Cr Mo Cast Steel Fatigue Life Prediction Method Based On Particle Filter

Fracture,corrosion and wear are the three main failure modes in engineering components or materials,and fracture is the most dangerous failure mode whose frequency is the highest,which may cause disastrous consequences.Therefore,the causes of fracture of materials and preventive controls become one of the most concerned problems that scientific research workers and engineers care about.The fracture of material is a very complicated process.It is affected by many factors including the nature of the material itself,environmental factors,job stress,shape and size of structures,the structure of the material,defect and etc.Moreover,it is usually the result of the above factors that work together,which makes the analysis of the material fracture process even more uncertain as well as increases the difficulty of controlling the fractures.The research is on the basis of a new kind of material of chromium stainless steel,using the stress and strain data of cycle index of chromium stainless steel tested by MTS fatigue testing machine,combining with the Kalman filter algorithm and the particle filter algorithm,thus proposing a new prediction of fatigue.Specific research contents include:(1)Analyze the stress and strain data of chromium stainless steel tested by MTS test.Calculate the damage of chrome molybdenum steel in each cycle time.Calculate the approximate relationship between crack and damage under the known damage crack model.(2)Utilizing the known model,analyze changing rules of crack along with the cycle times,as the prior distribution.(3)Combine prior distribution of the changing rules along with the cycle times of chromium stainless steel crack and calculate the change law of damage along with the cycle times.Use Kalman filter algorithm and the particle filter algorithm,deriving the changing rules along with the cycle times of chromium stainless steel crack.(4)Use the derived changing rules along with the cycle times of chromium stainless steel crack.Combine some of the properties of chromium stainless steel itself,predicting fatigue life of chromium stainless steel under different stress.Using Kalman filter algorithmand the particle filter algorithm can remove the interference of unknown factors in the process of measuring crack as much as possible,thus deriving the relatively optimal value of the fatigue crack propagation,which is of certain guiding significance.