Özet:

In this study, an industrial internet of things (IIoT) based sensor card system has been developed to predict the failures that may occur in induction motors (IMs), which is widely used in the industry and therefore it is important to take predictive maintenance measures. The realized system has been tested on a 3-phase IM with 250 kW power and 315L body structure. The conditions of this IM were detected by the sensors in the embedded system and transferred to a cloud network with the embedded system. The ESP-WROOM-32 microcontroller, which includes Wi-Fi and Bluetooth communication protocols in the sensor card application, is mounted on a LIS3DH accelerometer that detects frequency-dependent vibration data in three axes and NTC IM at 10 KΩ for temperature data. By evaluating these sensor data, predictive maintenance determinations that may occur in the IM were made and predictive maintenance decisions were made for the IM to send warnings to the users with these detections.

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