Development of a Computational Tool Based on Intelligent Computing Models for Condition Monitoring in Rotating Machinery

This project addresses the need to minimize production time and costs in competitive industrial environments, where failures in rotating equipment are a primary cause of high operational expenses. The proposed solution focuses on developing a computational tool that utilizes intelligent computing models for real-time condition monitoring of rotating machinery. The approach is based on applying data mining and artificial intelligence techniques, following the fundamental phases of feature extraction, feature selection, and classification, previously developed by the GIDTEC group. The methodology includes an exhaustive analysis of the processes, components, sensors, and communication protocols associated with the machinery. Subsequently, the system is designed, appropriate intelligent algorithms are selected, and the software is developed, considering options like Matlab or Python. A key component is the design and implementation of an intuitive Human-Machine Interface (HMI) to facilitate user interaction with the analysis results in an understandable language. Finally, the prototype will be validated through extensive testing and its deployment on real rotating machinery to ensure its accuracy and online operability.<br/><br/><b>Goal</b>: <br/>To design and implement an advanced computational tool, based on intelligent computing models, with the primary purpose of performing condition monitoring on rotating machinery.<br/><br/><b>Research lines</b>: <br/>Simulation and optimization of industrial processes