MATLAB Power Spectrum Estimation for Pulsating Wind Speed Time History

In this text, we will analyze pulsating wind speed time history using MATLAB power spectrum estimation techniques. To ensure accuracy in our spectral analysis, we implement the Hanning window method as our primary analysis tool. The Hanning window function helps reduce spectral leakage by applying a smooth weighting to the time-domain signal before Fourier transformation. Through this approach implemented in MATLAB code (typically using functions like pwelch or periodogram with window parameter specification), we can better understand the frequency domain characteristics of pulsating wind speeds and extract detailed information about wind speed variations. This method is widely applied in engineering fields because it helps engineers better understand and predict wind effects on structures. Key implementation steps include: loading time history data, applying the Hanning window function, performing FFT analysis, and calculating power spectral density. Therefore, when analyzing pulsating wind speed time histories, we should consider using MATLAB power spectrum estimation with the Hanning window method to obtain more accurate and detailed spectral results for engineering applications.