2026-04-20T09:40:50Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/95172024-08-01T00:05:27Zcom_10259_4219com_10259_5086com_10259_2604col_10259_4220

Alvarado-Hernandez, Alvaro Ivan Checa Cruz, David Osornio-Ríos, Roque Alfredo Bustillo Iglesias, Andrés Antonino Daviu, Jose A. 2024-07-31T10:09:06Z 2024-07-31T10:09:06Z 2024-06-22 2079-9292 http://hdl.handle.net/10259/9517 10.3390/electronics13132447 2079-9292 Kinematic chains are crucial in numerous industrial settings, playing a key role in various processes. Over recent years, several methods have been developed to monitor and maintain these systems effectively. One notable method is the analysis of infrared thermal images, which serves as a non-invasive and effective approach for identifying various electromechanical issues. Additionally, Virtual Reality (VR) is a burgeoning technology that, despite its limited use in industrial contexts, offers a cost-effective and accessible solution for the training and education of industrial workers on specialized engineering subjects. Nevertheless, most virtual environments are based on numerical simulations. This paper presents the design and development of a Virtual Reality training module for the detection of fourteen electromechanical fault cases in a kinematic chain. The VR training tool developed is based on actual thermographic data derived from experiments conducted on an authentic kinematic chain. During these experiments, thermal images were captured using an low-cost infrared sensor. The thermographic images were processed by calculating the histogram and fifteen statistical indicators, which served to differentiate fault cases in the VR application. A comprehensive evaluation was carried out with a group of vocational students specialized in electrical and automation installations to determine the effectiveness and practicality of the VR training module. This research has been partially supported by Banco Santander under the scholarship program Santander Iberoamérica Research 2019/20. This investigation was partially supported by the REMAR Project (Ref. number CPP2022-009724) funded by the Ministry of Science and Innovation of Spain (MCIN/AEI/10.13039/501100011033) and by the European Union NextGenerationEU/PRTR. application/pdf eng MDPI Electronics. 2024, V. 13, n. 13, 2447 https://doi.org/10.3390/electronics13132447 info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023/CPP2022-009724/ES/Simuladores inteligentes adaptativos en Realidad Extendida para la mejora de procesos de Mantenimiento de Alto Riesgo/REMAR Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess Digital image processing Fault detection Induction motors Infrared imaging Virtual reality Informática Computer science A Virtual Reality Environment Based on Infrared Thermography for the Detection of Multiple Faults in Kinematic Chains info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Electronics 13 13 2447