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Resumen

 

RELATIONSHIP BETWEEN OIL POLLUTION WITH SILICA AND ENGINE WEAR

RELACIÓN ENTRE LA CONTAMINACIÓN DEL ACEITE CON SÍLICE Y EL DESGASTE DEL MOTOR
PhD. Simón J. Fygueroa Salgado.
MSc. Gonzalo G. Moreno Contreras.
MSc. Juan C. Serrano Rico.

Abstract: Spectroscopic analysis of automotive engine oil is highly effective to detecting wear. The results obtained using this technique are the major wear metal concentrations present in used oil samples that in the case of motor vehicles are: aluminum, chromium, copper, tin, iron, nickel, lead and silicon. The aim of this paper is to carry out a statistical investigation from the results of spectroscopic analysis of a large number of used oil samples taken to different vehicle engines and stored in a database in order to relate the silicon content with wear metals content. It also considers service type influence, taking into account transport and public works vehicle engines.

Keywords: Predictive maintenance, fault diagnosis, oil analysis, internal combustion engines, wears, contamination, dust, silicon.

Resumen: La técnica de análisis espectrométrico de aceites de motores de automoción es altamente efectiva para detectar su desgaste. Los resultados de la aplicación de esta técnica son las concentraciones metálicas de los principales metales de desgaste presentes en muestras de aceite usado; en el caso de los motores de vehículos industriales se consideran aluminio, cromo, cobre, estaño, hierro, níquel, plomo y silicio. El objetivo de la presente ponencia es llevar a cabo una investigación estadística con el objetivo de relacionar el contenido de silicio con los contenidos de metales de desgaste, a partir de los resultados obtenidos del análisis espectrométrico de un elevado número de muestras de aceite usado, tomadas en motores de diferentes vehículos almacenados en una base de datos. Se considera además, la influencia del tipo de servicio, examinando por separado el caso de los motores de vehículos de transporte y el de los de obras públicas.

Palabras clave: Mantenimiento predictivo, diagnóstico de fallas, análisis de aceite, motores de combustión interna, desgaste, contaminación, polvo, silicio.