Residual Fatigue Life Prediction of Ball Bearings Based on Paris Law and RMS

Paris law can reflect the failure mechanism of materials and is usually used to be a method to predict fatigue life or residual fatigue life.But the variable which can represent the health of machine is hardly measured on line.To a degree,the difficulty of on-line application restricts the scope of application of Paris law.The relationship between characteristic values of vibration signals and the variable in the Paris equation which can describe the health of machine is investigated by taking ball bearings as investigative objects.Based on 6205 deep groove ball bearings as a living example,historical lives and vibration signals are analyzed.The feasibility of describing that variable in the Paris equation by the characteristic value of vibration signals is inspected.After that vibration signals decomposed by empirical mode decomposition（EMD）,root mean square（RMS） of intrinsic mode function（IMF） involving fault characteristic frequency has a consistent trend with the diameter of flaws.Based on the trend,two improved Paris models are proposed and the scope of application of them is inspected.These two Paris Models are validated by fatigue residual life data from tests of rolling element bearings and vibration signals monitored in the process of operation of rolling element bearings.It shows that the first improved Paris Model is simple and plain and it can be easily applied in actual conditions.The trend of the fatigue residual life predicted by the second improved Paris model is close to the actual conditions and the result of the prediction is slightly greater than the truth.In conclusion,after the appearance of detectable faults,these improved models based on RMS can predict residual fatigue life on line and a new approach to predict residual fatigue life of ball bearings on line without disturbing the machine running is provided.

Aluminum Alloy Fatigue Crack Damage Prediction Based on Lamb Wave-Systematic Resampling Particle Filter Method

Fatigue crack prediction is a critical aspect of prognostics and health management research.The particle filter algorithm based on Lamb wave is a potential tool to solve the nonlinear and non-Gaussian problems on fatigue growth,and it is widely used to predict the state of fatigue crack.This paper proposes a method of lamb wavebased early fatigue microcrack prediction with the aid of particle filters.With this method,which the changes in signal characteristics under different fatigue crack lengths are analyzed,and the state-and observation-equations of crack extension are established.Furthermore,an experiment is conducted to verify the feasibility of the proposed method.The Root Mean Square Error(RMSE)of the three different resampling methods are compared.The results show the system resampling method has the highest prediction accuracy.Furthermore,the factors affected by the accuracy of the prediction are discussed.

Predictive fatigue crack growth law of high-strength steels

The fatigue resistance of metallic materials is generally attributed to both strength and toughness.Unfortunately,these properties are mutually exclusive in most materials.Classical theories like Paris’law only provide some data correlation schemes rather than a predictive capability,which cannot satisfactorily guide the anti-fatigue design.In this study,for the first time,the predictive fatigue crack growth rate law is proposed by considering the effects of both strength and toughness.Accordingly,a quantitative criterion is established for judging the fatigue crack resistance of high-strength steels.The predictive law would provide a unique view to the quantitative anti-fatigue design of metallic materials.

An estimation of stress intensity factor in a clamped SE(T) specimen through numerical simulation and experimental verification:case of FCGR of AISI H11 tool steel

A finite element analysis of stress intensity factors （KI） in clamped SE（T）c specimens （dog bone profile） is presented. A J-integral approach is used to calculate the values of stress intensity factors valid for 0.125≤a/W≤0.625. A detailed comparison is made with the work of other researchers on rectangular specimens. Different boundary conditions are explored to best describe the real conditions in the laboratory. A sensitivity study is also presented to explore the effects of variation in specimen position in the grips of the testing machine. Finally the numerically calculated SIF is used to determine an FCGR curve for AISI Hll tool steel on SE（T）c specimens and compared with C（T） specimen of the same material.