Modeling Variability in Service Loading Spectra
Modeling Variability in Service Loading Spectra
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DOI：
10.1520/jai11561
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发表时间：
2004-02
期刊：
影响因子：
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通讯作者：
D. Socie;M. Pompetzki
中科院分区：
文献类型：
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作者：
D. Socie;M. Pompetzki
本文介绍了一种方法，统计外推一个单一的测量服务负载的历史，预期的长期服务使用谱。首先将实测的时间历程处理成雨流计数直方图。采用非参数核平滑技术将周期雨流直方图转换为概率密度直方图。一旦获得概率密度直方图，蒙特卡罗方法用于产生任何所需数量的周期的雨流直方图。一个新的加载历史，然后重建从预期雨流直方图，它可以与概率疲劳分析相结合，以获得结构的耐久性估计。获得地面车辆的载荷谱的估计是困难的，因为有许多用户，每个用户具有不同的服务使用。外推方法扩展到联合收割机数据从几个用户获得的负载谱，代表更严重的用户在人口中。
This paper describes a methodology for statistically extrapolating a single measured service loading history to the expected long-term service usage spectra. The measured time history first is processed into a rainflow counted histogram. Nonparametric kernel smoothing techniques are employed to convert the rainflow histogram of cycles into a probability density histogram. Once the probability density histogram is obtained, Monte Carlo methods are used to produce a rainflow histogram of any desired number of cycles. A new loading history then is reconstructed from the expected rainflow histogram, which can be combined with a probabilistic fatigue analysis to obtain an estimate of the durability of a structure. Obtaining an estimate of the loading spectra for a ground vehicle is difficult because there are many users, each with different service usage. The extrapolating methodology is extended to combine data from several users to obtain loading spectra that represent more severe users in the population.