Diseño de sistema de monitoreo predictivo de motores eléctricos mediante análisis de vibración y parámetros eléctricos

Abstract

CONDITION FOR PUBLICATION OF PROJECT. Predictive maintenance is a key technique for anticipating failures in industrial electric motors. This project aims to design and implement a predictive monitoring system for a 120V motor, with the goal of detecting mechanical failures at an early stage. The system seeks to meet the need for a practical training tool for engineering students, based on the hypothesis that vibration analysis will enable effective diagnosis. A system was developed that integrated a National Instruments CompactDAQ for electrical and vibration data acquisition, applying signal processing techniques and the ISO 10816 standard. A SCADA interface was implemented in LabVIEW that allowed real-time visualization and the activation of alerts. The MQTT protocol was used for remote visualization. The most relevant results included the correct acquisition of real-time data and the system's ability to distinguish between the behavior of the motor under normal conditions and with simulated faults. Vibration measurements and spectral analyses showed anomalous behavior that allowed the fault to be detected before further damage occurred. In conclusion, the designed system is functional and is considered a valuable educational tool for training future engineers, aligning their learning with industrial demands and strengthening the laboratory's research capabilities. Keywords: Predictive monitoring, maintenance, LabVIEW, vibrations.