Thermal Imaging Fault Detection for Rolling Element Bearings

Abstract

In rotating machinery, rolling element bearings are one of the most critical components and a large majority of system failures arise from faulty bearings. Hence, there is an increasing demand to find an effective and reliable condition monitoring technique. In this paper, a procedure for detecting various types of bearing faults using thermal imaging is presented and assessed. Five different fault cases are tested: no fault (NF), line fault (LF), small circle fault (SCF), double line fault (DLF), and large circle fault (LCF). Experiments were conducted on the BENTLY NEVADA RK4 Rotor Kit. The tests were performed at 1500 RPM and 2000 RPM. A video is recorded for 10 minutes using FLIR thermal imaging camera and images are extracted from the video and processed to detect the average temperature at the bearing hotspot using MATLAB. Analysis of the results show that Thermal Imaging can be used as an effective means to differentiate between different types of faults that occur in the outer race of the rolling element bearing.