基于POT法确定风压系数极值的自动阈值选取与参数估计

陈元坤1,2,毛丹3,李寿科3,刘敏3,陈晓强1,陈俊1,孙洪鑫3

振动与冲击 ›› 2023, Vol. 42 ›› Issue (16) : 138-146.

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振动与冲击 ›› 2023, Vol. 42 ›› Issue (16) : 138-146.
论文

基于POT法确定风压系数极值的自动阈值选取与参数估计

  • 陈元坤1,2,毛丹3,李寿科3,刘敏3,陈晓强1,陈俊1,孙洪鑫3
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Automated threshold selection and parameter estimation for determining extreme wind pressure coefficients based on peaks over threshold method

  • CHEN Yuankun1,2,MAO Dan3,LI Shouke3,LIU Min3,CHEN Xiaoqiang1,CHEN Jun1,SUN Hongxin3
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摘要

风压系数极值是确定建筑围护结构设计风荷载的重要变量。实现阈值自动选取和合适的模型参数估计方法是保证超阈值模型极值计算结果精确性的先决条件,也是当前超越阈值模型研究的热点和难点。以CAARC高层建筑刚性模型测压风洞试验数据为基础开展超越阈值模型极值计算方法研究,通过对独立峰值数量和相关性研究独立峰值提取方法的性能;采用蒙特卡罗法研究4种不同的广义Pareto分布参数估计方法的性能,给出最佳参数估计方法选择建议;提出基于形状参数或极值估计结果稳定性的变点-局部比较阈值自动选取新方法。研究结果表明,基于变点理论-形状参数\极值稳定性阈值自动选取方法具有较小的样本依赖性,以及有较好的样本非高斯适用性,由此构建的改进超越阈值模型计算风压系数极值与标准极值的偏差小于5%,且完全实现阈值客观、自动选取,研究结论完善了小样本风压系数极值估计方法,对确定建筑围护结构设计风荷载具有重要意义,且可推广到其它极值估计领域。

Abstract

The extreme pressure coefficient is an important variable to determine the design wind load of building’s claddings and components. The realization of automatic threshold selection and selection of a proper parameter estimation method is a prerequisite to ensure the accuracy of the extreme value calculation results of the peaks over-threshold model, and it is the hotspot and difficulty of the peaks over-threshold model. Based on the wind tunnel tests of the rigid model of CAARC high-rise building, the research on the extreme pressure coefficients calculation method about peaks over threshold model is carried out, and the performance of the declustering method for independent peaks is studied by the number and correlation of independent peaks. The performance of the generalized Pareto distribution parameter estimation method is studied by Monte Carlo approach, and the best parameter estimation method is proposed. A change point-local comparison method based on the stability of shape parameters or extreme value estimation results is proposed. The best threshold is automatically selected by the new method. The research results show that the automatic threshold selection method based on the change point theory has small sample dependence and good non-Gaussian applicability of samples. The proposed method can achieve a deviation of less than 5% versus block maximum method, and fully realize the automatic selection of threshold by the modified POT model. The research conclusions are helpful for extreme value estimation of pressure coefficients and are of great significance for determining design wind loads of building’s claddings and components, as well as can be extended to other extreme value estimation fields.

关键词

超越阈值模型 / 极值 / 阈值选取 / 参数估计 / 独立峰值 / 风压系数 / 风洞试验

Key words

Peaks Over threshold model / Extreme value / Threshold selection / Parameter estimation / Independent peaks / Pressure coefficient / Wind tunnel test

引用本文

导出引用
陈元坤1,2,毛丹3,李寿科3,刘敏3,陈晓强1,陈俊1,孙洪鑫3. 基于POT法确定风压系数极值的自动阈值选取与参数估计[J]. 振动与冲击, 2023, 42(16): 138-146
CHEN Yuankun1,2,MAO Dan3,LI Shouke3,LIU Min3,CHEN Xiaoqiang1,CHEN Jun1,SUN Hongxin3. Automated threshold selection and parameter estimation for determining extreme wind pressure coefficients based on peaks over threshold method[J]. Journal of Vibration and Shock, 2023, 42(16): 138-146

参考文献

[1] 田玉基, 杨庆山. 非高斯风压时程峰值因子的简化计算式[J]. 建筑结构学报, 2015, 36(3):20-28.(Tian Yuji,Yang Qingshan.Reduced formula of peak factor for non-gaussian wind pressure history[J].Journal of Building Structures, 2015, 36(3):20-28.(in Chinese))
[2] Liu, M., Chen, X., Yang, Q.Estimation of peak factor of non-Gaussian wind pressures by improved moment-based hermite model. J. Eng. Mech, 2017. 143 (7),06017006.
[3] 罗颖, 黄国庆, 杨庆山,田玉基. 基于高阶矩的非高斯风压极值计算[J]. 建筑结构学报, 2018, 039(002):146-152.(Luo Ying,Huang Guoqing,Yang Qingshan,Tian Yuji.Calculation of peak for non-gaussian wind pressure based on high-order moments[J].Journal of Building Structures, 2018, 039(002):146-152.(in Chinese))
[4] 操金鑫, 田村幸雄, 吉田昭仁. 阶梯形平屋顶及其参数对建筑屋面极值风压的影响[J]. 振动与冲击, 2012, 31(9):1-8.( CAO J.,TAMURA Yukio, YOSHIDA Akihito. Effect of setback and its parameters on peak wind pressures on multi-level flat roofs[J]. Journalof Vibrationand Shock,2012, 31(9):1-8)
[5] Simiu, E. and N.A. Heckert, Extreme wind distribution tails: a “peaks over threshold” approach. Journal of Structural Engineering, 1996. 122(5): p. 539-547.
[6] Duthinh D, Pintar A L, Simiu E. Estimating peaks of stationary random processes: A peaks-over-threshold approach[J]. Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 2017, 3(4): 04017028.
[7] 全涌, 顾明 ,陈斌, 田村幸雄.非高斯风压的极值计算方法[J].力学学报,2010,42(03):560-566.(Quan Yong,Gu Ming, Chen Bin,Tamura Yukio.Study on the extreme value estimating method of non-gaussian wind pressure[J].Chinese Journal of Theoretical and Applied Mechanics. 2010,42(03):560-566(in Chinese))
[8] Haan L D . Extreme Value Statistics[J]. Extreme Value Theory and Applications, 1994.
[9] Naess A , Clausen P H . Combination of the peaks-over-threshold and bootstrapping methods for extreme value prediction[J]. Structural Safety, 2001, 23( 4):315-330.
[10] Hosking J R M, Wallis J R. Parameter and quantile estimation for the generalized Pareto distribution[J]. Technometrics, 1987, 29(3): 339-349.
[11] Bermudez P , Kotz S . Parameter estimation of the generalized Pareto distribution—Part I[J]. Journal of Statistical Planning & Inference, 2010, 140(6):1353-1373.
[12] Scarrott C, MacDonald A. A review of extreme value threshold estimation and uncertainty quantification[J]. REVSTAT–Statistical Journal, 2012, 10(1): 33-60.
[13] Davison A C, Smith R L. Models for exceedances over high thresholds[J]. Journal of the Royal Statistical Society: Series B (Methodological), 1990, 52(3): 393-425.
[14] Coles S, Bawa J, Trenner L, et al. An introduction to statistical modeling of extreme values[M]. London: Springer, 2001.
[15] Zhang X, Zwiers F W, Li G. Monte Carlo experiments on the detection of trends in extreme values[J]. Journal of Climate, 2004, 17(10): 1945-1952.
[16] Liang B, Shao Z, Li H, et al. An automated threshold selection method based on the characteristic of extrapolated significant wave heights[J]. Coastal Engineering, 2019, 144: 22-32.
[17] 李正农,伍欢庆.风压极值的阈值模型研究[J].地震工程与工程振动,2015,35(01):189-198.(Li Zhengnong,Wu Huanqing.A study on extreme windpressure: POT model[J].Earthquake Engineering and Engineering Dynamics. 2015,35(01):189-198(in Chinese))
[18] Ding J, Chen X. Assessment of methods for extreme value analysis of non-Gaussian wind effects with short-term time history samples[J]. Engineering Structures, 2014, 80: 75-88.
[19] Pickands III J. Statistical inference using extreme order statistics[J]. Annals of statistics, 1975, 3(1): 119-131.
[20] 毛丹.高层建筑表面风荷载及其极值估计方法[D],湖南科技大学,2021.(Dan Mao. Wind Load onHigh-rise Building and Extreme Value Estimation Method, Hunan University of Science and Technology .2021)
[21] Aminikhanghahi, S., Cook, D. J. (2017). A survey of methods for time series change point detection. Knowledge and information systems, 51(2), 339-367.
[22] 中华人民共和国国家标准. 建筑结构荷载规范(GB 50092012)[S]. 北京:中国建筑工业出版社,2012. (GB50009. Load Code for the Design of Building Structure; Ministry of Housing and Urban-Rural Construction of the People’s Republic of China: Beijing, China, 2012. (in Chinese)

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