Abstract <p>With the continuous increase in people’s demand for electricity, to ensure the stable operation of the power system, accurate analysis of grid signals has become the primary task in improving power quality. This article uses a combination of FFT and wavelet transform to accurately analyze the steady-state and transient components in signals, improving detection accuracy. The specific plan is to use Newton interpolation to quasi synchronize the original sampling sequence, achieving consistency between the sampling period and the actual period; Using the modulemaximum method on the original signal to detect the presence of transient disturbances. The results showed that quasi synchronization can accurately correct the collected signals with high restoration and synchronization; The improved windowed interpolation FFT achieves a detection accuracy of 0.3% for steady-state harmonics; Wavelet divides the frequency band and uses module maxima to detect signal singularity, accurately extracting transient disturbance signals with an accuracy of up to 5%; Furthermore, we can apply this new combination algorithm to more complex power signal processing.</p>