| Mechanical equipment,as a tribology system,comprises with different kinds of friction coupling,the wear of which can lead directly the energy consuming,compenent failure,poor performance of the whole system,decreasing of the reliability etc.. Wear process, due to environmental factors and the impact of different materials, demonstrates the complexity and diversity. Because the factors that affect the wear process have random characteristics, and have relation to time,so stochastic process theory can be used to describe the process of wear well, and can more accurately reflect the regularity and dynamic nature of wear process.It is significient for the reliability prediction of components or systems scientificly and accurately, at the same time studying the failure process in order to take targeted measures to improve the abrasion resistance, as well as arrangements for proper maintenance.The key to the forecasting of the wear is the prediction model.The most wear prediction models developed based on the wear mechanism could not be in commen use and had not considered the randomness in mind,so the predictions are inaccurate usually. This dissertation studies the influencing factors from the probability point of view and develops the wear prediction model which considers not only the main factors but also the micro elements which effect the wear system as a common factor.The reliability prediction is studied on the base of the model. The detail contents are as following:(1) Experimental samples were made and disposed according to the experiment objectives and the scientific experiment plans are developed by the experimental design theory,by which the the experiment object is achieved,the desired information have been got and the experiment cost have been saved.(2) The main factors that affect the wear performance are analysed from the point of environmental factors, working conditions and material properties, and the variables to build model are determined combined with the results of single experimental factors. The wear prediction model is built using partial least-squares regression method, the fittness and predection effect have been inspected.(3) Wear volume distribution and the relation between wear volume and time for sliding wear reliability prediction are studied and proved by experiment. The method to determine the reliability under certain life and the work life for relative reliability are studied combined with the wear prediction model when the wear rate obeys normal distribution and the wear volume is liner with the wear time.(4)Basic wear random process model is established.Wear process is analysed and the basic random process model is bulit according to the statochastic theory.The differenc of the parameters in the static model and the random process model are analyed. The wear process of steel materials is analyzed and the statochastic model is developed according to the result of experiment. The experiment results of gears are analyzed by statistcs method and the random process model is established.(5)Reliability prediction model for continuous and uniform wear is built according to the basic random process model and fuzzy random reliability prediction method.The reliability prediction for continuous and non-uniform wear and non-continuous wear are also studied using pure death process,poisson process and renewal process theory,and the prediction moels are bulit.The failure time of gears are analyzed according to poisson process theory and the failure model is bulit.(6)Surface modification of laser cladding technology is often used to increase the wear reliability. High-quality coating on the surface of CrMo cast iron is developed with reasonable set of laser cladding parameters,and the structure of the coating is studied. The model of the wear rates prediction of laser cladding layer on CrMo cast iron and wear mechanism maps are established and the friction and wear properties are studied.The wear properties of the coating and the substrate are compared. |
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