Optimal Design On Three-stage Running-in Condition Of Diesel Engine Main Bearing Based On Fractal Theory

There is temporary fluctuation of friction,temperature and wear rate in the initial sliding between fresh solid surfaces,which is accompanied by the elastic and plastic deformation,workhardening,debris accumulation,interfacial transformation and changes in crystallographic orientation.This process is termed as running in.Since the running-in process is significant for extending the working life of tribosystems and ensuring stable operation,researchers attempt to interpret the complex behavior and realize the active design of running in.There are obvious fractal characteristics in friction signal and running-in surface.Based on fractal theory,this thesis carried out the optimization design research on multi-stage running-in condition of diesel engine main bearing.This research will realize the quantitative description of the running-in quality,as well as enrich the nonlinear theory.The conclusion will provide a theoretical basis for the design of running-in conditions.Reasonable sampling length is the basis for calculating fractal dimension of surface topography and friction signal.A series of profiles with same sampling interval and different lengths were generated by the Weierstrass-Mandelbrot?W-M?function.Root-mean-square?RMS?method was utilized to calculate the fractal dimension of W-M curves with determined fractal dimensions.What is more,the fractal dimension of friction signals was also calculated by RMS method.Fluctuation tends to be weakened,and the linearity of the scaling region is improved with the increase of sampling length.The estimated fractal dimension increases with the sampling length,and eventually tends to saturation.In order to accurately calculate fractal dimension,sampling length of friction signal should be more than 8000 points.Study was taken on the running-in conditions of babbitt alloy of main bearing and 45#steel of diesel engine main bearing with different lubrication conditions.Abrasive wear and adhesive wear are main wear form of Babbitt alloy,accompanied by fatigue pitting and oxidative wear.There is significant distinction on the stability of friction signal under different working conditions.Running-in can hardly occure under dry friction.Running-in can occure under lean oil lubrication when load is low and speed is high.Stable running-in difficultly occure under lean oil lubrication when load is high and speed is high.Running-in can occure with test conditions under rich oil lubrication.Although,the stability is diverse.It is easier to obtain stable running-in under high load and low speed.Also,it is easier to achieve stable running-in under low load and high speed.Primary and secondary factors which infiluence running-in under rich oil lubrication was be studied.Three-stage running-in prediction models of friction signal fractal dimension D_cof,pin surface topography fractal dimension D_sand running-in time T_totalare established by response-surface-methodology?RSM?.Third stage running-in time T₃,second stage running-in time T₂and third stage sliding speed V₂have a greater influence on D_cof.Second and third stage load P₂,first stage load P₁and second stage running-in time T₂have a greater influence on D_s.However,first stage running-in time T₁has the smallest influence on both.Therefore,the good quality of running-in surface,strong signal stability and short running-in time were considered as three goals of multi-objective optimization design.The principle of multi-stage running-in parameters is proposed as follows.At first stage load should be larger,the speed and running-in time should be smaller.At second stage load and speed should be smaller.What is more,the region of running-in time is large.At third stage load,speed and running-in time should be smaller.The optimal running-in parameter set provides a specific reference for the optimization design of the three-stage running-in.Running-in parameters can be selected according to different main optimised objectives.