Barrelyzer: Design and Implementation of a Low-Cost Tank Barrel Inspection System

Franco Rivadeneira, Diego Godinez, Daniela Carcausto, Sebastian Ruiz, Bruno Ivazeta, Diego Quiroz, Jose Balbuena

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

Maintaining confined spaces such as 10 cm barrels and pipes is a challenging task to perform without the use of intelligent systems. However, these devices are high-priced and require special training for the operators. Hence, the present paper proposes the design of a low-cost cannon barrel inspection robot. An important factor to consider in the design is the rifling of the cannon barrels. As a result, the robot was implemented and able to navigate on a simulated environment through rifling, measuring the position of the robot with an error of 4% with a confidence level of 99% and detecting defects using Convolutional Neural Networks with an F1-Score of 82.70% using AdamW optimizer.

Idioma originalInglés
Título de la publicación alojadaProceedings of the International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2023) - Advances in Computer Sciences - Exploring Innovations at the Intersection of Computing Technologies
EditoresMarcelo V. Garcia, Carlos Gordón-Gallegos, Asier Salazar-Ramírez, Carlos Nuñez
EditorialSpringer Science and Business Media Deutschland GmbH
Páginas531-545
Número de páginas15
ISBN (versión impresa)9783031692277
DOI
EstadoPublicada - 2024
EventoInternational Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2023 - Ambato, Ecuador
Duración: 6 nov. 202310 nov. 2023

Serie de la publicación

NombreLecture Notes in Networks and Systems
Volumen775 LNNS
ISSN (versión impresa)2367-3370
ISSN (versión digital)2367-3389

Conferencia

ConferenciaInternational Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2023
País/TerritorioEcuador
CiudadAmbato
Período6/11/2310/11/23

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