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| Optimization of Camshaft Grinding Process Parameters Based on Response Surface Method and Particle Swarm Optimization Algorithm |
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| Key Words:camshaft grinding parameter optimization response surface methodology particle swarm optimization algorithm microscopic analysis |
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| Abstract:In order to improve the surface grinding quality and processing efficiency of the camshaft workpiece， an orthogonal experimental design for camshaft grinding was developed， the process parameters for precision grinding of quenched ductile iron camshafts were optimized. By establishing optimized variables characterized by key parameters such as grinding wheel linear velocity， workpiece speed， and grinding depth， non-linear mathematical models with grinding vibration acceleration values and surface roughness values as target responses were constructed. Based on the shape characteristics of the camshaft， an instantaneous material removal rate model for the workpiece was developed. The optimization objective was to minimize grinding vibration and surface roughness while maximizing the material removal rate. The process parameters were optimized using a comprehensive function method and particle swarm optimization （PSO） algorithm. The results indicate that under the conditions of a grinding wheel linear velocity of 80.673 1 m/s， workpiece speed of 35 r/min， and grinding depth of 30 μm， grinding vibration decreased by 20.8%， camshaft surface roughness decreased by 11.88%， and the material removal rate increased by 22.739 mm3/s. Surface morphology analysis of the workpiece after grinding was conducted using scanning electron microscope （SEM）， and semi-quantitative determination of elemental composition was performed. The results suggest that a smaller grinding wheel linear velocity， higher workpiece speed， and greater grinding depth lead to more significant influences of surface defects and deformation on camshaft surface roughness. |
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