Abstract:

The recent trend towards the smart and lowenergy consumption of the industrial automation process has established the necessity of the efficient, inexpensive diagnostic that can guarantee the safety of the machines and their uninterrupted work. Traditional ways of monitoring motor driven systems are sometimes reduced to manual inspections or to the inflexible control units that do not offer the possibility of fault prediction and real-time energy analysis. This paper has discussed an IoT based twocontroller system of real time fault prevention and energy monitoring of industrial motors in precision machinery. The system suggested combines an Arduino Uno that can be used to collect multi-sensor data (temperature, vibration, current, voltage, and speed) and a NodeMCU (ESP8266) that allows gaining access to wireless communication and cloud visualization using the ThingSpeak platform. A Hi-Link isolated power module offers stable low voltage operation which is safe. The threshold violations generate the alerts that are preventive and allow controlling the motor remotely using the cloud interface with ON/OFF. It also calculates the instantaneous power and total energy use on the dashboard to assess the motor efficiency and how it is used. The experiments indicate the lowlatency transmission of data and high detection rates, proving that the system can be used to make a prediction about a fault and optimize the energy consumption. The suggested framework provides a scalable industry 4.0 compatible framework that can be expanded to Industry 5.0-based practices of AI-assisted adaptive maintenance.