MATLAB Bearing Fault Detection Using Envelope Demodulation Method

The MATLAB bearing fault detection program serves as a critical tool for machinery condition monitoring and predictive maintenance. This implementation employs envelope demodulation methodology, where the core algorithm involves extracting the signal envelope through Hilbert transform and subsequently performing frequency domain analysis to identify characteristic fault frequencies. Key technical components include configurable signal preprocessing, envelope detection using analytic signal computation, and spectral analysis via Fast Fourier Transform (FFT) with frequency resolution optimization. The program architecture allows easy adaptation through parameter adjustments - users simply modify the sampling frequency variable and specify the target data file path. The code implements automatic frequency calibration and peak detection algorithms to accurately identify dominant fault frequencies from the envelope spectrum. The distributed package contains validation datasets including vibration signals with known bearing defects, where the primary fault characteristic frequency is precisely 107Hz. This enables immediate verification of the detection algorithm's performance. The implementation emphasizes computational efficiency through vectorized operations and includes error handling for data input validation. Proper configuration and utilization of this fault detection system can significantly enhance equipment reliability by enabling early identification of bearing degradation, thereby preventing catastrophic failures and reducing maintenance costs through proactive intervention strategies. The code structure follows modular design principles, separating data loading, signal processing, and result visualization into distinct functions for maintainability and extensibility.