Open AccessCharacterization of the mechanical vibration signals associated with unbalance and misalignment in rotating machines, using the cepstrum transformation and the principal component analysis
Author(s) -
C. L. Sandoval-Rodríguez,
J. G. Ascanio Villabona,
C. G. Cárdenas-Arias,
Arly Darío Rincón Quintero,
Brayan Eduardo Tarazona Romero
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/844/1/012057
Subject(s) - principal component analysis , cepstrum , matlab , vibration , flywheel , computer science , transformation (genetics) , acoustics , engineering , speech recognition , artificial intelligence , physics , mechanical engineering , biochemistry , chemistry , gene , operating system
In the present document, the Cepstrum transform and the analysis of principal components were used to differentiate amplitudes in the mechanical vibrations produced by unbalance and misalignment with respect to a reference group. This document requires three stages. It begins with levelling in order to establish the control group. The unbalancing was carried out with a known mass located in the two radial distances of the first and second flywheels. The misalignment was made by running the sliding supports back 0.5, 1.0 and 1.5 degrees. In the second stage, Matlab algorithms were created for both cepsctrum and main component analysis. In the last stage the obtained data were analyzed identifying the differences that may exist in the analyzed records. The project focused on the use of Matlab to find differences at a frequency of 30 Hz. The results obtained made it possible to determine that it is possible to find differences with the proposed methodology.