Electrical Machine Breakdown Monitoring System Using IoT

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Abstract

Nowadays, electrical machines of different types and designs are used in hybrid production systems. Electrical machines are needed to control and implement various mechanisms to produce final products. However, sometimes, electrical machines stop working and cause downtime. This affects workers’ productivity during peak hours and reduces business profits. To overcome this problem, a suitable machine-monitoring system is required so that the problem can be addressed and rectified immediately. In this paper, an IoT prototype for an electrical machine failure monitoring system using Heltec LoRa ESP32 as the microcontroller to communicate with the Blynk IoT platform server was proposed and developed. The monitored parameter values are voltage, current and motion sensor readings. A ZMPT101b voltage sensor is used to measure the AC voltage, while an ACS712 current sensor is used to measure the AC current flowing through the machine. In addition, a tilt sensor is used to detect the vibrating motion of the motor. The measured values indicate machine health and are monitored using the developed Blynk IoT GUI platform, which is accessible from mobile phones and the web. A notification from Blynk application will be sent to users to alert them about a specific condition when a value measured and uploaded to the Blynk cloud exceeds the configured average. Three tests were performed using the serial monitor, the Blynk application and the multimeter, and the results showed that the lowest percentage of error between the voltage sensor readings extracted from the serial monitor and the multimeter was 1.19% and the lowest percentage of error between the current sensor readings extracted from the serial monitor and the multimeter was 17.63%. Overall, all parameter values were successfully displayed on the IoT platform. In future works, the accuracy of the current sensor can be improved by integrating a signal conditioning circuit to filter out noise.

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APA

Wan Mohd Supian, W. R., Mohd Nordin, I. N. A., … Muhammad Razif, M. R. (2022). Electrical Machine Breakdown Monitoring System Using IoT. Journal of Advanced Industrial Technology and Application, 3(2). https://doi.org/10.30880/jaita.2022.03.02.001

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