# Virtual Reality Training Application for the Condition-Based Maintenance of Induction Motors
## 7 Conclusions  
In this work, the development of a VR-based application for teaching and training for condition-based maintenance in induction motors is presented. The widespread use of induction motors makes it necessary to understand the basis of their operation condition as an essential aspect of any maintenance program. Additionally, the implementation of condition-based maintenance programs aims to safeguard their operating condition and its availability. The application has two training modules. The first was focused on the main components of induction motors, the assembly of workbenches and familiarization with the elements of induction motors. The second module employs motor current signature analysis to detect induction motor failures, such as broken rotor bars, misalignments, unbalances, and gradual wear on gear teeth. The practical implementation of MCSA represents a difficult task and is crucial in the training of new maintenance technicians. Therefore, this application, with embedded data from real experimental test benches and the correct use of virtual reality tools, is a solution for training these aspects. The tool has been designed considering that, in VR educational applications, the \"novelty effect\" and the user's amazement for the innovative technology of using HMDs must be minimized. Moreover, the design of this tool aims to avoid reductions in learning efficiency due to a lack of control of the VR interface. For this purpose, different introductory levels have been designed in the form of interactive tutorials, placing special emphasis on creating natural user interfaces. This application follows the idea that, rather than learning theory in a formal manner, the real potential of VR lies in \"learning by doing\". There are many factors why this cannot be done in traditional trainings, such as access to the material or its high cost. This virtual reality application helps to increase interest in the material based on the students' preference for practice-oriented learning content. Thus, through VR tools, the simulation of these complicated processes can be accomplished in an efficient and cost-effective manner. During the validation, an analysis of a satisfaction/usability test was performed, and the satisfaction and belief of its usability with students was found to be very high. This result is particularly interesting in the context of the SARS-CoV-2 (COVID-19) crisis, which highlights the growing demand for distance learning content. Future studies will look at the massive assessment of the training capacity of the application to determine its suitability for its possible inclusion in regular educational programs, where learning outcomes should also be evaluated and compared with other learning methodologies. Moreover, an additional prospective avenue for this research to follow is that the improvement of this VR-based application will facilitate any demonstration of the importance of induction motor efficiency for energy efficiency, operational expenses and how the system losses will build up in the different applications. Finally, the application makes use of motor current signature analysis (MCSA) to detect induction motor failures such as broken rotor bars, misalignments, unbalances, and gradual wear on gearing teeth. It is expected to address the incorporation of other methods as well as the simulation of its operating working condition under the influence of additional faults of induction motors, focusing on the detection of multiple and/or combined faults. The VR application is available for download at the following URL: [https://3 dub.es/en/electricmotors](https://3 dub.es/en/electricmotors). Conceptualization, D.C. and R.A.O.-R.; methodology, D.C., J.J.S.-D. and A.B. ; validation, J.J.S.-D. and D.C.; formal analysis, D.C. and R.A.O.-R.; investigation, J.A.A.-D. and J.J.S.-D.; resources, J.A.A.-D.; data curation, A.B.