Experimental Wavelet Analysis of Rotor-Rub Vibration Sign
Eduardo Rubio1, César Chávez-Olivares2, Alejandro Cervantes-Herrerai3
1Eduardo Rubio, Centro de Ciencias de la Ingeniería, Universidad Autónoma de Aguascalientes, Aguascalientes, Ags., Mexico.
2Alejandro Cervantes-Herrera, Centro de Ciencias de la Ingeniería, Universidad Autónoma de Aguascalientes, Aguascalientes, Ags., Mexico.
5Chávez-Olivares, Centro de Ciencias de la Ingeniería, Universidad Autónoma de Aguascalientes, Aguascalientes, Ags., Mexico.
Manuscript received on September 16, 2019. | Revised Manuscript received on 24 September, 2019. | Manuscript published on October 10, 2019. | PP: 1756-1759 | Volume-8 Issue-12, October 2019. | Retrieval Number: L32221081219/2019©BEIESP | DOI: 10.35940/ijitee.L3222.1081219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Experimental, Rotor-rub, Time-Frequency Analysis, Rotating Machinery
Scope of the Article: Frequency Selective Surface