Optimization method and experimental research on robot belt grinding trajectory of additive blade with non-uniform allowance distribution

• Published in: International journal of advanced manufacturing technology Vol. 131; no. 7-8; pp. 4201 - 4216
• Main Authors: Zhao, Xiaoyu, Xiao, Guijian, Zhang, Tangming, Zheng, Zihan, Yu, Jingyan
• Format: Journal Article
• Language: English
• Published: London Springer London 01-04-2024; Springer Nature B.V
• Subjects: Abrasive belts; Acceleration; Algorithms; B spline functions; Belt grinding; CAE) and Design; Computer-Aided Engineering (CAD; Data points; Engineering; Grinding; Industrial and Production Engineering; Interpolation; Mechanical Engineering; Media Management; Optimization; Original Article; Robots; Surface roughness; Trajectory planning; Aeroadditive blade; Robotic belt grinding; NURBS spline curves; Minimum Snap algorithm
• ISSN: 0268-3768; 1433-3015
• DOI: 10.1007/s00170-024-13146-1

When robotic belt grinding was used to machine aeroadditive blade that had non-uniform distribution of the allowance, the traditional trajectory planning method did not take into account of the complexity of error control of curved profile, which results in lower face shape accuracy; to address this question, this research proposed a new trajectory planning method. Firstly, a series of robot position data nodes were obtained through the iso-parametric line method, and node interpolation was applied to obtain the non-uniform rational B-spline (NURBS) curves which passed through the data points; based on the homogenous matrix transformation of NURBS curve, the initial position of the grinding head was modeled and the pose was solved. Secondly, the minimum snap planning algorithm was used to optimize path optimization of the initial grinding head posture trajectory; by minimizing optimization of the objective function snap, a smooth trajectory was obtained without a large impact on speed and acceleration of the grinding trajectory path. On this basis, the corridor trajectory planning with quadratic constraints was further adopted to ensure the profile error of the blade. Finally, the effectiveness of the proposed trajectory planning algorithm was verified by ADAMS-MATLAB co-simulation; in addition, the additive blade grinding experiment was conducted on the robotic abrasive belt grinding experimental system; the experimental results showed that the accuracy of the blade surface is up to 0.04 μm, and the average surface roughness is 0.32 μm. The proposed method has more advantages than the traditional method.