RT Journal Article
T1 Condition monitoring of critical mechanical elements through Graphical Representation of State Configurations and Chromogram of Bands of Frequency
A1 Bustos Caballero, Alejandro
A1 Rubio Alonso, Higinio
A1 Castejón Sisamón, Cristina
A1 García Prada, Juan Carlos
AB Fault detection is a crucial aspect to avoid catastrophic failures on mechanical systems, as well as to save money for companies. Currently, a number of non-destructing tests, signal processing analysis and artificial intelligence techniques are used for processing larger and larger amounts of maintenance data in all industry fields, either independently or combined. This manuscript presents a novel methodology for the condition monitoring of machinery, based on vibration analysis. The methodology is supported on two novel signal processing techniques: Graphical Representation of State Configurations (GRSC) and Chromogram of Bands of Frequency (CBF). These two new techniques apply basic concepts of the machine deterioration theory to the frequency spectrum. In order to prove the successful of the work presented, the methodology is tested against two real examples: vibration signals from the Case Western Reserve University (CWRU) Bearing Data Centre, and vibration signals from a high-speed train in normal operation. The results show that these new techniques can process large amounts of data without using artificial intelligence, identify adequately the operating condition of the tested systems and give precise information about that operating system by means of simple graphs and colours.
PB Elsevier
SN 0263-2241
YR 2019
FD 2019-03
LK https://hdl.handle.net/10016/33960
UL https://hdl.handle.net/10016/33960
LA eng
NO The work is supported by the Spanish Government through the MAQ-STATUS DPI2015-69325-C2-1-r project.
DS e-Archivo
RD 18 jul. 2024