平行钢丝斜拉索疲劳性能评定Ⅰ:钢丝疲劳寿命模型

摘要

平行钢丝斜拉索疲劳性能评定研究分为两部分,该文为第一部分:钢丝疲劳寿命模型.根据三参数幂函数应力-寿命模型与指定应力幅下疲劳寿命服从两参数Weibull分布,推导表征疲劳寿命的多参数Weibull模型,将疲劳寿命与应力幅统一在模型中.进一步根据疲劳截尾数据的条件概率分布建立疲劳模型参数EM估计算法,通过分析文献中钢绞线疲劳数据及研究开展的高强钢丝疲劳数据阐述多参数Weibull模型的适用性与优点.研究表明:该多参数Weibull模型能够较好地描述钢丝及钢绞线疲劳试验数据,指定应力幅时疲劳寿命简化为两参数Weibull分布,指定疲劳寿命时应力幅简化为三参数Weibull分布.文中提出的模型参数EM估计算法有效地解决了含有截尾数据的模型参数估计问题,采用全部疲劳试验数据进行模型参数估计,提高模型参数估计的准确性.%As the first part with respect to the fatigue property assessment of the parallel wire stay cable,a fatigue life model of the steel wire is established.The three-parameter power function is employed to describe the fatigue stress-life model,and the two-parameter Weibull distribution is used to represent the fatigue life of steel wire under the specified stress range.Supposed that the fatigue life of individual wire calculated by the two models are equivalent under the specified stress range with the identical survival probability,a novel multi-parameter Weibull model for the fatigue life assessment of steel wire is deduced,in which fatigue life and stress range are compatible.On the basis of conditional probability distribution of the censored data,an improved expectation maximization (EM) algorithm is employed to estimate the parameters of the proposed model.The fatigue data of the strands from the literature are analyzed to illustrate the fitness and characteristics of the proposed model.Finally,the fatigue life model for the steel wire is established based on the fatigue data obtained by fatigue experiment.The results indicate that the proposed fatigue life model can fit the fatigue data of strands and steel wires better.For the specified stress range,the probability distribution of the fatigue life is simplified as a two-parameter Weibull model.For the specified fatigue life,the probability distribution of the corresponding stress range is simplified as a three-parameter Weibull model.It is convenient to deal with the censored data with the proposed EM algorithm.The whole fatigue data are pooled together to estimate the parameters of the proposed fatigue life model,thus the accuracy of the parameter estimation can be improved.