Research on weak signal detection method for power system fault based on improved wavelet threshold

Abstract

Corresponding weak signals will be generated in case of power system failure in order to ensure the safe and stable operation of power system and detect the weak signal in real time, a denoising method based on improved wavelet threshold algorithm is proposed by analyzing the change of weak signal under noise interference. Firstly, the monitoring signal is decomposed by EMD. Secondly, each IMF component is transformed by wavelet transform to eliminate the noise in the wavelet coefficients of each scale. Finally, the denoised signal is obtained through the signal reconstruction mechanism. The experimental results show that the denoising method based on the improved wavelet threshold method not only removes the noise, but also retains more fault information features. Therefore, this method overcomes the interference of noise on signal stability and detects weak signals accurately and effectively. When there is strong noise in the power system, this method can still accurately observe the weak signal, effectively shield the influence of noise on the signal, improve the detection efficiency and accuracy, and is of great significance to ensure the stable operation of the power system.

Keywords

• Power system fault
• Weak signal detection
• Signal denoising
• Improved wavelet threshold
• Empirical Mode Decomposition (EMD)