Use of Proximity-Based Shaft Displacement Sensors for Rolling Element Bearing Fault Diagnosis

PurposeTraditional bearing health monitoring relies on acceleration signals from accelerometers on bearing housings. Displacement sensors, like proximity probes, are commonly used for rotor vibration monitoring and balance checks. This research aims to investigate the efficacy of employing displacement vibration signals for the detection of faults in rolling element bearings.MethodsThis study establishes that through appropriate signal processing of raw shaft displacement data, reliable indications of bearing faults can be obtained. Time-domain vibration signals are decomposed into intrinsic-mode functions (IMFs) using ensemble empirical mode decomposition. The most relevant IMF, containing fault-related information, is selected based on a proposed impulsiveness indicator. Autocorrelation of the energy time series of the sensitive IMF is suggested for fault classification.ResultsThe proposed methodology is validated using experimental data from damaged bearings and an accelerated bearing life test. A comprehensive comparison between displacement sensors and accelerometers confirms that, with suitable signal processing, displacement sensors effectively capture bearing fault information and assess fault severity.ConclusionsThis research establishes that, with proper signal processing, displacement sensors are effective for bearing health monitoring and assessing fault severity. This work highlights the potential of using displacement sensors, enhanced by advanced signal processing, for reliable bearing health assessment.