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电能质量短期扰动分类检测的db1小波分析法
Classification and Detection of Short Duration Disturbance for Power Quality Using db1 Wavelet Analysis
【摘要】 针对电能质量扰动具有非稳态、突发性的特点,提出了一种电能质量短期扰动分类和检测的新方法。通过检测奇异信号的模极大值,检测出扰动起始时间、终止时间和扰动发生时刻的幅值。仿真结果表明上述方法是有效的,检测的数据是准确的。
【Abstract】 Aimed at the characteristics of power quality disturbance, a new method is introduced for detecting. classifying and quantifying the short duration variations of power quality. Using the db1 wavelet basis function lower frequency coefficient, this method can identify among the voltage sag, voltage swell, voltage interruption and detect their start time, end time and magnitude. The simulation result shows that the method is efficient and the detected data is precise.
【关键词】 电能质量;
短期扰动;
分类与检测;
小波变换;
奇异性;
模极大值;
【Key words】 power quality; short duration disturbance; classification and detection; wavelet transform; singularity; modulo maximum;
【Key words】 power quality; short duration disturbance; classification and detection; wavelet transform; singularity; modulo maximum;
- 【文献出处】 吉林电力 ,Jilin Electric Power , 编辑部邮箱 ,2003年05期
- 【分类号】TM714
- 【被引频次】7
- 【下载频次】136