| ZHANG Sheng-jiang,WANG Ming-di,NI Chao,XU You-yuan,YIN Zi-hang,LIN Yao,GUO Min-chao,WANG Xian-bao.Multi-objective Optimization of Laser Cladding Process Parameters on QT800-2 Ductile Iron Surface[J],50(7):74-82 |
| Multi-objective Optimization of Laser Cladding Process Parameters on QT800-2 Ductile Iron Surface |
| Received:August 09, 2020 Revised:March 26, 2021 |
| View Full Text View/Add Comment Download reader |
| DOI：10.16490/j.cnki.issn.1001-3660.2021.07.006 |
| KeyWord:laser cladding cladding quality ductile cast iron process parameters orthogonal experiment NSGA-II algorithm process optimization |
| Author | Institution |
| ZHANG Sheng-jiang |
School of Mechanical and Electrical Engineering, Soochow University, Suzhou , China |
| WANG Ming-di |
School of Mechanical and Electrical Engineering, Soochow University, Suzhou , China |
| NI Chao |
School of Mechanical and Electrical Engineering, Soochow University, Suzhou , China |
| XU You-yuan |
School of Mechanical and Electrical Engineering, Soochow University, Suzhou , China |
| YIN Zi-hang |
School of Mechanical and Electrical Engineering, Soochow University, Suzhou , China |
| LIN Yao |
School of Mechanical and Electrical Engineering, Soochow University, Suzhou , China |
| GUO Min-chao |
School of Mechanical and Electrical Engineering, Soochow University, Suzhou , China |
| WANG Xian-bao |
School of Mechanical and Electrical Engineering, Soochow University, Suzhou , China |
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| Abstract: |
| To solve the problems of cladding layer collapse and uneven thickness in the process of laser cladding Fe-based alloy on the surface of ductile cast iron, the optimal process parameter group of side-axis powder feeding laser cladding was determined, and the parameter optimization methods were compared and analyzed. Select the process parameters (laser power, scanning speed, powder feeding speed) as the optimization variables and the surface quality of the cladding layer (surface roughness, hardness) as the optimization indicators, and perform the range analysis by designing the L9(34) orthogonal test to get the optimized parameter combination; perform parameter optimization through the neural network prediction model combined with NSGA-II multi-objective optimization algorithm. By comparing the actual optimization effects of these two optimization methods on the surface quality of the cladding layer, the optimal process parameter group is determined. The influence of the three process parameters on the overall quality is in order:laser power, scanning speed, powder feeding speed, and the combination of orthogonal optimization parameters reduces the surface roughness of the cladding layer by 23.3% and the hardness by 7.1%; while the optimized parameter combination by the NSGA-II genetic algorithm can reduce the surface roughness by 40.5% and increase the hardness by 6.6%. The optimal combination of process parameters is:laser power 4614 W, powder feeding speed 2.6 r/min, scanning speed 325.6 mm/min. The use of NSGA-II genetic algorithm can obtain better optimization results than orthogonal experiments; through reasonable selection of process parameters, it can solve the problems of cladding layer collapse and thickness unevenness, thereby greatly improving the surface quality of the cladding layer. |
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