Induction motors are an important component in various industrial applications due to their reliability in long-term opeation. Failure of induction motors can cause production disruptions and significant repair costs. This research develops an Internet of Things (IoT)-based vibration monitoring system using ADXL345 accelerometer sensors and ESP32 microcontrollers. The vibration data obtained is sent to a computer via asynchronous serial communication, where the computer performs FFT calculations and frequency analysis to extract dominant information from the vibration signal. Damage detection is performed using a combination of heuristics and threshold rules to classify the motor status as healthy or ambiguous. The classification results are then sent back via the MQTT protocol and can be visualized in real-time through a dashboard. This system enables predictive maintenance, thereby minimizing the risk of sudden failure and increasing operational efficiency.
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