To compare the effect of different level of self-lubrication for bearings using statistical analysis of vibration signal

Material coating plays an important role in the field of engineering and the characteristics of coating can be corroborated through vibration analysis. In this work, two different bearing are selected, one is having coating of Al2O3 deposited by plasma thermal spray process (NBC30205) and other is having coating of wear resistant carbon deposited by physical vapour deposition process. These two bearings are made to run at three different linear velocities under loading conditions and their vibration signals were recorded. The statistical moments of these vibration signals are calculated and results are presented in context with the properties of coating. The results reveals that the bearing having wear resistant carbon deposited yields lower values of statistical moment as this coating is having self-lubricating property. The spectral contents of these signals were also calculated by taking the RMS of Fast Fourier transform, where carbon coated material is yielding to lower value than the Al2O3 coated bearing. The lower value of spectral content clearly reveals the less value of harshness present in the signal, which is due to better lubrication. In all the responded parameters randomness of spectral contents is exhibiting the maximum variation and could be set as benchmark for studying the different level of self-lubrication. (c) 2018 Elsevier Ltd. All rights reserved.