Reading Data from Excel Sheets and Analyzing Frequency Spectrum, Phase Spectrum, and Total Harmonic Distortion (THD)

To perform comprehensive signal analysis, the initial step involves reading time-domain data from an Excel spreadsheet using MATLAB's `readtable()` or `xlsread()` functions. The imported data should be validated for proper formatting and sampling rate consistency. For spectral analysis, the Fast Fourier Transform (FFT) algorithm is implemented through MATLAB's `fft()` function to decompose the signal into its frequency components. The magnitude spectrum is calculated by taking the absolute value of the FFT results, while the phase spectrum is obtained using the `angle()` function applied to the complex FFT output. Total Harmonic Distortion (THD) analysis requires calculating the ratio of the root-sum-square of harmonic components to the fundamental frequency magnitude. This can be implemented using MATLAB's `thd()` function from the Signal Processing Toolbox or through custom code that identifies harmonic peaks in the frequency spectrum. Visualization is crucial for interpretation - the analysis results should be plotted using MATLAB's `plot()`, `stem()`, or `semilogx()` functions to display time-domain signals, frequency spectra (with proper frequency axis scaling), phase relationships, and THD values. The `subplot()` function can organize these visualizations into a comprehensive multi-panel figure for comparative analysis. Proper signal preprocessing (detrending, windowing) and post-processing (frequency bin correction, dB scaling) should be applied to ensure accurate spectral representations and meaningful THD calculations.