| WU Shao-jie,LIU Huai-ju,ZHANG Ren-hua,ZHANG Xiu-hua,GE Yi-bo.Prediction of Surface Integrity Parameters of Shot Peening Based on Orthogonal Experiment and Data-driven[J],50(4):86-95 |
| Prediction of Surface Integrity Parameters of Shot Peening Based on Orthogonal Experiment and Data-driven |
| Received:January 05, 2020 Revised:May 09, 2020 |
| View Full Text View/Add Comment Download reader |
| DOI：10.16490/j.cnki.issn.1001-3660.2021.04.008 |
| KeyWord:shot peening strengthening residual stress surface roughness orthogonal experiment data-driven finite element simulation |
| Author | Institution |
| WU Shao-jie |
State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing , China |
| LIU Huai-ju |
State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing , China |
| ZHANG Ren-hua |
State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing , China |
| ZHANG Xiu-hua |
State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing , China |
| GE Yi-bo |
Shanghai Peentech Equipment Tech.Co.Ltd, Shanghai , China |
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| Abstract: |
| This paper aims to study the influence of process parameters of shot peening on the surface integrity of 18CrNiMo7-6 roller and acquire the mapping relation between process parameters and surface integrity, so as to improve the quality and efficiency of shot peening process. During this, Python language was used for the secondary development of Abaqus to establish the random multi-shots model of shot peening simulation and the experimental verification was carried out. Orthogonal experiment was designed to study the effect laws of impact angle, impact velocity, shot diameter, coverage and shot type on residual stress and surface roughness, and the importance value of each process parameter on the comprehensive effect of shot peening was obtained by the random forest algorithm. With impact angle, impact velocity, shot diameter, coverage, shot type and surface depth as input values and residual stress and surface roughness as output values, a prediction model of shot peening surface integrity based on neural network was established. Through the orthogonal test, it is found that the shot diameter and impact velocity have a significant influence on the surface roughness. The importance of each shot peening process parameter to the comprehensive shot peening effect of 18CrNiMo7-6 roller is impact angle (0.249), impact velocity (0.224), shot type (0.193), coverage (0.173) and shot diameter (0.161). The optimal combination of process parameters within the range of each process parameter is that the impact angle is 90°, the impact velocity is 80 m/s, the shot diameter is 0.7 mm, the coverage is 300%, and the shot material is cast steel shot. The average relative error of the shot peening surface integrity prediction model based on neural network is less than 7%. Therefore, it is concluded that the shot peening surface integrity prediction model based on neural network can accurately represent the mapping relation between the shot peening process parameters and surface integrity parameters, thus providing relevant reference for shot peening process. |
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