2026-04-20T09:42:21Zhttps://riubu.ubu.es/oai/request

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

00925njm 22002777a 4500 dc Alvarado-Hernandez, Alvaro Ivan author Checa Cruz, David author Osornio-Ríos, Roque Alfredo author Bustillo Iglesias, Andrés author Antonino Daviu, Jose A. author 2024-06-22 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. 2079-9292 http://hdl.handle.net/10259/9517 10.3390/electronics13132447 2079-9292 Digital image processing Fault detection Induction motors Infrared imaging Virtual reality A Virtual Reality Environment Based on Infrared Thermography for the Detection of Multiple Faults in Kinematic Chains