In hydraulic systems, the presence of foreign material in the system oil accounts for the majority of system troubles due to mechanical wear of components, sticking of different parts etc. Therefore, it is essential to maintain an adequate cleanliness level of the fluid at all times through filtration. Mechanical filters are used for this purpose, to separate solid particles from the system oil. As a hydraulic filter gets accumulated with dirt throughout its service life, the pressure drop over the filter element increases. This pressure drop is typically used for determining the lifetime of a filter element: once a predetermined pressure drop at certain flow conditions has been reached, the filter has accumulated enough dirt to require servicing or replacement.

In this paper, a correlation model has been developed to describe the effects of flow and fluid properties on the dirt holding capacity and the service life duration of a hydraulic filter. For this purpose, extensive laboratory tests have been carried out in order to measure the pressure drop development of a filter unit at different oil flow rates, viscosities and gravimetric contamination levels.

The work in this paper has been done as part of the initial research for investigating the effects of different flow and fluid parameters on hydraulic filtration. The aim of the overall research project is to develop an IoT-enabled smart filter unit that could predict its remaining lifetime, and estimate the condition of the system oil as well.

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