Effect of Bearing Surface Characteristics on Bearing Oil Film Thickness

1989 ◽  
Author(s):  
Bert H. Clampitt
Keyword(s):  
Film Thickness ◽  
Surface Characteristics ◽  
Bearing Surface ◽  
Oil Film

Experimental Analysis of Journal Bearings

1995 ◽  
Vol 117 (3) ◽  
pp. 589-592 ◽  
Author(s):  
A. H. Elkholy ◽  
A. Elshakweer
Keyword(s):  
Film Thickness ◽  
Experimental Technique ◽  
Experimental Analysis ◽  
Journal Bearing ◽  
Journal Bearings ◽  
Bearing Surface ◽  
General Outline ◽  
Modes Of Operation ◽  
Oil Film ◽  
Design Charts

This study presents a comprehensive technique, which could be applied to almost any rotating equipment to identify and diagnose journal bearing problems that relate to metal-to-metal bearing surface contact. Orbital measurements that describe bearing parameters in different modes of operation were experimentally obtained and analyzed. Such parameters may include: attitude angle, minimum oil film thickness, and the possibility of metal-to-metal rubbing occurrence. The general outline of the presented experimental technique was substantiated using the Raimondi–Boyd well-documented design charts and good correlation between experimental and analytical results was obtained.

Measurement of the Journal Locus in the Con-Rod Big-End Bearing of an Automobile Gasoline Engine

1973 ◽  
Vol 95 (2) ◽  
pp. 249-254 ◽  
Author(s):  
M. Hiruma ◽  
S. Furuhama
Keyword(s):  
Film Thickness ◽  
Gasoline Engine ◽  
The Other ◽  
Inertia Force ◽  
Bearing Surface ◽  
Automobile Engine ◽  
Combustion Pressure ◽  
Oil Film ◽  
New Device ◽  
Automobile Gasoline

To measure the absolute oil film thickness or the journal center locus in con-rod big-end bearings of a practical automobile engine, a special new device and procedure have been developed. By means of this method, the measurement could be carried out stably up to full load at 5000 rpm. These measurements revealed that the journal travels along the vicinity of bearing surface by the inertia force. In the combustion period, however, the journal center passes near the center point of the bearing. On the other hand, under a misalignment condition, the minimum oil film thickness depends on the combustion pressure. Therefore in the future many of the problems related to con-rod big-end bearings will be resolved by this method.

The Surface-Roughness of Bearing-Surfaces and its Relation to Oil Film Thickness at Breakdown

1949 ◽  
Vol 161 (1) ◽  
pp. 73-79 ◽  
Author(s):  
A. Cameron
Keyword(s):  
Surface Roughness ◽  
Film Thickness ◽  
Hydrodynamic Theory ◽  
Quantitative Relation ◽  
Metal Contact ◽  
Initial Contact ◽  
Frictional Drag ◽  
Average Roughness ◽  
Finished Steel ◽  
Oil Film

In this paper the relation of surface roughness of bearing surfaces to allowable film thickness is studied quantitatively with a simple Michell pad apparatus. The pads used were faced with white metal and ran against mild steel collars. The lubricants studied were water, soap solution, paraffin, and light oil. There was little difference in the frictional behaviour of any of the lubricants, except that the aqueous lubricants would not run with very finely finished steel surfaces. The onset of metal to metal contact was detected by an increase in the frictional drag, and also by the change in electrical conductivity between the pad and collar—an extremely sensitive method. The paper shows that there is, at any rate for this system, a quantitative relation between the total surface roughness of the rubbing surfaces and the calculated oil film thickness both at the initial metal to metal contact and seizure. Initial contact occurs when the outlet film thickness, calculated from normal hydrodynamic theory, falls to three times the maximum surface roughness and seizure occurs when it is double the average roughness.

Influence of Surface Waviness on the Thermal Elastohydrodynamic Lubrication of an Eccentric-Tappet Pair

2013 ◽  
Vol 135 (2) ◽  
Author(s):  
J. Wang ◽  
C. H. Venner ◽  
A. A. Lubrecht
Keyword(s):  
Film Thickness ◽  
Elastohydrodynamic Lubrication ◽  
Surface Waviness ◽  
Film Pressure ◽  
Oil Film ◽  
Working Cycle ◽  
Temperature Oscillations ◽  
Minimum Film Thickness ◽  
Traction Coefficient ◽  
Oil Film Pressure

The effect of single-sided and double-sided harmonic surface waviness on the film thickness, pressure, and temperature oscillations in an elastohydrodynamically lubricated eccentric-tappet pair has been investigated in relation to the eccentricity and the waviness wavelength. The results show that, during one working cycle, the waviness causes significant fluctuations of the oil film, pressure, and temperature, as well as a reduction in minimum film thickness. Smaller wavelength causes more dramatic variations in oil film. The fluctuations of the pressure, film thickness, temperature, and traction coefficient caused by double-sided waviness are nearly the same compared with the single-sided waviness, but the variations are less intense.

scholarly journals Artificial Neural Network Model for Monitoring Oil Film Regime in Spur Gear Based on Acoustic Emission Data

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Yasir Hassan Ali ◽  
Roslan Abd Rahman ◽  
Raja Ishak Raja Hamzah
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Film Thickness ◽  
Spur Gear ◽  
Back Propagation Algorithm ◽  
Elman Neural Network ◽  
Feed Forward ◽  
Oil Film ◽  
Feed Forward Network ◽  
Artificial Neural

The thickness of an oil film lubricant can contribute to less gear tooth wear and surface failure. The purpose of this research is to use artificial neural network (ANN) computational modelling to correlate spur gear data from acoustic emissions, lubricant temperature, and specific film thickness (λ). The approach is using an algorithm to monitor the oil film thickness and to detect which lubrication regime the gearbox is running either hydrodynamic, elastohydrodynamic, or boundary. This monitoring can aid identification of fault development. Feed-forward and recurrent Elman neural network algorithms were used to develop ANN models, which are subjected to training, testing, and validation process. The Levenberg-Marquardt back-propagation algorithm was applied to reduce errors. Log-sigmoid and Purelin were identified as suitable transfer functions for hidden and output nodes. The methods used in this paper shows accurate predictions from ANN and the feed-forward network performance is superior to the Elman neural network.

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