Insulator leakage current data compression based on EMD and compressed sending

Chunjiang Pang, Xiao Xie
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Abstract

In order to increase transmission and processing speed, it is essential to compress the non-stationary leakage current in the insulator monitored system. 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. However, computational complexity is high in CS recovery process of non-stationary signals. In this paper, CS combines with empirical mode decomposition method (EMD). Decompose Non-stationary leakage current into a finite number of stationary intrinsic mode functions (IMF), and then CS processes stationary IMFs. The experiment results indicate that it enhances not only the speed of process and operational efficiency but also compression ratio and reconstruction accuracy in the case that CS processes leakage current signal by EMD decomposition.
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基于EMD和压缩发送的绝缘子泄漏电流数据压缩
为了提高传输和处理速度,必须对绝缘子监测系统中的非平稳泄漏电流进行压缩处理。压缩感知(Compressed Sensing, CS)将采样和压缩结合在一起,利用少量的采样可以很好地重构信号,既降低了硬件要求,又提高了压缩效率。然而,在非平稳信号的CS恢复过程中,计算复杂度较高。在本文中,CS与经验模态分解方法(EMD)相结合。将非平稳泄漏电流分解为有限个平稳内模函数(IMF),然后CS对平稳内模函数进行处理。实验结果表明,CS对泄漏电流信号进行EMD分解处理,不仅提高了处理速度和运算效率,而且提高了压缩比和重构精度。
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