方位(导航)                        
                
                                
                        
                            表面粗糙度                        
                
                                
                        
                            表面光洁度                        
                
                                
                        
                            材料科学                        
                
                                
                        
                            冶金                        
                
                                
                        
                            复合材料                        
                
                                
                        
                            法律工程学                        
                
                                
                        
                            工程类                        
                
                                
                        
                            计算机科学                        
                
                                
                        
                            人工智能                        
                
                        
                    
            作者
            
                Tiantian He,Wen-Bo Chen,Zeyuan Liu,Zhipeng Gong,Sanming Du,Yongzhen Zhang            
         
                    
            出处
            
                                    期刊:Lubricants
                                                         [Multidisciplinary Digital Publishing Institute]
                                                        日期:2025-04-18
                                                        卷期号:13 (4): 187-187
                                                        被引量:3
                                 
         
        
    
            
            标识
            
                                    DOI:10.3390/lubricants13040187
                                    
                                
                                 
         
        
                
            摘要
            
            Surface roughness plays a crucial role in determining surface quality, influencing factors such as vibration, noise, assembly precision, lubrication, and wear resistance in bearings. This research examines how surface roughness (Sa) affects the friction and wear characteristics of GCr15 steel under conditions with adequate oil lubrication while varying the applied load. The findings indicate that with an increase in Sa, the friction coefficient of GCr15 steel also increases. As the load rises from 15 N to 35 N, the friction coefficient remains relatively constant. However, higher loads lead to more severe wear of the microprotrusions on the surface of GCr15 steel. The wear area first decreases and then increases as Sa increases. The minimum wear area occurs when Sa is 0.5 μm. Additionally, a back propagation neural network (BPNN) model has been developed to predict the wear performance of GCr15 steel. Validation experiments show that the average prediction error for the BPNN model is 10.64%.
         
            
 
                 
                
                    
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