基于二维DCT的电能质量监测数据压缩方法  

A compression approach of power quality monitoring data based on two-dimension DCT

作　　者：胡志坤[1] 何志敏[1] 安庆[2] 孙克辉[1] 丁家峰[1] 

机构地区：[1]中南大学物理科学与技术学院,湖南长沙410083 [2]河南省电力公司周口供电公司,河南周口466001

出　　处：《中南大学学报（自然科学版）》2011年第4期1021-1027,共7页Journal of Central South University:Science and Technology

基　　金：国家自然科学基金资助项目(60904077);深圳市科技计划基础研究项目(JC200903180555A)

摘　　要：为处理大量的电能质量监测数据,提出一种基于分块二维DCT算法的电能质量监测数据的压缩方法。该方法按周期倍数将电能质量监测数据进行截断和重组,构成二维表示的电能质量监测数据。对二维电能质量监测数据按照8×8矩阵进行分块,并对每个分块矩阵进行二维DCT变换。将所有分块矩阵中同一位置的元素提取出来构成分块重排矩阵,每个分块重排矩阵中的元素处在同一个能量级。根据分块重排矩阵的平均能量对重排矩阵进行量化,得到的量化矩阵和保留的分块重排矩阵作为压缩的结果数据。仿真结果表明:当均方误差为3.89%时,压缩比可以达到82.8%。A compression approach of power quality monitoring data based on two-dimension discrete cosine transform（DCT） was presented to deal with huge data about power quality event detection.The monitoring data was truncated and recomposed in multiple cycles to transform the one-dimension data into the two-dimension data,which was a matrix in essence.The matrix was divided into some sub-blocks,which were all 8×8 matrices.These matrices were performed by two-dimension DCT.The elements at the same location of all sub-matrices formed a new matrix,and the elements were at the equivalent energy level.The energy levels of new matrices were measured by average energy,and quantitative matrix was obtained by a threshold of average energy.The new matrices and quantitative matrix were used to represent the monitoring data set.The simulation result shows that the data compression ratio can reach 82.8% when the mean square deviation is 3.89%.

关 键 词：离散余弦变换 电能质量监测 数据压缩 

分 类 号：TM933.4[电气工程—电力电子与电力传动]