In actual engineering, the actual road test or indoor bench test is usually used to collect the data of the road load of the parts to acquire the fatigue life estimation of the auto parts. This paper proposes a method for load spectrum construction based on the mixed distribution probability model using the data of the road load spectrum collected in the test site. Pau Ta criteria outlier elimination and wavelet signal denoising are applied to analyze the original road load spectrum data. Then the maximum likelihood estimation method is used to estimate the generalized Pareto distribution parameters of all excesses. The Pareto distribution is also employed to extrapolate the load spectrum. Through the characteristic analysis of the load spectrum, the one-dimensional and two-dimensional program load spectrum of the hub is established based on the mixed probability distribution model, which provides a theoretical basis for the life prediction of the hub. In addition, the research results of this paper provide inspirations for the fatigue life prediction and fatigue durability bench test of automotive parts subjected to the complexity and variability of random loads.
There are various uncertain factors in most practical engineering applications, such as input loads, structural sizes, manufacturing tolerance, and initial and boundary conditions. The interval method and grey number theory are common methods to deal with uncertainty. In this article, the interval truncation method and grey number theory are improved. And a mixed method is proposed to represent the confidence interval of output result based on the improved interval truncation method and improved grey number theory. The proposed methods’ feasibility is verified by a stepped bar; the methods are applied to the analysis of aircraft landing gear safety uncertainty.
Based on the analysis of load spectrum data, the loading sequence and the interaction between loads are considered, a fatigue life prediction model based on load spectrum is proposed. The load spectrum is preprocessed and the probability density function of mean and amplitude are fitted. The running condition of the train is analyzed, the one-dimensional program load spectrum of wheel and axle load is constructed by extrapolating the load spectrum. According to the modified fatigue cumulative damage method, the fatigue life of the axle is predicted with the one-dimensional program load spectrum. The relevant factors that affect the strength of the part are fully considers in the model. It more accurately reflects the objective facts of the component fatigue process. The result has more engineering reference significance and it provides a theoretical basis for the design and manufacture of train axles and ensuring safe operation.
To more accurately predict the fatigue life of components under the action of random loads, it is necessary to explore the influence of the interaction between the load sequence and the load on the life prediction. Based on the Manson-Halford method and Corten-Dolan model, this paper establishes a fatigue cumulative damage model that takes into account both the load order and the interaction between loads, and also takes into account the loads near the fatigue limit. The fatigue life of mechanical parts under random load can be calculated through this model, which provides a theoretical basis for life prediction under random load spectrum. The fatigue life of mechanical parts under random load can be calculated through this model, which provides a theoretical basis for life prediction under random load spectrum. Comparing the calculation results of the proposed model with the results of Palmgren Miner, Manson-Halford method, and Corten-Dolan model, it is found that the fatigue damage model established can reasonably predict the fatigue life of parts. Comparison and verification of examples further prove the accuracy and reliability of the proposed model.
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