Virtual Reality System for training in the detection
and solution of failures in induction motors

  • Gustavo Caiza,
  • Marco Riofrio-Morales,
  • Veronica Gallo C.,
  • Santiago Alvarez-T.,
  • Wilson O. Lopez,
  • Marcelo V. Garcia 
  • Universidad Politecnica Salesiana, UPS, Rumichaca y Moran Valverde av., Quito, 170146, Ecuador
  • b  Universidad Tecnica de Ambato, UTA, Colombia Av. and Chile st., Ambato, 180103, Ecuador 
  • c,d  Instituto Superior Tecnológico María Natalia Vaca, ISTMNV, Bolivariana Av. and El Condor Av., Ambato, 180205, Ecuador 
  • e  Universidad Tecnologica Indoamerica, UTI, Antonio Clavijo st., Ambato, 180103, Ecuador (f)Universidad Tecnica de Ambato, UTA, Colombia Av. and Chile st., Ambato, 180103, Ecuador
  • f  University of Basque Country, UPV/EHU, Alameda Urquijo, Bilbao, 48013, Spain
Cite as
Caiza G., Riofrio-Morales M., Gallo V.C., Alvarez-T. S, Lopez W.O., Garcia M.V. (2021). Virtual Reality System for training in the detection and solution of failures in induction motors. Proceedings of the 33rd European Modeling & Simulation Symposium (EMSS 2021), pp. 199-207. DOI:


The changing industrial world in which we find ourselves has forced companies to evolve technologically, restructuring their processes and improving their human resources skills. The acceptance by management of a fourth industrial revolution in transition to a fifth has led them to look for an economical way to stay updated and with the necessary skills to optimize their production chain. This work presents the development of virtual reality (VR) system for training in detecting faults in three-phase electric motors. A sample of 30 people was used, homogeneously divided into a control group and an experimental group. To evaluate the VR systems usability, the System Usability Scale (SUS) was used, obtaining an average value of 73.33, classifying the system as efficient for the proposed task. On the other hand, in terms of time and knowledge retention, the performance of this system was compared with the execution of a conventional one. For the training time, an optimization of 57.73% was obtained, while through a p-value of 0.000003, it was confirmed that this VR system provides a novel teaching methodology for the instruction and retention of technical knowledge.


  1. Baygin, Mehmet; Karakose Mehmet; Akin, E. (2016). ITHET 2016 : 2016 15th International Conference on Information Technology Based Higher Education and Training (ITHET) : September 8-10, 2016, Istanbul, Turkey. Institut of Electrical and Electronics Engineer ing. 
  2. Caiza, G., Garcia, C. A., Naranjo, J. E., and Garcia, M. V. (2021). Assessment of Engineering Techniques for Failures Simulation in Induction Motors Using Nu merical Tool. pages 307–319. 
  3. Cervera, M., Grandon, N., Rivera, M., and Besoain, F. (2019). Improving the selection of IQF raspberries in processing lines: A Virtual Reality approach for training and selecting personnel. 2018 IEEE Biennial Congress of Argentina, ARGENCON 2018, pages 1–7. 
  4. Chibani, D., Achour, N., and Daoudi, A. (2020). SPIDAR Welder a haptic interface for virtual welding training. CCSSP 2020 - 1st International Conference on Commu nications, Control Systems and Signal Processing, pages 293–297. 
  5. Davila Delgado, J. M., Oyedele, L., Beach, T., and Demian, P. (2020). Augmented and Virtual Reality in Construction: Drivers and Limitations for Indus try Adoption. Journal of Construction Engineering and Management, 146(7):04020079. 
  6. Fireteanu, V., Constantin, A. I., Leconte, V., and Lom bard, P. (2018). Analysis of the Evolution of Stator Short-circuit and Rotor Bar Breakage Faults in a
  7. Squirrel-cage Induction Motor. SPEEDAM 2018 - Pro ceedings: International Symposium on Power Electronics, Electrical Drives, Automation and Motion, pages 190– 195. 
  8. He, Q., Cheng, X., and Cheng, Z. (2019). A VR-based Complex Equipment Maintenance Training System. Proceedings - 2019 Chinese Automation Congress, CAC 2019, pages 1741–1746. 
  9. Kim, S.-U., Lee, K., Cho, J.-H., Koo, K.-C., and Kim, S. B. (2017). Toward an Evaluation Model of User Experiences on Virtual Reality Indoor Bikes. European Scientific Journal, 7881(June):1857–7881. 
  10. Lacko, J. (2020). Health safety training for industry in virtual reality. Proceedings of the 30th International Conference on Cybernetics and Informatics, K and I 2020, pages 1–5. 
  11. Lewis, J. R. and Sauro, J. (2009). The factor struc ture of the system usability scale. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformat ics), 5619 LNCS:94–103. 
  12. Lustosa, E. B. S., De MacEdo, D. V., and Rodrigues, M. A. F. (2018). Virtual simulator for forklift train ing. Proceedings - 2018 20th Symposium on Virtual and Augmented Reality, SVR 2018, pages 18–26. 
  13. Lustosa, E. B. S., De MacEdo, D. V., and Rodrigues, M. A. F. (2018). Virtual simulator for forklift train ing. Proceedings - 2018 20th Symposium on Virtual and Augmented Reality, SVR 2018, pages 18–26. 
  14. Maloma, E., Muteba, M., and Nicolae, D. V. (2017). Ef fect of rotor bar shape on the performance of three phase induction motors with broken rotor bars. Pro ceedings - 2017 International Conference on Optimiza tion of Electrical and Electronic Equipment, OPTIM 2017 and 2017 Intl Aegean Conference on Electrical Machines and Power Electronics, ACEMP 2017, pages 364–369. 
  15. Meldrum, D., Glennon, A., Herdman, S., Murray, D., and McConn-Walsh, R. (2012). Virtual reality rehabil itation of balance: Assessment of the usability of the Nintendo Wii ® Fit Plus. Disability and Rehabilitation: Assistive Technology, 7(3):205–210. 
  16. Naranjo, J., Urrutia Urrutia, F., Garcia, M., Gallardo Cardenas, F., Franklin, T., and Lozada-Martinez, E. (2019). User experience evaluation of an inter active virtual reality-based system for upper limb rehabilitation. In 2019 6th International Conference on eDemocracy and eGovernment, ICEDEG 2019. 
  17. Nurkertamanda, D., Saptadi, S., Widharto, Y., and Maliansari, A. N. (2019). Feasibility evaluation: Vir tual laboratory application based on virtual reality for lathe engine training simulation. 2019 6th Interna tional Conference on Frontiers of Industrial Engineering, ICFIE 2019, pages 6–10. 
  18. Randeniya, N., Ranjha, S., Kulkarni, A., and Lu, G. (2019). Virtual Reality Based Maintenance Training Effectiveness Measures - A Novel Approach for Rail Industry. IEEE International Symposium on Industrial Electronics, 2019-June:1605–1610. 
  19. Rozo-García, F. (2020). Revisión de las tecnologías presentes en la industria 4.0. Revista UIS Ingenierías, 19(2):177–191. 
  20. Sharfina, Z. and Santoso, H. B. (2017). An Indonesian adaptation of the System Usability Scale (SUS). 2016 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2016, pages 145–148. 
  21. Shen, S., Chen, H. T., and Leong, T. W. (2019). Train ing transfer of bimanual assembly tasks in cost differentiated virtual reality systems. 26th IEEE Con ference on Virtual Reality and 3D User Interfaces, VR 2019 - Proceedings, pages 1152–1153. 
  22. Urbina Pérez, M. G., Mecalco Reyes, J., Muñoz Herrera, C. A., and Cruz Silva, S. P. (2021). Las fortalezas y debilidades de los ambientes virtuales/digitales en crisis sanitarias; caso de estudio Covid-19 en México. 
  23. Wang, C. (2019). Research on panoramic image process ing technology based on virtual reality technology. Proceedings - 2019 International Conference on Virtual Reality and Intelligent Systems, ICVRIS 2019, pages 55– 58.