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https://repositorio.utn.edu.ec/handle/123456789/13587
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 docuemento: | 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 |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
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ARTÍCULO SCOPUS Expert System for Diagnosis.pdf | Artículo | 592.82 kB | Adobe PDF | Visualizar/Abrir |
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