Low-Cost Vibration Data Acquisition System for Induction Motor Bearing Fault Diagnosis Using FFT

The Ball bearing is a crucial part of different types of electrical rotating machines. The fault diagnosis of bearing implementation methods plays a significant role in maintaining the safe operation of these rotating machines. Over the past twenty years, numerous researchers have conducted bearing fault diagnosis using expensive sensors such as accelerometers. Nevertheless, small industries are unable to invest in these costly sensors due to their high price. To tackle this issue, this paper suggests utilizing a low-cost and non invasive data acquisition system for bearing fault diagnosis. Vibration data is acquired under varying load conditions utilizing an affordable data acquisition device comprising an ESP32 microcontroller with an MPU9250 sensor from the Induction Motor (IM). Subsequently, the vibration data is processed using the Fast Fourier Transform for bearing fault diagnosis. The experimental bearing fault frequency outcomes were compared with theoretical values and revealed that they closely matched. This examination distinctly indicates that the suggested method can identify multiple bearing faults in induction motors using a cost-effective data acquisition system.