Comparative Study of Vibration Signal Using Wavelet Transform
Ayubkhan N. Mulani, Sangita N. Gujar · Zenodo (CERN European Organization for Nuclear Research) · 2017
Scientists have developed mathematical methods to imitate the processing performed by our body and extract the frequency information contained in a signal. These mathematical algorithms are called transforms and the most popular among them is the Fourier Transform. The method to analyze non-stationary signals is to first filter different frequency bands, cut these bands into slices in time, and then analyze them. The wavelet transform uses this approach. The wavelet transform or wavelet analysis is probably the most recent solution to overcome the shortcomings of the Fourier transform. In wavelet analysis the use of a fully scalable modulated window solves the signal-cutting problem. The window is shifted along the signal and for every position the spectrum is calculated. Then this process is repeated many times with a slightly shorter (or longer) window for every new cycle.