本文關(guān)鍵詞：車輛荷載作用下橋梁應(yīng)變極值估計(jì)的閾值選取　出處：《應(yīng)用數(shù)學(xué)和力學(xué)》2017年05期 　論文類型：期刊論文

  更多相關(guān)文章： 橋梁健康監(jiān)測(cè) 閾值選取方法 應(yīng)變極值 廣義Pareto分布

【摘要】：采用過閾法估計(jì)車輛荷載作用下橋梁的應(yīng)變極值,合理的閾值選取十分關(guān)鍵.閾值選取過大,信息量少,閾值選取過小,廣義Pareto分布模型參數(shù)估計(jì)偏差大.常用的閾值選取方法不能較好地適用于車輛荷載作用下的應(yīng)變極值估計(jì).基于太平湖大橋車輛荷載作用下1年的應(yīng)變數(shù)據(jù),對(duì)擬合結(jié)果較好的3種混合分布進(jìn)行Monte-Carlo(蒙特-卡洛)抽樣,對(duì)比同一樣本基于不同閾值的廣義Pareto分布模型的極值估計(jì)結(jié)果,提出了一種經(jīng)驗(yàn)式的閾值選取方法.與常用閾值選取方法相比,根據(jù)文中方法所得閾值估計(jì)的周應(yīng)變極值分布與實(shí)測(cè)結(jié)果更為接近,估計(jì)結(jié)果更好.
[Abstract]:Using the over-threshold method to estimate the strain extreme value of bridge under vehicle load, it is very important to select the reasonable threshold value. The threshold selection is too large, the amount of information is little, and the threshold value is too small. The parameter estimation deviation of the generalized Pareto distribution model is large. The commonly used threshold selection method is not suitable for the strain extremum estimation under vehicle load. Based on the response of Taipinghu Bridge under vehicle load for one year. Change the data. Monte-Carlo (Monte-Carlo) sampling is carried out for three mixed distributions with good fitting results, and the extremum estimation results of the generalized Pareto distribution model based on different thresholds of the same sample are compared. In this paper, an empirical threshold selection method is proposed. Compared with the conventional threshold selection method, the estimated maximum value distribution of the circumferential strain based on the proposed method is closer to the measured results and the estimated results are better.
【作者單位】： 合肥工業(yè)大學(xué)土木與水利工程學(xué)院;中南大學(xué)土木工程學(xué)院;
【基金】：中國博士后科學(xué)基金(2015M581982) 安徽省自然科學(xué)基金(1708085ME101)~~
【分類號(hào)】：U446
【正文快照】： (我刊編委任偉新來稿)引言極值理論指出[5],極值估計(jì)通常只與概率密度函數(shù)的高尾分布相關(guān),即車輛荷載效應(yīng)的極值估計(jì)應(yīng)只與重型車有關(guān).廣義Pareto分布(generalized Pareto distribution,GPD)模型作為樣本右尾數(shù)據(jù)的擬合模型,廣泛運(yùn)用于洪水高度、風(fēng)速、氣溫等的極值估計(jì)中,近，

本文編號(hào)：1408539