IoT Enabled Condition Monitoring of Low Voltage Motors using Fuzzy Inference System

In the revolutionized industry 4.0 vision, the predictive maintenance of the machines make the maintenance easy and smart using Internet of Things (IoT). It helps to improve the overall machine performance, capacity, sustainability and user safety. IoT serves as a well-planned structure for condition monitoring with the flexibility to integrate more number of devices to be monitored and controlled remotely. In this paper, a real-time condition monitoring prototype of low voltage industrial motor is developed. The prototype majorly monitors three vital parameters, temperature, vibration and speed of the motor using suitable sensors connected to Zigbee module sending data wirelessly to the remote end using IoT. These data are then fed from Thingspeak server to the Fuzzy Inference System (FIS) to estimate the health of the motor. The complete devised prototype performs the function of monitoring, processing data, decision making and data storage remotely without any considerable user intervention.