IoT-Based Intelligent Monitoring and Predictive Maintenance Framework for High-Power Electric Motor Drives

Abstract

Electric motor drives with high power consumption are vital elements of most industries, such as manufacturing, oil and gas processing, and transportation systems, and renewable energy plants, whereby consistent and steady operation is most important in ensuring that the system remains productive and stable. But, due to sudden breakdowns in the motor attributed to mechanical wear and tear, electrical malfunctions, overheating, and bearing erosion, the downtime in the operation, as well as the eventual maintenance expenses, may become many times higher, and safety may be a risk. The traditional maintenance methods, reactive maintenance and scheduled preventive maintenance are not much effective in identifying fault at an early stage since they are based upon regular inspections or they react once failure has already taken place. In response to these weaknesses, the given paper presents an Internet of things/IoT-driven intelligent monitoring and predictive maintenance system that is directly aimed at high-power electric motor drives. The given framework combines smart sensor networks, real-time data acquisition modules, IoT communication technologies and cloud-based analytics in order to facilitate constant monitoring of such important parameters of motor health like vibration, temperature, current, and voltage. The sensor data obtained are sent via an IoT gateway to a centralised platform where the data preprocessing, feature detection, and machine learning functions are implemented to detect deviant normal operating modes and anticipate possible failures. Predictive models compare past and present data to determine the health behaviour of equipment and can predict fault errors before the equipment breaks down disastrously. The experimental analysis shows that the proposed system has a high fault detection ability as well as allows to schedule the maintenance proactively, thus minimising the cases of unplanned down times and enhances the operation efficiency. All in all, the suggested IoT-based predictive maintenance system can help increase the reliability of equipment, streamline the maintenance planning process, and assist in the creation of intelligent industrial monitoring systems in accordance with the ethos of Industry 4.0.