Implementation of an Early-Stage Motor and Drive Fault Detection and Health Monitoring System

This paper presents the implementation of an early stage fault detection and health monitoring system for electric motors and their drive units. The study focuses on developing a cost-effective system capable of identifying abnormal behavior in both drive electronics and mechanical components before a major failure occurs. The proposed design integrates multiple sensing parameters such as vibration, acoustic signals, and electrical quantities including voltage and current. These inputs are processed using data-driven techniques to assess motor condition and identify fault patterns. A microcontroller-based platform is used for real-time monitoring and signal processing, providing early warnings through an intuitive serial interface. Experimental observations confirm that this approach can effectively detect drive faults, motor imbalance, and bearing wear at an early stage, reducing downtime and maintenance costs. This work demonstrates a practical and scalable method to enhance the reliability and operational safety of motor-driven systems, contributing to improved industrial efficiency and predictive maintenance strategies.