Research on real-time abnormal voltage detection and prediction method based on the linear tracking differentiator
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摘要: 現代電力電子設備對非平穩、時變電壓信號十分敏感,基于此提出了一種網側電壓異常檢測與預報的方法,通過對網側電壓信號進行實時檢測,向相關電力電子設備的控制電路發送網側電壓異常預報信號.為消除電壓信號中的常規噪聲干擾,首先采用線性跟蹤微分器對網側電壓信號進行濾波,在此基礎上,通過引入小波變換模極大值法檢測奇異點,對濾波后的信號進行電壓突變點的判斷,目標是準確預報出電網電壓中可能對電力電子設備造成危害的異常點.仿真與實驗結果表明,基于線性跟蹤微分器的小波信號檢測能夠實時準確地獲得理想信號的最佳逼近,提高了網側電壓故障檢測速度,通過實時的檢測與分析,該方法能夠為電力電子設備提供具有參考價值的預報信號.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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