Source Code for Wavelet Transform-Based Envelope Analysis in Bearing Fault Diagnosis

This paper presents a wavelet transform-based envelope analysis method applicable to bearing fault diagnosis. Wavelet transform is a signal processing technique that decomposes signals into different frequency components through multi-resolution analysis. The implementation typically involves applying discrete wavelet transform (DWT) functions like 'wavedec' in MATLAB to break down vibration signals into approximation and detail coefficients. Envelope analysis is an analytical method used to extract signal envelope curves, making it easier to detect fault characteristics in signals. The code implementation includes Hilbert transform operations or Teager-Kaiser energy operator to demodulate the signal and obtain the envelope spectrum. By combining wavelet transform and envelope analysis, we achieve accurate bearing fault diagnosis through characteristic frequency identification. The provided source code demonstrates complete workflow including signal preprocessing, wavelet decomposition selection (e.g., db4 wavelet), envelope extraction, and fault feature frequency calculation, helping readers better understand and apply this method in practical industrial applications.