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Compression Method of Power Quality Disturbances Based on Independent Component Analysis and Fast Fourier Transform

机译:基于独立分量分析和快速傅里叶变换的电能质量障碍压缩方法

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摘要

In power quality monitoring systems, a large volume of data is generated. A compression method should be used to perform the storage of data more efficiently. The present study proposes a compression method of power quality disturbances based on independent component analysis, Fast Fourier Transform and an adaptive threshold obtained using mathematical morphology. The independent component analysis algorithm returns three statistically independent components among themselves. Considering the noise and disturbances are statistically independent of the fundamental component, the independent component analysis algorithm isolates the noise and disturbances in the third component, where a threshold is applied, while the first and second components are presented to the Fast Fourier Transform in order to characterize the fundamental component. The results were compared with a Wavelet-based method in which the proposed method achieved compression rates slightly higher than the Wavelet-based method.
机译:在电能质量监测系统中,产生大量数据。应使用压缩方法更有效地执行数据存储。本研究提出了一种基于独立分量分析,快速傅里叶变换和使用数学形态获得的自适应阈值的电能质量障碍的压缩方法。独立的组件分析算法本身之间返回三个统计上独立的组件。考虑到噪声和干扰在统计上独立于基本组件,独立的分量分析算法将应用阈值的噪声和干扰隔离,其中应用阈值,而第一和第二组件呈现给快速傅里叶变换以便表征基本组成部分。将结果与基于小波的方法进行了比较,其中所提出的方法实现了略高于基于小波的方法的压缩速率。

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