Frequency-Domain Signal Characterization for Fault Detection in Rotating Mechanical Systems Using Fourier-Based Decomposition Techniques

الملخص

This study presents a comprehensive approach to fault detection in rotating mechanical systems through frequency-domain signal analysis using Fourier-based decomposition techniques. Time-domain vibration signals acquired from rotating machinery are transformed into the frequency domain to extract characteristic spectral components indicative of system health. The methodology leverages Fast Fourier Transform (FFT) algorithms and harmonic decomposition to isolate anomalies associated with mechanical imbalances, misalignments, and bearing wear. Experimental data collected from controlled test rigs under varying operational conditions validate the effectiveness of the proposed signal processing framework. Results demonstrate that frequency-domain analysis significantly enhances fault detectability compared to traditional time-domain inspection methods. This work contributes to the advancement of condition monitoring strategies by providing a robust, interpretable, and computationally efficient diagnostic tool applicable in industrial settings.