金刚石与磨料磨具工程2024，Vol.44Issue(3)：346-353,8.DOI:10.13394/j.cnki.jgszz.2023-0118
轴承表面Al2O3基陶瓷绝缘涂层的粗糙度预测
Roughness prediction of Al2O3-based ceramic insulation coating on bearing surface
摘要
Abstract
To improve the roughness prediction accuracy of Al2O3-based ceramic insulation coating on bearing sur-faces,a method based on the spectral confocal principle was proposed for measuring the surface of grinding wheels and quantifying the characteristic parameters of abrasive particles.The abrasive characteristic parameter K of the grinding wheel surface,the grinding wheel line speed vs,the workpiece feed speed f,the cutting depth ap,and the normal grind-ing force F were taken as input parameters.A BP neural network prediction model of workpiece surface roughness,which directly reflects the time-varying state of the grinding wheel surface,was established.The prediction perform-ance of the network model was verified using known grinding samples and four groups of unknown samples after grind-ing wheel wear.The results show that the predicted roughness results of the BP network model with known samples are consistent with the actual roughness results in terms of regularity and numerical values,with network output errors are all less than±0.04 μm.The network prediction accuracy for the four unknown samples decreases,but the absolute value of the maximum relative error does not exceed 20.00%.The neural network prediction model,which includes the char-acteristic parameters of abrasive particles on the grinding wheel surface,can be used to predict the roughness of Al2O3-based ceramic insulation coating on the bearing surface under the time-varying state of abrasive wear on the grinding wheel.It also demonstrates a certain generalization ability for unknown samples.关键词
Al2O3基陶瓷/绝缘涂层/粗糙度预测/BP神经网络/磨粒磨损Key words
Al2O3-based ceramics/insulating coating/roughness prediction/BP neural network/abrasive wear分类
矿业与冶金引用本文复制引用
徐钰淳,朱建辉,师超钰,王宁昌,赵延军,张高亮,乔帅,谷春青..轴承表面Al2O3基陶瓷绝缘涂层的粗糙度预测[J].金刚石与磨料磨具工程,2024,44(3):346-353,8.基金项目
国家重点研发计划(2020YFB2007900) （2020YFB2007900）
