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基于小波分析理论的电能质量扰动信号检测 被引量:4

Power Quality Disturbance Signal Detection Based on Wavelet Analysis Theory
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摘要 随着电力电子器件在电力系统中的广泛使用,电能质量问题己经成为供电系统和用户共同关注的重要问题。对电能质量进行快速的检测和准确的分类,进而进行有效的治理是提高用电效率的重要途径。本文使用小波检测算法来进行信号扰动的定位,利用小波变换良好的时频局部化特性,根据小波变换模极大值原理,通过对信号的多分辨率分解,实现了扰动信号的检测。并且通过Matlab的仿真结果证实了小波检测算法的正确性和有效性。 With the proliferation of electronically controlled equipments in power system,power quality has been a great issue to both suppliers and users of electricity. In order to improve the power efficiency,it is necessary to detect the power quality sensitively,classify them accurately and clear them effectively. We use of wavelet algorithm to carry out the positioning signal power quality in this paper. The wavelet transform is a method which is adaptive and localized in both the time domain and frequency domain. According to wavelet transform modulus maxima theory,we take the detection of power quality disturbances signal by the means of multi-resolution decomposition. And Matlab simulation results from the test confirmed the accuracy of positioning algorithm.
作者 王程刚
出处 《仪器仪表标准化与计量》 2010年第5期12-15,28,共5页 Instrument Standardization & Metrology
关键词 电能质量 小波变换 模极大值 暂态扰动 奇异性检测 Power Quality Wavelet Transform Modulus Maxima Transient Disturbance Signal Strangeness Detect
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