Aplicaciones de Máquinas de Soporte Vectorial en el Diagnóstico de Motores de Combustión

Translated title of the contribution: Applications of Support Vector Machines in the Diagnosis of Combustion Engines

Nestor Diego Rivera Campoverde, Christian Xavier Barreto Cajamarca, Luis Patricio Zhunio Lituma

Research output: Chapter in Book/Report/Conference proceedingChapter


The present work shows the procedure realized for the training and validation of an algorithm that predict, the damage in the internal combustion engine’s different components and whose diagnosis uses to generate excessive times of maintenance. Several stages, which show up for the generation of the algorithm music consists in the classification of which ones the data that better they interpret and that tell a failure from other, these failures are related to the calibration between electrodes of the spark plug, the percentage of opening of the injector and the pressure of the fuel pump. Straightaway has trained a machine of classification than, on the basis of saying process of learning, help to predict of adequate way the existence and the position of the damage in point. Finally there appears an analysis of the percentages of reliability of the algorithm realized by means of the use of the SVM on having applied it in the diagnosis of flaws in the engine, where it is observed that it is possible to obtain a reliability of 96.5 %, with a percentage error of 3,448 % corresponding to only one it fails badly classified.
Translated title of the contributionApplications of Support Vector Machines in the Diagnosis of Combustion Engines
Original languageSpanish (Ecuador)
Title of host publicationDesarrollo Tecnológico en Ingeniería Automotriz
PublisherEditorial Abya-Yala
ISBN (Print)978-9978-10-288-6
StatePublished - 31 Dec 2017

CACES Knowledge Areas

  • 8145A Logistics and Transportation


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