Caracterización de emisiones acústicas en sistemas con miras a su potencial diagnóstico y mantenimiento
In this work, predictive maintenance actions are carried out by monitoring the condition with acoustic signals and finally an algorithm is developed and implemented in the Matlab software capable of processing, analyzing and diagnosing the condition of one of the 4 ball bearing components in rotary...
- Autores:
-
Gómez Soto, Juan Camilo
- Tipo de recurso:
- Fecha de publicación:
- 2020
- Institución:
- Universidad de San Buenaventura
- Repositorio:
- Repositorio USB
- Idioma:
- spa
- OAI Identifier:
- oai:bibliotecadigital.usb.edu.co:10819/8032
- Acceso en línea:
- http://hdl.handle.net/10819/8032
- Palabra clave:
- Mantenimiento predictivo
Análisis espectral
Rodamientos a balines
Señales acústicas
Cartas de Charlotte
Spectral analysis
Predictive maintenance
Ball bearings
Acoustic signals
Charlotte letters
Acústica
Software
- Rights
- License
- Atribución-NoComercial-SinDerivadas 2.5 Colombia
| Summary: | In this work, predictive maintenance actions are carried out by monitoring the condition with acoustic signals and finally an algorithm is developed and implemented in the Matlab software capable of processing, analyzing and diagnosing the condition of one of the 4 ball bearing components in rotary mechanical systems, following the diagnosis letters from Charlotte's technical associates. In addition, commercial reference bearings FAG6005-2RSR with real failures are used, product of high occupational exposure. This work consists of two stages. The first one is focused on implementing a measurement assembly establishing objective parameters in order to set a reliable and versatile measurement methodology, the second stage belongs to the development of an algorithm that characterizes acoustic signals with two bearing states (failed and non-failed) and automatically establishes the current state of the component from amplitude and frequency analysis |
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