A Smart Industrial Protection System for Three-Phase Equipment Using Data Analytics for Real Time Fault Detection

Abstract

In this study, a smart protection system was designed for three-phase equipment’s with real-time fault detection and data analytics capabilities. The proposed system integrates all protection functions of over/under voltage, phase sequence, phase failure detection, voltage imbalance monitoring and earth leakage protection under a single intelligent framework to provide enhanced safety and reliability for industrial motors in comparison to the currently existing protection systems which operate independently and do not offer much monitoring capability. Electrical parameters are monitored continuously, and the motor is automatically switched off if the parameters change in an abnormal manner to avoid overheating, insulation failure, loss of efficiency, and equipment damage. One key feature in this work is the combination of protection hardware with Python-based data analytics for processing numerical and graphical fault data in real time under various operating conditions, utilizing Jupyter Notebook. The proposed approach offers better accuracy of fault detection, quicker response to abnormal conditions, better visualization of fault behaviour, and better support for predictive maintenance and decision-making during operation when compared to benchmark conventional relay-based systems. According to experimental research, the developed system has a considerable effect on reducing the risk of a motor failure and enhances the reliability of the system and industrial safety. Moreover, the study points out the possible incorporation of artificial intelligence techniques in the future for intelligent fault prediction in the fields of industrial control and automation.