Study On The Wear Life Prediction Method Of Gears In Vehicle Transmission System

Aimed at predicting the wear life of gears in vehicle transmission system,a wear calculation model under dynamic conditions for involute spur gears is proposed,which is used to analyze the change rules of wear amount,wear rate,and dynamic characteristics.And in order to solve the problem of residual useful life prediction of gears in service,whose initial condition is still not clear,a state space model of gear wear based on Gamma distribution is proposed.Finally,a series of gear wear experiments based on oil analysis technology are carried out to quantitatively analyze the actual trends of wear amount.And the experiment data would be used to modify the dimensionless wear coefficient K,provide sample data for the state space model,as well as verify the above two models.The main research contents were as follows:（1）The wear mechanism and damage forms of gears were studied at first.Then,a wear calculation model based on dynamic meshing force was proposed by combining Archard’s wear equation and a nonlinear dynamic model of gear system.And in view of the fact that the tooth profile would be changed due to wear,an analytic geometry system consisting of 3 coordinate systems was established to describe the whole meshing process and the tooth changing profile after wear,and complete the contact analysis to update the sliding coefficient.Besides,the dynamic meshing force would also be recalculated according to wear amount.Thus a cyclic iterative calculation model of gear wear was completed.（2）Based on the calculation model under dynamic conditions of gear wear,the numerical simulation analysis of gear wear process was completed by Matlab.From this,the dynamic characteristics of gear such as angular velocity,angular acceleration,dynamic transmission error and meshing force with wear at different time steps were obtained;and the distribution of wear depth at each meshing point,the total wear mass,and wear rate were also acquired.Then the influences of working conditions like rotational speed and input torque on the dynamic meshing force and wear distribution of gear were analyzed.（3）A state space model of gear wear based on Gamma distribution was established.And a method combined Experience maximization algorithm and particle filter algorithm was used here to estimate the model parameters,according to the oil analysis data.Then,with the state space model,whose parameters were known,the probability density distribution of residual useful life was obtained,as well as the expectation of residual useful life.（4）A series of gear wear experiments based on oil analysis technology were carried out.By using oil analysis technology to test the density of Fe and the amount of particle in the oil periodically,the quantitative trends of wear amount were obtained.The obtained data was used to modify the dimensionless wear coefficient K,provide sample data for the state space model,as well as verify the above two models.