基于压缩传感理论的绝缘子泄漏电流数据压缩

Data Compression of Insulator Leakage Current Based on the Compressed Sensing

绝缘子泄漏电流数据量大,给监测系统数据存储和传输带来巨大的负担。针对这个问题,提出基于压缩传感理论(Compressed Sensing,CS)的数据压缩方法,CS将采样与压缩合并进行,少量采样就能很好地恢复信号,不仅降低对硬件要求,而且提高压缩效率。将泄漏电流信号进行小波变换的稀疏分解,然后对稀疏的泄漏电流信号进行高斯测量编码,最后应用正交匹配追踪算法(OMP)重构信号。实验结果表明,对绝缘子泄漏电流进行CS数据压缩具很高的压缩比,恢复的信号也比较理想。

The huge data of insulator leakage current increases the burden of data storage and transmission in the monitoring system.Aiming at this problem,the paper puts forward data compression based on the compressed sensing.Compressed Sensing（CS） combines sampling and compression with a small amount of sample to reconstruct signal well,which not only reduces hardware requirements but also improves compression efficiency.First leakage current was decomposed by Wavelet Transform.Then adopted Gaussian observation matrix to compress the sparse leakage current.Reconstructed signal by Orthogonal matching pursuit algorithm（OMP） finally.The experimental results show that insulator leakage current was processed by CS,which had high compression ratio and rather reconstruction signal.