本文選題：移動(dòng)荷載識別 + 識別精度　； 參考：《華北水利水電大學(xué)》2017年碩士論文

【摘要】：橋梁的移動(dòng)荷載識別屬于結(jié)構(gòu)動(dòng)力學(xué)逆問題的范疇,大多數(shù)橋梁移動(dòng)荷載識別方法最終都轉(zhuǎn)化為線性方程組的求解,不同的求解方法得到的結(jié)果識別精度不同。為了改進(jìn)時(shí)域法(TDM)識別橋面移動(dòng)荷載時(shí)存在的識別精度受測量噪聲、測點(diǎn)類型及數(shù)量影響較大等缺陷,本文基于第一識別法,第二識別法,頻時(shí)域法和時(shí)域法的基本理論,結(jié)合橋梁的移動(dòng)荷載識別特點(diǎn),探討了幾種移動(dòng)荷載識別相關(guān)的正則化方法,提出了基于分段多項(xiàng)式截?cái)嗥娈愔捣纸夥?PPTSVD)識別橋梁移動(dòng)荷載。采用簡化歐拉梁模型,以兩軸常力移動(dòng)軸載和兩種類型時(shí)變移動(dòng)荷載為例,由反演車輛荷載作用下橋梁的彎矩響應(yīng)和加速度響應(yīng)識別橋面移動(dòng)荷載,對12種不同測點(diǎn)布置工況進(jìn)行數(shù)值模擬分析,得到了不同噪聲水平下分段多項(xiàng)式截?cái)嗥娈愔捣纸夥?PPTSVD)的識別結(jié)果,并將該識別精度與時(shí)域法(TDM)和截?cái)嗥娈愔捣纸夥?TSVD)識別精度進(jìn)行比較。其中PPTSVD與TDM識別精度比較結(jié)果表明:兩種識別方法的識別誤差均隨測量噪聲增大而增大,當(dāng)噪聲水平達(dá)到10%時(shí),TDM對應(yīng)的12種識別工況中有11種識別工況識別誤差均超過100%,識別結(jié)果不能接受;PPTSVD對應(yīng)的12種識別工況識別誤差均低于100%且其中有10種識別工況識別誤差低于30%,其抗噪性能較TDM提高明顯。兩種方法識別精度均受測點(diǎn)類型及數(shù)量影響較大,當(dāng)識別工況包含較多加速度響應(yīng)測點(diǎn)時(shí)兩種方法識別精度較高。當(dāng)僅由彎矩響應(yīng)識別橋梁移動(dòng)荷載時(shí),TDM識別結(jié)果不能接受而PPTSVD仍能給出較好的識別結(jié)果。PPTSVD識別精度高、識別結(jié)果受測點(diǎn)類型及數(shù)量影響較小且具有良好的魯棒性,更適應(yīng)于橋梁移動(dòng)荷載的現(xiàn)場識別。
[Abstract]:The identification of moving loads of bridges belongs to the inverse problem of structural dynamics. Most of the identification methods of moving loads of bridges are transformed into the solution of linear equations, and the accuracy of the results obtained by different methods is different. In order to improve the identification accuracy of bridge deck moving load by time domain method (TDM), such as measurement noise, type and number of measuring points, this paper is based on the basic theory of the first identification method, the second identification method, the frequency time domain method and the time domain method. Combined with the characteristics of bridge moving load identification, several regularization methods related to moving load identification are discussed, and a method based on piecewise polynomial truncated singular value decomposition (PPTSVD) is proposed to identify the bridge moving load. A simplified Euler beam model is used to identify the moving loads on the deck of the bridge under the action of vehicle loads by taking two axial constant moving axle loads and two types of time-varying moving loads as examples, and the moment response and acceleration response of the bridge under the action of the vehicle load are inversed to identify the moving loads on the bridge deck. Through numerical simulation and analysis of 12 different measuring point layout conditions, the recognition results of piecewise polynomial truncated singular value decomposition (PPTSVD) under different noise levels are obtained. The recognition accuracy is compared with time domain method (TDM) and truncated singular value decomposition method (TSVD). The comparison of recognition accuracy between PPTSVD and TDM shows that the recognition errors of the two methods increase with the increase of measurement noise. When the noise level reaches 10, 11 of the 12 identification conditions corresponding to TDM have more than 100 recognition errors. The recognition results can not accept that the recognition errors of the 12 identification conditions corresponding to PPTSVD are all less than 100% and there are 10 identifiers among them. When the recognition error is less than 30, the anti-noise performance of the system is better than that of TDM. The accuracy of the two methods is greatly affected by the type and number of measuring points, and the two methods have higher recognition accuracy when the identification conditions contain more acceleration response points. When only the moment response is used to identify the moving load of the bridge, the PPTSVD can still give a better recognition result. The accuracy of the identification is high, and the identification result is less affected by the type and number of the measured points and has good robustness. It is more suitable for the field identification of bridge moving load.
【學(xué)位授予單位】：華北水利水電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：U441

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 陳修輝;孫銘霞;;基于HKBFO優(yōu)化神經(jīng)網(wǎng)絡(luò)的懸索橋動(dòng)載識別[J];延邊大學(xué)學(xué)報(bào)(自然科學(xué)版);2015年03期

2 王儀;虞婷婷;瞿偉廉;;橋上列車移動(dòng)荷載參數(shù)自動(dòng)識別系統(tǒng)試驗(yàn)[J];噪聲與振動(dòng)控制;2015年02期

3 王偉;唐懷平;;基于動(dòng)力響應(yīng)的橋梁移動(dòng)載荷識別[J];應(yīng)用數(shù)學(xué)和力學(xué);2014年S1期

4 陳震;余嶺;;基于截?cái)郍SVD方法的橋梁移動(dòng)荷載識別[J];振動(dòng)與沖擊;2014年10期

5 張欣;杜修力;;橋梁行車激勵(lì)辨識的實(shí)驗(yàn)?zāi)B(tài)方法[J];振動(dòng).測試與診斷;2013年03期

6 王寧波;任偉新;李苗;;基于影響線的橋梁移動(dòng)荷載識別[J];振動(dòng)與沖擊;2013年03期

7 夏樟華;宗周紅;李嘉維;孫建林;;基于健康監(jiān)測系統(tǒng)的大跨度連續(xù)剛構(gòu)橋移動(dòng)荷載識別[J];中國公路學(xué)報(bào);2012年05期

8 王蕾;侯吉林;歐進(jìn)萍;;基于荷載形函數(shù)的大跨橋梁結(jié)構(gòu)移動(dòng)荷載識別[J];計(jì)算力學(xué)學(xué)報(bào);2012年02期

9 張青霞;段忠東;Lukasz Jankowski;王豐;;基于形函數(shù)方法快速識別結(jié)構(gòu)動(dòng)態(tài)荷載的試驗(yàn)驗(yàn)證[J];振動(dòng)與沖擊;2011年09期

10 瞿偉廉;王儀;;根據(jù)響應(yīng)識別橋上列車荷載的模糊模式識別方法[J];噪聲與振動(dòng)控制;2011年01期

相關(guān)碩士學(xué)位論文 前1條

1 陳震;橋梁移動(dòng)荷載識別的不適定問題研究[D];長江科學(xué)院;2007年

，

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