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MONITORING THE CONDITION OF A VALVE AND LINEAR ACTUATOR IN HYDRAULIC SYSTEMS

机译:液压系统中阀门和线性执行器的状态监测

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摘要

The topic of condition monitoring has been a growing area of research in both academia and industry for much of the last two decades. Condition monitoring of fluid power equipment has been no exception to this trend. Much of the research work associated with monitoring the condition of fluid power equipment has centered on pump and motor components due to their relatively high cost and complexity. The work in this paper focuses on the lesser expensive, but more common components of valves and linear actuators. The primary focus of the work presented here pertains to assessing the independent component condition of a valve-controlled linear actuator circuit. The paper first presents simulation studies to establish techniques for proper data collection, neural network training and output interpretation. The neural network approach is then applied to a valve and linear actuator of a John Deere 410E Backhoe Loader. The results indicate that the concept can be applied to a commercial system and is feasible for implementation.
机译:在过去的二十多年中,状态监测一直是学术界和工业界研究的一个增长领域。流体动力设备的状态监控也不例外。由于其相对较高的成本和复杂性,与监视流体动力设备的状态有关的许多研究工作都集中在泵和电动机组件上。本文的工作重点是阀门和线性执行器的价格较低但较常见的组件。此处介绍的工作的主要重点在于评估阀控线性执行器电路的独立组件条件。本文首先介绍了仿真研究,以建立适当的数据收集,神经网络训练和输出解释技术。然后将神经网络方法应用于John Deere 410E反铲装载机的阀门和线性执行器。结果表明该概念可以应用于商业系统,并且可以实现。

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