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																						Prediction Method of Locomotive Wheel Degradation Based on Gamma Process
											                            			
                            			
						
                            			 
                            				ZHANG Yi-min, LIN Lu-yang, LYU Hao
                            			 
                              			2018, 39 (4): 
																					522-526. 
																														DOI: 10.12068/j.issn.1005-3026.2018.04.014
																				
                              			 
                              			
                                		
			                            	According to measured wheel wear data, the nonstationary Gamma process was used to establish the degradation model of locomotive wheel rim, and the repair time of 95% reliability was predicted by using the two methods a and b combined with wheel rim wear threshold. Method a uses the Bootstrap method to randomly generate a set of empirical distributions of pseudo-life, with Weibull distribution fitting forecasting repair time of 473900km. Method b uses the secondary fourth-order moment method based on the maximum entropy to predict the repair time of 488900km. The results showed that the lifetime of method a is more conservative than that of the empirical method, and the failure distribution of method  b is more consistent with that of the experience distribution, and the repair time is 450000km.
			                             
                              			
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