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Calibration in the robot-assisted belt grinding of complex blades is regarded as one of the key bottlenecks of measurement accuracy. To enhance the accuracy, a TCP-based (tool center point) calibration method is proposed in this paper to calibrate the relationship between the precalibrated 3D laser scanner and the robot end-effector by using criterion spheres as the calibration object. Based on the description of the robot-scanning system from the perspectives of coordinates and scanner measurement modes, the calibration strategies on translational and rotational motions of the robot are provided to determine the translation vector and the orientation matrix. Calibration experiments on the criterion sphere are performed, both the calibration errors (positioning error and orientation error) and sphere fitting error are calculated. A typical case on the robotic belt grinding of 84K-2R1 aviation blade is conducted to validate the calibration results. Finally, the key factors influencing the calibration accuracy are analyzed. It has been demonstrated that the TCP-based calibration method proposed is effective, concise, and time-saving, and can be widely applied in the robot-assisted belt grinding operation.

Comprehensive study of the microscopic material removal mechanism remains an open challenge facing the robotic belt grinding of complex geometries. In the present paper, a new material removal rate (MRR) model is developed underlying the motion trajectory of single spherical abrasive grain by taking into consideration the elastic deformation of the heterogeneous contact wheel. In this model, the contact pressure distribution at the contact wheel–workpiece interface is determined by converting the three-dimensional contact problem into a one-dimensional linear spring model with respect to the large deformation of the contact wheel. In addition, the combined modulus and Poisson's ratio of the heterogeneous contact wheel are further considered based on the geometric relation of the Young's modulus and Poisson's ratio. Compared with the existing MRR model, the proposed MRR model can significantly reduce both the root mean square error (RMSE) and mean absolute percentage error (MAPE) values from 2.401 to 1.725, and 18.426% to 14.942%, respectively. Particularly, an optimization strategy from the perspective of process parameters is implemented to balance the grinding quality and efficiency.

This work is motivated by the fact that one key parameter of r 0, which is defined as the effective contact radius of grain, in grinding temperature calculation model (TCM) proposed by Marinescu et al. is usually assumed as a constant in the range of 5–20 μm in different grinding conditions, and this assumption often leads to poor prediction accuracy and limits the widespread application of this model. In this paper, an improved temperature calculation model (I-TCM) considering the grain geometry and distribution is proposed to further optimize the grinding temperature. In this new model, the convection heat transfer coefficient (h f ) is modified considering the cone angle (θ), grain size (g), and grain concentration (V g) effects, and the “workpiece-wheel” partition ratio (R ws) is improved considering the cone angle effect. Theoretical analysis and experiments are carried out for verification in details. The results show that the I-TCM gives the better match with the experimental results than the existing TCM, in which the R ws values characterized by the cone angle and effective contact radius of grain are more sensitive to the grinding temperature than the convection heat transfer coefficient. Furthermore, the effects by the grain size and grain concentration on the grinding temperature could be negligible for the simplification of the calculation process. The I-TCM given in this paper is helpful to the optimization and control of temperature in a practical grinding process.