基于动力测试的桥梁结构损伤识别与综合评估理论研究
|
摘要
桥梁是交通运输系统的重要组成部分，桥梁结构的健康状态是交通运输系统正常运转的前提。桥梁结构在其服役期间，由于受到荷载、环境腐蚀及自然灾害等作用，损伤不可避免。一旦损伤达到一定程度，将导致桥梁结构发生破坏，对国民经济和人民的生命财产安全造成巨大的损失。因此，对桥梁结构进行健康监测研究，有重要的理论意义和实用价值。
结构损伤识别方法是桥梁结构健康监测的基础和重要组成部分，近年来人们一直试图寻找能够适用于桥梁结构的损伤识别方法。基于动力测试的结构损伤识别方法是目前国内外研究的热点。虽然该方法的研究已经取得了很大的进展，提出了很多的损伤识别理论和方法，但是由于受到人们认识水平、试验测试技术和现场条件的限制，使得基于动力测试的结构损伤识别的研究仍然进展缓慢，存在很多问题，目前也难以有效应用于工程实践。因此，研究能适合工程实际应用，并且损伤识别结果可靠准确的结构损伤识别方法具有十分重要的现实意义。本文在现有结构损伤识别方法的基础上，针对目前研究中存在的问题，对桥梁结构损伤识别方法进行了研究，主要内容如下：
1．在对现有传感器优化布置方法分析比较的基础上，针对传统方法的不足，提出了基于能量系数-有效独立的传感器优化布置方法。本文所提出的传感器优化布置方法是以反映节点自由度模态应变能的系数来修正反映最大线性无关的有效独立法，使传感器布置方案进一步综合优化。以简支钢桁架梁桥为数值算例对本文方法进行验证，所得的方案用多种准则进行评价的结果都较好，既能保证测量振型向量的正交性，又能保证扩阶振型的准确性，并且有较强的抗噪声能力，是一种适合桥梁结构的较为理想的传感器优化布置方法。
2．在讨论常用于结构损伤识别的几个指标的基础上，提出了基于灰关联曲率绝对差的损伤识别指标。该指标对结构损伤具有很高的灵敏度，而且仅需低阶模态信息即可获得很好的识别效果。同时，在灰关联曲率绝对差指标的基础上，本文采用分步识别法和多样本平均处理法，用来解决测试模态不完整和测试噪声问题。算例分析表明，本文提出的损伤指标能较好的识别出结构损伤，并具有一定的抗噪声能力。
3．在介绍反问题和模型修正方法的基础上，利用坐标模态保证准则和频率构建优化目标函数，提出了基于克隆选择算法的损伤识别方法，克服了传统优化算法在计算中碰到的由于梯度矩阵病态或奇异而使计算无法完成的现象，提高了计算效率。对简支钢桁架梁桥中设定的损伤进行了识别研究，结果表明本文提出的方法能明确的识别出结构的损伤位置及程度，而且具有较好的抗噪声能力，适合于实际工程应用。
4．提出了基于集成神经网络的结构多级损伤识别方法，采用分阶段改进参数作为网络的输入参数，分步实现对损伤的报警、定位和程度识别，克服了单个神经网络功能的单一局限性，增强了网络的泛化能力、降低了网络规模、减少了网络的训练样本集和训练时间。数值模拟的结果表明，本文提出的基于集成神经网络的结构多级损伤识别方法是有效的，而且具有一定的抗噪声的能力。
5．在金水沟特大桥竣工动载试验的基础上，确立了大桥的健康基本状态。依托铁道部科学研究院金水沟特大桥健康监测课题，结合金水沟特大桥自身结构特点，对其健康监测实施方案进行了设计。采用本文提出的三种损伤识别方法对金水沟特大桥主梁关键位置所设定的损伤进行无噪声情况下的识别研究，比较了三种方法的优缺点。
6．在介绍传统桥梁综合评估方法的基础上，将可拓理论应用于实际桥梁工程之中，提出了基于组合权重的区间可拓评价理论，建立了桥梁状态等级评定模型。工程实例表明，本文所提出的评价模型能够对桥梁状态进行客观、可靠的评价。
Bridge is one of the important compositions of the transportation system, and the healthy situation of the bridge structure is the basis for the well operating of the transportation system. During the service lives of the bridge structure, affected by the loads, environmental collisions and natural disaster, the damages of the bridge are unavoidable. Once the damages amount to some extent, the structure of the bridge will be destroyed, which will cause damages to the state economics and the people's lives and properties. Therefore, it is of theoretical significance and practical value to make researches on the health monitoring of the bridge structure.
Structural damage identification method is the basis and important part of the health monitoring of the bridge structure. In recent years, researchers tried a lot to find the damage identification method for the bridge structure. Structural damage identification method based on the dynamic test is the hot issue at home and abroad. Although the research of this method has made great progress and many damage identification methods and theories have been proposed, limited by the factors such as our understanding, the testing technique and the field condition, the structural damage identification method based on the dynamic test has not made any substantial progresses, and could not be in widely applied. Thus, to make research on the structural damage identification method which is proper in practice with accurate results is of great practical value. The thesis is based on the past studies and makes researches on the structural damage identification method aimed at the existed problems at present, and the contents are shown below:
1 .Based on the comparison analysis of the existing sensor placement optimization, the improved sensor placement optimization method based on the energy coefficient-effective independence method was proposed, which compensated the weaknesses of the traditional methods. Reflecting the coefficient of the node freedom modal strain energy, the proposed method can modify the effective independence reflecting the maximum linear independence, and further optimize the sensor placement designs. Taking the simply supported steel truss beam bridge as a numerical example, the results showed that the evaluations of the designs were good, and the method can ensure the orthogonality of the measurement vibration pattern vector, and can also ensure the accuracy of the expanded order vibration and has better anti-noise ability, which is an ideal method appropriate for the bridge structure.
2.Based on the traditional modal parameter structural damage identification, a damage identification index based on the grey relation curvature absolute difference was proposed. This index had high sensitivity to the structural damage and had good effects only in the need of the low-order modal information. Meanwhile, on the basis of the grey relation curvature absolute difference, the thesis suggested hierarchical identification method and multi-sample average dealing method to solve the incomplete of the measurement modal and the data noise. The numerical example illustrated that the proposed damage index could well reflect the structural damage and had better anti-noise ability.
3.On the basis of the reverse problem and model modification method, the coordinate modal assurance criterion and the frequency were used to establish the optimization object function, and the damage identification method based on clonal selection algorithm was proposed, which overcomes the difficulty that during the traditional algorithm when the gradient matrix was morbid or singular, and the calculation would not complete. The calculation efficiency was improved by the proposed method. The identification damage in the simply supported steel truss beam bridge was also studied and the result showed that the proposed method could identify the location and the extent of the damage, had better ability of anti-noise, and was especially proper for the engineering practices.
4.Multi-grade damage identification method based on the integrated neural networks was proposed, and the alerting, locating and extent identification were realized by step, which strengthened the generalization ability of the networks, made the networks scale smaller and reduced the training sample size and training time of the networks. The numerical simulation demonstrates that the proposed method is effective and has the anti-noise ability.
5.On the basis of the completion and dynamic load test of Jin Shui Gou Bridge, the health condition was established. Relying on the subject of Jin Shui Gou Bridge health monitoring of China Academy of Railway Science, and according to the characteristics of the bridge, the health monitoring implementation design of rigid frame-continuous beam structure was made. Three methods which were proposed in this paper were compared through the research on the damage identification of main beam of Jin Shui Gou Bridge.
6.0n the basis of the introduction of the traditional bridge comprehensive evaluation methods, the extension theory was applied in the engineering. The interval extension evaluation theory based on the combined weight was proposed and the bridge condition grade evaluation model was also established. The engineering case shows that the proposed model can make objective and reliable evaluations.
结构损伤识别方法是桥梁结构健康监测的基础和重要组成部分，近年来人们一直试图寻找能够适用于桥梁结构的损伤识别方法。基于动力测试的结构损伤识别方法是目前国内外研究的热点。虽然该方法的研究已经取得了很大的进展，提出了很多的损伤识别理论和方法，但是由于受到人们认识水平、试验测试技术和现场条件的限制，使得基于动力测试的结构损伤识别的研究仍然进展缓慢，存在很多问题，目前也难以有效应用于工程实践。因此，研究能适合工程实际应用，并且损伤识别结果可靠准确的结构损伤识别方法具有十分重要的现实意义。本文在现有结构损伤识别方法的基础上，针对目前研究中存在的问题，对桥梁结构损伤识别方法进行了研究，主要内容如下：
1．在对现有传感器优化布置方法分析比较的基础上，针对传统方法的不足，提出了基于能量系数-有效独立的传感器优化布置方法。本文所提出的传感器优化布置方法是以反映节点自由度模态应变能的系数来修正反映最大线性无关的有效独立法，使传感器布置方案进一步综合优化。以简支钢桁架梁桥为数值算例对本文方法进行验证，所得的方案用多种准则进行评价的结果都较好，既能保证测量振型向量的正交性，又能保证扩阶振型的准确性，并且有较强的抗噪声能力，是一种适合桥梁结构的较为理想的传感器优化布置方法。
2．在讨论常用于结构损伤识别的几个指标的基础上，提出了基于灰关联曲率绝对差的损伤识别指标。该指标对结构损伤具有很高的灵敏度，而且仅需低阶模态信息即可获得很好的识别效果。同时，在灰关联曲率绝对差指标的基础上，本文采用分步识别法和多样本平均处理法，用来解决测试模态不完整和测试噪声问题。算例分析表明，本文提出的损伤指标能较好的识别出结构损伤，并具有一定的抗噪声能力。
3．在介绍反问题和模型修正方法的基础上，利用坐标模态保证准则和频率构建优化目标函数，提出了基于克隆选择算法的损伤识别方法，克服了传统优化算法在计算中碰到的由于梯度矩阵病态或奇异而使计算无法完成的现象，提高了计算效率。对简支钢桁架梁桥中设定的损伤进行了识别研究，结果表明本文提出的方法能明确的识别出结构的损伤位置及程度，而且具有较好的抗噪声能力，适合于实际工程应用。
4．提出了基于集成神经网络的结构多级损伤识别方法，采用分阶段改进参数作为网络的输入参数，分步实现对损伤的报警、定位和程度识别，克服了单个神经网络功能的单一局限性，增强了网络的泛化能力、降低了网络规模、减少了网络的训练样本集和训练时间。数值模拟的结果表明，本文提出的基于集成神经网络的结构多级损伤识别方法是有效的，而且具有一定的抗噪声的能力。
5．在金水沟特大桥竣工动载试验的基础上，确立了大桥的健康基本状态。依托铁道部科学研究院金水沟特大桥健康监测课题，结合金水沟特大桥自身结构特点，对其健康监测实施方案进行了设计。采用本文提出的三种损伤识别方法对金水沟特大桥主梁关键位置所设定的损伤进行无噪声情况下的识别研究，比较了三种方法的优缺点。
6．在介绍传统桥梁综合评估方法的基础上，将可拓理论应用于实际桥梁工程之中，提出了基于组合权重的区间可拓评价理论，建立了桥梁状态等级评定模型。工程实例表明，本文所提出的评价模型能够对桥梁状态进行客观、可靠的评价。
Bridge is one of the important compositions of the transportation system, and the healthy situation of the bridge structure is the basis for the well operating of the transportation system. During the service lives of the bridge structure, affected by the loads, environmental collisions and natural disaster, the damages of the bridge are unavoidable. Once the damages amount to some extent, the structure of the bridge will be destroyed, which will cause damages to the state economics and the people's lives and properties. Therefore, it is of theoretical significance and practical value to make researches on the health monitoring of the bridge structure.
Structural damage identification method is the basis and important part of the health monitoring of the bridge structure. In recent years, researchers tried a lot to find the damage identification method for the bridge structure. Structural damage identification method based on the dynamic test is the hot issue at home and abroad. Although the research of this method has made great progress and many damage identification methods and theories have been proposed, limited by the factors such as our understanding, the testing technique and the field condition, the structural damage identification method based on the dynamic test has not made any substantial progresses, and could not be in widely applied. Thus, to make research on the structural damage identification method which is proper in practice with accurate results is of great practical value. The thesis is based on the past studies and makes researches on the structural damage identification method aimed at the existed problems at present, and the contents are shown below:
1 .Based on the comparison analysis of the existing sensor placement optimization, the improved sensor placement optimization method based on the energy coefficient-effective independence method was proposed, which compensated the weaknesses of the traditional methods. Reflecting the coefficient of the node freedom modal strain energy, the proposed method can modify the effective independence reflecting the maximum linear independence, and further optimize the sensor placement designs. Taking the simply supported steel truss beam bridge as a numerical example, the results showed that the evaluations of the designs were good, and the method can ensure the orthogonality of the measurement vibration pattern vector, and can also ensure the accuracy of the expanded order vibration and has better anti-noise ability, which is an ideal method appropriate for the bridge structure.
2.Based on the traditional modal parameter structural damage identification, a damage identification index based on the grey relation curvature absolute difference was proposed. This index had high sensitivity to the structural damage and had good effects only in the need of the low-order modal information. Meanwhile, on the basis of the grey relation curvature absolute difference, the thesis suggested hierarchical identification method and multi-sample average dealing method to solve the incomplete of the measurement modal and the data noise. The numerical example illustrated that the proposed damage index could well reflect the structural damage and had better anti-noise ability.
3.On the basis of the reverse problem and model modification method, the coordinate modal assurance criterion and the frequency were used to establish the optimization object function, and the damage identification method based on clonal selection algorithm was proposed, which overcomes the difficulty that during the traditional algorithm when the gradient matrix was morbid or singular, and the calculation would not complete. The calculation efficiency was improved by the proposed method. The identification damage in the simply supported steel truss beam bridge was also studied and the result showed that the proposed method could identify the location and the extent of the damage, had better ability of anti-noise, and was especially proper for the engineering practices.
4.Multi-grade damage identification method based on the integrated neural networks was proposed, and the alerting, locating and extent identification were realized by step, which strengthened the generalization ability of the networks, made the networks scale smaller and reduced the training sample size and training time of the networks. The numerical simulation demonstrates that the proposed method is effective and has the anti-noise ability.
5.On the basis of the completion and dynamic load test of Jin Shui Gou Bridge, the health condition was established. Relying on the subject of Jin Shui Gou Bridge health monitoring of China Academy of Railway Science, and according to the characteristics of the bridge, the health monitoring implementation design of rigid frame-continuous beam structure was made. Three methods which were proposed in this paper were compared through the research on the damage identification of main beam of Jin Shui Gou Bridge.
6.0n the basis of the introduction of the traditional bridge comprehensive evaluation methods, the extension theory was applied in the engineering. The interval extension evaluation theory based on the combined weight was proposed and the bridge condition grade evaluation model was also established. The engineering case shows that the proposed model can make objective and reliable evaluations.
引文
[1]丁大钧，蒋永生．土木工程总论[M]．北京：中国建筑工业出版社，1997
[2]刘效尧，蔡健，刘晖．桥梁损伤诊断[M]．北京：人民交通出版社，2002
[3]周修南，刘圣根．圣水大桥倒塌的教训[J]．钢结构，1997，V01．12，No．35
[4]荆龙江．预应力混凝土斜拉桥损伤识别理论及应用研究[D]．浙江杭州：浙江大学博士学位论文，2007
[5]李雪艳．结构损伤识别方法论述[C]．第七届全国声动理论及应用学术会议论文集，广东佛山，1999
[6]郑文．状态监测及故障诊断技术在采油平台上的应用[J]．广州大学学报，2000，14(3)：6～9
[7]谢强，薛松涛．土木工程结构健康监测的研究状况与进展[J]．中国科学基金，2001，5：285～288
[8]刘继承，周传荣．一个基于优化的有限元模型修正方法[J]．冲击与振动，2003，22(2)：33～34
[9]夏品奇，James M W Browrljohn．斜拉桥有限元建模与模型修正[J]．振动工程学报，2003，16(2)：219～223
[10]蒋华．基于静力测试数据的桥梁结构损伤识别与评定理论研究[D]．四川成都：西南交通大学博士学位论文，2005
[11]杜思义．基于频率变化与单元摄动理论的结构损伤识别方法研究[D]．重庆：重庆大学博士学位论文，2005
[12]向天宇，赵人达，刘海波．基于静力测试数据的预应力混凝土连续梁结构损伤识别[J]．土木工程学报，2003，36(11)：79～82
[13]蔡晶，吴智深，李兆霞．静力荷载作用下结构参数识别及状态评估的统计分析[J]．工程力学，2004，21(6)：76～83
[14]张清华、李乔、唐亮．斜拉桥结构损伤识别的概率可靠度法[J]．铁道学报．2005，27(3)：70～75
[15]崔飞，袁万城．基于静态应变及位移测量的结构损伤识别法[J]．同济大学学报，2000，28(1)：5～8
[16]Sanayei M,Saletnik M.J.Parametre estimation of structures from static strain measurements Ⅰ:Formulation[J].Journal of structural engineering,1996,122(5):555～562
[17]Banan M R,Hjelmstad K D.Parametre estimation of structures from static response Ⅰ:computational aspects[J].Journal of structural Engineering,1994,120(11):3243～3258
[18]Hajela P,Soero F J.Recent developments in damage detection based on system indentification metheods[J].Structural Optimization, 1990(2):1～10
[19]张启伟，范立础．利用动静力测量数据的桥梁结构损伤识别[J]．同济大学学报，1998，26：528～532
[20]徐祖年，王柏生．基于振动测试的大跨桥梁损伤检测[J]．合肥工业大学学报(自然科学版)，2001，24(5)：945～949
[21]Wollf T. Fault detection in structures from changes in their modal parameters[J].Proceedings of 7th IMAC,1989:87～94
[22]Fox C H J.The location of defects in structures:A comparison of the use of natural frequency and mode shaped data[J].Proceedings of 1Oth IMAC,1992:522～528
[23]Jenks W G.Squids for nondestructive evaluation[J].Journal of Physics & Applied Physics,1997,30(3):293～323
[24]Ratcliffe C P,Damage detection using a modified Laplacian operator on mode shape data[J].Journal of Sound and Vibration,1998, 204(3):505～517
[25]Pandey A K,Biswas M,Samman M M.Damage detection from changes in curvature mode shape[J].Journal of Sound and Vibration,1991, 145(2):321～332
[26]李德葆，陆秋海，秦权．承弯结构的曲率模态分析[J]．清华大学学报(自然科学版)，2002，42(2)：224～227
[27]邓焱．梁及桥梁应变模态与损伤测量的新方法[J]．清华大学学报(自然科学版)，2000，40(11)：123～127
[28]郑明刚，刘天雄，朱继梅等．曲率模态在桥梁状态监测中的应用[J]．振动与冲击，2000，19(2)：81～83
[29]Salawn O S.Damage location using vibration mode shapes[C].Proceedings of 12th IMAC,1994:933～939
[30]Pandey AK,Biswas M.Damage detection from changes in flexibility[J].Journal of Sound and Vibration,1994,169(1):3～17
[31]伊娟．基于柔度改变的连续梁桥损伤诊断研究[J]．华东公路，2001(3)： 25～27
[32]慕宝晖，邬瑞锋，蔡贤辉，李桂华．一种桁架结构损伤识别的柔度阵法[J]．计算力学学报，2001，18(1)：42～47
[33]董聪，范立础，陈肇元．结构智能健康诊断的理论与方法[J]．中国铁道科学，2002，23(1)：11～24
[34]Huang T J.Structural damaged detection using energy transfer ratio[C].Proceedings of 14th IMAC,1996:26～132
[35]Liang Z.On detection of damage location of bridges[C].Proceedings of IMAC,1996:308～312
[36]Ceasar J C.Damage location in a space truss model using modal strain energy[C].Proceedings of 15th IMAC,Florida,1997:1786～1792
[37]史治宇．结构破损定位的单元模态应变能变化率法[J]．振动工程学报，1998，11(3)：357～360
[38]Venkatasubramanian V,Chan K.A neural network methodology for process fault diagnosis.Journal of AICHE,1989,35(12):1993～2002
[39]Kirkegaard P H,Rytter A.The use of neural networks for damage detection and location in a steel member[J].Neural Networks and Combinatorial Optimization in Civil and Structural Engineering, Edinburgh,U K,1993:1～9
[40]Wu X,Ghaboussi J,Garrett J H.Use of neural networks in detection of structural damage[J].Computers & Structures,1992,42(4):649～659
[41]管迪华．模态分析技术[M]．北京：清华大学出版社，1996
[42]Pandy P C,Barai S V.Multilayer perceptron in damage detection of bridge structural[J].Computers & Structures,1995,54(4):597～608
[43]Elkordy M F,Chang K C,Lee 6C.Application of neural networks in vibrational signature analysis.Journal of Engineering Mechanics,1994, 120(2):251～264
[44]Chen S S,Kim S.Neural network based signal monitoring in a smart structural system.Smart Structures and Materials 1994:Smart Sensing, Processing,and Instrumentation,J S Sirkis(ed.),SPIE,1994,2191:176～186
[45]Mitsuru Nakamura,Masrisami F,Anatassios G.etal.A method for nonparametric damage detection through the use of neural networks. Earthquake Engineering and Structural Dynamics,1998,27:997～1010
[46]徐宜桂，史铁林，杨叔子．基于神经网络的结构动力模型修改和破损诊断研究[J]．振动工程学报，1997，10(1)：8～12
[47]陆秋海等．利用模态试验参数识别结构损伤的神经网络法[J]．工程力学，1999，16(1)：35～42
[48]韩小云，刘瑞言．基于神经网络和模糊综合评判的梁故障诊断研究[J]．国防科技大学学报，1996，18(1)：17～22
[49]王柏生，倪一清等．框架结构连接损伤识别神经网络输入参数的确定[J]．振动工程学报，2000，13(1)：138～141
[50]姜绍飞．基于神经网络的结构优化与损伤检测[M]．北京：科学出版社，2002
[51]Dang NH.Embedded systems for the assessment of structural damage[C].NED for Health Monitoring and Diagnostics,San Diego,2002:4701～4717
[52]Amaravadi V.Structural integrity monitoring of composite patch repairs using wavelet analysis and neural network[C].NED for Health Monitoring and Diagnostics,San Diego,2002:4701～4718
[53]Wang P,Vachtsevanos G.Fault prognosis using dynamic wavelet neural networks[C].Maintenance And Reliability Conference,MARCON 99,Gatlinburg, May 10～12,1999.
[54]Vachtsevanos G,Wang P.A Wavelet neural network framework for diagnostics of complex engineered systems[C].Maintenance and Reliability Conference, MARCON 98,Knoxville,May 12～14,1998.
[55]Vachtsevanos G,Wang P,Khiripet N. Prognostication:algorithms and performance assessment methodologies[C]. ATP Fall National Meeting ConditionBased Maintenance Workshop,San Jose,California,November 15～ 17,1999
[56]Sun Z,Chang C C.Structural damage assessment based on wavelet packet transform[J].Journal of Structural Engineering,ASCE,2002,128(10): 1354～1361.
[57]Andenbrandt C A.An Extension the Theory of Convergence and a Proof of the Time Complexity of Genetic Algorithms.In 1999,[343]:53～68
[58]Hesser J,Manner R.Investigation of the M-Heuristic for Otimal Mutation Probability.In 1992,[340]:115～125
[59]Fogarty T C.Varying the Probability of Mutation in the Genetic Algorithms. In 1989,[335]:104～109
[60]Srinivas M,Patnaik L M.Adaptive Probabilities of Crossever and Mutation in Gas[C].IEEE Tans on SMC,1994,24(4):656～667
[61]Mares C,Surace C.An application of gorithms to identify damage in elastic structures[J].Journal of Sound and Vibration,1996,195(2):195～215
[62]Frisewell M I,Penny JET,Garvey S D.A combined genetic and eigensensitivity algorithm for the location of damage in struvtures[J]. Computers & Structures,1998,69(5):547～556
[63]Harrison C,Butler R.Locating delaminations in composite beams using gradient techniques and a genetical gorithm[J].AIAA Journal,2001,39(7): 1383～1389
[64]程远胜，区达光，谭国焕等．基于分级遗传算法的结构损伤识别方法[J]．华中科技大学学报(自然科学版)，2002，30(8)：73～75
[65]冯新．土木工程中结构识别方法的研究[D]．辽宁大连：大连理工大学博士学位论文，2002
[66]曹树谦，张文德，萧龙翔．振动结构模态分析[M]．天津：天津大学出版社，2001
[67]李兆霞，李爱群，陈鸿天．大跨桥梁结构以健康监测和状态评估为目标的有限元模拟[J]．东南大学学报，2003，33(5)：562～273
[68]徐士代．环境激励下工程结构模态参数识别[D]．江苏南京：东南大学博士学位论文，2006
[69]黄天立．结构系统和损伤识别的若干方法研究[D]．上海：同济大学博士学位论文，2007
[70]公茂盛．基于强震记录的结构模态参数识别与应用研究[D]．黑龙江哈尔滨：中国地 震局工程力学研究所博士学位论文，2005
[71]韩大建，谢峻．大跨度桥梁健康监测技术的近期研究进展[J]．桥梁建设，2000，6：69～73
[72]彭涛．基于传感器最优配置的故障检测方法研究[D]．湖南长沙：中南大学博士学位论文，2005
[73] Fu-Kuo Chang. The International Workshop on Structural Health Monitoring(4nd)Held in Stanford,California on September 15～17,2003
[74]刘福强，张令弥．作动器／传感器优化配置的研究进展[J]．力学进展，2000(4)：506～516
[75]Kammer D C. Sensor placement for on-orbit modal identification and correlation of large space structures[J].Journal of Guidance:Control and dynamics,1991,14(2):251～259
[76]李国强，李杰．工程结构动力检测理论与应用[M]．北京：科学出版社，2002
[77]Shi Z Y,Law S S,Zhang L M.Optimizing sensor placement for structural damage detection[J].Journal of Engrg Mech,ASCE,2000,126(11):1173～1179
[78]王山山，任青文．结构模态参数测试的传感器优化布置研究[J]．动力学与控制学报，2005，3(1)：67～71
[79]G Heo,M L Wang,D Satpathi.Optimal transducer placement for health monitoring of long span bridge[J].Soil Dynamic and Earthquake Engineering, 1997, 16:496～502
[80]吴子燕，代凤娟，宋静等．损伤检测中的传感器优化布置方法研究[J]．西北工业大学学报，2007，25(4)：504～507
[81]Guyan R J.Reduction of Stiffness and Mass Matrices[J].AIAA Journal, 1965, 3(2),380
[82]O'Callahan.A Processing for an Improved Reduced System(IRS)Model[C]. Proceedings of 7th International Modal Analysis Conference.1989,17～21
[83]O'Callahan,Avitabile P,Riemer R.System Equivalent Reduction Expansion Process[C].Proceedings of 7th International Modal Analysis Conference, 1989,29～37
[84]K F Alvin. Finite Element Model Update via Bayesian Estimation and Minimization of Dynamic Residuals[J].AIAA Journal,1997,35(5):879～886
[85]S S Law,Z Y Shi,L M Zhang.Structural damage detection from incomplete and noisy modal test data[J].Journal of Engineering Mechanics.ASCE, 1998,124(11):1280～1288
[86]张德文，魏阜旋．模型修正与破损诊断[M]．北京：科学出版社，1999
[87]谢峻．基于振动的桥梁结构损伤识别方法研究[D]．广东广州：华南理工大学博士学位论文，2003
[88]郭国会．桥梁结构动力损伤诊断方法研究[D]．湖南长沙：湖南大学博士学位论文，2001
[89]董晓马．智能结构的损伤诊断及传感器优化配置研究[D]．江苏南京：东南大学博士学位论文，2006
[90]王山山．基于振动理论的水工结构无损检测技术研究[D]．江苏南京：河海大学博士学位论文，2005
[91]李德葆，陆秋海．实验模态分析及其应用[M]．北京：科学出版社，2001
[92]B.Jaishi,W.X.Ren.Structural finite element model updating using ambient vibration test results[J].Journal of Structural Engineering,ASCE, 131(4),617～628,2005
[93]A.K.Garg,D.Roy Mahapatra,S.Suresh,etal.Estimation of composite damage model parameters using spectral finite element and neural network[J]. Composites Science and Technology,2004(64):2477～2493
[94]董聪．现代结构系统可靠性理论及其应用[M]．北京：科学出版社，2001
[95]邓众，严普强．桥梁结构损伤的振动模态检测[J]．振动、测试与诊断，1999，19(3)：157～163
[96]张德文，魏阜旋．模型修正与破损诊断[M]．北京：科学出版社，1999
[97]唐小兵．结构损伤识别与数值模拟[D]．湖北武汉：武汉理工大学博士学位论文，2004
[98]史治宇，罗绍湘，张令弥．结构破损定位的单元模态应变能变化率法[J]．振动工程 学报，1998，11(3)：356～360
[99]邓聚龙．灰色系统基本方法[M]．武汉：华中工学院出版社，1987
[100]Chang T.C,Lin S.J.Grey relationanalysis of carbon dioxide emissions from industrial production and energy uses in Taiwan[J]. Journal of Environmental Management,1999,56(4):247～257
[101] Liang R.H. Application of grey relation analysis to hydroelectric generation scheduling.International Journal of Electrical Power & Energy Systems[J].1999,21(5):357～364
[102]Wang S.X,Lin C.R.The Analysis of seismic data structure and oil and gas prediction[J].Applied Geophysics,2004,1(2):12～17
[103]吕锋，刘翔，刘泉．七种灰色系统关联度的比较研究[J]．武汉工业大学学报，2000，22(2)：41～43
[104]雨宫好文，佐藤幸男．信号处理入门[M]．北京：科学出版社，2000
[105]Farrar CR,Cone KM.Vibration testing of the 1-40 bridge before and after the introduction of damage[J].Proceedings of the 13th international Modal Analysis Conference,1995(1):203～209
[106]Doebling S W,Farrar C R,Prime M B,etal.Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics:A Literature Review. Los Alamos National Laboratory Report,LA-13070-MS,1996
[107]黄光远，刘小军．数学物理反问题[M]．济南：山东科学技术出板社，1993
[108] Davies A.R. On the maximum likelihood regularization of fredholm convolution equation of first kind.In:Treatment of Integral equation by numerical methods.New York:Academic Press,1982:95～105
[109]魏培君，章梓茂．弹性动力学反问题的不适定性及其广义解[J]．力学与实践，2001，23(3)：43～45
[110]赵红兵．基于能量测试和优化方法的结构单元损伤识别[D]．辽宁大连：大连理工大学博士学位论文，2005
[111]H.Baruh,S.Ratan.Damage detection in the flexible structures[J].Sound and Vibration,1993,166(1):21～30
[112]J.M.Ricles,J.B.Kosmatka.Damage detection in elastic structures using vibratory residual forces and weighted sensitivity[J].AIAA J.,1992, 30(9):2310～2316
[113]张清华．基于概率可靠度的结构损伤识别理论研究及应用[D]．四川成都：西南交通大学博士学位论文，2006
[114]吴小平．复杂桥梁结构综合监测系统开发研究[D]．浙江杭州：浙江大学博士学位论文，2005
[115]刘东，寥日东，左正兴．分析／试验模型相关及修正技术若干问题[J]．强度与环境，2003，30(1)：23～30
[116]袁颖．桥梁结构损伤识别方法的相关问题研究[D]．辽宁大连：大连理工大学博士学位论文，2005
[117]Friswell M I,Penny J E T,Garvey S D.A combined genetic and eigen sensitivity algorithm for the location of damage in structures[J]. Computers & Structures,1998,69(5):547～556
[118]Koh C G,Chen Y F,Liaw C Y.A hybrid computational strategy for identification of structural parameters.Computers and Structures,2003, (81):107～117
[119]Chou J H,Ghaboussi J.Genetic algorithm in structural damage detection. Computers and Structures,2001,(79):1335～1353
[120]邹大力．基于计算智能的结构损伤识别研究[D]．辽宁大连：大连理工大学博士学位论文，2005
[121]潘正君，康立山，陈毓屏．演化计算[M]．北京：清华大学出版社，1998
[122]陈国良，王煦法，庄镇泉，王东生．遗传算法及其应用[M]．北京：人民邮电出版社，1996
[123]周明，孙树栋．遗传算法原理及应用[M]．北京：国防工业出版社，1999
[124]云庆夏．进化算法[M]．北京：冶金工业出版社，2000
[125]Farmer,J.D.,Packard,N.H.& Perelson,A.S.(1986), “The Immune System, Adaptation,and Machine Learning.”[J],Physica 22D,pp 187～204
[126] Thomas P.Runarsson, Xin Yao. Stochastic Ranking for Constrained Evolutionary Optimization.IEEE Transactions on Evolutinary Computation, 2000，Vol．4，No．3，284～294
[127]杜海峰，焦李成，公茂果，刘若辰．免疫克隆选择算法与进化算法[M]．西安：西安电子科技大学出版社，2005
[128]L.N.De Castro, F.J.Von Zuben. The Clonal Selection Algorithm with Engineering Applications.In:D.Whitley,D.E.Goldberg,E.Cant(?)-Paz,L. Spector,I.C.Parmee,H.Beyer.Proceedings of the Genetic and Evolutionary Computation Conference.Morgan Kaufmann,Las Vegas:2000,36～37
[129]焦李成，杜海峰，刘芳，公茂果．免疫优化计算、学习与识别[M]．北京：科学出版社，2006
[130]于善谦，王洪海．免疫学导论[M]．北京：高等教育出版社，1999
[131]杜海峰，焦李成，公茂果，刘若辰．一种免疫克隆选择网络及其学习算法[J]．模式识别与人工智能，2005，18(2)，198～204
[132]Mroz Z,Lekszycki T.Identification of Damage in Structures Using Parameter Dependent Modal Response.Proceedings of ISMA25,Noise and Vibration Engineering,Leuven,elgium,2000
[133]O.S Salawu.Detection of structural damage through changes in frequency: a review[J].Engineering Structures.1997,19(9):718～723
[134]马宏伟，杨桂通．结构损伤探测的基本方法和研究进展[J]．力学进展，1999，29(4)：13～27
[135]靳蕃．神经计算智能基础原理·方法[M]．成都：西南交通大学出版社，2000
[136]Simon Haykin．神经网络原理[M]．北京：机械工业出版社，2003
[137]陈守余，周梅春．人工神经网络模拟实现与应用[M]．武汉：中国地质大学出版社，2000
[138]李士勇．模糊控制·神经控制和智能控制[M]．哈尔滨：哈尔滨工业出版社，1996
[139]何振亚．神经智能[M]．长沙：湖南科学技术出版社，1997
[140]Hecht-NielSen R.Counter-propagation network[A].Proc.of International Conference on Nueral networks,1987,19～32
[141]袁旭东．基于不完备信息土木工程结构损伤识别方法研究[D]．辽宁大连：大连理工大学博士学位论文，2005
[142]Hansen L K,Salamon P.Neural network ensembles[J].IEEE Trans Pattern Analysis and Machine Intelligence,1990,12(10):993～1001
[143]周开利，康耀红．神经网络模型及其MATLAB仿真程序设计[M]．北京：清华大学出版社，2005
[144]王若林．桥梁实时在线检测与健康监测若干问题研究[D]．湖北武汉：武汉大学博士学位论文，2005
[145]金水沟特大桥静动载试验报告[R]．铁道部科学研究院，2005
[146]金水沟特大桥健康监测方案设计[R]．铁道部科学研究院，2007
[147]廖旭．大跨度连续刚构典型病害及加固对策研究[D]．四川成都：西南交通大学硕士学位论文，2005
[148]俞峰，杨成梧．物元分析方法在地下水质量综合评判中的应用[J]．水资源与水工程学报，2005，16(2)：35～38
[149]蔡文．物元模型及其应用[M]．北京：科学技术文献出版社，1994
[150]杨文渊，徐犇．桥梁维修与加固[M]．北京：人民交通出版社，1989
[151]施洲．基于动力测试的桥梁结构损伤识别及性能评定理论与应用研究[D]．四川成都：西南交通大学博士学位论文，2006
[152]郭彤，李爱群，李兆霞，韩晓林．大跨桥梁结构状态评估方法研究进展[J]．东南大学学报(自然科学版)，2004，34(5)：699～704
[153]JTJ H12-2003，公路养护技术规范[S]
[154]胡宝清．区域水环境质量的区间可拓评价方法及应用[J]．中国工程科学，2001，3(6)：53～56
[155]杨雅勋，李子青，郝宪武．组合赋权灰关联法在桥梁加固方案优选中的应用[J]．郑州大学学报(工学版)，2006，27(4)：84～88
[156]宋光兴，邹平．多属性群决策中决策者权重的确定方法[J]．系统工程，2001，19(4)：84～89
[157]王成，陈中文，饶从军．科研基金项目评审的模糊群决策方法[J]．武汉理工大学学报(信息与管理工程版)，2006，28(1)：124～126
[158]马亚丽，王东炜，张爱林．在役桥梁结构健康等级的多级模糊综合评判[J]．北京工业大学学报，2005，31(1)：36～40
[159]徐荣桥．结构分析的有限元法与MATLAB程序设计[M]．北京：人民交通出版社，2006
[160]王齐，胡晓．MATLAB在振动信号处理中的应用[M]．北京：中国水利水电出版社， 2006
[161]钟珞，饶文碧，邹承明．人工神经网络及其融合应用技术[M]．北京：科学出版社，2007
[162]赵国藩，金伟良，贡金鑫．结构可靠度理论[M]．北京：中国建筑工业出版社，2000
[163]许树柏．层次分析法原理[M]．天津：天津大学出版社，1988
[164]陈卫东，蔡荫林，于诗源．工程优化方法[M]．哈尔滨：哈尔滨工程大学出版社，2006
[165]卢险峰．最优化方法应用基础[M]．上海：同济大学出版社，2003
[166]粟塔山．最优化计算原理与算法程序设计[M]．长沙：国防科技大学出版社，2001
[2]刘效尧，蔡健，刘晖．桥梁损伤诊断[M]．北京：人民交通出版社，2002
[3]周修南，刘圣根．圣水大桥倒塌的教训[J]．钢结构，1997，V01．12，No．35
[4]荆龙江．预应力混凝土斜拉桥损伤识别理论及应用研究[D]．浙江杭州：浙江大学博士学位论文，2007
[5]李雪艳．结构损伤识别方法论述[C]．第七届全国声动理论及应用学术会议论文集，广东佛山，1999
[6]郑文．状态监测及故障诊断技术在采油平台上的应用[J]．广州大学学报，2000，14(3)：6～9
[7]谢强，薛松涛．土木工程结构健康监测的研究状况与进展[J]．中国科学基金，2001，5：285～288
[8]刘继承，周传荣．一个基于优化的有限元模型修正方法[J]．冲击与振动，2003，22(2)：33～34
[9]夏品奇，James M W Browrljohn．斜拉桥有限元建模与模型修正[J]．振动工程学报，2003，16(2)：219～223
[10]蒋华．基于静力测试数据的桥梁结构损伤识别与评定理论研究[D]．四川成都：西南交通大学博士学位论文，2005
[11]杜思义．基于频率变化与单元摄动理论的结构损伤识别方法研究[D]．重庆：重庆大学博士学位论文，2005
[12]向天宇，赵人达，刘海波．基于静力测试数据的预应力混凝土连续梁结构损伤识别[J]．土木工程学报，2003，36(11)：79～82
[13]蔡晶，吴智深，李兆霞．静力荷载作用下结构参数识别及状态评估的统计分析[J]．工程力学，2004，21(6)：76～83
[14]张清华、李乔、唐亮．斜拉桥结构损伤识别的概率可靠度法[J]．铁道学报．2005，27(3)：70～75
[15]崔飞，袁万城．基于静态应变及位移测量的结构损伤识别法[J]．同济大学学报，2000，28(1)：5～8
[16]Sanayei M,Saletnik M.J.Parametre estimation of structures from static strain measurements Ⅰ:Formulation[J].Journal of structural engineering,1996,122(5):555～562
[17]Banan M R,Hjelmstad K D.Parametre estimation of structures from static response Ⅰ:computational aspects[J].Journal of structural Engineering,1994,120(11):3243～3258
[18]Hajela P,Soero F J.Recent developments in damage detection based on system indentification metheods[J].Structural Optimization, 1990(2):1～10
[19]张启伟，范立础．利用动静力测量数据的桥梁结构损伤识别[J]．同济大学学报，1998，26：528～532
[20]徐祖年，王柏生．基于振动测试的大跨桥梁损伤检测[J]．合肥工业大学学报(自然科学版)，2001，24(5)：945～949
[21]Wollf T. Fault detection in structures from changes in their modal parameters[J].Proceedings of 7th IMAC,1989:87～94
[22]Fox C H J.The location of defects in structures:A comparison of the use of natural frequency and mode shaped data[J].Proceedings of 1Oth IMAC,1992:522～528
[23]Jenks W G.Squids for nondestructive evaluation[J].Journal of Physics & Applied Physics,1997,30(3):293～323
[24]Ratcliffe C P,Damage detection using a modified Laplacian operator on mode shape data[J].Journal of Sound and Vibration,1998, 204(3):505～517
[25]Pandey A K,Biswas M,Samman M M.Damage detection from changes in curvature mode shape[J].Journal of Sound and Vibration,1991, 145(2):321～332
[26]李德葆，陆秋海，秦权．承弯结构的曲率模态分析[J]．清华大学学报(自然科学版)，2002，42(2)：224～227
[27]邓焱．梁及桥梁应变模态与损伤测量的新方法[J]．清华大学学报(自然科学版)，2000，40(11)：123～127
[28]郑明刚，刘天雄，朱继梅等．曲率模态在桥梁状态监测中的应用[J]．振动与冲击，2000，19(2)：81～83
[29]Salawn O S.Damage location using vibration mode shapes[C].Proceedings of 12th IMAC,1994:933～939
[30]Pandey AK,Biswas M.Damage detection from changes in flexibility[J].Journal of Sound and Vibration,1994,169(1):3～17
[31]伊娟．基于柔度改变的连续梁桥损伤诊断研究[J]．华东公路，2001(3)： 25～27
[32]慕宝晖，邬瑞锋，蔡贤辉，李桂华．一种桁架结构损伤识别的柔度阵法[J]．计算力学学报，2001，18(1)：42～47
[33]董聪，范立础，陈肇元．结构智能健康诊断的理论与方法[J]．中国铁道科学，2002，23(1)：11～24
[34]Huang T J.Structural damaged detection using energy transfer ratio[C].Proceedings of 14th IMAC,1996:26～132
[35]Liang Z.On detection of damage location of bridges[C].Proceedings of IMAC,1996:308～312
[36]Ceasar J C.Damage location in a space truss model using modal strain energy[C].Proceedings of 15th IMAC,Florida,1997:1786～1792
[37]史治宇．结构破损定位的单元模态应变能变化率法[J]．振动工程学报，1998，11(3)：357～360
[38]Venkatasubramanian V,Chan K.A neural network methodology for process fault diagnosis.Journal of AICHE,1989,35(12):1993～2002
[39]Kirkegaard P H,Rytter A.The use of neural networks for damage detection and location in a steel member[J].Neural Networks and Combinatorial Optimization in Civil and Structural Engineering, Edinburgh,U K,1993:1～9
[40]Wu X,Ghaboussi J,Garrett J H.Use of neural networks in detection of structural damage[J].Computers & Structures,1992,42(4):649～659
[41]管迪华．模态分析技术[M]．北京：清华大学出版社，1996
[42]Pandy P C,Barai S V.Multilayer perceptron in damage detection of bridge structural[J].Computers & Structures,1995,54(4):597～608
[43]Elkordy M F,Chang K C,Lee 6C.Application of neural networks in vibrational signature analysis.Journal of Engineering Mechanics,1994, 120(2):251～264
[44]Chen S S,Kim S.Neural network based signal monitoring in a smart structural system.Smart Structures and Materials 1994:Smart Sensing, Processing,and Instrumentation,J S Sirkis(ed.),SPIE,1994,2191:176～186
[45]Mitsuru Nakamura,Masrisami F,Anatassios G.etal.A method for nonparametric damage detection through the use of neural networks. Earthquake Engineering and Structural Dynamics,1998,27:997～1010
[46]徐宜桂，史铁林，杨叔子．基于神经网络的结构动力模型修改和破损诊断研究[J]．振动工程学报，1997，10(1)：8～12
[47]陆秋海等．利用模态试验参数识别结构损伤的神经网络法[J]．工程力学，1999，16(1)：35～42
[48]韩小云，刘瑞言．基于神经网络和模糊综合评判的梁故障诊断研究[J]．国防科技大学学报，1996，18(1)：17～22
[49]王柏生，倪一清等．框架结构连接损伤识别神经网络输入参数的确定[J]．振动工程学报，2000，13(1)：138～141
[50]姜绍飞．基于神经网络的结构优化与损伤检测[M]．北京：科学出版社，2002
[51]Dang NH.Embedded systems for the assessment of structural damage[C].NED for Health Monitoring and Diagnostics,San Diego,2002:4701～4717
[52]Amaravadi V.Structural integrity monitoring of composite patch repairs using wavelet analysis and neural network[C].NED for Health Monitoring and Diagnostics,San Diego,2002:4701～4718
[53]Wang P,Vachtsevanos G.Fault prognosis using dynamic wavelet neural networks[C].Maintenance And Reliability Conference,MARCON 99,Gatlinburg, May 10～12,1999.
[54]Vachtsevanos G,Wang P.A Wavelet neural network framework for diagnostics of complex engineered systems[C].Maintenance and Reliability Conference, MARCON 98,Knoxville,May 12～14,1998.
[55]Vachtsevanos G,Wang P,Khiripet N. Prognostication:algorithms and performance assessment methodologies[C]. ATP Fall National Meeting ConditionBased Maintenance Workshop,San Jose,California,November 15～ 17,1999
[56]Sun Z,Chang C C.Structural damage assessment based on wavelet packet transform[J].Journal of Structural Engineering,ASCE,2002,128(10): 1354～1361.
[57]Andenbrandt C A.An Extension the Theory of Convergence and a Proof of the Time Complexity of Genetic Algorithms.In 1999,[343]:53～68
[58]Hesser J,Manner R.Investigation of the M-Heuristic for Otimal Mutation Probability.In 1992,[340]:115～125
[59]Fogarty T C.Varying the Probability of Mutation in the Genetic Algorithms. In 1989,[335]:104～109
[60]Srinivas M,Patnaik L M.Adaptive Probabilities of Crossever and Mutation in Gas[C].IEEE Tans on SMC,1994,24(4):656～667
[61]Mares C,Surace C.An application of gorithms to identify damage in elastic structures[J].Journal of Sound and Vibration,1996,195(2):195～215
[62]Frisewell M I,Penny JET,Garvey S D.A combined genetic and eigensensitivity algorithm for the location of damage in struvtures[J]. Computers & Structures,1998,69(5):547～556
[63]Harrison C,Butler R.Locating delaminations in composite beams using gradient techniques and a genetical gorithm[J].AIAA Journal,2001,39(7): 1383～1389
[64]程远胜，区达光，谭国焕等．基于分级遗传算法的结构损伤识别方法[J]．华中科技大学学报(自然科学版)，2002，30(8)：73～75
[65]冯新．土木工程中结构识别方法的研究[D]．辽宁大连：大连理工大学博士学位论文，2002
[66]曹树谦，张文德，萧龙翔．振动结构模态分析[M]．天津：天津大学出版社，2001
[67]李兆霞，李爱群，陈鸿天．大跨桥梁结构以健康监测和状态评估为目标的有限元模拟[J]．东南大学学报，2003，33(5)：562～273
[68]徐士代．环境激励下工程结构模态参数识别[D]．江苏南京：东南大学博士学位论文，2006
[69]黄天立．结构系统和损伤识别的若干方法研究[D]．上海：同济大学博士学位论文，2007
[70]公茂盛．基于强震记录的结构模态参数识别与应用研究[D]．黑龙江哈尔滨：中国地 震局工程力学研究所博士学位论文，2005
[71]韩大建，谢峻．大跨度桥梁健康监测技术的近期研究进展[J]．桥梁建设，2000，6：69～73
[72]彭涛．基于传感器最优配置的故障检测方法研究[D]．湖南长沙：中南大学博士学位论文，2005
[73] Fu-Kuo Chang. The International Workshop on Structural Health Monitoring(4nd)Held in Stanford,California on September 15～17,2003
[74]刘福强，张令弥．作动器／传感器优化配置的研究进展[J]．力学进展，2000(4)：506～516
[75]Kammer D C. Sensor placement for on-orbit modal identification and correlation of large space structures[J].Journal of Guidance:Control and dynamics,1991,14(2):251～259
[76]李国强，李杰．工程结构动力检测理论与应用[M]．北京：科学出版社，2002
[77]Shi Z Y,Law S S,Zhang L M.Optimizing sensor placement for structural damage detection[J].Journal of Engrg Mech,ASCE,2000,126(11):1173～1179
[78]王山山，任青文．结构模态参数测试的传感器优化布置研究[J]．动力学与控制学报，2005，3(1)：67～71
[79]G Heo,M L Wang,D Satpathi.Optimal transducer placement for health monitoring of long span bridge[J].Soil Dynamic and Earthquake Engineering, 1997, 16:496～502
[80]吴子燕，代凤娟，宋静等．损伤检测中的传感器优化布置方法研究[J]．西北工业大学学报，2007，25(4)：504～507
[81]Guyan R J.Reduction of Stiffness and Mass Matrices[J].AIAA Journal, 1965, 3(2),380
[82]O'Callahan.A Processing for an Improved Reduced System(IRS)Model[C]. Proceedings of 7th International Modal Analysis Conference.1989,17～21
[83]O'Callahan,Avitabile P,Riemer R.System Equivalent Reduction Expansion Process[C].Proceedings of 7th International Modal Analysis Conference, 1989,29～37
[84]K F Alvin. Finite Element Model Update via Bayesian Estimation and Minimization of Dynamic Residuals[J].AIAA Journal,1997,35(5):879～886
[85]S S Law,Z Y Shi,L M Zhang.Structural damage detection from incomplete and noisy modal test data[J].Journal of Engineering Mechanics.ASCE, 1998,124(11):1280～1288
[86]张德文，魏阜旋．模型修正与破损诊断[M]．北京：科学出版社，1999
[87]谢峻．基于振动的桥梁结构损伤识别方法研究[D]．广东广州：华南理工大学博士学位论文，2003
[88]郭国会．桥梁结构动力损伤诊断方法研究[D]．湖南长沙：湖南大学博士学位论文，2001
[89]董晓马．智能结构的损伤诊断及传感器优化配置研究[D]．江苏南京：东南大学博士学位论文，2006
[90]王山山．基于振动理论的水工结构无损检测技术研究[D]．江苏南京：河海大学博士学位论文，2005
[91]李德葆，陆秋海．实验模态分析及其应用[M]．北京：科学出版社，2001
[92]B.Jaishi,W.X.Ren.Structural finite element model updating using ambient vibration test results[J].Journal of Structural Engineering,ASCE, 131(4),617～628,2005
[93]A.K.Garg,D.Roy Mahapatra,S.Suresh,etal.Estimation of composite damage model parameters using spectral finite element and neural network[J]. Composites Science and Technology,2004(64):2477～2493
[94]董聪．现代结构系统可靠性理论及其应用[M]．北京：科学出版社，2001
[95]邓众，严普强．桥梁结构损伤的振动模态检测[J]．振动、测试与诊断，1999，19(3)：157～163
[96]张德文，魏阜旋．模型修正与破损诊断[M]．北京：科学出版社，1999
[97]唐小兵．结构损伤识别与数值模拟[D]．湖北武汉：武汉理工大学博士学位论文，2004
[98]史治宇，罗绍湘，张令弥．结构破损定位的单元模态应变能变化率法[J]．振动工程 学报，1998，11(3)：356～360
[99]邓聚龙．灰色系统基本方法[M]．武汉：华中工学院出版社，1987
[100]Chang T.C,Lin S.J.Grey relationanalysis of carbon dioxide emissions from industrial production and energy uses in Taiwan[J]. Journal of Environmental Management,1999,56(4):247～257
[101] Liang R.H. Application of grey relation analysis to hydroelectric generation scheduling.International Journal of Electrical Power & Energy Systems[J].1999,21(5):357～364
[102]Wang S.X,Lin C.R.The Analysis of seismic data structure and oil and gas prediction[J].Applied Geophysics,2004,1(2):12～17
[103]吕锋，刘翔，刘泉．七种灰色系统关联度的比较研究[J]．武汉工业大学学报，2000，22(2)：41～43
[104]雨宫好文，佐藤幸男．信号处理入门[M]．北京：科学出版社，2000
[105]Farrar CR,Cone KM.Vibration testing of the 1-40 bridge before and after the introduction of damage[J].Proceedings of the 13th international Modal Analysis Conference,1995(1):203～209
[106]Doebling S W,Farrar C R,Prime M B,etal.Damage identification and health monitoring of structural and mechanical systems from changes in their vibration characteristics:A Literature Review. Los Alamos National Laboratory Report,LA-13070-MS,1996
[107]黄光远，刘小军．数学物理反问题[M]．济南：山东科学技术出板社，1993
[108] Davies A.R. On the maximum likelihood regularization of fredholm convolution equation of first kind.In:Treatment of Integral equation by numerical methods.New York:Academic Press,1982:95～105
[109]魏培君，章梓茂．弹性动力学反问题的不适定性及其广义解[J]．力学与实践，2001，23(3)：43～45
[110]赵红兵．基于能量测试和优化方法的结构单元损伤识别[D]．辽宁大连：大连理工大学博士学位论文，2005
[111]H.Baruh,S.Ratan.Damage detection in the flexible structures[J].Sound and Vibration,1993,166(1):21～30
[112]J.M.Ricles,J.B.Kosmatka.Damage detection in elastic structures using vibratory residual forces and weighted sensitivity[J].AIAA J.,1992, 30(9):2310～2316
[113]张清华．基于概率可靠度的结构损伤识别理论研究及应用[D]．四川成都：西南交通大学博士学位论文，2006
[114]吴小平．复杂桥梁结构综合监测系统开发研究[D]．浙江杭州：浙江大学博士学位论文，2005
[115]刘东，寥日东，左正兴．分析／试验模型相关及修正技术若干问题[J]．强度与环境，2003，30(1)：23～30
[116]袁颖．桥梁结构损伤识别方法的相关问题研究[D]．辽宁大连：大连理工大学博士学位论文，2005
[117]Friswell M I,Penny J E T,Garvey S D.A combined genetic and eigen sensitivity algorithm for the location of damage in structures[J]. Computers & Structures,1998,69(5):547～556
[118]Koh C G,Chen Y F,Liaw C Y.A hybrid computational strategy for identification of structural parameters.Computers and Structures,2003, (81):107～117
[119]Chou J H,Ghaboussi J.Genetic algorithm in structural damage detection. Computers and Structures,2001,(79):1335～1353
[120]邹大力．基于计算智能的结构损伤识别研究[D]．辽宁大连：大连理工大学博士学位论文，2005
[121]潘正君，康立山，陈毓屏．演化计算[M]．北京：清华大学出版社，1998
[122]陈国良，王煦法，庄镇泉，王东生．遗传算法及其应用[M]．北京：人民邮电出版社，1996
[123]周明，孙树栋．遗传算法原理及应用[M]．北京：国防工业出版社，1999
[124]云庆夏．进化算法[M]．北京：冶金工业出版社，2000
[125]Farmer,J.D.,Packard,N.H.& Perelson,A.S.(1986), “The Immune System, Adaptation,and Machine Learning.”[J],Physica 22D,pp 187～204
[126] Thomas P.Runarsson, Xin Yao. Stochastic Ranking for Constrained Evolutionary Optimization.IEEE Transactions on Evolutinary Computation, 2000，Vol．4，No．3，284～294
[127]杜海峰，焦李成，公茂果，刘若辰．免疫克隆选择算法与进化算法[M]．西安：西安电子科技大学出版社，2005
[128]L.N.De Castro, F.J.Von Zuben. The Clonal Selection Algorithm with Engineering Applications.In:D.Whitley,D.E.Goldberg,E.Cant(?)-Paz,L. Spector,I.C.Parmee,H.Beyer.Proceedings of the Genetic and Evolutionary Computation Conference.Morgan Kaufmann,Las Vegas:2000,36～37
[129]焦李成，杜海峰，刘芳，公茂果．免疫优化计算、学习与识别[M]．北京：科学出版社，2006
[130]于善谦，王洪海．免疫学导论[M]．北京：高等教育出版社，1999
[131]杜海峰，焦李成，公茂果，刘若辰．一种免疫克隆选择网络及其学习算法[J]．模式识别与人工智能，2005，18(2)，198～204
[132]Mroz Z,Lekszycki T.Identification of Damage in Structures Using Parameter Dependent Modal Response.Proceedings of ISMA25,Noise and Vibration Engineering,Leuven,elgium,2000
[133]O.S Salawu.Detection of structural damage through changes in frequency: a review[J].Engineering Structures.1997,19(9):718～723
[134]马宏伟，杨桂通．结构损伤探测的基本方法和研究进展[J]．力学进展，1999，29(4)：13～27
[135]靳蕃．神经计算智能基础原理·方法[M]．成都：西南交通大学出版社，2000
[136]Simon Haykin．神经网络原理[M]．北京：机械工业出版社，2003
[137]陈守余，周梅春．人工神经网络模拟实现与应用[M]．武汉：中国地质大学出版社，2000
[138]李士勇．模糊控制·神经控制和智能控制[M]．哈尔滨：哈尔滨工业出版社，1996
[139]何振亚．神经智能[M]．长沙：湖南科学技术出版社，1997
[140]Hecht-NielSen R.Counter-propagation network[A].Proc.of International Conference on Nueral networks,1987,19～32
[141]袁旭东．基于不完备信息土木工程结构损伤识别方法研究[D]．辽宁大连：大连理工大学博士学位论文，2005
[142]Hansen L K,Salamon P.Neural network ensembles[J].IEEE Trans Pattern Analysis and Machine Intelligence,1990,12(10):993～1001
[143]周开利，康耀红．神经网络模型及其MATLAB仿真程序设计[M]．北京：清华大学出版社，2005
[144]王若林．桥梁实时在线检测与健康监测若干问题研究[D]．湖北武汉：武汉大学博士学位论文，2005
[145]金水沟特大桥静动载试验报告[R]．铁道部科学研究院，2005
[146]金水沟特大桥健康监测方案设计[R]．铁道部科学研究院，2007
[147]廖旭．大跨度连续刚构典型病害及加固对策研究[D]．四川成都：西南交通大学硕士学位论文，2005
[148]俞峰，杨成梧．物元分析方法在地下水质量综合评判中的应用[J]．水资源与水工程学报，2005，16(2)：35～38
[149]蔡文．物元模型及其应用[M]．北京：科学技术文献出版社，1994
[150]杨文渊，徐犇．桥梁维修与加固[M]．北京：人民交通出版社，1989
[151]施洲．基于动力测试的桥梁结构损伤识别及性能评定理论与应用研究[D]．四川成都：西南交通大学博士学位论文，2006
[152]郭彤，李爱群，李兆霞，韩晓林．大跨桥梁结构状态评估方法研究进展[J]．东南大学学报(自然科学版)，2004，34(5)：699～704
[153]JTJ H12-2003，公路养护技术规范[S]
[154]胡宝清．区域水环境质量的区间可拓评价方法及应用[J]．中国工程科学，2001，3(6)：53～56
[155]杨雅勋，李子青，郝宪武．组合赋权灰关联法在桥梁加固方案优选中的应用[J]．郑州大学学报(工学版)，2006，27(4)：84～88
[156]宋光兴，邹平．多属性群决策中决策者权重的确定方法[J]．系统工程，2001，19(4)：84～89
[157]王成，陈中文，饶从军．科研基金项目评审的模糊群决策方法[J]．武汉理工大学学报(信息与管理工程版)，2006，28(1)：124～126
[158]马亚丽，王东炜，张爱林．在役桥梁结构健康等级的多级模糊综合评判[J]．北京工业大学学报，2005，31(1)：36～40
[159]徐荣桥．结构分析的有限元法与MATLAB程序设计[M]．北京：人民交通出版社，2006
[160]王齐，胡晓．MATLAB在振动信号处理中的应用[M]．北京：中国水利水电出版社， 2006
[161]钟珞，饶文碧，邹承明．人工神经网络及其融合应用技术[M]．北京：科学出版社，2007
[162]赵国藩，金伟良，贡金鑫．结构可靠度理论[M]．北京：中国建筑工业出版社，2000
[163]许树柏．层次分析法原理[M]．天津：天津大学出版社，1988
[164]陈卫东，蔡荫林，于诗源．工程优化方法[M]．哈尔滨：哈尔滨工程大学出版社，2006
[165]卢险峰．最优化方法应用基础[M]．上海：同济大学出版社，2003
[166]粟塔山．最优化计算原理与算法程序设计[M]．长沙：国防科技大学出版社，2001
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |