Abstract-Rolling element bearings are critical mechanical components in rotating machinery. Fault detection and diagnosis in the early stages of damage is necessary to prevent their malfunctioning and failure during operation. Vibration monitoring is the most widely used and cost-effective monitoring technique to detect, locate and distinguish faults in rolling element bearings. This paper presents an algorithm using feed forward neural network for automated diagnosis of localized faults in rolling element bearings. Normal negative log-likelihood value and kurtosis value extracted from time-domain vibration signals are used as input features for the neural network. Trained neural networks are able to classify different states of the bearing with 100% accuracy. The proposed procedure requires only a few input features, resulting in simple preprocessing and faster training. Effectiveness of the proposed method is illustrated using the bearing vibration data obtained experimentally.
The present work reports the effect of leading-edge tubercles on aerodynamic performance and flow features of a cambered airfoil E216 at a Reynolds number of 100,000 and at various angles of attack in the pre-stall regime. Amplitude values of 2 mm, 4 mm and 8 mm and wavelength values of 15.5 mm, 31 mm and 62 mm are used for both experimental and simulation studies. The Transition-SST RANS model is used to simulate transition phenomenon (laminar separation bubble) and threedimensional flow features over the airfoil. Wind tunnel experimental results are used for the performance analysis and the validation of the simulation methodology. The experimental values of C l and C d are 1.37 and 0.081, respectively, at a stall angle of 12 • for the plain airfoil. The experimental results show that the lift generated by tubercled airfoils is higher than that produced by the plain airfoil in the pre-stall region but lower at the stall angle. A maximum benefit of 4.51% in C l is obtained for the tubercled airfoil with the highest amplitude (8 mm) and wavelength (64 mm) at 6 • angle of attack. A higher C d is observed for all the tubercled airfoils than for the plain one. The simulation is mainly carried out to study the flow structure. Simulation results indicate the presence of laminar separation bubbles on the plain airfoil with a straight separation and reattachment line parallel to the trailing edge. The tubercles considerably altered the laminar separation bubble formation and the flow structure. A sinusoidal laminar separation bubble is formed on the tubercled airfoils with reduced bubble length. The laminar separation bubble along the trough is formed ahead of that at peak. Two pairs of counter-rotating vortices are formed on the airfoil surface along the trough at two different chord-wise locations which strongly alter the flow pattern over it. Prandtl's secondary flow of the first kind is the key reason for the vortex formation.
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