Prediction and analysis of material removal characteristics for robotic belt grinding based on single spherical abrasive grain model

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.

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Optimization of Coated SiC Belt Grinding of Alumina Ceramics

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.76-78.38 ◽

2009 ◽

Vol 76-78 ◽

pp. 38-42 ◽

Cited By ~ 1

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.

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

Sensors ◽

10.3390/s19071635 ◽

2019 ◽

Vol 19 (7) ◽

pp. 1635 ◽

Cited By ~ 3

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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An adaptive modeling approach based on ESN for robotic belt grinding

The 2010 IEEE International Conference on Information and Automation ◽

10.1109/icinfa.2010.5512461 ◽

2010 ◽

Cited By ~ 3

Author(s):

Hongbo Lv ◽

Yixu Song ◽

Peifa Jia ◽

Zhongxue Gan ◽

Lizhe Qi

Keyword(s):

Belt Grinding ◽

Adaptive Modeling ◽

Modeling Approach ◽

Robotic Belt Grinding

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