Abstract
This paper presents a method for design multi-section proportional directional valve Throttle grooves with ANN method, which aims at getting a better flow stability. There exists a coupling matter during the opening and closing process between the throttling notches, so that it’s difficult to parameterize the complex flow field characteristics Cd and the structure boundary of the spool grooves. However, in this paper, an ANN was built with data from CFD results, while the typical structural parameters (U type, the O-type and C-type), operating parameters was input vectors, the discharge coefficient as output vectors. Meanwhile, all of the needed data is taken from the three-dimensional CFD analysis, which are organized properly and verified by a bench scale test on a rig. Then, with throttling stiffness as optimization objective to evaluate flow stability, an optimal design process is carried out to optimize to optimize the structure of coupling grooves with ANN models and genetic algorithm. Ultimately, the optimized structure is verified better by the physical test on test rig, therefore, the significance of design method is proved.
Highlights
As the main power distribution element of the hydraulic excavator system, which is an open loop system, the multi-section proportional directional valve plays a vital role in the stability and reliability of the system
As for the difficulty to realize the parameterization of flow field characteristics Cd during the design process of the multi-section proportional directional valve, many achievements have been made by researchers
This paper has taken a certain type of multi-section proportional directional valve as an example, based on the rig test to verify the validity of the three-dimensional CFD analysis and the means of artificial neural networks for prediction of discharge coefficient, to optimize the coupling groove s structure with the aim of better throttling stability
Summary
As the main power distribution element of the hydraulic excavator system, which is an open loop system, the multi-section proportional directional valve plays a vital role in the stability and reliability of the system. In the opening and closing process, there is multi-notch coupling throttling effect, while the mapping relationship between the topological structure of the throttling groove and its complex working conditions is difficult to parameterize. This paper has taken a certain type of multi-section proportional directional valve as an example, based on the rig test to verify the validity of the three-dimensional CFD analysis and the means of artificial neural networks for prediction of discharge coefficient, to optimize the coupling groove s structure with the aim of better throttling stability.
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