Real-Time Low-Cost Fault Detection System Placed in Non-Drive End of Motors Based on Neural Networks

Electric motors are vital components in various industrial applications, from production manufacturing to transportation and power generation. They are indispensable parts of machinery and equipment required for the industry, and their effective running is a must for maintaining operational efficiency and productivity. However, a motor suffers from different kinds of faults that can be expensive in terms of downtime, loss of production, and repair costs. Early detection of these faults is important in reducing unscheduled shutdowns, maintenance costs, and workplace accidents. This paper presents the design of a low-cost, real-time fault detection system for motors installed on the Non-Drive End based on neural networks, with the aim of enhancing operational efficiency and reducing maintenance costs in industries.