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提出了短时电能质量扰动分类和检测的双小波分析法。利用双小波 (db1和db2 4 )各自的优点 ,把电能质量 5种扰动 (电压凹陷、电压凸起、电压间断、暂态脉冲和暂态振荡 )有效地从含有噪声的采样信号中鉴别出来 ,并能实现扰动的各项指标测定。该方法弥补了以往小波检测方法中 ,当噪声污染严重或扰动发生、终止在工频相角为 0或π附近时 ,可能检测不到或误判断的不足。仿真计算结果表明 ,该方法对扰动的分类简单、有效 ,对扰动各项指标测定尤其是电压凹陷、凸起和间断的时刻及幅度的确定 ,精度甚高
Proposed a dual wavelet analysis method for the classification and detection of short-term power quality disturbances. Using the respective advantages of dual wavelet (db1 and db2 4), the five power quality disturbances (voltage sags, voltage bumps, voltage discontinuities, transient pulses and transient oscillations) are efficiently identified from the noisy sampled signal, And to achieve the perturbation of the indicators measured. This method makes up for the deficiencies that can not be detected or misjudged when the noise pollution is serious or disturbance occurs in the past wavelet detection method and terminated when the phase angle of the power frequency is around 0 or π. The simulation results show that this method is simple and effective for the classification of disturbances, and the determination of the indexes of disturbance, especially the determination of the time and amplitude of voltage sags, bumps and breaks, is very precise