Wavelet-based intelligent system for monitoring non-stationary disturbances

A. Gaouda, S. Kanoun, M. Salama, A. Chikhani
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引用次数: 10

Abstract

This paper presents a wavelet-based procedure that will assist in automated detecting, classifying, and measuring of different power system disturbances. Two pattern recognition techniques are used to evaluate the efficiency of the features of the nonstationary signal in the wavelet domain. The paper also presents a new technique that can monitor the variations of the RMS value and any further changes in the nonstationary signal.
基于小波的非平稳扰动智能监测系统
本文提出了一种基于小波的程序,可以帮助自动检测、分类和测量不同的电力系统干扰。采用两种模式识别技术来评估非平稳信号在小波域的特征效率。本文还提出了一种监测均方根值变化和非平稳信号进一步变化的新技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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