Loading and unloading operations are widely employed in industrial robots and CNC machine tools. In the present study, an effective algorithm is established for optimum time-jerk path planning and reducing the vibration of the serial manipulator, and enhancing the robot efficiency. To this end, the manipulator's trajectory is constructed using quintic B-spline interpolation in the joint space and the optimal objective function is constructed in terms of time and mean jerk. A hybrid improved whale optimization and particle swarm optimization (IWOA-PSO) method is proposed to optimize the objective function. First, WOA is improved by employing adaptive weight and threshold to balance exploration and exploitation of the WOA to prevent falling into the local optimum solution. Then, PSO method and IWOA techniques are combined to enhance the convergence speed of the IWOA. Applying different algorithms to 23 benchmark functions demonstrate superiority of the proposed algorithm to state-of-the-art algorithms. A 6-DOF serial industrial manipulator integrated in CNC machine was taken as a case study and the joint positions are considered the IWOA-PSO inputs. All calculations are performed in the MATLAB 2018b environment. The obtained results demonstrate that the proposed IWOA-PSO can effectively reduce the jerk of the robot while improving its work efficiency.
Optimal path planning in the welding process enhances the processing and manufacturing efficiency. An effective algorithm for optimum path planning of a six-axis welding industrial robot is established in this paper. The robot’s trajectory is constructed using 5-th B spline interpolation in the joint space, and a cost function is constructed in terms of both time and mean jerk. An improved whale optimization algorithm (IWOA) is presented to address the time-jerk optimal trajectory planning issue. The robot’s joint positions are considered the IWOA input, while the MATLAB 2018b software is utilized to perform the optimization algorithm. Numerical simulations demonstrate that IWOA can effectively reduce the jerk of the robot while improving its work efficiency.
The higher the natural frequency of the material is, the more resistant it is to deformation under impulse loading. To explore the influence of micro-abrasive and micro-jet impact on the natural frequency and resonance amplitude value of the material under ultrasonic cavitation, 18 sets of single-factor controlled variable ultrasonic cavitation experiments were carried out on a polished specimen of 6061 aluminum alloy (30 mm × 30 mm × 10 mm). With the increase of the abrasive content in the suspension, the natural frequency of the workpiece first increased, then decreased and remained stable. With the increase of the ultrasonic amplitude, the resonance amplitude value of the material increased, reaching the maximum at 0.1789 m·s−2 and then decreased. The effect of ultrasonic amplitude on the natural frequency of the material was greater than that of the abrasive content, and the effect of the abrasive content on the common amplitude value was greater than that of the ultrasonic amplitude. This research provides a certain reference significance for exploring the influence of power ultrasonic micro-cutting on material properties and avoiding the occurrence of resonance phenomenon of the workpiece under different working conditions.
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