The rainflow counting method is a reasonable cyclecounting procedure for fatigue life calculation and simulation testing of structures.It defines cycles as closed stress /strain hysteresis loops.Application of the rainflow counting method requires a data processing of the loading spectrum,which consists of the elimination of non-peak value data points,load time histories adjustment and loop extraction.In the data processing of the loading spectrum,if a stress point is neither the peak nor the valley,it will be identified and eliminated from the loading spectrum.Generally,the loading process is idealized as a single peak-valley straight line.But in actually,there are polylines or nearly straight lines between peaks and valleys which can't be ignored.Therefore,in the process of eliminating such data points,it will produce error in method itself.To reduce the error produced by the traditional method itself,a new method which can well simplify the polylines in data processing of loading spectrum is proposed in this paper.Comparing with the original approximation method,the proposed method has higher precision.
When a nonlinear fatigue damage accumulation model based on damage curve approach is used to get better residual life prediction results, it is necessary to solve the problem caused by the uncertain exponent of the model. Considering the effects of load interaction, the assumption that there is a linear dependence between the exponent ratio and the loading ratio is established to predict fatigue residual life of materials. Three experimental data sets are used to validate the rightness of the proposition. The comparisons of experimental data and predictions show that the predictions based on the proposed proposition are in good accordance with the experimental results as long as the parameters that represent the linear correlativity are set an appropriate value. Meanwhile, the accuracy of the proposition is approximated to that of an existing model. Therefore, the proposition proposed in this paper is reasonable for residual life prediction.
We present a new nonparametric predictive inference(NPI)method using a power-normal model for accelerated life testing(ALT).Combined with the accelerating link function and imprecise probability theory,the proposed method is a feasible way to predict the life of the product using ALT failure data.To validate the method,we run a series of simulations and conduct accelerated life tests with real products.The NPI lower and upper survival functions show the robustness of our method for life prediction.This is a continuous research,and some progresses have been made by updating the link function between different stress levels.We also explain how to renew and apply our model.Moreover,discussions have been made about the performance.
A method for reliability analysis of the competing failure with the probabilistic failure threshold value not the fixed threshold value is presented, which involves the random shocks and the degradation is independent and dependent respectively. Specifically, for the dependent condition, the effect due to the random shocks on the degradation is considered with a damage factor. In addition, the dependent competing failure model is applied to the reliability analysis of the k-out-of-n systems. Finally, two studied cases are presented to illustrate the proposed method, and the results show the proposed method is reasonable.
A modified nonlinear fatigue damage accumulation model based on the Manson-Halford theory was presented,and the new model was developed for fatigue life prediction under constant and variable amplitude loading, which took the effects of the load interactions and the phenomenon of material's strength degradation into account. The experimental data of the 30 Cr Mn Si A and the LY-12 cz from literature were used to verify the proposed model. And from the good agreement between the experimental data and predicted results,we can see it clear that the proposed method can be applied to predicting fatigue life under different loadings.
