Interval dynamic reliability analysis of mechanical components under multistage load based on strength degradation

Fatigue Fract Eng Mat Struct

Jiang

et al. 2020

Self Cite

To accurately predict the degraded fatigue life of components under random loads, anelasticity effect of metal on life estimation needs to be explored. Weighting coefficient and dynamic elastic modulus are introduced to modify the calculation process of the model. By establishing an equal-amplitude fatigue median surface and applying Miner linear fatigue cumulative damage theory, a fatigue life prediction model of the component under random loads is proposed. The model can be used to calculate the degraded fatigue life of components, which provides a theoretical basis for life estimation under random load spectrum. The two-dimensional load spectrum is compared with the unprocessed two-dimensional load spectrum and the one-dimensional program spectrum in life prediction results. With the comparison of the target life and simulation life and the data calculated by the model of the automobile front stabilizer bar, it is concluded that the data obtained by the modified model are more reasonable and accurate.

\sum_{i = 1}^{k} \frac{n_{i}}{N_{i}} = 1

29 . According to the relationship between cumulative damage and fatigue life of materials, the fatigue life expression is

T = \frac{1}{D}

.…”

Section: Statement Of Problemssupporting

confidence: 73%

Prediction and evaluation of fatigue life for mechanical components considering anelasticity‐based load spectrum

Wang

Fatigue Fract Eng Mat Struct

Jiang

et al. 2020

Self Cite

“…Analyzing both the loading sequence and interaction, become a problem needed to solve in fatigue cumulative damage. 37…”

Section: Statement Of Problemsmentioning

confidence: 99%

Fatigue life prediction of train wheel shaft based on load spectrum characteristics

Luo

Wang

Advances in Mechanical Engineering

et al. 2021

Self Cite

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.

“…In order to reduce the influence of uncertainty and obtain the optimal structure with the minimum failure probability, 2 more recent progress have been made on structural reliability analysis under uncertainty reliability 3,4 . And analysis methods have been widely developed and applied in structural reliability analysis 5,6 . Such as the first‐order reliability method (FORM), 7,8 the second‐order reliability method (SORM) 9 and Monte Carlo simulation (MCs) 8,10 method.…”

Section: Introductionmentioning

confidence: 99%

Reliability analysis of excavator boom considering mixed uncertain variables

Zhang

Quality & Reliability Eng

et al. 2020

Self Cite

There are differences among sampling data and representation types of uncertain interval, fuzzy and random variables, which increases the complexity of structure reliability analysis. A α, β‐Cut‐FORM is proposed to analyze structure reliability considering the mixed uncertain variables. Fuzzy variables are optimized on the interval under two cut sets (α, β) based on the theory of cut set optimization. Interval variables are modeled with probability using a uniformity method. The proposed method involves the nested probabilistic analysis and interval analysis. The first‐order reliability method (FORM) is used for probabilistic analysis and nonlinear optimization is used for interval analysis. The excavator boom performance function is established for reliability analysis considering the mixed uncertain input variables, which verifies the effectiveness and advantages of the proposed method. And it has great application for safe and reliable design of excavator boom.