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目錄
前言
主要符號(hào)
第0章緒論1
0.1結(jié)構(gòu)健康監(jiān)測(cè)的研究與應(yīng)用概況1
0.1.1傳感技術(shù)3
0.1.2數(shù)據(jù)科學(xué)與工程12
0.2結(jié)構(gòu)損傷識(shí)別與模型修正23
0.2.1模態(tài)參數(shù)識(shí)別23
0.2.2結(jié)構(gòu)損傷識(shí)別28
0.2.3結(jié)構(gòu)模型修正40
0.3結(jié)構(gòu)健康監(jiān)測(cè)數(shù)據(jù)分析建模與安全評(píng)定44
0.3.1監(jiān)測(cè)數(shù)據(jù)分析44
0.3.2監(jiān)測(cè)數(shù)據(jù)建模與安全評(píng)定49
0.4結(jié)構(gòu)災(zāi)害監(jiān)測(cè)數(shù)據(jù)分析與評(píng)估57
0.4.1結(jié)構(gòu)風(fēng)效應(yīng)監(jiān)測(cè)數(shù)據(jù)分析57
0.4.2結(jié)構(gòu)地震非線性模型識(shí)別與評(píng)估61
0.5結(jié)構(gòu)健康監(jiān)測(cè)的Benchmark模型66
0.6結(jié)構(gòu)健康監(jiān)測(cè)系統(tǒng)的應(yīng)用69
0.6.1橋梁結(jié)構(gòu)69
0.6.2國(guó)家游泳中心79
0.6.3某高層建筑81
0.6.4結(jié)構(gòu)健康監(jiān)測(cè)管理軟件系統(tǒng)平臺(tái)82
第1章數(shù)字信號(hào)的基礎(chǔ)知識(shí)86
1.1傅里葉變換86
1.2離散信號(hào)的傅里葉變換與快速傅里葉變換87
1.2.1離散傅里葉變換87
1.2.2快速傅里葉變換88
1.2.3柵欄效應(yīng)88
1.2.4頻率分辨率89
1.2.5能量泄漏與加窗90
1.3采樣定理93
1.4拉普拉斯變換96
1.4.1拉普拉斯變換的定義96
1.4.2拉普拉斯變換的函數(shù)微分性質(zhì)98
1.5信號(hào)濾波與去噪98
1.5.1濾波99
1.5.2小波去噪102
第2章數(shù)據(jù)壓縮采樣104
2.1數(shù)據(jù)壓縮采樣的數(shù)學(xué)原理104
2.1.1壓縮感知問(wèn)題描述104
2.1.2稀疏性105
2.1.3測(cè)量矩陣106
2.1.4優(yōu)化求解算法106
2.2應(yīng)用實(shí)例108
2.2.1橋梁監(jiān)測(cè)加速度壓縮采樣108
2.2.2大跨空間結(jié)構(gòu)監(jiān)測(cè)加速度壓縮采樣117
第3章無(wú)線傳輸數(shù)據(jù)丟失恢復(fù)算法121
3.1無(wú)線傳輸數(shù)據(jù)丟失概述121
3.2無(wú)線傳輸數(shù)據(jù)丟失恢復(fù)算法126
3.2.1無(wú)測(cè)量噪聲的數(shù)據(jù)丟失恢復(fù)算法126
3.2.2有測(cè)量噪聲的數(shù)據(jù)丟失恢復(fù)算法127
3.3應(yīng)用實(shí)例128
3.3.1橋梁監(jiān)測(cè)數(shù)據(jù)丟失恢復(fù)128
3.3.2大跨空間結(jié)構(gòu)監(jiān)測(cè)數(shù)據(jù)丟失恢復(fù)140
第4章結(jié)構(gòu)模態(tài)分析理論基礎(chǔ)144
4.1單自由度結(jié)構(gòu)的頻響函數(shù)和脈沖響應(yīng)函數(shù)144
4.1.1線性黏滯阻尼動(dòng)力系統(tǒng)144
4.1.2線性結(jié)構(gòu)阻尼動(dòng)力系統(tǒng)148
4.1.3頻響函數(shù)曲線性質(zhì)150
4.1.4不同荷載作用下結(jié)構(gòu)頻響函數(shù)和脈沖響應(yīng)函數(shù)155
4.2多自由度結(jié)構(gòu)頻響函數(shù)159
4.3多自由度結(jié)構(gòu)實(shí)模態(tài)頻響函數(shù)和脈沖響應(yīng)函數(shù)163
4.3.1多自由度結(jié)構(gòu)模態(tài)參數(shù)163
4.3.2多自由度結(jié)構(gòu)實(shí)模態(tài)頻響函數(shù)與單位脈沖響應(yīng)函數(shù)166
4.3.3算例分析168
4.4多自由度結(jié)構(gòu)復(fù)模態(tài)頻響函數(shù)174
4.4.1線性黏滯阻尼動(dòng)力系統(tǒng)174
4.4.2線性結(jié)構(gòu)阻尼動(dòng)力系統(tǒng)179
4.4.3復(fù)模態(tài)性質(zhì)180
4.4.4復(fù)模態(tài)頻響函數(shù)及脈沖響應(yīng)函數(shù)181
4.4.5算例分析184
第5章環(huán)境激勵(lì)下結(jié)構(gòu)模態(tài)參數(shù)識(shí)別方法188
5.1頻域分解法188
5.2NExT法與ERA法192
5.2.1NExT法192
5.2.2ERA法195
5.3隨機(jī)子空間方法202
5.4時(shí)變環(huán)境結(jié)構(gòu)模態(tài)參數(shù)分析208
5.4.1主成分分析方法208
5.4.2神經(jīng)網(wǎng)絡(luò)建模方法212
5.5應(yīng)用實(shí)例214
5.5.1結(jié)構(gòu)健康監(jiān)測(cè)系統(tǒng)概況214
5.5.2結(jié)構(gòu)模態(tài)參數(shù)識(shí)別結(jié)果215
5.5.3環(huán)境因素與模態(tài)參數(shù)關(guān)系模型222
第6章結(jié)構(gòu)損傷識(shí)別方法233
6.1基于模態(tài)參數(shù)的結(jié)構(gòu)損傷識(shí)別方法233
6.1.1基于頻率的結(jié)構(gòu)損傷識(shí)別方法233
6.1.2基于振型的結(jié)構(gòu)損傷識(shí)別方法235
6.2結(jié)構(gòu)損傷識(shí)別信息融合方法238
6.2.1D-S證據(jù)理論238
6.2.2Bayesian推理241
6.2.3D-S證據(jù)理論與Bayesian推理的比較242
6.2.4基于信息融合的結(jié)構(gòu)損傷識(shí)別方法246
6.3算例分析249
6.3.1橋梁有限元模型249
6.3.2結(jié)構(gòu)損傷識(shí)別結(jié)果250
第7章結(jié)構(gòu)模型修正255
7.1模態(tài)參數(shù)靈敏度方法255
7.1.1結(jié)構(gòu)模態(tài)參數(shù)靈敏度255
7.1.2結(jié)構(gòu)參數(shù)估計(jì)方法257
7.2Bayesian概率方法261
7.3應(yīng)用實(shí)例264
7.3.1斜拉橋子結(jié)構(gòu)特征264
7.3.2待修正結(jié)構(gòu)參數(shù)268
7.3.3修正結(jié)構(gòu)參數(shù)270
第8章車(chē)輛荷載極值模型與疲勞荷載譜273
8.1車(chē)輛荷載監(jiān)測(cè)數(shù)據(jù)特征273
8.2隨機(jī)過(guò)程概率模型與極值概率模型277
8.2.1濾過(guò)Poisson過(guò)程與極值概率模型277
8.2.2濾過(guò)Weibull過(guò)程與極值概率模型279
8.2.3平穩(wěn)二項(xiàng)隨機(jī)過(guò)程與極值概率模型279
8.2.4更新過(guò)程與極值概率模型281
8.3基于監(jiān)測(cè)數(shù)據(jù)的車(chē)輛荷載極值建模與概率模型284
8.3.1截口分布概率模型284
8.3.2到達(dá)時(shí)間概率模型287
8.3.3極值概率模型數(shù)值計(jì)算方法288
8.3.4應(yīng)用實(shí)例291
8.4基于監(jiān)測(cè)數(shù)據(jù)的車(chē)輛疲勞荷載譜建模與模型298
8.4.1中國(guó)車(chē)輛分類(lèi)298
8.4.2車(chē)輛疲勞荷載譜300
8.4.3車(chē)流量預(yù)測(cè)Logistic方法302
8.4.4應(yīng)用實(shí)例303
第9章車(chē)輛荷載時(shí)空分布識(shí)別與建模307
9.1車(chē)輛荷載時(shí)空分布識(shí)別方法307
9.1.1二值圖像形態(tài)學(xué)方法308
9.1.2車(chē)輛圖像識(shí)別310
9.1.3車(chē)輛定位318
9.2車(chē)輛荷載隨機(jī)場(chǎng)建模320
9.2.1馬爾科夫隨機(jī)場(chǎng)理論基礎(chǔ)321
9.2.2聯(lián)合樹(shù)算法323
9.2.3車(chē)輛荷載隨機(jī)場(chǎng)模型326
9.3應(yīng)用實(shí)例328
9.3.1車(chē)輛荷載識(shí)別328
9.3.2車(chē)輛荷載建模330
第10章基于監(jiān)測(cè)數(shù)據(jù)的主梁安全評(píng)定方法334
10.1應(yīng)變監(jiān)測(cè)數(shù)據(jù)特征334
10.1.1鋼筋混凝土橋梁334
10.1.2鋼橋337
10.2應(yīng)變監(jiān)測(cè)數(shù)據(jù)的解耦340
10.2.1趨勢(shì)項(xiàng)應(yīng)變解耦方法340
10.2.2混凝土收縮與徐變應(yīng)變解耦方法343
10.3基于監(jiān)測(cè)應(yīng)變的結(jié)構(gòu)承載力極限狀態(tài)安全評(píng)定348
10.3.1關(guān)鍵構(gòu)件荷載效應(yīng)概率模型349
10.3.2關(guān)鍵構(gòu)件抗力衰減模型358
10.3.3結(jié)構(gòu)承載力極限狀態(tài)可靠度評(píng)估方法359
10.3.4應(yīng)用實(shí)例361
10.4基于監(jiān)測(cè)應(yīng)變的鋼箱梁疲勞累積損傷評(píng)估方法365
10.4.1鋼材疲勞累積損傷基礎(chǔ)理論365
10.4.2鋼箱梁構(gòu)造細(xì)節(jié)疲勞壽命曲線368
10.4.3鋼箱梁疲勞荷載效應(yīng)譜計(jì)算方法370
10.4.4應(yīng)用實(shí)例371
第11章基于監(jiān)測(cè)數(shù)據(jù)的拉索安全評(píng)定方法373
11.1拉索時(shí)變索力識(shí)別方法374
11.1.1索力監(jiān)測(cè)數(shù)據(jù)特征374
11.1.2時(shí)不變索力識(shí)別方法379
11.1.3時(shí)變索力識(shí)別方法381
11.1.4算例分析386
11.2承載力極限狀態(tài)評(píng)估方法396
11.2.1拉索時(shí)變抗力模型396
11.2.2荷載效應(yīng)極值模型402
11.2.3時(shí)變承載力極限狀態(tài)安全評(píng)定404
11.2.4應(yīng)用實(shí)例406
11.3基于S-N曲線的拉索疲勞累積損傷評(píng)估與壽命預(yù)測(cè)方法416
11.3.1高強(qiáng)鋼絲疲勞壽命預(yù)測(cè)模型416
11.3.2拉索疲勞壽命預(yù)測(cè)模型418
11.3.3拉索疲勞荷載效應(yīng)譜計(jì)算方法419
11.3.4應(yīng)用實(shí)例420
11.4拉索疲勞累積損傷與壽命預(yù)測(cè)的斷裂力學(xué)方法432
11.4.1高強(qiáng)鋼絲斷裂力學(xué)基本理論432
11.4.2高強(qiáng)鋼絲腐蝕疲勞退化模型434
11.4.3拉索疲勞壽命評(píng)估方法437
第12章大跨度橋梁風(fēng)和風(fēng)效應(yīng)監(jiān)測(cè)數(shù)據(jù)分析439
12.1風(fēng)與風(fēng)效應(yīng)監(jiān)測(cè)系統(tǒng)設(shè)計(jì)方法439
12.2風(fēng)場(chǎng)監(jiān)測(cè)數(shù)據(jù)分析方法442
12.2.1平均風(fēng)速442
12.2.2風(fēng)速剖面443
12.2.3脈動(dòng)風(fēng)湍流強(qiáng)度與湍流積分尺度444
12.2.4脈動(dòng)風(fēng)速功率譜446
12.2.5陣風(fēng)因子448
12.2.6脈動(dòng)風(fēng)的空間相關(guān)性449
12.2.7風(fēng)場(chǎng)展向不均勻性449
12.3風(fēng)壓場(chǎng)與繞流場(chǎng)監(jiān)測(cè)數(shù)據(jù)分析方法449
12.3.1風(fēng)壓場(chǎng)449
12.3.2繞流場(chǎng)451
12.4主梁渦激振動(dòng)監(jiān)測(cè)數(shù)據(jù)分析方法455
12.4.1渦激振動(dòng)判別條件456
12.4.2渦激振動(dòng)特征456
12.5主梁抖振響應(yīng)監(jiān)測(cè)數(shù)據(jù)分析方法458
12.6斜拉索渦激振動(dòng)監(jiān)測(cè)數(shù)據(jù)分析方法459
12.6.1平均風(fēng)速的空間變換關(guān)系459
12.6.2斜拉索渦激振動(dòng)起振風(fēng)況分析459
12.6.3斜拉索渦激振動(dòng)參與模態(tài)的估計(jì)方法461
12.7應(yīng)用實(shí)例1462
12.7.1某大跨度懸索橋風(fēng)與風(fēng)效應(yīng)監(jiān)測(cè)系統(tǒng)462
12.7.2風(fēng)場(chǎng)監(jiān)測(cè)數(shù)據(jù)與分析466
12.7.3風(fēng)壓場(chǎng)與繞流場(chǎng)監(jiān)測(cè)數(shù)據(jù)與分析472
12.7.4主梁渦激振動(dòng)監(jiān)測(cè)數(shù)據(jù)與分析477
12.7.5主梁抖振監(jiān)測(cè)數(shù)據(jù)分析480
12.8應(yīng)用實(shí)例2484
12.8.1某大跨度斜拉橋及斜拉索渦激振動(dòng)監(jiān)測(cè)系統(tǒng)概況484
12.8.2斜拉索渦激振動(dòng)監(jiān)測(cè)數(shù)據(jù)分析485
第13章結(jié)構(gòu)地震反應(yīng)監(jiān)測(cè)數(shù)據(jù)分析與損傷識(shí)別489
13.1地震地面運(yùn)動(dòng)和結(jié)構(gòu)地震反應(yīng)監(jiān)測(cè)數(shù)據(jù)分析489
13.1.1地震地面運(yùn)動(dòng)工程特性分析490
13.1.2結(jié)構(gòu)地震損傷快速分析方法501
13.2基于數(shù)據(jù)驅(qū)動(dòng)的結(jié)構(gòu)非線性損傷定位方法508
13.2.1識(shí)別方法508
13.2.2算例分析511
13.3結(jié)構(gòu)非線性模型參數(shù)識(shí)別方法520
13.3.1識(shí)別方法520
13.3.2算例分析522
13.4基于完備集的結(jié)構(gòu)非線性模型及其參數(shù)識(shí)別方法530
13.4.1識(shí)別方法530
13.4.2算例分析533
13.5基于非完備集的結(jié)構(gòu)非線性模型及其參數(shù)識(shí)別方法535
13.5.1識(shí)別方法535
13.5.2算例分析539
第14章結(jié)構(gòu)健康監(jiān)測(cè)的Benchmark模型543
14.1健康監(jiān)測(cè)系統(tǒng)概況543
14.1.1工程概況543
14.1.2結(jié)構(gòu)健康監(jiān)測(cè)系統(tǒng)544
14.2結(jié)構(gòu)修正有限元模型547
14.2.1初始有限元模型548
14.2.2修正有限元模型551
14.3拉索狀態(tài)評(píng)估Benchmark問(wèn)題551
14.3.1拉索索力監(jiān)測(cè)數(shù)據(jù)551
14.3.2退役高強(qiáng)鋼絲和斜拉索疲勞特性552
14.3.3拉索狀態(tài)評(píng)估Benchmark問(wèn)題554
14.4主梁損傷識(shí)別Benchmark問(wèn)題554
14.4.1監(jiān)測(cè)數(shù)據(jù)555
14.4.2檢測(cè)數(shù)據(jù)558
14.4.3損傷識(shí)別Benchmark問(wèn)題558
參考文獻(xiàn)560
Contents
Preface
Main Symbols
Introduction
Chapter 1Basic knowledge of signal processing86
1.1Fourier transform86
1.2Discrete Fourier transform and fast Fourier transform of signal87
1.2.1Discrete Fourier transform87
1.2.2Fast Fourier transform88
1.2.3Picket fence effect88
1.2.4Frequency resolution89
1.2.5Energy leakage and window-added90
1.3Sampling theory93
1.4Laplace transform96
1.4.1Definition of Lappace transform96
1.4.2Function differential property of Lappace transform98
1.5Filtering and denosing of signal98
1.5.1Filtering99
1.5.2Denosing102
Chapter 2Compressive sampling104
2.1Principle of compressive sampling104
2.1.1Problem of compressive sampling104
2.1.2Sparsity105
2.1.3Measurement matrix106
2.1.4Optimizaiton algorithm106
2.2Case study108
2.2.1Compressive sampling of accleration data of bridge108
2.2.2Compressive sampling of accleration data of large span spatial structure117
Chapter 3Lost data recovery for wireless data transmission121
3.1Data loss reasons for wireless data transmission121
3.2Algorithm for lost data recovery126
3.2.1Lost data recovery without noise126
3.2.2Lost data recovery with noise127
3.3Case study128
3.3.1Data lost recovery for monitored data of bridge128
3.3.2Data lost recovery for monitored data of large span spatial structure140
Chapter 4Structural modal analysis144
4.1Frequency response function and impulse response function of single degree-of-freedom structure144
4.1.1Linear viscous damping dynamic system144
4.1.2Linear structure damping dynamic system148
4.1.3Characteries of frequency response function curve150
4.1.4Frequency response function and impulse response function under different loads155
4.2Frequency response function of multiple degree-of-freedom structure159
4.3Frequency response function and impulse response function of multiple degree-of-freedom structure163
4.3.1Modal parameters of multiple degree-of-freedom structure163
4.3.2Frequency response function and impulse response function of multiple degree-of-freedom structure166
4.3.3Example168
4.4Complex modal frequency response function of multiple degree-of-freedom structure174
4.4.1Linear structure damping dynamic system174
4.4.2Linear viscous damping dynamic system179
4.4.3Complex modal properties180
4.4.4Frequency response function and impulse response function of complex modal181
4.4.5Example184
Chapter 5Modal identification from ambient vibration of structure188
5.1Frequency domain decomposition188
5.2NExT and ERA192
5.2.1NExT192
5.2.2ERA195
5.3Stochastic subspace identification202
5.4Modal identification of bridge with ambient effects208
5.4.1Principle component analysis208
5.4.2Modelling by artifical neural network212
5.5Case study214
5.5.1Introduction of the structural health monitoring system214
5.5.2Results of structural modal identification215
5.5.3Model of the ambient effects and modal parameters222
Chapter 6Structural damage identification233
6.1Modal-based structural damage identfication methods233
6.1.1Frequency-based structural damage identfication methods233
6.1.2Mode shape-based structural damage identfication methods235
6.2Structural damage identification based on information fusion238
6.2.1D-S evidence theory238
6.2.2Bayesian theory241
6.2.3Comparison of D-S evidence theory and Bayesian theory242
6.2.4Structural damage identification based on information fusion246
6.3Example249
6.3.1Finite element model of bridge249
6.3.2Results of structural damage identification250
Chapter 7Structural model updating255
7.1Structural model updating based on modal sensitivity analysis255
7.1.1Modal sensitivity analysis255
7.1.2Structural parameters estimation257
7.2Bayesian model updating for structure261
7.3Case study264
7.3.1Substructure characteristics of cable stayed bridges264
7.3.2Updating structural parameters268
7.3.3Updated structural parameters270
Chapter 8Extreme value distribution and fatigue load spectrum of vehicle loads273
8.1Characteristics of monitored vehicle loads273
8.2Stochastic process and corresponding extreme value distribution277
8.2.1Filtered Poisson process and EV distribution277
8.2.2Filtered Weibull process and EV distribution279
8.2.3Stationary Binomial process and EV distribution279
8.2.4Renewal process and EV distribution281
8.3Extreme value distribution modelling based on monitored vehicle loads284
8.3.1Truncated distribution model284
8.3.2Probability distribution model of inter-arrival times287
8.3.3Numerical simulation method of EV distribution288
8.3.4Case study291
8.4Fatigue spectrum modelling of vehicle loads298
8.4.1Vehicles classification in China298
8.4.2Fatigue load spectrum300
8.4.3Logistic method of traffic prediction302
8.4.4Case study303
Chapter 9Identification and modeling of the spatio-temporal distribution of vehicle loads307
9.1Identification of spatio-temporal distribution of vehicle loads307
9.1.1Morphological processing of the binary image308
9.1.2Vehicle image identification310
9.1.3Vehicle localization318
9.2The random field model of vehicle loads320
9.2.1Introduction to Markov random field321
9.2.2Junction tree algorithm323
9.2.3The random field model of vehicle loads on bridge deck326
9.3Case study328
9.3.1Vehicle load identification328
9.3.2Vehicle load modeling330
Chapter 10Structural safety evaluation of girder based on monitored data334
10.1Characteristics of monitored strain334
10.1.1Reinforced concrete bridge334
10.1.2Steel bridge337
10.2Decoupling of monitored strain340
10.2.1Decoupling of trend strain340
10.2.2Decoupling of shrinkage and creep for concrete343
10.3Ultimate limit state assessment based on monitoring strain348
10.3.1Probability distribution of load effects for key members349
10.3.2Resistance deterioration model358
10.3.3Reliability evaluation method of ultimate limit state359
10.3.4Case study361
10.4Fatigue damage assessment of steel box girder based on monitored strain365
10.4.1Basic theory of cumulative fatigue damage365
10.4.2Fatigue life curve of structural details in steel box girder368
10.4.3Fatigue spectrum of monitored load effects370
10.4.4Case study371
Chapter 11Safety assessment for cables based on monitored data373
11.1Time variant cable force identification method374
11.1.1Monitored cable forces characteristics374
11.1.2Time invariant cable force identification method379
11.1.3Time variant cable force identification method381
11.1.4Example386
11.2Ultimate limit state evaluation396
11.2.1Resistance model of cables396
11.2.2Extreme value distribution of load effect402
11.2.3Time dependent ultimate limit state evaluation of cables404
11.2.4Case study406
11.3Fatigue damage assessment and life prediction of cables based on S-N curve416
11.3.1Fatigue life prediction model of high strength steel wires416
11.3.2Fatigue life prediction model of cables418
11.3.3Fatigue load spectrum based on monitored cable forces419
11.3.4Case study420
11.4Cumulative fatigue damage assessment and life prediction of cables based on linear elastic fracture mechanics432
11.4.1Basic theory of linear elastic fracture mechanics for steel wire432
11.4.2Corrosion fatigue degradation model of steel wires434
11.4.3Fatigue life assessment of Cables437
Chapter 12The monitoring data analysis method of the wind and wind effects of large-span bridges439
12.1The design method of wind and wind effects monitoring system439
12.2The analysis method of wind-field monitoring data442
12.2.1Mean wind speed442
12.2.2Wind profile443
12.2.3Turbulence intensity and integral scale of fluctuating wind444
12.2.4Power spectrum of fluctuating wind446
12.2.5Gust wind factor448
12.2.6Spatial correlation of fluctuating wind449
12.2.7Span-wise inhomogeneity of wind field449
12.3The data analysis method of wind pressure field and flow field around bluff bodies449
12.3.1Wind pressure field449
12.3.2Flow filed around bluff bodies451
12.4The data analysis method of vortex-induced vibrations of girders455
12.4.1The identification criterion of vortex-induced vibrations456
12.4.2Characteristics of vortex-induced vibrations456
12.5The data analysis method of buffeting responses of girders458
12.6The data analysis method of vortex-induced vibrations of stayed cables459
12.6.1Spatial transformation of wind velocity459
12.6.2The critical wind condition of vortex-induced vibrations of stayed cables459
12.6.3A method of estimating participation modes of vortex-induced vibrations461
12.7Case study 1462
12.7.1The wind and wind effects monitoring system of a suspension bridge462
12.7.2Wind field466
12.7.3Wind-pressure field and flow field around the box girder472
12.7.4Vortex induced vibrations of the box girder477
12.7.5Buffeting responses of the box girder480
12.8Case study 2484
12.8.1Field monitoring system of a cable-stayed bridge484
12.8.2The data analysis of vortex-induced vibrations of stayed cables485
Chapter 13The analysis of monitored earthquake ground motion and structural seismic response data and structural damage detection489
13.1The analysis of monitored earthquake ground motion and structural seismic response data489
13.1.1Engineering characteristics of earthquake ground motion490
13.1.2Fast and practical method of structural seismic damage detection501
13.2Data-driven based structural nonlinear damage location method508
13.2.1Detection method508
13.2.2Example511
13.3Identification method for the parameters of structural nonlinear model520
13.3.1Identification method520
13.3.2Example522
13.4Identification method for structural nonlinear model and its parameter based on complete observing set530
13.4.1Identification method530
13.4.2Example533
13.5Identification method for structural nonlinear model and its parameter based on incomplete observing set535
13.5.1Identification method535
13.5.2Example539
Chapter 14Benchmark model for structural health monitoring543
14.1General introduction of the bridge and structural health monitoring system543
14.1.1General introduction of the bridge543
14.1.2Structural health monitoring system544
14.2Initial and updated finite element model547
14.2.1Initial finite element model548
14.2.2Updated finite element model551
14.3Condition assessment benchmark problem for cables551
14.3.1Monitored data of cable forces551
14.3.2Fatigue properties of replaced steel wires and cables552
14.3.3Condition assessment benchmark problem for cables554
14.4Damage identification benchmark problem for girder554
14.4.1Monitored datasets555
14.4.2Testing datasets558
14.4.3Damage identification benchmark problem for girder558
References560