标志的增加量，实现低频无损压缩。根据各部分所占的能量百分比来自动选取阈值，利用改进的稀疏矩阵三元组进行高频压缩。结果表明该方法不仅保证了压缩重构的质量而且极大地提高了压缩比。