Experimental Investigations on Finding Ball Bearing Defects Using Signature Analysis
DOI:
https://doi.org/10.51983/ajsat-2014.3.2.796Keywords:
Signal characteristics, Time domain analysis, frequency domain analysisAbstract
This paper presents for identify the defected bearing using vibration frequency. There have been a lot of researches on diagnosing rolling element bearing faults using wavelet analysis, but almost all methods are not ideal for picking up fault signal characteristics under strong noise. The rolling element bearing is used widely in all rotating components. It is one of the most susceptible components in a machine because it is most often under maximum load and high speed running conditions. This paper describes the suitability of vibration monitoring and analysis techniques to become aware of defects in antifriction bearings. Time domain analysis, frequency domain analysis and spike energy analysis have been working to identify different defects in bearings.
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