Open AccessExperimental Wavelet Analysis of Rotor-Rub Vibration Signal
Author(s) -
Eduardo Rubio*,
Alejandro Cervantes-Herrera,
Chávez Olivares
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.l3222.1081219
Subject(s) - rubbing , rotor (electric) , vibration , stator , wavelet , signal (programming language) , fast fourier transform , accelerometer , wavelet transform , acoustics , casing , computer science , time–frequency analysis , engineering , physics , artificial intelligence , mechanical engineering , computer vision , algorithm , programming language , operating system , filter (signal processing)
A common defective phenomenon in rotating machinery is rotor-casing rub that generates impacts when the rotor rubs against the stator. Vibration sensors and data analysis techniques are commonly used for fault signature extraction and mechanical systems diagnosis. In this paper, an experimental characterization of rotor-rub is made by time-frequency analysis by means of the wavelet transform. A rotor kit, equipped with a variable speed DC motor, an accelerometer and a data acquisition system are used to acquire the mechanical vibration data. Vibration signal in frequency and time-frequency domains are shown for no-rubbing, light, and severe rubbing cases. Results show that FFT is unable to report where in time particular components of rubbing appear. However, the time-frequency analysis is able to give location information in time to differentiate light from severe rubbing, and extract the main spectral components showing a spectrum rich in high frequency components, characteristic of this phenomenon.