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Título : Expert System for Diagnosis of Motor Failures in Electronic Injection Vehicles
Autor : Sandoval Pillajo, Ana Lucía
Tarupi, Alexis
Basantes Andrade, Andrea Verenice
Granda Gudiño, Pedro David
García Santillán, Iván Danilo
Tipo documento : Article
Palabras clave : EXPERT SYSTEMS;MECHANICAL ENGINEERING;ARTIFICIAL INTELLIGENCE
Fecha de publicación : 1-mar-2023
Fecha de creación : 10-ene-2019
Resumen : Today, cars are an indispensable element in the society, as well as the vehicle diagnosis of minor and serious mechanical failures. This process is carried out through two methods: (i) manually, inspecting possible common causes; and (ii) automatically, using a failure identification scanner. In both cases the assistance of a car expert is required. However, how could a common user briefly diagnose vehicle failures? The objective of this project has been to build an expert system module for vehicular diagnosis to help the common user, identifying automotive failures and the severity of the vehicle damage. It also helps to prevent major damages and possible accidents, as well as to achieve a technical and effective communication when the situation is being explained to the mechanical assistance which can be even by telephone. The module design was composed by four phases: (i) do background research about failure diagnosis, (ii) production rules; (iii) inference engine; and (iv) user interface. The results show that the expert system module is 71,43% effective, so that it helps the common user to identify electronic engine failures without the assistance of a professional in the area.
URI : http://repositorio.utn.edu.ec/handle/123456789/13587
Ciudad. País: Ibarra. Ecuador.
Aparece en las colecciones: Publicaciones FICA

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