Beamformed Envelope Spectrum of acoustic signals for bearing diagnostics under varying speed conditions

Rolling element bearings are critical components in rotating machinery. Early damage detection methods are usually based on vibration signals from accelerometers. Microphones provide an interesting alternative, as they acquire system level information and could allow reducing the number of sensors. However, the bearing signature is mixed in these signals with noise coming from other nearby sources. Beamforming methods can enhance the targeted bearing signature while suppressing the contributions of other noise sources in the environment. The bearing impulses related to the localized surface defects are function of speed, and thus under varying speed conditions become nonstationary. Angular resampling based methods are therefore needed to compensate for the speed fluctuations in order to detect bearing damages. The goal of this paper is to propose a method for bearing diagnostics under varying speed conditions using an array of microphones and an encoder. The method is based on angular resampling of the microphone signals in function of the shaft speed and enhancing them using delay-sum beamforming based on the known positions of the microphones relative to the tested bearing. The method is validated on an experimental dataset acquired at a KU Leuven bearing test rig, under varying rotating speed conditions.