Interpolated FFT Algorithm Using Hanning Window

The interpolated FFT algorithm utilizing Hanning window provides an effective solution for harmonic analysis in power system signals. This approach significantly improves spectral resolution and measurement accuracy by implementing windowing before FFT computation, enabling more precise detection and localization of harmonic components. The algorithm typically involves applying Hanning window weighting to the time-domain signal samples using the formula w(n) = 0.5(1 - cos(2πn/N)), followed by zero-padded FFT transformation. Through interpolation techniques applied to the FFT results, the method can reconstruct missing data points and compensate for non-integer harmonic frequencies, yielding more complete and reliable analysis outcomes. The interpolation process often employs peak detection algorithms and polynomial fitting methods around dominant spectral bins to achieve sub-bin frequency estimation. Therefore, the Hanning-windowed interpolated FFT algorithm represents a viable and efficient methodology for both research and practical applications in power system harmonic analysis studies, particularly beneficial for handling asynchronous sampling scenarios and improving measurement precision under noisy conditions.