Analysis and prediction of surface roughness for robotic belt grinding of complex blade considering coexistence of elastic deformation and varying curvature

2021 ◽  
Author(s):  
XiaoHu Xu ◽  
SongTao Ye ◽  
ZeYuan Yang ◽  
SiJie Yan ◽  
DaHu Zhu ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Elastic Deformation ◽  
Belt Grinding ◽  
Robotic Belt Grinding

scholarly journals An Investigation of Surface Corrosion Behavior of Inconel 718 after Robotic Belt Grinding

Materials ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 2440 ◽  
Author(s):  
Junwei Wang ◽  
Jijin Xu ◽  
Xiaoqiang Zhang ◽  
Xukai Ren ◽  
Xuefeng Song ◽  
...  
Keyword(s):  
Residual Stress ◽  
Surface Roughness ◽  
Corrosion Resistance ◽  
Corrosion Behavior ◽  
Process Parameters ◽  
Inconel 718 ◽  
Dissolution Behavior ◽  
Belt Grinding ◽  
Surface Corrosion ◽  
Robotic Belt Grinding

Surface corrosion resistance of nickel-based superalloys after grinding is an important consideration to ensure the service performance. In this work, robotic belt grinding is adopted because it offers controllable material processing by dynamically controlling process parameters and tool-workpiece contact state. Surface corrosion behavior of Inconel 718 after robotic belt grinding was investigated by electrochemical testing in 3.5 wt % NaCl solution at room temperature. Specimens were characterized by morphology, surface roughness and residual stress systematically. The potentiodynamic polarization curves and electrochemical impedance spectroscopy (EIS) analysis indicate the corrosion resistance of the specimen surface improves remarkably with the decrease of abrasive particle size. It can be attributed to the change of surface roughness and residual stress. The energy dispersive X-ray spectroscopy (EDS) indicates that niobium (Nb) is preferentially attacked in the corrosion process. A plausible electrochemical dissolution behavior for Inconel 718 processed by robotic belt grinding is proposed. This study is of significance for achieving desired corrosion property of work surface by optimizing grinding process parameters.

Experiment and Surface Roughness Prediction Model for Ti-6Al-4V in Abrasive Belt Grinding

2016 ◽  
Vol 1136 ◽  
pp. 42-47 ◽  
Author(s):  
Ya Xiong Chen ◽  
Yun Huang ◽  
Gui Jian Xiao ◽  
Gui Lin Chen ◽  
Zhi Wu Liu ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Great Influence ◽  
Grinding Force ◽  
Work Piece ◽  
Belt Grinding ◽  
Abrasive Belt ◽  
Belt Speed ◽  
Feeding Speed

In abrasive belt grinding, abrasive belt granularity, abrasive belt speed,feeding speed and grinding force have a great influence on the surface roughness. In order to predicate the surface roughness of Ti-6Al-4V,a response surface methodology are used to build the model to predict surface roughness,and the influence of various parameters on surface roughness was analysed. The research shows that with the abrasive belt granularity and abrasive belt speed increasing,the work piece surface roughness decreases;with the grinding force and feeding speed increasing,the work piece surface roughness increases. Through the test,the response surface methodology with high prediction accuracy,provides a theoretical basis for the reasonable selection of abrasive belt grinding parameters.

scholarly journals Experimental study on laser assisted belt grinding of shark-skin bio-inspired riblets under different surface roughness

Procedia CIRP ◽  
2020 ◽  
Vol 89 ◽  
pp. 277-281
Author(s):  
Yun Huang ◽  
Yuan Wu ◽  
Yi He ◽  
Quanzhong Zhao ◽  
Guijian Xiao ◽  
...  
Keyword(s):  
Experimental Study ◽  
Surface Roughness ◽  
Belt Grinding ◽  
Shark Skin

scholarly journals A Method for Obtaining Optimal Path in Angle and Avoiding Collision for Robotic Belt Grinding

2019 ◽  
Vol 2019 ◽  
pp. 1-19
Author(s):  
Tie Zhang ◽  
Xiaohong Liang ◽  
Ye Yu ◽  
Bin Zhang
Keyword(s):  
Coordinate System ◽  
Search Algorithm ◽  
Optimal Path ◽  
Recursive Method ◽  
Coordinate Plane ◽  
Angular Variation ◽  
Belt Grinding ◽  
Robotic Grinding ◽  
Path Search ◽  
Robotic Belt Grinding

The angular variation of the joints may be large, and collision between workpieces and tools may occur in robotic grinding. Therefore, this paper proposes an optimal robotic grinding path search algorithm based on the recursive method. The algorithm is optimized by changing the position of the tool coordinate system on the belt wheel; thus, the pose of the robot during grinding is adjusted. First, the position adjustment formula of the tool coordinate system is proposed, and a coordinate plane is established to describe the grinding path of the robot based on the position adjustment formula. Second, the ordinate value of this coordinate plane is dispersed to obtain the search field of the optimal robotic grinding path search algorithm. Third, an optimal robotic grinding path search algorithm is proposed based on the recursive method and single-step search process. Finally, the algorithm is implemented on the V-REP platform. Robotic grinding paths for V-shaped workpieces and S-shaped workpieces are generated using this algorithm, and a grinding experiment is performed. The experimental results show that the robotic grinding paths generated by this algorithm can smoothly complete grinding operations and feature a smaller angular variation of the joint than other methods and no collision.

Optimization of Coated SiC Belt Grinding of Alumina Ceramics

2009 ◽  
Vol 76-78 ◽  
pp. 38-42 ◽  
Author(s):  
Xavier Kennedy ◽  
S. Gowri
Keyword(s):  
Surface Roughness ◽  
Material Removal ◽  
High Hardness ◽  
Surface Damage ◽  
High Temperature Strength ◽  
Structural Ceramics ◽  
Alumina Ceramics ◽  
Belt Grinding ◽  
Grinding Parameters ◽  
Surface Damages

Advanced structural ceramics have been increasingly used in automotive, aerospace, military, medical and other applications due to their high temperature strength, low density, thermal and chemical stability. However, the Grinding of advanced ceramics such as alumina is difficult due to its low fracture toughness and sensitivity to cracking, high hardness and brittleness. In this paper, surface integrity and material removal mechanisms of Alumina ceramics ground with SiC abrasive belts, have been investigated. The surface damage have been studied with scanning electron microscope (SEM). The significance of grinding parameters on the responses was evaluated using Signal to Noise ratios.This research links the surface roughness and surface damages to grinding parameters. The optimum levels for maximum material removal and surface roughness been discussed.

scholarly journals An Adaptive Sliding-Mode Iterative Constant-force Control Method for Robotic Belt Grinding Based on a One-Dimensional Force Sensor

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1635 ◽  
Author(s):  
Tie Zhang ◽  
Ye Yu ◽  
Yanbiao Zou
Keyword(s):  
Force Control ◽  
Control Method ◽  
Sliding Mode ◽  
Force Sensor ◽  
Grinding Force ◽  
One Dimension ◽  
Constant Force ◽  
Belt Grinding ◽  
Robotic Belt Grinding ◽  
The Relationship

To improve the processing quality and efficiency of robotic belt grinding, an adaptive sliding-mode iterative constant-force control method for a 6-DOF robotic belt grinding platform is proposed based on a one-dimension force sensor. In the investigation, first, the relationship between the normal and the tangential forces of the grinding contact force is revealed, and a simplified grinding force mapping relationship is presented for the application to one-dimension force sensors. Next, the relationship between the deformation and the grinding depth during the grinding is discussed, and a deformation-based dynamic model describing robotic belt grinding is established. Then, aiming at an application scene of robot belt grinding, an adaptive iterative learning method is put forward, which is combined with sliding mode control to overcome the uncertainty of the grinding force and improve the stability of the control system. Finally, some experiments were carried out and the results show that, after ten times iterations, the grinding force fluctuation becomes less than 2N, the mean value, standard deviation and variance of the grinding force error’s absolute value all significantly decrease, and that the surface quality of the machined parts significantly improves. All these demonstrate that the proposed force control method is effective and that the proposed algorithm is fast in convergence and strong in adaptability.

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