基于模式相似度和LZW压缩编码的电能质量数据压缩方法

Power quality data compression based on pattern similarity and LZW compressed encoding

针对电能质量数据多数情况下具有周期性、对称性、奇偶性等特点,提出了一种基于模式相似度和LZW压缩编码的电能质量数据压缩处理方法。在该压缩算法中,利用模式相似度归一化距离测度良好的畸变识别能力,对畸变和非畸变数据分别进行无损和有损压缩;合理引入LZW编码压缩,进一步提高算法的压缩比。依据IEEE电能质量标准,在MATLAB7.10环境下对6种典型的电能质量扰动信号建模后,设计仿真实验,完成了归一化距离测度畸变检测能力的检验,并通过与一维离散小波变换数据压缩算法的性能比较,验证了该算法的压缩性能和可行性。

According to the traits of power quality data in symmetry,parity and periodicity,a data compression algorithm based on pattern similarity and LZW compressed encoding is introduced,which normalizes the distance of pattern similarity to identify the distortion for the lossy compression of undistorted data and the lossless compression of distorted data,and adopts reasonably the LZW compressed encoding to increase the compression ratio.Models are established in MATLAB7.10 environment for six kinds of typical power quality disturbance signal,simulative experiments are designed to check the distortion detection capability of normalized distance,and the comparison of compression effect between the proposed algorithm and the one-dimension discrete wavelet transform show its performance and feasibility.