Abstract

In response to the current problems of asynchronous sampling, spectrum leakage, and the fence effect, this paper proposes a combination of FFT and wavelet transform to accurately analyze the steady-state and transient components in the signal, improving detection accuracy. Firstly, we use Newton interpolation to quasi-synchronize the original sampling sequence, achieving consistency between the sampling period and the actual period. Secondly, the modulus maximum method is used on the original signal to detect the presence of transient disturbances. The results indicate that quasi-synchronization can accurately correct the collected signals with high restoration and synchronization accuracy. The improved windowed interpolation FFT achieves a detection accuracy of 0.3% for steady-state harmonics. The wavelet divides the frequency band and uses modulus maxima to detect signal singularity, accurately extracting transient disturbance signals with an accuracy of up to 5%. Similarly, for complex power signals, the analysis of hybrid algorithms also meets practical engineering needs.

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