A Virtual Reality Environment Based on Infrared Thermography for the Detection of Multiple Faults in Kinematic Chains

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-invasi...

Full description

Saved in:
Bibliographic Details
Published inElectronics (Basel) Vol. 13; no. 13; p. 2447
Main Authors Alvarado-Hernandez, Alvaro Ivan, Checa, David, Osornio-Rios, Roque A., Bustillo, Andres, Antonino Daviu, Jose A.
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.07.2024
Subjects
Cost analysis
Costs
Design
Effectiveness
Fault detection
Infrared analysis
Infrared imagery
Infrared imaging
Infrared radiation
Kinematics
Modules
Preventive maintenance
Thermal imaging
Thermography
Training
Virtual environments
Virtual reality
Online AccessGet full text

Cover

More Information
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2079-9292
2079-9292
DOI:10.3390/electronics13132447