Experimental Study on Condition Monitoring of Low Speed Bearings: Time Domain Analysis

TLDR

In condition monitoring of low‑speed rolling element bearings, vibration‑based techniques often fail to detect incipient faults because the low impact energy of the components’ relative motion limits signal strength. The study experimentally evaluates early fault detection in low‑speed REBs using an acoustic‑emission sensor and an accelerometer. A low‑speed fault‑simulation rig operating at 10 rpm was built, seeded with defect bearings, and instrumented with the AE sensor and accelerometer to collect data. The results determine the optimal frequency bandwidth and time‑domain statistical parameters for early detection of low‑speed bearing defects using AE signals.

Abstract

In condition monitoring of low speed rolling element bearings (REBs), traditional techniques involving vibration acceleration may not be able to detect a growing fault due to the low impact energy generated by the relative motion of the components. This study presents an experimental evaluation for incipient fault detection of low speed REBs by using an acoustic emission (AE) sensor and an accelerometer. A low speed fault simulation test rig was developed to simulate common machine faults with shaft speeds as low as 10rpm under loading conditions. Tests were conducted on the rig with various seeded defect bearings. This study reveals the best frequency bandwidth and suitable parameters for condition monitoring using AE signal for early detection of low speed bearing defects by means of statistical parameters in time domain.