For the application of parallel robots in the grinding industry, a parallel robot equipped with a constant force actuator that produces a constant force for grinding is designed. To study the characteristics of the parallel robot’s spatial positions and poses, the inverse solutions of the moving platform’s spatial positions and poses as well as the workspace where objects were ground were established by using DH parameters and geometric methods. The experimental results showed that the workspace where objects were ground was a cylinder with a cross section similar to a symmetric circular sector. To analyze the characteristics of the forces produced by the parallel robotic system, the dynamics equation was established via the Newton–Euler method to verify the rationality of the force decoupling design. Theoretical calculation combined with simulation and experimental analyses confirmed the viability of the theoretical analyses which lay a theoretical foundation for the design, manufacture and control of the parallel robotic system proposed in this paper.

An algorithm for automatically planning trajectories designed for painting large objects is proposed in this paper to eliminate the difficulty of painting large objects and ensure their surface quality. The algorithm was divided into three phases, comprising the target point acquisition phase, the trajectory planning phase, and the UR5 robot inverse solution acquisition phase. In the target point acquisition phase, the standard triangle language (STL) file, algorithm of principal component analyses (PCA), and k-dimensional tree (k-d tree) were employed to obtain the point cloud model of the car roof to be painted. Simultaneously, the point cloud data were compressed as per the requirements of the painting process. In the trajectory planning phase, combined with the maximum operating space of the UR5 robot, the painting trajectory of the target points was converted into multiple traveling salesman problem (TSP) models, and each TSP model was created with a genetic algorithm (GA). In the last phase, in conformity with the singularities of the UR5 robot’s motion space, the painting trajectory was divided into a recommended area trajectory and a non-recommended area trajectory and created by the analytical method and sequential quadratic programming (SQP). Finally, the proposed algorithm for painting large objects was deployed in a simulation experiment. Simulation results showed that the accuracy of the algorithm could meet the requirements of painting technology, and it has promising engineering practicability.

Three-dimensional printing is a transformative technology in the manufacturing industry which provides customization and cost-effectiveness for all walks of life due to its fast molding speed, high material utilization, and direct molding of arbitrary complex structural parts. This study aims to improve the molding accuracy of 3D printed polyether ether ketone (PEEK) samples by systematically studying key process parameters, including printing speed, layer thickness, nozzle temperature, and filling rate. The 3D printing nozzle has an important impact on the extrusion rate of the melt, and the fluid simulation of the nozzle was carried out to explore the variation characteristics of the melt flow rate in the nozzle and optimize the nozzle structure parameters. In order to effectively optimize the process, considering its inherent efficiency, robustness, and cost-effectiveness, the L9 orthogonal array experimental design scheme was used to analyze the effects of printing speed, layer thickness, nozzle temperature, and filling rate on the molding accuracy of the test sample, and the optimal combination of process parameters was optimized through the comprehensive weighted scoring method so as to improve the molding accuracy of the 3D printed PEEK sample; finally, the molding accuracy of the components printed using the Sermoon-M1 3D printer with the optimized nozzle structure was printed. The results show that the nozzle structure is optimal when the convergence angle is 120° and the aspect ratio is 2, and the outlet cross-section velocity is increased by 2.5% and 2.7%, respectively. The order of influence strength on the dimensional accuracy of the test sample is layer thickness > filling rate > nozzle temperature > printing speed. The optimal combination of parameters is: a printing speed of 15 mm/s, a layer thickness of 0.1 mm, a nozzle temperature of 420 °C, and a filling rate of 50%. The insights derived from this study pave the way for predicting and implementing the selection of optimal process parameters in the production of 3D printed products, with important implications for the optimal molding accuracy of printed components.

Two algorithms that are distinct from the closed algorithm are proposed to create the inverse kinematics model of the UR10 robot: the Sequential Quadratic Programming (SQP) algorithm and the Back Propagation-Sequential Quadratic Programming (BP-SQP) algorithm. The SQP algorithm is an iterative algorithm in which the fundamental tenet is that the joint’s total rotation radian should be at a minimum when the industrial robot reaches the target attitude. With this tenet, the SQP algorithm establishes the inverse kinematics model of the robot. Since the SQP algorithm is overly reliant on the initial values, deviations occur easily and the solution speed, and the accuracy of the algorithm is undermined. To assuage this disadvantage of the SQP algorithm, a BP-SQP algorithm incorporating a neural network is introduced to optimize the initial values. The results show that the SQP algorithm is an iterative algorithm that relies excessively on the initial values and has a narrow range of applications. The BP-SQP algorithm eliminates the limitations of the SQP algorithm, and the time complexity of the BP-SQP algorithm is greatly reduced. Subsequently, the effectiveness of the SQP algorithm and the BP-SQP algorithm is verified. The results show that the SQP and BP-SQP algorithms can significantly reduce the operation time compared with the closed algorithm, and the BP-SQP algorithm is faster but requires a certain number of samples as a prerequisite.

The current design method for wind turbine airfoils and vortex generators (VGs) is independent, which cannot be used to simultaneously design wind turbine airfoils and VGs with high aerodynamic performance. Therefore, an aerodynamic-shaped integrated design method for wind turbine airfoils and VGs is proposed. The aerodynamic-shaped VGs instead of plate VGs are introduced to be installed on wind turbine blade section. The blade airfoil and aerodynamic-shaped VGs are both expressed by B-spline function. Then, the optimal mathematic model of wind turbine airfoil with aerodynamic shaped VGs is established, for which the multi-objective functions are maximum lift to drag ratio plus maximum lift coefficient. DU97-W-300 and CLARKY-117 airfoils are selected as initial objects to be optimized simultaneously by combining CFD simulation and particle swarm optimization (PSO) algorithm. The optimal results indicate that the maximum lift coefficient and lift to drag ratio of the optimized blade with novel VGs show the increase of 9.3% and 7.5%, respectively, compared to initial design. In addition, through the comparative analysis of streamlines and vorticity contours, the new blade section with novel VGs could produce larger induced vortex and could effectively restrain the fluid separation on the blade surface. This study provides a good reference to the design and application of wind turbine airfoils and VGs.