本文關(guān)鍵詞：基于貝葉斯原理的既有橋梁車輛荷載效應(yīng)概率分布模型研究　出處：《華南理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 既有橋梁結(jié)構(gòu) 車輛荷載效應(yīng) 概率分布模型 截口分布 最大值分布 目標(biāo)使用期 貝葉斯原理

【摘要】：隨著我國交通事業(yè)的發(fā)展，機動車輛的數(shù)量不斷增長，公路橋梁的數(shù)量也不斷增加，橋梁構(gòu)件承載能力評估的重要性日益凸顯。車輛荷載效應(yīng)作為公路橋梁的主要可變荷載效應(yīng)，直接反映了橋梁所承受的車輛荷載情況，因此橋梁車輛荷載效應(yīng)的確定對于橋梁構(gòu)件承載能力評估具有重要意義。 公路橋梁的車輛荷載效應(yīng)可以采用概率模型進(jìn)行描述。我國現(xiàn)行公路橋梁設(shè)計規(guī)范中的車輛荷載效應(yīng)概率分布模型是依據(jù)上世紀(jì)90年代全國4個具有代表性的WIM(Weigh In Motion)測點的實測自然車隊確定的，計算采用的橋型結(jié)構(gòu)主要為簡支梁和多跨連續(xù)梁。在考慮不同時間、不同地域以及不同橋梁結(jié)構(gòu)形式的前提下，規(guī)范的車輛荷載效應(yīng)模型已不能滿足當(dāng)前既有橋梁構(gòu)件承載能力評估的需求，因此本文針對既有橋梁的車輛荷載效應(yīng)概率分布模型進(jìn)行研究。 既有橋梁車輛荷載效應(yīng)概率分布模型的研究包括車輛荷載效應(yīng)截口分布及目標(biāo)使用期內(nèi)車輛荷載效應(yīng)最大值分布的研究。其中車輛荷載效應(yīng)截口分布反映的是某一時間截口處既有橋梁的受載情況，隨著橋梁運行時間的推移，車輛荷載效應(yīng)截口分布需要不斷更新；而目標(biāo)使用期內(nèi)車輛荷載效應(yīng)最大值分布則反映了目標(biāo)使用期內(nèi)既有橋梁的受載情況。 本文的主要工作內(nèi)容包括： (1)車輛荷載效應(yīng)樣本的獲取。采用新光大橋橋址附近區(qū)域具有代表性的WIM系統(tǒng)實測自然車隊對新光大橋進(jìn)行加載，利用車輛荷載效應(yīng)影響面得到新光大橋構(gòu)件車輛荷載效應(yīng)樣本。 (2)車輛荷載效應(yīng)截口分布的確定。采用極大似然估計法和皮爾遜2檢驗法對新光大橋車輛荷載效應(yīng)概率分布模型進(jìn)行參數(shù)估計和擬合檢驗，確定新光大橋車輛荷載效應(yīng)截口分布的分布類型及參數(shù)。 (3)車輛荷載效應(yīng)截口分布的更新。確定了包含更新方法、更新路線、更新周期等方面在內(nèi)的車輛荷載效應(yīng)截口分布更新策略，并提出一種基于貝葉斯原理的車輛荷載效應(yīng)截口分布更新方法，利用少量效應(yīng)樣本對車輛荷載效應(yīng)截口分布進(jìn)行更新。 (4)目標(biāo)使用期內(nèi)車輛荷載效應(yīng)最大值分布的確定。引入目標(biāo)使用期的概念，并基于平穩(wěn)二項隨機過程假設(shè)，由車輛荷載效應(yīng)截口分布推導(dǎo)目標(biāo)使用期內(nèi)的車輛荷載效應(yīng)最大值分布，確定可直接用于構(gòu)件承載力評估的對應(yīng)于0.95分位數(shù)的車輛荷載效應(yīng)標(biāo)準(zhǔn)值。 本文的主要結(jié)論包括： (1)基于新光大橋橋址附近區(qū)域的實測自然車隊，計算分析得到的一般運行狀態(tài)下和密集運行狀態(tài)下的新光大橋車輛荷載效應(yīng)截口分布都服從對數(shù)正態(tài)分布。 (2)所提出的新光大橋車輛荷載效應(yīng)截口分布的更新策略，包括更新方法、更新路線、更新周期及更新中初始參數(shù)的選取，能夠滿足新光大橋健康監(jiān)測系統(tǒng)全橋構(gòu)件承載能力評估的需求，并可為其他既有橋梁的車輛荷載效應(yīng)截口分布的更新提供思路。 (3)基于貝葉斯原理的車輛荷載效應(yīng)截口分布更新方法，可針對車輛荷載效應(yīng)截口分布對數(shù)正態(tài)模型，采用少量較新的車輛荷載效應(yīng)試驗樣本，實現(xiàn)對多樣本的車輛荷載效應(yīng)先驗截口分布的小幅修正。 (4)由已知的車輛荷載效應(yīng)截口分布外推得到目標(biāo)使用期內(nèi)車輛荷載效應(yīng)最大值分布及對應(yīng)的車輛荷載效應(yīng)標(biāo)準(zhǔn)值。結(jié)果顯示，，由于一般運行狀態(tài)下的車輛荷載分布比密集狀態(tài)下離散程度大，因此一般運行運行狀態(tài)下的車輛荷載效應(yīng)最大值分布的標(biāo)準(zhǔn)差比密集運行狀態(tài)下大，導(dǎo)致部分構(gòu)件在一般運行狀態(tài)下的車輛荷載效應(yīng)標(biāo)準(zhǔn)值略大于密集運行狀態(tài)下的標(biāo)準(zhǔn)值。
[Abstract]:With the development of transportation, the number of motor vehicles is growing, the number of highway bridges is increasing, the importance of evaluating the bearing capacity of bridge components has become increasingly prominent. The main effect of vehicle load effect as highway bridge variable load directly reflects the situation of the bridge under the vehicle load, so the vehicle load effect of bridge for sure has an important significance to evaluate the bearing capacity of the bridge structure.
Vehicle load effect of highway bridges can be described by probabilistic model. Our current code for design of highway bridges in the vehicle load effect probability distribution model is based on the last century, the 90s national 4 representative WIM (Weigh In Motion) measured natural team points are identified, the calculation of bridge structure is the main beam and multi span continuous beam. In consideration of different time, different regions and different forms of bridge structure under the premise, vehicle load effect model specification can not meet the current needs of both the assessment of carrying capacity of bridge components, so the article studied the effect of vehicle load of the existing bridge probability distribution model.
Both of the probability distribution model of load effect of bridges and vehicles including section distribution and target vehicle load effect using the vehicle load effect period distribution of the maximum value. The effect of vehicle load distribution section is reflected in a section at the time of the existing bridge load, with the bridge running time, vehicle load effect section the distribution of the need to constantly update; and the target using the vehicle load effect during the period of maximum distribution reflects the target use period of the existing bridge load.
The main contents of this paper are as follows:
(1) acquisition of vehicle load effect samples. A representative WIM system is used to load the Xinguang Bridge in the vicinity of the Xinguang Bridge site. The vehicle load effect sample of Xinguang Bridge component is obtained by vehicle load effect surface.
(2) determine the section distribution of load effect of vehicles. By using the maximum likelihood estimation method and Pearson parameter estimation and fitting test of Xinguang Bridge vehicle load effect probabilistic distribution model of 2 test, to determine the effect of vehicle load of Xinguang Bridge section distribution type and parameters.
(3) update the section distribution of traffic load effect. The included update method, update the route update period, the effect of vehicle load distribution section update strategy, and put forward a kind of vehicle load effect Bayesian updating method based on the principle of section distribution, with a small amount of sample and effect the effect of vehicle load distribution section to be updated.
(4) the target using the vehicle load effect during the period of maximum distribution is determined. By introducing the concept of the target period, and based on the stationary random process by the two hypothesis, the effect of vehicle load distribution is derived using the section target vehicle load effect within the period of maximum distribution, determine the standard vehicle load effect can be directly used for the corresponding evaluation of bearing capacity of member in the 0.95 percentile value.
The main conclusions of this paper include:
(1) the measured natural Fleet area near the Xinguang Bridge Site Based on the calculation and analysis of Xinguang Bridge effect of vehicle load distribution section obtained under normal operating state and intensive operation conditions are subject to lognormal distribution.
(2) the new bridge vehicle load effect section distribution update strategy, including update method, update the route, select the initial parameter update cycle and update, to meet the full bridge bearing capacity evaluation of Xinguang Bridge Health monitoring system needs, and can provide reference for other bridges with vehicle load effect section the distribution of the update.
(3) the effect of vehicle load distribution Bayesian updating method based on the principle of the section, the vehicle load effect section lognormal distribution model, a few samples of new vehicle load effect, to realize the multi sample vehicle load effect prior distribution of small amplitude correction section.
(4) from the known effect of vehicle load distribution section extrapolated target using the vehicle load effect within the period of maximum standard vehicle load effect distribution and corresponding values. The results show that the vehicle loads are generally running under the condition of intensive distribution than the discrete degree, because of the effect of vehicle load the general operation condition of maximum the value of standard deviation of the distribution of intensive operation state, the standard vehicle load effect leads to some components in the normal operating state was slightly higher than the standard value of intensive operation.

【學(xué)位授予單位】：華南理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：U441.2

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