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基于修正幅值定量检测电能质量扰动方法
引用本文:朱锋峰,任震,黄雯莹.基于修正幅值定量检测电能质量扰动方法[J].电力自动化设备,2004,24(6):9-13.
作者姓名:朱锋峰  任震  黄雯莹
作者单位:华南理工大学,理学院,广东,广州,510640;华南理工大学,电力学院,广东,广州,510640;华南理工大学,电力学院,广东,广州,510640;华南理工大学,理学院,广东,广州,510640
基金项目:国家自然科学基金资助项目(50077008),广东省自然科学基金资助项目(033044)
摘    要:首先,提出了2个实值小波函数和基于这2个小波变换的修正幅值的新指标,从理论上说明:利用该修正幅值可以诊断电压的实际频率是否等于工频频率:在实际频率没有发生偏离的情形下,利用该修正幅值可以精确确定出电压幅值;而在实际频率偏离工频频率的情形下,也给出了利用修正幅值确定电压幅值的方法,并且在已知实际频率偏离工频频率范围的前提下,给出了利用修正幅值估计电压所产生的误差范围。其次,推导出了这2个实值小波变换的递推公式。最后,还应用基于这2个小波变换的修正幅值对常见的三种电压畸形波进行了检测。

关 键 词:小波变换  电能质量  故障检测
文章编号:1006-6047(2004)06-0009-05

Quantitative detection of power quality disturbance based on adjusting amplitude
ZHU Feng-feng,REN Zhen,HUANG Wen-ying.Quantitative detection of power quality disturbance based on adjusting amplitude[J].Electric Power Automation Equipment,2004,24(6):9-13.
Authors:ZHU Feng-feng  REN Zhen  HUANG Wen-ying
Affiliation:ZHU Feng-feng 1,2,REN Zhen 2,HUANG Wen-ying 1
Abstract:Two novel real wavelets and a new index-adjusting amplitude ,which is based on the two real wavelet transforms ,are presented.The following two conclusions are explained in theory.The adjusting amplitude can be used to diagnose whether the actual frequency of voltage is equal to the dating frequency.When the actual frequency is equal to the dating frequency ,the adjusting amplitude may exactly determine the voltage amplitude.When the actual frequency is not equal to the dating frequency ,a method of determining voltage amplitude is given by applying the adjusting amplitude.Furthermore ,when deviation of the actual frequency from the dating frequency is known ,the discrepancy between the estimated value given by the adjust amplitude and the actual voltage is determined.The recursive formulas for the two wavelet transform coefficients are derived.The adjusting amplitude based on the two real wavelet transforms are used to detect three typical types of voltage waveform aberrance.This project is supported by National Natural Science of China ( 50077008 ) and Natural Science of Guangdong Province ( 033044 ) .
Keywords:wavelet transform  power quality  fault detection4
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