Publication: Aplicación de técnicas de procesamiento para el mantenimiento basado en la condición
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2019-09
Defense date
2019-10-15
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Abstract
El mantenimiento es una de las áreas más importantes que existen dentro de cualquier empresa inmersa en el sector industrial. La correcta elección del tipo de mantenimiento, su programación y los costes asociados serán de gran influencia e incluso determinantes en el transcurso de la producción de la propia empresa.
Durante el desarrollo de este documento, se profundizará en un tipo de mantenimiento denominado mantenimiento predictivo, en concreto el “condition monitoring” o mantenimiento basado en la condición, mediante el cual se monitorizará de manera continua uno o más parámetros de interés en máquinas cuya criticidad sea elevada. Esta criticidad puede determinarse bien por la reducción de la calidad o parada en la producción o incluso por cuestiones de seguridad en los operarios. En cualquier tipo de sistema productivo, se puede observar claramente la predominancia de las máquinas rotativas frente a cualquier otro tipo de máquinas, es por ello que se estudiará en concreto los modos de fallos de uno de los elementos más importantes presentes en las máquinas, como son los rodamientos. Estos elementos son los encargados de soportar las solicitaciones de cargas estáticas y dinámicas que aparecen durante el funcionamiento.
Se procederá en concreto al análisis de las vibraciones de los rodamientos mediante técnicas de procesamiento en el dominio de la frecuencia. Dichas señales proporcionan información muy útil sobre el estado dinámico de la máquina, y mediante el estudio de estas se podrá determinar si el funcionamiento de la máquina es el adecuado. Se trabajará con datos experimentales de la base de datos de acceso público de la Case Western Reserve University, que a su vez obtuvieron realizando diversos ensayos controlados en laboratorio.
Industrial maintenance is one of the biggest and most important section that we can find inside any company. The correct selection of the methods and the associated costs will affect and determinate the performance of the productive sistems and activities of the company. In this document, we’ll be talking deep about one kind of maintenance that is included in predictive maintenance techniques, that is known as condition monitoring. Going through these techniques, we’ll be able to monitor the continuous evolution of one or more parameters that can give us information and represent the condition of machines with high levels of criticity. Analyzing any type of productive system, we can find out that rotative machinery is probably the most important type of machines used in any sector of the industry. That’s the main reason why among this project we’ll be studying one of the most critical elements that we can find inside any rotatory machine, the bearings. Bearings are the elements that are suposed to hold the static and dynamic loads that show up in rotative machines during their performance. Specifically, we’ll be studying vibration signals from the bearings using processing techniques based on the frequency domain. These signals provide us very useful information about the dynamic condition of the machine and analyzing them we’ll be able to know if the machine’s behavior is the one that we expect. We’ll be working with experimental data obtained from the bearing database of the Case Western Reserve University.
Industrial maintenance is one of the biggest and most important section that we can find inside any company. The correct selection of the methods and the associated costs will affect and determinate the performance of the productive sistems and activities of the company. In this document, we’ll be talking deep about one kind of maintenance that is included in predictive maintenance techniques, that is known as condition monitoring. Going through these techniques, we’ll be able to monitor the continuous evolution of one or more parameters that can give us information and represent the condition of machines with high levels of criticity. Analyzing any type of productive system, we can find out that rotative machinery is probably the most important type of machines used in any sector of the industry. That’s the main reason why among this project we’ll be studying one of the most critical elements that we can find inside any rotatory machine, the bearings. Bearings are the elements that are suposed to hold the static and dynamic loads that show up in rotative machines during their performance. Specifically, we’ll be studying vibration signals from the bearings using processing techniques based on the frequency domain. These signals provide us very useful information about the dynamic condition of the machine and analyzing them we’ll be able to know if the machine’s behavior is the one that we expect. We’ll be working with experimental data obtained from the bearing database of the Case Western Reserve University.
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Keywords
Mantenimiento, Sector industrial, Condition monitoring, Maquinaria, Industrial maintenance