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 rn(DCT) was presented to deal with huge data about power quality event detection. The monitoring data was truncated and rnrecomposed in multiple cycles to transform the one-dimension data into the two-dimension data, which was a matrix in rnessence. The matrix was divided into some sub-blocks, which were all 8 × 8 matrices. These matrices were performed by rntwo-dimension DCT. The elements at the same location of all sub-matrices formed a new matrix, and the elements were rnat the equivalent energy level. The energy levels of new matrices were measured by average energy, and quantitative rnmatrix was obtained by a threshold of average energy. The new matrices and quantitative matrix were used to represent rnthe monitoring data set. The simulation result shows that the data compression ratio can reach 82.8％ when the mean rnsquare deviation is 3.89％.
展开▼
