油液污染程度、流量和粘度对液压过滤器压降发展和持污能力的影响

A. Jokinen, O. Calonius, M. Pietola, J. Gorle
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引用次数: 2

摘要

在液压系统中,由于部件的机械磨损、不同部件的粘滞等原因,系统油中异物的存在占了系统故障的大部分。因此,通过过滤,始终保持流体的足够清洁度是至关重要的。机械过滤器用于此目的,从系统油中分离固体颗粒。随着液压过滤器在其使用寿命中积累污垢,滤芯上的压降会增加。该压降通常用于确定过滤器元件的使用寿命:一旦在特定流量条件下达到预定的压降,则过滤器已经积累了足够的污垢,需要维修或更换。本文建立了一个描述流量和流体性质对液压过滤器持污能力和使用寿命影响的相关模型。为此目的,进行了大量的实验室试验,以测量在不同油流量、粘度和重量污染水平下过滤装置的压降发展情况。本文所做的工作是研究不同流量和流体参数对水力过滤影响的初步研究的一部分。整个研究项目的目标是开发一种支持物联网的智能过滤装置,该装置可以预测其剩余寿命,并估计系统油的状况。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effects of Oil Contamination Level, Flow Rate and Viscosity on Pressure Drop Development and Dirt Holding Capacity of Hydraulic Filter
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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