目录 前言 主要符号 第0章绪论1 0.1结构健康监测的研究与应用概况1 0.1.1传感技术3 0.1.2数据科学与工程12 0.2结构损伤识别与模型修正23 0.2.1模态参数识别23 0.2.2结构损伤识别28 0.2.3结构模型修正40 0.3结构健康监测数据分析建模与安全评定44 0.3.1监测数据分析44 0.3.2监测数据建模与安全评定49 0.4结构灾害监测数据分析与评估57 0.4.1结构风效应监测数据分析57 0.4.2结构地震非线性模型识别与评估61 0.5结构健康监测的Benchmark模型66 0.6结构健康监测系统的应用69 0.6.1桥梁结构69 0.6.2国家游泳中心79 0.6.3某高层建筑81 0.6.4结构健康监测管理软件系统平台82 第1章数字信号的基础知识86 1.1傅里叶变换86 1.2离散信号的傅里叶变换与快速傅里叶变换87 1.2.1离散傅里叶变换87 1.2.2快速傅里叶变换88 1.2.3栅栏效应88 1.2.4频率分辨率89 1.2.5能量泄漏与加窗90 1.3采样定理93 1.4拉普拉斯变换96 1.4.1拉普拉斯变换的定义96 1.4.2拉普拉斯变换的函数微分性质98 1.5信号滤波与去噪98 1.5.1滤波99 1.5.2小波去噪102 第2章数据压缩采样104 2.1数据压缩采样的数学原理104 2.1.1压缩感知问题描述104 2.1.2稀疏性105 2.1.3测量矩阵106 2.1.4优化求解算法106 2.2应用实例108 2.2.1桥梁监测加速度压缩采样108 2.2.2大跨空间结构监测加速度压缩采样117 第3章无线传输数据丢失恢复算法121 3.1无线传输数据丢失概述121 3.2无线传输数据丢失恢复算法126 3.2.1无测量噪声的数据丢失恢复算法126 3.2.2有测量噪声的数据丢失恢复算法127 3.3应用实例128 3.3.1桥梁监测数据丢失恢复128 3.3.2大跨空间结构监测数据丢失恢复140 第4章结构模态分析理论基础144 4.1单自由度结构的频响函数和脉冲响应函数144 4.1.1线性黏滞阻尼动力系统144 4.1.2线性结构阻尼动力系统148 4.1.3频响函数曲线性质150 4.1.4不同荷载作用下结构频响函数和脉冲响应函数155 4.2多自由度结构频响函数159 4.3多自由度结构实模态频响函数和脉冲响应函数163 4.3.1多自由度结构模态参数163 4.3.2多自由度结构实模态频响函数与单位脉冲响应函数166 4.3.3算例分析168 4.4多自由度结构复模态频响函数174 4.4.1线性黏滞阻尼动力系统174 4.4.2线性结构阻尼动力系统179 4.4.3复模态性质180 4.4.4复模态频响函数及脉冲响应函数181 4.4.5算例分析184 第5章环境激励下结构模态参数识别方法188 5.1频域分解法188 5.2NExT法与ERA法192 5.2.1NExT法192 5.2.2ERA法195 5.3随机子空间方法202 5.4时变环境结构模态参数分析208 5.4.1主成分分析方法208 5.4.2神经网络建模方法212 5.5应用实例214 5.5.1结构健康监测系统概况214 5.5.2结构模态参数识别结果215 5.5.3环境因素与模态参数关系模型222 第6章结构损伤识别方法233 6.1基于模态参数的结构损伤识别方法233 6.1.1基于频率的结构损伤识别方法233 6.1.2基于振型的结构损伤识别方法235 6.2结构损伤识别信息融合方法238 6.2.1D-S证据理论238 6.2.2Bayesian推理241 6.2.3D-S证据理论与Bayesian推理的比较242 6.2.4基于信息融合的结构损伤识别方法246 6.3算例分析249 6.3.1桥梁有限元模型249 6.3.2结构损伤识别结果250 第7章结构模型修正255 7.1模态参数灵敏度方法255 7.1.1结构模态参数灵敏度255 7.1.2结构参数估计方法257 7.2Bayesian概率方法261 7.3应用实例264 7.3.1斜拉桥子结构特征264 7.3.2待修正结构参数268 7.3.3修正结构参数270 第8章车辆荷载极值模型与疲劳荷载谱273 8.1车辆荷载监测数据特征273 8.2随机过程概率模型与极值概率模型277 8.2.1滤过Poisson过程与极值概率模型277 8.2.2滤过Weibull过程与极值概率模型279 8.2.3平稳二项随机过程与极值概率模型279 8.2.4更新过程与极值概率模型281 8.3基于监测数据的车辆荷载极值建模与概率模型284 8.3.1截口分布概率模型284 8.3.2到达时间概率模型287 8.3.3极值概率模型数值计算方法288 8.3.4应用实例291 8.4基于监测数据的车辆疲劳荷载谱建模与模型298 8.4.1中国车辆分类298 8.4.2车辆疲劳荷载谱300 8.4.3车流量预测Logistic方法302 8.4.4应用实例303 第9章车辆荷载时空分布识别与建模307 9.1车辆荷载时空分布识别方法307 9.1.1二值图像形态学方法308 9.1.2车辆图像识别310 9.1.3车辆定位318 9.2车辆荷载随机场建模320 9.2.1马尔科夫随机场理论基础321 9.2.2联合树算法323 9.2.3车辆荷载随机场模型326 9.3应用实例328 9.3.1车辆荷载识别328 9.3.2车辆荷载建模330 第10章基于监测数据的主梁安全评定方法334 10.1应变监测数据特征334 10.1.1钢筋混凝土桥梁334 10.1.2钢桥337 10.2应变监测数据的解耦340 10.2.1趋势项应变解耦方法340 10.2.2混凝土收缩与徐变应变解耦方法343 10.3基于监测应变的结构承载力极限状态安全评定348 10.3.1关键构件荷载效应概率模型349 10.3.2关键构件抗力衰减模型358 10.3.3结构承载力极限状态可靠度评估方法359 10.3.4应用实例361 10.4基于监测应变的钢箱梁疲劳累积损伤评估方法365 10.4.1钢材疲劳累积损伤基础理论365 10.4.2钢箱梁构造细节疲劳寿命曲线368 10.4.3钢箱梁疲劳荷载效应谱计算方法370 10.4.4应用实例371 第11章基于监测数据的拉索安全评定方法373 11.1拉索时变索力识别方法374 11.1.1索力监测数据特征374 11.1.2时不变索力识别方法379 11.1.3时变索力识别方法381 11.1.4算例分析386 11.2承载力极限状态评估方法396 11.2.1拉索时变抗力模型396 11.2.2荷载效应极值模型402 11.2.3时变承载力极限状态安全评定404 11.2.4应用实例406 11.3基于S-N曲线的拉索疲劳累积损伤评估与寿命预测方法416 11.3.1高强钢丝疲劳寿命预测模型416 11.3.2拉索疲劳寿命预测模型418 11.3.3拉索疲劳荷载效应谱计算方法419 11.3.4应用实例420 11.4拉索疲劳累积损伤与寿命预测的断裂力学方法432 11.4.1高强钢丝断裂力学基本理论432 11.4.2高强钢丝腐蚀疲劳退化模型434 11.4.3拉索疲劳寿命评估方法437 第12章大跨度桥梁风和风效应监测数据分析439 12.1风与风效应监测系统设计方法439 12.2风场监测数据分析方法442 12.2.1平均风速442 12.2.2风速剖面443 12.2.3脉动风湍流强度与湍流积分尺度444 12.2.4脉动风速功率谱446 12.2.5阵风因子448 12.2.6脉动风的空间相关性449 12.2.7风场展向不均匀性449 12.3风压场与绕流场监测数据分析方法449 12.3.1风压场449 12.3.2绕流场451 12.4主梁涡激振动监测数据分析方法455 12.4.1涡激振动判别条件456 12.4.2涡激振动特征456 12.5主梁抖振响应监测数据分析方法458 12.6斜拉索涡激振动监测数据分析方法459 12.6.1平均风速的空间变换关系459 12.6.2斜拉索涡激振动起振风况分析459 12.6.3斜拉索涡激振动参与模态的估计方法461 12.7应用实例1462 12.7.1某大跨度悬索桥风与风效应监测系统462 12.7.2风场监测数据与分析466 12.7.3风压场与绕流场监测数据与分析472 12.7.4主梁涡激振动监测数据与分析477 12.7.5主梁抖振监测数据分析480 12.8应用实例2484 12.8.1某大跨度斜拉桥及斜拉索涡激振动监测系统概况484 12.8.2斜拉索涡激振动监测数据分析485 第13章结构地震反应监测数据分析与损伤识别489 13.1地震地面运动和结构地震反应监测数据分析489 13.1.1地震地面运动工程特性分析490 13.1.2结构地震损伤快速分析方法501 13.2基于数据驱动的结构非线性损伤定位方法508 13.2.1识别方法508 13.2.2算例分析511 13.3结构非线性模型参数识别方法520 13.3.1识别方法520 13.3.2算例分析522 13.4基于完备集的结构非线性模型及其参数识别方法530 13.4.1识别方法530 13.4.2算例分析533 13.5基于非完备集的结构非线性模型及其参数识别方法535 13.5.1识别方法535 13.5.2算例分析539 第14章结构健康监测的Benchmark模型543 14.1健康监测系统概况543 14.1.1工程概况543 14.1.2结构健康监测系统544 14.2结构修正有限元模型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拉索状态评估Benchmark问题551 14.3.1拉索索力监测数据551 14.3.2退役高强钢丝和斜拉索疲劳特性552 14.3.3拉索状态评估Benchmark问题554 14.4主梁损伤识别Benchmark问题554 14.4.1监测数据555 14.4.2检测数据558 14.4.3损伤识别Benchmark问题558 参考文献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
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