Development of low-cost vibration monitoring machine learning system on machinery using IoT

Daud, Muhammad Aminuddin (2024) Development of low-cost vibration monitoring machine learning system on machinery using IoT. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Vibration analysis is crucial to this project. The goal of this project is to demonstrate growing interest of Blynk IoT applications by creating a low-cost vibration monitoring system with which to monitor the vibration of the target machinery. The Hibiscus Sense, an accelerometer (model number: GY-521 MPU6050), and a 5000mAh battery pack make up this cheap vibration monitoring system. The Hibiscus Sense is an ESP32 development board that incorporates a microcontroller, accelerometer MPU6050, and temperature sensor BME280. It was a piece of equipment that connected to the Internet of Things and exchanged data using radio frequency networks like Wi-Fi and Bluetooth Low Energy (BLE). The CPU within the Hibiscus Sense manages the MPU6050 and GY-521 accelerometers and sends the data they collect over Wi-Fi to the Blynk app. Three MPU6050s are used to monitor the motor's vibrations. This cheap vibration monitor is controlled using the Arduino Software Development Kit (IDE) and Blynk. For vibration analysis, the Arduino IDE is used to build the code, while Blynk is utilized to display the received data in gauge form and trend form.

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