基于跟踪微分器的网侧电压异常检测方法研究

Research on real-time abnormal voltage detection and prediction method based on the linear tracking differentiator

  • 摘要: 现代电力电子设备对非平稳、时变电压信号十分敏感,基于此提出了一种网侧电压异常检测与预报的方法,通过对网侧电压信号进行实时检测,向相关电力电子设备的控制电路发送网侧电压异常预报信号.为消除电压信号中的常规噪声干扰,首先采用线性跟踪微分器对网侧电压信号进行滤波,在此基础上,通过引入小波变换模极大值法检测奇异点,对滤波后的信号进行电压突变点的判断,目标是准确预报出电网电压中可能对电力电子设备造成危害的异常点.仿真与实验结果表明,基于线性跟踪微分器的小波信号检测能够实时准确地获得理想信号的最佳逼近,提高了网侧电压故障检测速度,通过实时的检测与分析,该方法能够为电力电子设备提供具有参考价值的预报信号.

     

    Abstract: One kind of detection and prediction method for abnormal grid voltage has been designed due to the case that modern power electronic equipment is sensitive to non-stationary time-varying voltage signal. This method sends the network voltage abnormal warning signal to control-circuits of modern equipment through detecting the grid voltage in time. To eliminate the conventional noise jamming of the voltage signal,this scheme adopts linear tracking differentiator to filter the signal. On this basis,wavelet transform modulus maxima are proposed in singularity detection,so as to accurately forecast abnormal harm points in power electronic devices caused by the grid voltage. Simulation and experimental results show that the wavelet analysis based on linear tracking differentiator can obtain the best approximation of the ideal signal and provide more useful forecasting signals for power electronics equipment,thus the fault detection speed and efficiency are improved significantly.

     

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