Electrical Machine Breakdown Monitoring System Using IoT - Wan Mohd Supian, Wan Rusydi; Mohd Nordin, Ili Najaa Aimi; Khamis, Nurulaqilla; Muhammad Razif, Muhammad Rusydi (Journal of Advanced Industrial Technology and Application, 2022)
Nowadays, electric machines of various types and designs are mainly used in hybrid production systems. Electrical machines are required to control and implement various mechanisms for the production of final products. However, sometimes, for unknown reasons, electrical machines stop working and cause downtime. As a result, this affects work productivity during peak hours and reduces the profitability of the company. To overcome this problem, a proper electrical machine monitoring system is required so that the problem can be addressed and resolved immediately. In this thesis, a prototype of IoT based on the motor breakdown monitoring system using Heltec Lora ESP32 as a microcontroller to communicate with the Blynk IoT platform server is proposed and developed. The parameter values that were monitored are voltage, current and motion sensor reading. The ZMPT101b voltage sensor was used to measure AC voltage while the ACS712 current sensor was used to measure AC current flow through the electrical machine. Moreover, a tilt sensor was used to detect the vibration movement of the motor. The measured values indicate the condition of the motor and were monitored using the developed GUI Blynk IoT platform that can be viewed from mobile phones and website. Email and SMS notifications are sent to users to warn of specified conditions when the measured and uploaded values to the Blynk cloud exceed the configured average values. The effectiveness of the value parameter is analyzed by comparing it with standard measuring device such as clamp meter and multimeter. There were 3 experimental trials conducted and the results showed the lowest average percentage error for voltage sensor was 0.19% and for the current sensor was 17.36%. The tilt sensor on the other hand was not responding to the motor vibrations due to the low sensitivity of the sensor. Overall, all parameter values were successfully displayed on the IoT platform. In the future, the accuracy of the current sensor can be improved by integrating a signal conditioning circuit to filter out noise. Other parameter values suitable for monitoring the motor's status can also be used, such as temperature and water flow sensors