Detection of Localized Fault in Inner Race of Deep Groove Ball Bearing Based on MSC-Adams

ABSTRACTThis work aims to enhance an approach to detect localized fault on the inner race of deep groove ball bearing in presence of generated vibration.Experiments is equipped to measure vibrations signals for different sizes of deep groove ball bearing in the presence of localized surface fault to diagnosis the unhealthy bearing. Dynamic model based on MSC-ADAMS can serve as a tool to obtain vibration responses that generated due to the bearing faults. Root mean square (RMS), crest factor, kurtosis and skewness will serve as indicators of average amplitude of envelope analysis signals. The vibration signals pattern collected from the simulation model and experimental data have the same results.The accelerometers attach in two positions to determine the suitable detection method of a fault on the inner race on both the loaded and un-loaded zones. It can be concluded that the acceleration RMS ratio is more effective in detecting the defect for acceleration response. Also the acceleration kurtosis ratios may be used to detect the fault located at the loaded zone. While acceleration crest factor and skewness ratios are failed to indicate the fault diagnosis.