Position-varying surface roughness prediction method considering compensated acceleration in milling of thin-walled workpiece

2021 ◽  
Author(s):  
Zequan Yao ◽  
Chang Fan ◽  
Zhao Zhang ◽  
Dinghua Zhang ◽  
Ming Luo
Keyword(s):  
Surface Roughness ◽  
Prediction Method ◽  
Surface Roughness Prediction ◽  
Roughness Prediction ◽  
Thin Walled

scholarly journals Surface Roughness Prediction Method of Titanium Alloy Milling based on CDH Platform

2021 ◽  
Author(s):  
Liu Xianli ◽  
Sun Yanming ◽  
Yue Caixu ◽  
Wei Xudong ◽  
Sun Qingzhen ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Titanium Alloy ◽  
Prediction Accuracy ◽  
Search Strategy ◽  
Prediction Method ◽  
Pattern Search ◽  
Apache Hadoop ◽  
Surface Roughness Prediction ◽  
Svm Algorithm ◽  
Roughness Prediction

Abstract Generally, off-line methods are used for surface roughness prediction of titanium alloy milling. However, studies show that these methods have poor prediction accuracy. In order to resolve this shortcoming, a prediction method based on Cloudera's Distribution Including Apache Hadoop (CDH) platform is proposed in the present study. In this regard, data analysis and process platform is designed based on the CDH, which can upload, calculate and store data in real-time. Then this platform is combined with the Harris hawk optimization (HHO) algorithm and pattern search strategy, and an improved hybrid optimization (IHHO) method is proposed accordingly. Then this method is applied to optimize the SVM algorithm and predict the surface roughness in the CDH platform. The obtained results show that the prediction accuracy of IHHO method reaches 95%, which is higher than the conventional methods of SVM, BAT-SVM, GWO-SVM and WOA-SVM.

Research on Surface Roughness of Supersonic Vibration Auxiliary Side Milling for Titanium Alloy

2021 ◽  
Author(s):  
XueTao Wei ◽  
caixue yue ◽  
DeSheng Hu ◽  
XianLi Liu ◽  
YunPeng Ding ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Finite Element ◽  
Prediction Model ◽  
Simulation Model ◽  
Finite Element Simulation ◽  
Simulation Software ◽  
Surface Roughness Prediction ◽  
Contour Shape ◽  
Element Simulation ◽  
Roughness Prediction

Abstract The processed surface contour shape is extracted with the finite element simulation software, and the difference value of contour shape change is used as the parameters of balancing surface roughness to construct the infinitesimal element cutting finite element model of supersonic vibration milling in cutting stability domain. The surface roughness trial scheme is designed in the central composite test design method to analyze the surface roughness test result in the response surface methodology. The surface roughness prediction model is established and optimized. Finally, the finite element simulation model and surface roughness prediction model are verified and analyzed through experiment. The research results show that, compared with the experiment results, the maximum error of finite element simulation model and surface roughness prediction model is 30.9% and12.3%, respectively. So, the model in this paper is accurate and will provide the theoretical basis for optimization study of auxiliary milling process of supersonic vibration.

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