4.6 Article

Virtual Reality Training Application for the Condition-Based Maintenance of Induction Motors

Journal

APPLIED SCIENCES-BASEL
Volume 12, Issue 1, Pages -

Publisher

MDPI
DOI: 10.3390/app12010414

Keywords

virtual reality; induction motors; fault detection; FFT; eye tracking

Funding

  1. Banco Santander [2019/20]
  2. ACIS project of the Consejeria de Empleo of the Junta de Castilla y Leon (Spain) [INVESTUN/21/BU/0002]

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The use of virtual reality (VR) as a training method offers a more engaging and interactive approach compared to traditional methods, especially for young students who are accustomed to continuous entertainment. This research focuses on the development of a VR-based application for teaching and training in the condition-based maintenance of induction motors, utilizing natural interactions with the VR environment. The usability of this VR tool has been validated with graduate and undergraduate students, demonstrating its suitability for both learning basic knowledge and practical skills related to induction motor maintenance.
The incorporation of new technologies as training methods, such as virtual reality (VR), facilitates instruction when compared to traditional approaches, which have shown strong limitations in their ability to engage young students who have grown up in the smartphone culture of continuous entertainment. Moreover, not all educational centers or organizations are able to incorporate specialized labs or equipment for training and instruction. Using VR applications, it is possible to reproduce training programs with a high rate of similarity to real programs, filling the gap in traditional training. In addition, it reduces unnecessary investment and prevents economic losses, avoiding unnecessary damage to laboratory equipment. The contribution of this work focuses on the development of a VR-based teaching and training application for the condition-based maintenance of induction motors. The novelty of this research relies mainly on the use of natural interactions with the VR environment and the design's optimization of the VR application in terms of the proposed teaching topics. The application is comprised of two training modules. The first module is focused on the main components of induction motors, the assembly of workbenches and familiarization with induction motor components. The second module employs motor current signature analysis (MCSA) to detect induction motor failures, such as broken rotor bars, misalignments, unbalances, and gradual wear on gear case teeth. Finally, the usability of this VR tool has been validated with both graduate and undergraduate students, assuring the suitability of this tool for: (1) learning basic knowledge and (2) training in practical skills related to the condition-based maintenance of induction motors.

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