Lubrication systems form an integral part of aircraft and automobiles. Failure of lubrication systems can occur due to contamination or degradation of oil which can lead to excessive wear and failure of rotating components. This leads to unnecessary downtime and increase in maintenance costs. Oil contamination occurs when metallic or non-metallic particles are produced due to wear of the machine components such as bearings, gears etc. and these particles may not be always captured by the filtering system that are already in the lubrication system. Hence, the particles can clog oil paths and accelerate the wear of moving parts. In addition to this, variations in thermal stresses causes oxidation and thereby degradation of the oil. Contamination can also be in the form of liquids such as water droplets or fuel from heat exchangers. Currently, on-line oil condition monitoring systems use sensors that are based on eddy current, optical, capacitive to detect contamination in oil for preventive maintenance especially for aircraft engine bearings, aviation gearboxes etc. These sensors have some major drawbacks: prone to surface contamination, non-linearity, insensitive to detect extremely small particulates or false detection such as trapped bubbles.
A new sensor based on platinum thin film heat transfer gauges has been developed at the University of Oxford that works on the principle of measuring the change in thermal product of the material that is in contact. The sensor is able to detect any form of contamination in oil and can be used for both off-line and on-line condition monitoring. The sensor is found to be quite sensitive and can detect extremely small concentrations of contaminants of the order 0.01 % by volume. This paper presents a detailed computational and experimental study carried out to test contamination in oil at room temperatures. The three-dimensional, time-dependent, implicit numerical simulations were carried out using the commercial computational fluid dynamics package FLUENT®. The simulation incorporates conjugate heat transfer to obtain the heating curves of the sensor with and without contamination. This was necessary to understand the range of the sensor and also to study the variations in heat transfer from the sensor to the material that is in contact with the sensor, which otherwise would not have been possible through experiments. The numerical heating curves are then compared with experimentally obtained heating curves. The comparison showed that the numerical and experimental data to agree well and are within 1 %.
