Experimental wavelet analysis of Rotor-Rub vibration signal

0Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

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.

References Powered by Scopus

Wavelet analysis: Mother wavelet selection methods

236Citations
N/AReaders
Get full text

Detection of the rubbing-caused impacts for rotor-stator fault diagnosis using reassigned scalogram

132Citations
N/AReaders
Get full text

Customized wavelet denoising using intra- and inter-scale dependency for bearing fault detection

78Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Rubio, E., Chávez-Olivares, C., & Cervantes-Herrera, A. (2019). Experimental wavelet analysis of Rotor-Rub vibration signal. International Journal of Innovative Technology and Exploring Engineering, 8(12), 1756–1759. https://doi.org/10.35940/ijitee.L3222.1081219

Readers' Seniority

Tooltip

Professor / Associate Prof. 2

100%

Readers' Discipline

Tooltip

Engineering 2

100%

Save time finding and organizing research with Mendeley

Sign up for free