scholarly journals Prediction model of needle valve body extrusion grinding process based on PSO-SVR

2021 ◽  
Vol 2024 (1) ◽  
pp. 012041
Author(s):  
Ruibin Xie ◽  
Shuzhen Yang ◽  
Chenzhe Sun ◽  
Tao Yu
Keyword(s):  
Prediction Model ◽  
Needle Valve ◽  
Grinding Process ◽  
Valve Body

scholarly journals Numerical Simulation of Solid Particle Erosion in Aluminum Alloy Spool Valve

2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Jin-gang Liu ◽  
Gao-sheng Wang ◽  
Tian-heng Peng ◽  
Sheng-qiang Jiang
Keyword(s):  
Particle Size ◽  
Aluminum Alloy ◽  
Prediction Model ◽  
Particle Shape ◽  
Two Phase ◽  
Wear Prediction ◽  
Valve Body ◽  
Fluent Software ◽  
Improved Design ◽  
Spool Valve

Aluminum alloy spool valve body material is prone to severe wear on the wall under the condition of oil contamination. Aiming at this problem, combined with the theory of liquid-solid two-phase flow and erosion wear, the wear prediction model of aluminum alloy sliding valve wall is established based on computational fluid dynamics, and the effects of turbulence and wall materials, particle size distribution, and particle shape on particle motion are discussed. The calculation of the wear prediction model is done with Fluent software. This study predicts the wear of the wall under actual working conditions and calculates the influence of particle size, particle shape, and pressure difference on the wall wear of the aluminum alloy sliding valve. The research results have certain significance for the maintenance and upkeep of aluminum alloy sliding valve wall, improved design, and life prediction.

Heat flux distribution and temperature prediction model for dry and wet cylindrical plunge grinding

2018 ◽  
Vol 233 (10) ◽  
pp. 2047-2060 ◽  
Author(s):  
Jingzhu Pang ◽  
Chongjun Wu ◽  
Yiming Shen ◽  
Siqi Liu ◽  
Qingxia Wang ◽  
...  
Keyword(s):  
Heat Flux ◽  
Prediction Model ◽  
Surface Temperature ◽  
Contact Zone ◽  
Flux Distribution ◽  
Grinding Process ◽  
Grinding Temperature ◽  
Heat Flux Distribution ◽  
Temperature Prediction ◽  
Workpiece Surface

The grinding heat is generally partitioned into the workpiece, wheel, chips and fluid in grinding process. The total amount of heat flux entering into the workpiece greatly affects the final workpiece surface temperature, which may cause undesirable workpiece burn. Moreover, the variable grinding chip thickness and fluid injection speed along the grinding contact zone could substantially change the specific energy and the shape of the heat source correspondingly. In this article, a Weibull heat flux distribution model for both dry and wet grinding temperature prediction was proposed by analyzing two key parameters: energy partition Rw and shape parameter k. The value of Rw was obtained by considering the real contact length, the active grits number and the average grit radius r0 on the basis of traditional formulas. The relationship between shape parameters k and useful flow was established by a FLUENT simulation of the convective grinding fluid applied in grinding contact zone with wheel-workpiece minimum clearance. The grinding temperature and grinding force experiments were conducted on a grinding machine MGKS1332/H to validate the proposed heat flux model. The calculated workpiece surface temperature distribution was obtained by using the experimental heat flux obtained by the reverse algorithm, and the error between calculated temperature and experimental temperature was analyzed. With the monitored force signals and the proposed temperature prediction model, the grinding temperature for both dry and wet grinding can be predicted, which will be helpful to the optimization and control of temperature in grinding process.

Modelling and experiment of gear hob tooth profile error for relief grinding

2021 ◽  
pp. 095440542110172
Author(s):  
Shuying Yang ◽  
Weifang Chen ◽  
Zhiqiang Wang ◽  
Yanfeng Zhou
Keyword(s):  
Prediction Model ◽  
High Speed ◽  
Tooth Profile ◽  
Grinding Wheel ◽  
Grinding Process ◽  
Feed Speed ◽  
Machining Parameters ◽  
Profile Error ◽  
Mechanical Coupling ◽  
Axial Profile

Gear hob is an important tool that is most used in gear processing. Hob accuracy directly exerts an overwhelming influence on the quality of the processed gear. Generally, the hob tooth profile accuracy is mainly determined by relief grinding process. Studies on tooth profile errors of gear hobs caused by severe friction and cutting with the high-speed rotation of the wheel during the form grinding machining of hobs are limited. Thus, a theoretical model of the tooth profile error prediction under different machining parameters was established based on the analysis of coupling influence of high temperature and high strain rate on gear hobs in the relief grinding process. The model was completed on the basis of the dynamic explicit integral finite element method of thermo-mechanical coupling. Through the prediction model, the influence of the grinding depth ap, feed speed Vw and grinding speed Vs on the tooth profile error can be analysed. In addition, an algorithm for accurately calculate the grinding wheel axial profile by combining instantaneous envelope theory and hob normal tooth profile was proposed. The hob relief grinding experiments were carried out using the proposed grinding wheel profile algorithm. The relative error of the prediction obtained by comparing the calculation results of the prediction model with the experimental results is within 10%. Results prove the validity of the prediction model. This finding is greatly important for optimising the accuracy of hob relief grinding.

Research on the Impact of Needle Valve Orifice Chamfering on the Performance Based on Fluent

2014 ◽  
Vol 1039 ◽  
pp. 10-16
Author(s):  
Yong Tao ◽  
Hong Xia Cai ◽  
Yu Jie Bai ◽  
Ting Ting Yu
Keyword(s):  
Fluid Dynamics ◽  
Flow Field ◽  
Flow Coefficient ◽  
Needle Valve ◽  
Grinding Process ◽  
Nozzle Orifice ◽  
Engine Cylinder ◽  
Fluent Software ◽  
The Impact ◽  
Computing Method

Needle valve is the key component of diesel engine cylinder. Changing the nozzle Orifice chamferinging will influence the flow coefficient and spray performance. Firstly, we proposed a physical model of abrasive flow field inside the needle valve based on computational fluid dynamics technology. Then, we set the computing method and boundary type. Finally, we simulated the abrasive flow field using fluent software. The result is useful for guidance in the actual grinding process.

An Intelligent Prediction of Surface Roughness on Precision Grinding

2017 ◽  
Vol 261 ◽  
pp. 221-225
Author(s):  
Ning Ding ◽  
Chang Long Zhao ◽  
Xi Chun Luo ◽  
Qing Hua Li ◽  
Yao Chen Shi
Keyword(s):  
Surface Roughness ◽  
Prediction Model ◽  
Grinding Wheel ◽  
Grinding Process ◽  
Precision Grinding ◽  
Wheel Wear ◽  
Surface Roughness Prediction ◽  
Fuzzy Neural ◽  
Roughness Prediction ◽  
Wear Condition

Precision grinding is generally used as the final finishing process, and it determines the surface quality of the machined component. It’s very difficult to achieve on-line measurement of the surface roughness. The purpose of this research was to study the surface roughness prediction and avoid the defect happening in the grinding process. A surface roughness prediction model was proposed in this paper, which presented the relationship between surface roughness and the wear condition of grinding wheel and grinding parameters. An AE sensor was used to collect the grinding signals during the grinding process to obtain the grinding wheel wear condition. Besides, a fuzzy neural network was used to obtain the prediction surface roughness. Grinding trials were performed on a high precision CNC cylindrical grinder (MGK1420) to evaluate the surface roughness prediction model. Experiment verified that the developed prediction system was feasible and had high prediction accuracy.

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