Inner and Outer Races Bearing Damage Detection using Low-cost Fault Detecting Sensors

Abstract

Bearings are small components of a machine used in various industries. However, bearings have an important role in transferring energy from the main motor to other parts. Therefore, monitoring the condition of the bearings is very necessary to keep the production process running smoothly. The study provides a new perspective that bearing damages were analyzed by low-cost sensors, namely the Accelerometer sensor (ADXL-335) and Arduino Uno. The results showed that the low-cost sensor developed in this study was able to detect damage to the ball bearing. The Fast Fourier Transform (FFT) signal processing tool works compatible with the low-cost sensor and could be used to determine the type of damage to the bearing by analyzing the signal frequency spectrum. In this process, there were several frequencies that appear with characteristics related to the condition of the bearing. The working frequency of the shaft rotation on the bearing with normal conditions was 10 Hz, the frequency with damage to the inner race of the bearing was 55.52 Hz, and the bearing with damage to the outer race included a frequency of 34.47 Hz.