基于应变模态法智能识别海洋导管架平台的构件裂纹
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摘要
海洋平台结构庞大,受风、浪、流和冰等环境因素长期作用,同时还受到地震、台风、海啸和船舶碰撞等意外作用的威胁。在载荷作用下,导管架海洋平台会出现裂纹。由于平台部分结构位于海面以下,裂纹不易被发现,难以直接进行人工检测。当重要部件发生裂纹并在极端海况下产生扩展时,会导致整个结构失效,危及工作人员的生命安全,产生重大的经济损失和海洋环境污染。所以,及时并尽早地发现结构的裂纹具有重要意义。
本文以某一含四分之一跨处单裂纹的简支梁为例,计算了该梁的非贯穿单边裂纹损伤侧上、下表面、贯穿裂纹的上表面和内部非贯穿裂纹表面裂纹和内部裂纹等情况的不同损伤程度的位移模态和应变模态。根据已有的基于应变模态差分原理的损伤位置直接指标法ISMSD,利用等间距差分格式计算该简支梁非贯穿单边裂纹应变模态差分曲线,经Matlab编程计算将曲线进行光滑,计算得到直接指标值。由直接指标值的最大值找到对应的两有效极值点,这两个有效极值点间即是损伤位置。实例计算简支梁非贯穿单边裂纹损伤应变模态差分曲线,这些应变模态差分曲线在损伤处发生剧烈变化。差分曲线非峰值点损伤在损伤处不出现极值,因而损伤处的差分值不为零。损伤量不同,差分曲线损伤处突变程度略有不同,其规律相似。
运用带有Grubbs的支持向量机法和带有Grubbs的BP神经网络法对该非贯穿裂纹简支梁进行损伤程度智能识别,识别并评估了四分之一跨处单裂纹的损伤程度,并从性能及准确度方面对两种方法进行了比较。若选取应变模态差作为网络输入指标,本文采用的两种方法都可以得到比较高的识别精度,而且有良好适应性。支持向量机方法相对误差更小。
采用有限元软件ANSYS计算了某导管架海洋平台模型的一水平管件在完整状态、含单裂纹、含双裂纹三种情形时不同位置和不同损伤程度的频率和应变模态。验证了损伤会引起结构的频率降低和应变模态突变,频率降低的幅度随损伤程度的增加而增大。此外还发现,微小裂纹损伤时引起的频率变化很小：水平管端点损伤和中点损伤的频率下降幅度基本一致；双裂纹情形时的频率下降幅度均高于单裂纹情形时；损伤处应变模态曲线发生了显著改变,随损伤量的增加,应变模态曲线突变增大。
采用SCE-UA算法和粗粒度并行遗传算法对平台模型的10处单裂纹进行了损伤程度的逐一智能识别。将应变模态差作为SCE-UA算法和遗传算法的输入数据,这两种方法均能取得较高的识别精度,具有良好的适应性。其中SCE-UA算法损伤识别结果误差更小,更精确。
振动诊断中的应变模态法具有相对简单,成本较低,具有实时性、在线性、提取信号方便性和遥测性、可控性等诸多优点。本文的研究为工程实际应用提供了一定的参考价值,在结构损伤诊断识别中具有推广价值。
Offshore platforms are giant structures, subject to various environmental loads, such as wind, wave, currents, and ice. Other environmental loads may also come from earthquakes, typhoons, tsunamis, ship collisions and other accidents. Under these dynamic loads, cracks may occur and further develop at the structural members of an offshore platform. It is impossible to inspect the platform structural components beneath the sea level. Therefore, cracks can be a great threat to the platform. Damages at important structural components may lead to catastrophic results. Therefore, it is necessary to discover and identify the cracks in time to ensure the structural safety.
This dissertation adopts the intelligent diagnosis method based on the strain mode method to identify the crack at quarter span of a simply supported beam and a single crack at a jacket offshore platform pipe. The crack can be non-impenetrable into the beam section, while staying at the surface and in the beam with a certain depth. The author computes the displacement modes and the strain modes of all above cases. Based on the strain mode difference principle, direct index Ismsd——uses the equidistant difference scheme, without the modal characteristics of the original structure. FEM numerical simulations for non-impenetrate crack of different levels are also carried out. It is found that the strain mode differential curve of the damaged beam sharply changes at the damage location. The criteria of damage location detection are obtained by strain mode difference curves through a cubic spline interpolation. Through the two extremum points corresponding to ISMSD, the damage location can be found.
To intelligently identify the damage level for a single crack at the non-impenetrable beam, the support vector machine (SVM) with the Grubbs and the BP neural network with Grubbs network are used. The differences between the strain mode shapes can be due to the network input. The performance and the accuracy of the two methods have been compared. The SVM approach is of higher accuracy.
FEM numerical simulation by ANSYS is used to obtain the frequencies and strain mode shapes of the horizontal pipe at a offshore jacket platform model. A single crack and double cracks of the pipe with different positions and different degrees are considered. Damage in the pipe would cause the natural frequencies shift to lower values. The frequencies decrease with the increase of damage level. In addition, the frequency drop is very obvious. The frequency variation level of the double-crack case is higher. The strain mode differential curve of the damaged pipe sharply changes at the damage location.
The ten single-cracks of the pipe in the platform model can be intelligently identified by SCE-UA and the coarse-grained parallel genetic algorithm. The network input are the differences between the strain mode shapes. The results of these two algorithms for the structural degree damage diagnosis show that both of the two methods have high identification accuracy and good adaptability. The error of SCE-UA algorithm is smaller.
The strain mode method is a goog method for damage diagnosis, which is simple, cheap and has the virtue of real time, convenience, remote control. The study of this dissertation has favorable application foreground and spread value for engineering.
本文以某一含四分之一跨处单裂纹的简支梁为例,计算了该梁的非贯穿单边裂纹损伤侧上、下表面、贯穿裂纹的上表面和内部非贯穿裂纹表面裂纹和内部裂纹等情况的不同损伤程度的位移模态和应变模态。根据已有的基于应变模态差分原理的损伤位置直接指标法ISMSD,利用等间距差分格式计算该简支梁非贯穿单边裂纹应变模态差分曲线,经Matlab编程计算将曲线进行光滑,计算得到直接指标值。由直接指标值的最大值找到对应的两有效极值点,这两个有效极值点间即是损伤位置。实例计算简支梁非贯穿单边裂纹损伤应变模态差分曲线,这些应变模态差分曲线在损伤处发生剧烈变化。差分曲线非峰值点损伤在损伤处不出现极值,因而损伤处的差分值不为零。损伤量不同,差分曲线损伤处突变程度略有不同,其规律相似。
运用带有Grubbs的支持向量机法和带有Grubbs的BP神经网络法对该非贯穿裂纹简支梁进行损伤程度智能识别,识别并评估了四分之一跨处单裂纹的损伤程度,并从性能及准确度方面对两种方法进行了比较。若选取应变模态差作为网络输入指标,本文采用的两种方法都可以得到比较高的识别精度,而且有良好适应性。支持向量机方法相对误差更小。
采用有限元软件ANSYS计算了某导管架海洋平台模型的一水平管件在完整状态、含单裂纹、含双裂纹三种情形时不同位置和不同损伤程度的频率和应变模态。验证了损伤会引起结构的频率降低和应变模态突变,频率降低的幅度随损伤程度的增加而增大。此外还发现,微小裂纹损伤时引起的频率变化很小：水平管端点损伤和中点损伤的频率下降幅度基本一致；双裂纹情形时的频率下降幅度均高于单裂纹情形时；损伤处应变模态曲线发生了显著改变,随损伤量的增加,应变模态曲线突变增大。
采用SCE-UA算法和粗粒度并行遗传算法对平台模型的10处单裂纹进行了损伤程度的逐一智能识别。将应变模态差作为SCE-UA算法和遗传算法的输入数据,这两种方法均能取得较高的识别精度,具有良好的适应性。其中SCE-UA算法损伤识别结果误差更小,更精确。
振动诊断中的应变模态法具有相对简单,成本较低,具有实时性、在线性、提取信号方便性和遥测性、可控性等诸多优点。本文的研究为工程实际应用提供了一定的参考价值,在结构损伤诊断识别中具有推广价值。
Offshore platforms are giant structures, subject to various environmental loads, such as wind, wave, currents, and ice. Other environmental loads may also come from earthquakes, typhoons, tsunamis, ship collisions and other accidents. Under these dynamic loads, cracks may occur and further develop at the structural members of an offshore platform. It is impossible to inspect the platform structural components beneath the sea level. Therefore, cracks can be a great threat to the platform. Damages at important structural components may lead to catastrophic results. Therefore, it is necessary to discover and identify the cracks in time to ensure the structural safety.
This dissertation adopts the intelligent diagnosis method based on the strain mode method to identify the crack at quarter span of a simply supported beam and a single crack at a jacket offshore platform pipe. The crack can be non-impenetrable into the beam section, while staying at the surface and in the beam with a certain depth. The author computes the displacement modes and the strain modes of all above cases. Based on the strain mode difference principle, direct index Ismsd——uses the equidistant difference scheme, without the modal characteristics of the original structure. FEM numerical simulations for non-impenetrate crack of different levels are also carried out. It is found that the strain mode differential curve of the damaged beam sharply changes at the damage location. The criteria of damage location detection are obtained by strain mode difference curves through a cubic spline interpolation. Through the two extremum points corresponding to ISMSD, the damage location can be found.
To intelligently identify the damage level for a single crack at the non-impenetrable beam, the support vector machine (SVM) with the Grubbs and the BP neural network with Grubbs network are used. The differences between the strain mode shapes can be due to the network input. The performance and the accuracy of the two methods have been compared. The SVM approach is of higher accuracy.
FEM numerical simulation by ANSYS is used to obtain the frequencies and strain mode shapes of the horizontal pipe at a offshore jacket platform model. A single crack and double cracks of the pipe with different positions and different degrees are considered. Damage in the pipe would cause the natural frequencies shift to lower values. The frequencies decrease with the increase of damage level. In addition, the frequency drop is very obvious. The frequency variation level of the double-crack case is higher. The strain mode differential curve of the damaged pipe sharply changes at the damage location.
The ten single-cracks of the pipe in the platform model can be intelligently identified by SCE-UA and the coarse-grained parallel genetic algorithm. The network input are the differences between the strain mode shapes. The results of these two algorithms for the structural degree damage diagnosis show that both of the two methods have high identification accuracy and good adaptability. The error of SCE-UA algorithm is smaller.
The strain mode method is a goog method for damage diagnosis, which is simple, cheap and has the virtue of real time, convenience, remote control. The study of this dissertation has favorable application foreground and spread value for engineering.
引文
[1]伯瑜.机械故障诊断基础[M].北京：冶金工业出版社,1995.
[2]钟秉林,黄仁.机械故障诊断学[M].北京：机械工业出版社,1998.
[3]刘效尧,蔡键,刘晖.桥梁损伤诊断[M].北京：人民交通出版社,2002.
[4]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.
[5]虞和济.设备故障诊断工程[M].北京：冶金工业出版社.
[6]马宏伟.结构损伤探测的基本方法和研究进展[J].力学进展,1999,29(4)513-527.
[7]顾培英.基于应变模态技术的结构损伤诊断直接指标法研究[D].南京：河海大学,2006.
[8]West W M. Illustration of the use of modal assurance criterion to detect structural changes in an orbiter test specimen. Proceedings of the Air Force Conference on Aircraft Structural Integrity.1984[C]:1-6.
[9]Allemang R J, Brown D L. A Correlation Coefficient for Madal Vector Analysis. Proceedings of the 1st International Modal Analysis Conference,1982[C],1:110-116.
[10]Lieven N A J, Ewins D J. Spatial Correlation of Mode Shapes, The Coordinate Modal Assurance Criterion(COMAC). Preceedings of the 6th International Modal Analysis Conference,1998[C]:1:690-695.
[11]Rizos P F, Asparagathos N, Dimarogonas A D. Identification of crack location and magnitude in a cantilever from vibration modes[J]. Journal of Sound and Vibration,1990,138(3):381-388.
[12]Fox C H J. The location of detections in structures:a comparison of the use of natural frequency and mode shape data. Proceedings of 10th IMAC,1992[C]:522-528.
[13]Mayes R L. Error localization using mode shapes an application to a two-link robot arm. Proceedings of 10th IMAC,1992[C]:886-891.
[14]Kam T Y, Lee T Y. Detection of cracks in structures using modal test data [J] Engineering Fracture Mechanics,1992,42(2):381-387.
[15]Salawu 0 S, Williams C. Bridge Assessment using forced vibration testing [J]. Journal of Structural Engineering,1995,121(2):161-173.
[16]续秀忠,华宏星,陈兆能.基于环境激励的模态参数辨识方法综述[J].振动与冲击,2002,21(3)：1-5.
[17]Pandey A K, Biswas M, Samman M M. Damage Detection from Changes in Curvature Mode Shapes[J]. Journal of Sound and Vibration,1991,145(2):321-332.
[18]Ratckiffe C P. Damage detection using a modified Laplacian operator on mode shape data[J]. Journal of Sound and Vibration,1997,204(3):505-517.
[19]邓焱,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.
[20]李功宇,郑华文.损伤结构的曲率模态分析[J].振动、测试与诊断,2002,22(2)：136-141.
[21]郑栋梁,李中付,华宏星.结构早期损伤识别技术的现状和发展趋势[J].振动与冲击,2002,22(2)1-6,10.
[22]Gysin H P. Critical application of the error matrix method for localization of finite element modeling inaccuracies. Proceedings of the 4th International Modal Analysis Conference.1986[C],2:1339-1351.
[23]Park Y S, Park H S and Lee S S. Weighted-error-matrix application to detect stiffness damage by dynamic-characteristic measurement[J]. The International Journal of Analytical and Experimental Modal Analysis,1988,3(3):101-107.
[24]Chen J C, Garba J A. Analytical model improvement using model test results[J]. AIAA Journal,1998,18:684-690.
[25]Lin C S. Location of modeling errors using modal test data[J]. AIAA Journal,1990, 28(9):1650-1654.
[26]Pandey A K, Biswas M, Samman M M. Damage detection from changes in curvature mode shapes. Journal of Sound and Vibration,1991,145(2):321-332.
[27]Pandey A K, Biswas M. Damage detection from changes in flexibility. Journal of Sound and Vibration,1994,169(1):3-17.
[28]Rahavendrachar M, Aktan A. Flexibility by multi-reference impact testing for bridge diagnostics[J]. Journal of Structural Engineering,1992,118(8):2186-2203.
[29]Aktan A E, Lee K L, Chuntavan C et al. Modal testing for structural identification and condition assessment of constructed facilities. Proceedings of the 12th International Modal Analysis Conference,1994[C]:462-468.
[30]Denoyer K K, Peterson L D. Model update using modal contribution to static flexibility error[J]. AIAA Journal,1997,35(11):1739-1745.
[31]Zhao J, Dewolf J T. Sensitivity study for vibration parameters used in damage detection. Journal of Structural Engineering,1999,125(4):410-416.
[32]Lu Q, Ren G, Zhao Y. Multiple damage location with flexibility curvature and relative frequency change for beam structures. Journal of Sound and Vibration,2002, 253:1101-1114.
[33]Bernal D. Load vectors for damage localization[J]. Journal of Engineering Mechanics,2002,128(1);7-14.
[34]李德葆.实验应变/应力模态分析若干问题的进展评述[J].振动与冲击,1996,15(1)： 13-17.
[35]陆秋海,李德葆.模态理论的进展[J].力学进展,1996,26(4)：464-472.
[36]村井等.动态设计分析的研究(第2报).小松技报,25(2),1979：73.
[37]Hillary B, Ewins D J. The use of strain gauges in force determination and frequency response function measurements. Proc. of 2nd IMAC,1984[C]:627-634.
[38]Staker C H. Modal analysis efficiency improved via strain frequency response functions. Proc. Of 3rd IMAC,1985 [C]:612-617.
[39]伊立言.应变计在实验模态分析中的应用.第二届全国振动理论及应用会议论文集[C].西安,1984.
[40]Song T C, Zhang P Q, Feng W Q, et al. The application of the time domain method in strain modal analysis. Proc. of 4th IMAC,1986[C]:3-6.
[41]Li D B, Zhang H C, Wang B. The principle and techniques of experimental strain modal analysis. Proc. of 7th IMAC, Los Angeles,1989[C]:1285-1289.
[42]Bernasconi 0, Ewins D J. Application of strain modal testing to real structures. Proc. of 7th IMAC. Los Angeles.1989[C]:1453-1464.
[43]Yam L H, Leung T P, Li D B, et al. Theoretical and experimental study of modal strain analysis[J]. Journal of Sound and Vibration,1996,192(2):251-260.
[44]Tsang, W F. Use of dynamic strain measurements for the modeling of structures. Proc. of 8th IMAC.1990[C]:1246-1251.
[45]李德葆,张元润,罗京.动态应变/应力场分析模态方法.第六届模态分析与试验学术交流会论文集[C],1991.
[46]孙世基,雷继锋.结构故障的应变模态诊断方法[[J].武汉水运工程学院学报,1992,16(1)：59-65.
[47]张红梅,李岩,裴强.低温下钢结构裂缝损伤识别方法(Ⅰ)[J].低温建筑技术,2004,101(5)：98-101.
[48]张开银,冯文琴.梁结构裂纹位置估计的应变模态折线图法[J].武汉水运工程学院学报,1991,15(3)：263-267.
[49]张开银.框架结构裂纹故障诊断[J].湖北工学院学报,1992,7(3-4)：63-68.
[50]张开银,唐湘晋,李景成.柱桩结构裂缝故障诊断的研究[J].武汉水运工程学院学报,1993,17(3)：363-368.
[51]瞿伟廉,陈伟.多层及高层框架结构地震损伤诊断的神经网络方法[J].地震工程与工程振动,2002,22(1)：43-48.
[52]瞿伟廉,陈超,魏文辉.基于应变模态的钢结构构件焊缝损伤定位方法的研究[J].世界地震工程,2002,18(2)：1-8.
[53]瞿伟廉,黄东梅.高耸塔架结构节点损伤基于神经网络的两步诊断法[[J].地震工程与工程振动,2003,23(2)：143-149.
[54]涂志华,张忠,赵立中,张培强.铝合金板低温动态特性及力学参数的实验研究[J].低温工程,1995,84(2)：9-13.
[55]Banan M R, Hjelmstad K D. Parameter estimation of structures from static response, I:Computational aspects[J]. Journal of Structural Engineering,1994, 120(11):3243-3258.
[56]Banan M R, Hjelmstad K D. Parameter estimation of structures from static response, II:Numerical simulation studies[J]. Journal of Structural Engineering,1994, 120(11):3259-3283.
[57]Nwosu D I, Swamidas A S J, Guigne J Y, et al. Studies on influence of cracks on the dynamic response of tubular t-joints for nondestructive evaluation. Proceeding of the 13th International Modal Analysis Conference.1995[C]:1122-1128.
[58]Sanayei M, Saletnik M J. Parameter estimation of structure from static strain measurements, Ⅰ:Formulation[J]. Journal of Structural Engineering,1996, 122(5):555-562.
[59]Sanayei M, Saletnik M J. Parameter estimation of structure from static strain measurements, Ⅱ:Error sensitivity analysis[J]. Journal of Structural Engineering, 1996,122(5):563-572.
[60]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.
[61]顾培英,陈厚群,李同春等.用应变模态技术诊断梁结构的损伤[J].地震工程与工程振动,2005,25(4)：50-53.
[62]崔飞,袁万成,史家钧.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(自然科学版),2001,28(1)：5-8.
[63]邓焱,严普强.梁及桥梁应变模态与损伤测量的新方法[J].清华大学学报,2000,40(11)：123-127.
[64]周先雁,沈蒲生.用应变模态对混凝土结构进行损伤识别的研究[[J].湖南大学学报,1997,24(5)：69-74.
[65]任权,李洪升,郭杏林.基于应变模态变化率的压力管道无损检测[J].大连理工大学学报,2001,41(6)：648-652.
[66]董聪.基于动力特性的结构损伤定位方法[J].力学与实践,1999,21(4)：62-63.
[67]Li Y Y, Cheng L, Yam L H, et al. Identification of damage locations for plate-like structures using damage sensitive indices:strain modal approach[J]. Computer and Structures,2002,80:1881-1894.
[68]刘文峰,柳春图.利用广义应变比能进行结构损伤识别的数值研究[[J].机械强度,2003,25(2)159-162.
[69]Mark J S. Detecting structural damage using transmittance function. Proceedings of 15th IIVIAC, Florida,1997[C]:638-644.
[70]Sampaio R P C, Mala N M M, Silva J M M. Damage detection using the frequency response function curvature methods[J]. Journal of Sound and Vibration,1999, 226(5):1029-1042.
[71]Lee U, Shin J A. Frequency response function-based structural damage identification method[J]. Computers and Structures,2002,80(2):117-132.
[72]Park N, Park Y S. Damage detection using spatially incomplete frequency response functions[J]. Mechanical Systems and Signal Processing,2003,17(3):519-532.
[73]Rach A M; Liszkai T R. Improving the performance of structural damage detection methods using advanced geneic algorithms[J]. Journal of Structural engineering. 2007,3(133):449-461.
[74]Thyagarajan S K, Schulz M J, Pai P F, et al. Detecting structural damage using frequency response functions[J]. Journal of Sound and Vibration,1998,210(1):162-170.
[75]郑明刚等.基于频响函数的结构损伤检测[J].机械科学与技术,2001,20(3)：458-461.
[76]李晏石,来德利.用应变传递特性诊断箱型梁裂纹的实验研究[J].同济大学学报,1999,27(5)：618-620.
[77]Kim H, Melhem H. Damage detection of structures by wavelet analysis[J]. Engineering Structures,2004,26(3):347-362.
[78]孙增寿,韩建刚,任伟新.基于小波分析的结构损伤检测研究进展[J].地震工程与工程振动,2005,25(2)：93-99.
[79]孙增寿,韩建刚,任伟新.基于曲率模态和小波变换的结构损伤位置识别[J].地震工程与工程振动,2005,25(4)：44-49.
[80]0vanesove A V, Suarez L E. Applications of wavelet transforms to damage detection in frame structures[J]. Engineering Structures.2004,26:39-49.
[81]Liew K M, Wang Q. Application of wavelet theory for crack identification in structures. Journal of Engineering Mechanics.1998,124(2):152-157.
[82]Hera A, Hou Z. Application of wavelet approach for ASCE Structural health monitoring benchmark studies[J]. Journal of Engineering Mechanics,2004,130(1):96-104.
[83]李洪泉,董亮,吕西林.基于小波变换的结构损伤识别与实验研究.土木工程学报,2003,36(5)：52-57.
[84]Sun Z and Chang C C. Structural damage assessment based on wavelet packet transform. Journal of Structural Engineering.2002,128(10):1354-1361.
[85]Han J G, Ren W X, Sun Z S. Wavelet packet based damage identification of beam structures[J]. International Journal of Solids and Structures,2005,42:6610-6627.
[86]Hong J C, Kim Y Y, Lee H C, et al. Damage detection using the Lipschitz exponent estimated by the wavelet transform:application to vibration modes of a beam[J]. International Journal of Solids and Structures,2002,39:1443-1816.
[87]任宜春,马石城,林琳.移动荷载作用下梁裂缝识别的小波分析方法研究[J].振动与冲击,2004,23(2)：82-85.
[88]Cawley P, Adams R D. Improved Frequency resolution from transient tests with short record lengths[J]. Journal of Sound and Vibration,1979,64(1):123-132.
[89]Elkordy M F, Chang K C, Lee G C. Neural networks trained by analytical simulated damage states[J]. Journal of Computing in Civil Engineering,1993,7(2):130-145.
[90]Pandey P C, Barai W V. Multiplayer perception in damage detection of bridge structures[J]. Computers and Structures.1995,54(4):597-608.
[91]Kirkegaard P H, Rytter A. The use of neural networks for damage detection and location in a steel member[C]. Neural networks and Combinatorial optimization in Civil and Structural Engineering. Edinburgh, UK,1993:1-9.
[92]Mitsuru N, Masrisami F, Anatassios G, et al. A Method for nonparametric damage detection through the use of neural networks[J]. Earthquake Engineering and Structural Dynamics,1998,27:997-1010.
[93]Chen S S, Kim S. Neural network based signal monitoring in a smart structural system. Smart Structures and Materials:Smart Sensing, Processing, and Instrumentation, Sirkis J S, SPIE,1994[C],2191:176-186.
[94]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.国防科技大学学报,1996,18(1)：176-186.
[95]Tsou P, Shen M H H. Structural damage detection and identification using neural networks[J]. AIAA Journal,1994,32(1):176-183.
[96]Yagawa G, Marsuda A, Kawate H, et al. Neural network approach to estimate stable crack growth in welded specimens[J]. International Journal Pressure Vessels and Piping, 1995,63:303-318.
[97]Yoshimura S, Marsuda A, Yagawa A. New regularization by transformation for neural network based inverse analyses and its application to structure identification[J]. International Journal of Numerical Methods in Engineering,1996,39:53-68.
[98]Kudva R, Surace C. Damage assessment of multiple cracked beams:numerical results and experimental validation[J]. Journal of Sound and Vibration,1997,206(4):567-588.
[99]Masri S F, Smyth A W. Application of neural networks for detection of changes in nonlinear systems[J]. Journal of Engineering Mechanics,2000,126(7):666-676.
[100]Cacciola P, Impollonia N and Muscolino G. Crack detection and location in a damaged beam vibrating under white noise[J]. Computers and Structures.2003,81(4): 1773-1782.
[101]Sahin M, Shenoi R A. Quantification and localization of damage in beam like structures by using artificial neural networks with experimental validation[J]. Engineering Structures,2003,25(4):1785-1442.
[102]Owolabi G M, Swamidas A S J and Seshadri R. Crack detection in beam using changes in frequencies and amplitudes of frequency response functions[J]. Journal of Sound and Vibration,2003,265(4):1-22.
[103]Liu S W, Huang J H and Sung J C. Detection of cracks using Neural networks and computational mechanics[J]. Journal of Sound and Vibration,2002,275(5):34-45.
[104]Zenon Waszczyszyn, leonard Ziemianski. Neural networks in mechanics of structures and materials new results and prospects of applications [J]. Computers and Structures, 2001,79:2261-2276.
[105]Ko J M, Sun Z G, Ni Y Q. Multi-stage identification scheme for detecting damage in cablestayed Kap Shui Mun Bridge [J], Engineering Structures,2002,24:857-868.
[106]Sahin M, Shenoi R A. Quantification and localization of damage in beam-like structures by using artificial neural networks with experimental validation[J]. Engineering Structures,2003,25:1785-1442.
[107]Norhisham Bakhary, Hong Hao, Andrew J. Deeks. Damage detection using artificial neural network with consideration of uncertainties[J]. Engineering Structures,2007, 29:2806-2815.
[108]Roopesh Kumar Reddy, Ranjan Ganguli. Structural damage detection in a helicopter rotor blade using radial basis function neural networks[J], Smart Mater. Struct,2003, 12:232-241.
[109]Yeung W T, Smith J W. Damage detection in bridges using neural networks for pattern recognition of vibration signatures [J]. Journal of Engineering Structures, 2005,27:685-698.
[110]Mehrjoo M, Khaji N, Moharrami H, et al. Damage detection of truss bridge joints using Artificial Neural Networks. Expert Systems with Applications 2008[C] 35: 1122-1131.
[111]Jong Jae Lee, Jong Won Lee, and Jin Hak Yi, et al. Neural networks-based damage detection for bridges considering errors in baseline finite element models [J], Journal of Sound and Vibration,2005,280:555-578.
[112]Holland J H. Adaptation in natural and artificial system[M]. University of Michigan Press,1975.
[113]Friswell M I, Penny J E T, Garvey S D. A combined genetic and eigensensitivity algorithm of the location of damage in structures [J]. Computers and Structures,1998, 69(5):547-556.
[114]易伟建,刘霞.基于遗传算法的结构损伤诊断研究.工程力学.2001,18(2),64-71.
[115]Mares C, Surace C. An application of genetic algorithms to identify damage in elastic structures. Journal of Sound and Vibration,1996,195(3):195-215.
[116]Chiang D Y, Lai W Y. Structural damage detection using the simulated evolution method[J]. AIAA Journal,1999,37(10):1331-1333.
[117]Koh C G. Distributive GA for large system identification problems. NDE for Health Monitoring and Diagnostics, San Diego,2002[C]:4702-4752.
[118]Mohammad-Taghi, Vakil Baghmisheh, Mansour Peimani. Crack detection in beam-like structures using genetic algorithms [J], Applied Soft Computing,2008,8:1150-1160.
[119]He R S, Hwang S F. Identifying damage in spherical laminate shells by using a hybridreal-parameter genetic algorithm[J]. Composite Structures,2006, 21(4):131-149.
[120]Jung-Huai Chou, Jamshid Ghaboussi. Genetic algorithm in structural damage detection[J]. Computers & Structures,2001,79:1335-1353.
[121]Rao M A, Srinivas J, Murthy B S N. Damage detection in vibrating bodies using genetic algorithms. Computers and Structures,2004,19(3):963-968.
[122]袁颖,林皋,柳春光,周爱红.遗传算法在结构损伤识别中的应用研究[J],防灾减灾工程学报,2005,25(4)：369-374.
[123]黄维平,王晓燕.基于改进CHC遗传算法的结构损伤诊断研究[J].振动、测试与诊断,2007,27(3)：232-235.
[124]朱劲松,肖汝诚,基于定期检测与遗传算法的大跨度斜拉桥损伤识别.土木工程学报,2006,39(5)：85-89.
[125]程远胜,区光达,谭国焕等.基于分级遗传算法的结构损伤识别方法.华中科技大学学报,2002,30(8)：73-75.
[126]邹大力,屈福政,孙铁兵.基于混合遗传算法的子结构损伤识别.农业机械学报,2005,36(8)：31-35.
[127]袁颖,林皋,柳春光等.遗传算法在结构损伤识别中的应用研究.防灾减灾工程学报,2005,25(4)：369-374.
[128]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,2007.
[129]Nello Cristianini, John Shawe Taylor. Support Vector Machine can do the Kernel-Based Learning Methods[M]. London:Cambridge University Press,2000.
[130]Vapnik V.Estimation of dependencies based on empirieal data[M]. NewYork: SpringerVerlag,1982.
[131]邓乃扬,田英杰.数据挖掘中的新方法一一支持向量机[M].北京：科学出版社,2004
[132]张学工.关于统计学习理论的支持向量机[J].自动化学报,2000,26(1)：32-42.
[133]Sebald D J, Bucklew J A. Support vector machine techniques for nonlinear equalizeanon [J]. Signal Processing,2000,48 (11):3217-3226.
[134]Shi Z, Han M. Support Vector Echo-State Machine for Chaotic Time-Series Prediction[J]. Neural Networks,2007,18 (2):359-372.
[135]Vapnik V.The Nature of Statistieal Learning Theory [M].New York: SpringerVerlag,1995.
[136]刘胜,李妍妍.基于支持向量机的锅炉过热系统建模研究[J].热能动力工程,2007,22(1)：38-41.
[137]Cortes C,Vapnik V. Support vector networks[J]. Machine Learning,1995, 20:273-297.
[138]Paula F. Viero. Ney Roytman. Application of some damage identification method in offshore platforms[J]. Marine Struetures,1999,2(12):107-126.
[139]Daniel Karunakaran, Mortern Barheim, Nile Spidsoe. Full-scale measurements from a large deepwater jack-up platform [J]. Marine Structures,1999,12(4):255-275.
[140]Coppolino R N and Rubin S. Detectability of structural failures in offshore platforms by ambient vibration monitoring [J].1980.OTC 3865.
[141]Hyoung M K, Theodore J Bartkowicz. An experimental study for damage detection using a hexagonal truss [J]. Computers and Structure,2001,2(79):173-182.
[142]Matias E. Wojnarowski, Stanley G. Stiansen and NeilE. Reddy. Structural integrity evaluation of a fixed platform using vibration criteria [J].1977. OTC 2909.
[143]Lalu Mangal, Idichandy V G, Ganapathy C, et al. Structural monitoring of offshore platforms using impulse and relaxation response [J]. Ocean Engineering,2001, 28(6):689-705.
[144]Etube L S, Brennan F P, Dover W D. Modeling of jack-up response for fatigue under simulated service condition [J]. Marine Structures,1999,12(4):327-348.
[145]Begg R D, Mackenzie A C, Dodds C J, et al. Structural Integrity Monitoring Using Digital Processing of Vibration Signals. Proc.8th Annual Offshore Technology Conference, Houston, TX,1976[C],305-311.
[146]Loland O and Dodds J C. Experience in developing and operating integrity monitoring system in north sea. Proc. of the 8th Annual Offshore Technology Conference.1976 [C], 313-319.
[147]Osegueda R A, Dsouza P D, and Qiang Y. Damage evaluation of offshore structures using resonant frequency shifts. Serviceability of Petroleum, Process, and Power Equipment, ASME PVP239/MPC 33,1992[C],31-37.
[148]Swamidas A S and Chen Y. Damage detection in a tripod tower platform (TTP) using modal analysis, ASME Offshore Technology,1992[C],1-B,577-583.
[149]Ambient Kondo, T. Hamamoto. Local damage detection of fFlexible offshore platforms using vibration. Proc. of the 4th International Offshore and Polar Engineering Conference.1994[C],4,400-407.
[150]Brincker R, Kirkegaard P H, Anderson P, et al. Damage Detection in an Offshore Structure. Proc. of the 13th International Modal Analysis Conference,1995[C], I,661-667.
[151]Icirn J T and Stubbs N. Assessment of the relative impact of model uncertainty on the accuracy of global nondestructive damage detection in Structures[R]. Report prepared for New MexicoState University,1993.
[152]Hansen K and Gudmestad O T. Reassessment of jacket type of platforms subject to wave-in-deck forces:current practice and future development. Society of Offshore and Polar Engineers,2001[C], California:482-489.
[153]Asgarian B, Amiri M, Ghafooripour A. Damage detection in jacket type offshore platforms using modal strain energy. Structural Engineering and Mechanics, 2009,33 (3):325-337.
[154]董聪,丁辉,高嵩.结构损伤识别和定位的基本原理与方法[J].中国铁道科学,1999,20(3)：89-94.
[155]Pandey M, Biswas, Samman M M. Damage detection from changes in curvature mode shapes [J]. Journal of Sound and Vibration,1991,145(2):321-332.
[156]张汝清,殷学刚,董明.计算结构力学[M]重庆：重庆大学出版社,1987.
[157]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,(2)：224-227.
[158]李长明.导数与微分[M].北京：科学出版社,1987.
[159]易大义,陈道琦.数值分析引论[M].浙江：淅江大学出版社,2000.
[160]薛毅,耿美英.数值分析[M].北京：北京工业大学出版社,2003.
[161]王勖成 有限单元法[M].北京：清华大学出版社,2003.
[162]金咸定赵德有船体振动学[M]上海：上海交通大学出版社,2000.
[163]孙卫泉.基于支持向量机的梁桥损伤识别[D].成都：西南交通大学,2008.
[164]王茂强.基于支持向量机的大跨度连续刚构桥损伤识别[D].成都：西南交通大学,2009.
[165]刘天怡.基于支持向量机和振动特性的结构损伤识别方法研究[D].武汉：武汉理工大学,2008.
[166]林丽,赵德有.导管架海洋平台结构模型裂纹扩展声发射特征提取[D].大连：大连理工大学,2009.
[167]Holland J H. Adaptation in natural and artificial system. [M] University of Michigan Press,1975.
[168]Duan Q Y, Gupta V K. Effective and efficient global optimization for conceptual rainfall-runoff models[J]. Water Resourses,1992.28(4):1015-1031.
[169]De Jong. Analysis of the Behaviour of a Class of Genetic Adaptive Systems. PhD Thesis.Depart. Of computer and Communication Sciences, University of Michigan, AnnArbor,1975.
[170]周尚明,关于现代工业自动化中的计算智能和信息处理问题的研究,in铁道部科学研究院博士后研究工作报告.1998.
[171]Matsumura T, Nakamura M, Okech J, et al. A parallel and distributed genetic algorithm on loosely-coupled multiprocessor systems. IEICE Trans. Fundam. Electron. Commun. Comput 1998. E81-A(4):540-546.
[172]陈国良,王熙法,庄镇泉等.遗传算法及其应用[M].北京：人民邮电出版社,1996.
[173]Beckers M L M, Derks E, Melssen W J, et al. Using Genetic Algorithms for Conformational Analysis of Biomacro molecules[J]. Comput Chem,1996.20(4):449-457.
[174]Easton F F, Mansour N. A Distributed Genetic Algorithm for Determ Inistic and Stochastic Labor[J]. Scheduling Problems European Of Operational Research,1999,118(3):505-523.
[175]Dengiz B, Altiparmak F, Smith A E. Local Search Genetic Algorithm for Optimal Design of Reliable Networks [J]. IEEE Transactionson Evolutionary Computation 1,1997.1(3): 179-188.
[176]Mayer M K. A Network Parallel Genetic Algorithm for The One Machine Sequencing Problem[J].Computers & Mathematics with Applications,1999.37(3):71-78.
[2]钟秉林,黄仁.机械故障诊断学[M].北京：机械工业出版社,1998.
[3]刘效尧,蔡键,刘晖.桥梁损伤诊断[M].北京：人民交通出版社,2002.
[4]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.
[5]虞和济.设备故障诊断工程[M].北京：冶金工业出版社.
[6]马宏伟.结构损伤探测的基本方法和研究进展[J].力学进展,1999,29(4)513-527.
[7]顾培英.基于应变模态技术的结构损伤诊断直接指标法研究[D].南京：河海大学,2006.
[8]West W M. Illustration of the use of modal assurance criterion to detect structural changes in an orbiter test specimen. Proceedings of the Air Force Conference on Aircraft Structural Integrity.1984[C]:1-6.
[9]Allemang R J, Brown D L. A Correlation Coefficient for Madal Vector Analysis. Proceedings of the 1st International Modal Analysis Conference,1982[C],1:110-116.
[10]Lieven N A J, Ewins D J. Spatial Correlation of Mode Shapes, The Coordinate Modal Assurance Criterion(COMAC). Preceedings of the 6th International Modal Analysis Conference,1998[C]:1:690-695.
[11]Rizos P F, Asparagathos N, Dimarogonas A D. Identification of crack location and magnitude in a cantilever from vibration modes[J]. Journal of Sound and Vibration,1990,138(3):381-388.
[12]Fox C H J. The location of detections in structures:a comparison of the use of natural frequency and mode shape data. Proceedings of 10th IMAC,1992[C]:522-528.
[13]Mayes R L. Error localization using mode shapes an application to a two-link robot arm. Proceedings of 10th IMAC,1992[C]:886-891.
[14]Kam T Y, Lee T Y. Detection of cracks in structures using modal test data [J] Engineering Fracture Mechanics,1992,42(2):381-387.
[15]Salawu 0 S, Williams C. Bridge Assessment using forced vibration testing [J]. Journal of Structural Engineering,1995,121(2):161-173.
[16]续秀忠,华宏星,陈兆能.基于环境激励的模态参数辨识方法综述[J].振动与冲击,2002,21(3)：1-5.
[17]Pandey A K, Biswas M, Samman M M. Damage Detection from Changes in Curvature Mode Shapes[J]. Journal of Sound and Vibration,1991,145(2):321-332.
[18]Ratckiffe C P. Damage detection using a modified Laplacian operator on mode shape data[J]. Journal of Sound and Vibration,1997,204(3):505-517.
[19]邓焱,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.
[20]李功宇,郑华文.损伤结构的曲率模态分析[J].振动、测试与诊断,2002,22(2)：136-141.
[21]郑栋梁,李中付,华宏星.结构早期损伤识别技术的现状和发展趋势[J].振动与冲击,2002,22(2)1-6,10.
[22]Gysin H P. Critical application of the error matrix method for localization of finite element modeling inaccuracies. Proceedings of the 4th International Modal Analysis Conference.1986[C],2:1339-1351.
[23]Park Y S, Park H S and Lee S S. Weighted-error-matrix application to detect stiffness damage by dynamic-characteristic measurement[J]. The International Journal of Analytical and Experimental Modal Analysis,1988,3(3):101-107.
[24]Chen J C, Garba J A. Analytical model improvement using model test results[J]. AIAA Journal,1998,18:684-690.
[25]Lin C S. Location of modeling errors using modal test data[J]. AIAA Journal,1990, 28(9):1650-1654.
[26]Pandey A K, Biswas M, Samman M M. Damage detection from changes in curvature mode shapes. Journal of Sound and Vibration,1991,145(2):321-332.
[27]Pandey A K, Biswas M. Damage detection from changes in flexibility. Journal of Sound and Vibration,1994,169(1):3-17.
[28]Rahavendrachar M, Aktan A. Flexibility by multi-reference impact testing for bridge diagnostics[J]. Journal of Structural Engineering,1992,118(8):2186-2203.
[29]Aktan A E, Lee K L, Chuntavan C et al. Modal testing for structural identification and condition assessment of constructed facilities. Proceedings of the 12th International Modal Analysis Conference,1994[C]:462-468.
[30]Denoyer K K, Peterson L D. Model update using modal contribution to static flexibility error[J]. AIAA Journal,1997,35(11):1739-1745.
[31]Zhao J, Dewolf J T. Sensitivity study for vibration parameters used in damage detection. Journal of Structural Engineering,1999,125(4):410-416.
[32]Lu Q, Ren G, Zhao Y. Multiple damage location with flexibility curvature and relative frequency change for beam structures. Journal of Sound and Vibration,2002, 253:1101-1114.
[33]Bernal D. Load vectors for damage localization[J]. Journal of Engineering Mechanics,2002,128(1);7-14.
[34]李德葆.实验应变/应力模态分析若干问题的进展评述[J].振动与冲击,1996,15(1)： 13-17.
[35]陆秋海,李德葆.模态理论的进展[J].力学进展,1996,26(4)：464-472.
[36]村井等.动态设计分析的研究(第2报).小松技报,25(2),1979：73.
[37]Hillary B, Ewins D J. The use of strain gauges in force determination and frequency response function measurements. Proc. of 2nd IMAC,1984[C]:627-634.
[38]Staker C H. Modal analysis efficiency improved via strain frequency response functions. Proc. Of 3rd IMAC,1985 [C]:612-617.
[39]伊立言.应变计在实验模态分析中的应用.第二届全国振动理论及应用会议论文集[C].西安,1984.
[40]Song T C, Zhang P Q, Feng W Q, et al. The application of the time domain method in strain modal analysis. Proc. of 4th IMAC,1986[C]:3-6.
[41]Li D B, Zhang H C, Wang B. The principle and techniques of experimental strain modal analysis. Proc. of 7th IMAC, Los Angeles,1989[C]:1285-1289.
[42]Bernasconi 0, Ewins D J. Application of strain modal testing to real structures. Proc. of 7th IMAC. Los Angeles.1989[C]:1453-1464.
[43]Yam L H, Leung T P, Li D B, et al. Theoretical and experimental study of modal strain analysis[J]. Journal of Sound and Vibration,1996,192(2):251-260.
[44]Tsang, W F. Use of dynamic strain measurements for the modeling of structures. Proc. of 8th IMAC.1990[C]:1246-1251.
[45]李德葆,张元润,罗京.动态应变/应力场分析模态方法.第六届模态分析与试验学术交流会论文集[C],1991.
[46]孙世基,雷继锋.结构故障的应变模态诊断方法[[J].武汉水运工程学院学报,1992,16(1)：59-65.
[47]张红梅,李岩,裴强.低温下钢结构裂缝损伤识别方法(Ⅰ)[J].低温建筑技术,2004,101(5)：98-101.
[48]张开银,冯文琴.梁结构裂纹位置估计的应变模态折线图法[J].武汉水运工程学院学报,1991,15(3)：263-267.
[49]张开银.框架结构裂纹故障诊断[J].湖北工学院学报,1992,7(3-4)：63-68.
[50]张开银,唐湘晋,李景成.柱桩结构裂缝故障诊断的研究[J].武汉水运工程学院学报,1993,17(3)：363-368.
[51]瞿伟廉,陈伟.多层及高层框架结构地震损伤诊断的神经网络方法[J].地震工程与工程振动,2002,22(1)：43-48.
[52]瞿伟廉,陈超,魏文辉.基于应变模态的钢结构构件焊缝损伤定位方法的研究[J].世界地震工程,2002,18(2)：1-8.
[53]瞿伟廉,黄东梅.高耸塔架结构节点损伤基于神经网络的两步诊断法[[J].地震工程与工程振动,2003,23(2)：143-149.
[54]涂志华,张忠,赵立中,张培强.铝合金板低温动态特性及力学参数的实验研究[J].低温工程,1995,84(2)：9-13.
[55]Banan M R, Hjelmstad K D. Parameter estimation of structures from static response, I:Computational aspects[J]. Journal of Structural Engineering,1994, 120(11):3243-3258.
[56]Banan M R, Hjelmstad K D. Parameter estimation of structures from static response, II:Numerical simulation studies[J]. Journal of Structural Engineering,1994, 120(11):3259-3283.
[57]Nwosu D I, Swamidas A S J, Guigne J Y, et al. Studies on influence of cracks on the dynamic response of tubular t-joints for nondestructive evaluation. Proceeding of the 13th International Modal Analysis Conference.1995[C]:1122-1128.
[58]Sanayei M, Saletnik M J. Parameter estimation of structure from static strain measurements, Ⅰ:Formulation[J]. Journal of Structural Engineering,1996, 122(5):555-562.
[59]Sanayei M, Saletnik M J. Parameter estimation of structure from static strain measurements, Ⅱ:Error sensitivity analysis[J]. Journal of Structural Engineering, 1996,122(5):563-572.
[60]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.
[61]顾培英,陈厚群,李同春等.用应变模态技术诊断梁结构的损伤[J].地震工程与工程振动,2005,25(4)：50-53.
[62]崔飞,袁万成,史家钧.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(自然科学版),2001,28(1)：5-8.
[63]邓焱,严普强.梁及桥梁应变模态与损伤测量的新方法[J].清华大学学报,2000,40(11)：123-127.
[64]周先雁,沈蒲生.用应变模态对混凝土结构进行损伤识别的研究[[J].湖南大学学报,1997,24(5)：69-74.
[65]任权,李洪升,郭杏林.基于应变模态变化率的压力管道无损检测[J].大连理工大学学报,2001,41(6)：648-652.
[66]董聪.基于动力特性的结构损伤定位方法[J].力学与实践,1999,21(4)：62-63.
[67]Li Y Y, Cheng L, Yam L H, et al. Identification of damage locations for plate-like structures using damage sensitive indices:strain modal approach[J]. Computer and Structures,2002,80:1881-1894.
[68]刘文峰,柳春图.利用广义应变比能进行结构损伤识别的数值研究[[J].机械强度,2003,25(2)159-162.
[69]Mark J S. Detecting structural damage using transmittance function. Proceedings of 15th IIVIAC, Florida,1997[C]:638-644.
[70]Sampaio R P C, Mala N M M, Silva J M M. Damage detection using the frequency response function curvature methods[J]. Journal of Sound and Vibration,1999, 226(5):1029-1042.
[71]Lee U, Shin J A. Frequency response function-based structural damage identification method[J]. Computers and Structures,2002,80(2):117-132.
[72]Park N, Park Y S. Damage detection using spatially incomplete frequency response functions[J]. Mechanical Systems and Signal Processing,2003,17(3):519-532.
[73]Rach A M; Liszkai T R. Improving the performance of structural damage detection methods using advanced geneic algorithms[J]. Journal of Structural engineering. 2007,3(133):449-461.
[74]Thyagarajan S K, Schulz M J, Pai P F, et al. Detecting structural damage using frequency response functions[J]. Journal of Sound and Vibration,1998,210(1):162-170.
[75]郑明刚等.基于频响函数的结构损伤检测[J].机械科学与技术,2001,20(3)：458-461.
[76]李晏石,来德利.用应变传递特性诊断箱型梁裂纹的实验研究[J].同济大学学报,1999,27(5)：618-620.
[77]Kim H, Melhem H. Damage detection of structures by wavelet analysis[J]. Engineering Structures,2004,26(3):347-362.
[78]孙增寿,韩建刚,任伟新.基于小波分析的结构损伤检测研究进展[J].地震工程与工程振动,2005,25(2)：93-99.
[79]孙增寿,韩建刚,任伟新.基于曲率模态和小波变换的结构损伤位置识别[J].地震工程与工程振动,2005,25(4)：44-49.
[80]0vanesove A V, Suarez L E. Applications of wavelet transforms to damage detection in frame structures[J]. Engineering Structures.2004,26:39-49.
[81]Liew K M, Wang Q. Application of wavelet theory for crack identification in structures. Journal of Engineering Mechanics.1998,124(2):152-157.
[82]Hera A, Hou Z. Application of wavelet approach for ASCE Structural health monitoring benchmark studies[J]. Journal of Engineering Mechanics,2004,130(1):96-104.
[83]李洪泉,董亮,吕西林.基于小波变换的结构损伤识别与实验研究.土木工程学报,2003,36(5)：52-57.
[84]Sun Z and Chang C C. Structural damage assessment based on wavelet packet transform. Journal of Structural Engineering.2002,128(10):1354-1361.
[85]Han J G, Ren W X, Sun Z S. Wavelet packet based damage identification of beam structures[J]. International Journal of Solids and Structures,2005,42:6610-6627.
[86]Hong J C, Kim Y Y, Lee H C, et al. Damage detection using the Lipschitz exponent estimated by the wavelet transform:application to vibration modes of a beam[J]. International Journal of Solids and Structures,2002,39:1443-1816.
[87]任宜春,马石城,林琳.移动荷载作用下梁裂缝识别的小波分析方法研究[J].振动与冲击,2004,23(2)：82-85.
[88]Cawley P, Adams R D. Improved Frequency resolution from transient tests with short record lengths[J]. Journal of Sound and Vibration,1979,64(1):123-132.
[89]Elkordy M F, Chang K C, Lee G C. Neural networks trained by analytical simulated damage states[J]. Journal of Computing in Civil Engineering,1993,7(2):130-145.
[90]Pandey P C, Barai W V. Multiplayer perception in damage detection of bridge structures[J]. Computers and Structures.1995,54(4):597-608.
[91]Kirkegaard P H, Rytter A. The use of neural networks for damage detection and location in a steel member[C]. Neural networks and Combinatorial optimization in Civil and Structural Engineering. Edinburgh, UK,1993:1-9.
[92]Mitsuru N, Masrisami F, Anatassios G, et al. A Method for nonparametric damage detection through the use of neural networks[J]. Earthquake Engineering and Structural Dynamics,1998,27:997-1010.
[93]Chen S S, Kim S. Neural network based signal monitoring in a smart structural system. Smart Structures and Materials:Smart Sensing, Processing, and Instrumentation, Sirkis J S, SPIE,1994[C],2191:176-186.
[94]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.国防科技大学学报,1996,18(1)：176-186.
[95]Tsou P, Shen M H H. Structural damage detection and identification using neural networks[J]. AIAA Journal,1994,32(1):176-183.
[96]Yagawa G, Marsuda A, Kawate H, et al. Neural network approach to estimate stable crack growth in welded specimens[J]. International Journal Pressure Vessels and Piping, 1995,63:303-318.
[97]Yoshimura S, Marsuda A, Yagawa A. New regularization by transformation for neural network based inverse analyses and its application to structure identification[J]. International Journal of Numerical Methods in Engineering,1996,39:53-68.
[98]Kudva R, Surace C. Damage assessment of multiple cracked beams:numerical results and experimental validation[J]. Journal of Sound and Vibration,1997,206(4):567-588.
[99]Masri S F, Smyth A W. Application of neural networks for detection of changes in nonlinear systems[J]. Journal of Engineering Mechanics,2000,126(7):666-676.
[100]Cacciola P, Impollonia N and Muscolino G. Crack detection and location in a damaged beam vibrating under white noise[J]. Computers and Structures.2003,81(4): 1773-1782.
[101]Sahin M, Shenoi R A. Quantification and localization of damage in beam like structures by using artificial neural networks with experimental validation[J]. Engineering Structures,2003,25(4):1785-1442.
[102]Owolabi G M, Swamidas A S J and Seshadri R. Crack detection in beam using changes in frequencies and amplitudes of frequency response functions[J]. Journal of Sound and Vibration,2003,265(4):1-22.
[103]Liu S W, Huang J H and Sung J C. Detection of cracks using Neural networks and computational mechanics[J]. Journal of Sound and Vibration,2002,275(5):34-45.
[104]Zenon Waszczyszyn, leonard Ziemianski. Neural networks in mechanics of structures and materials new results and prospects of applications [J]. Computers and Structures, 2001,79:2261-2276.
[105]Ko J M, Sun Z G, Ni Y Q. Multi-stage identification scheme for detecting damage in cablestayed Kap Shui Mun Bridge [J], Engineering Structures,2002,24:857-868.
[106]Sahin M, Shenoi R A. Quantification and localization of damage in beam-like structures by using artificial neural networks with experimental validation[J]. Engineering Structures,2003,25:1785-1442.
[107]Norhisham Bakhary, Hong Hao, Andrew J. Deeks. Damage detection using artificial neural network with consideration of uncertainties[J]. Engineering Structures,2007, 29:2806-2815.
[108]Roopesh Kumar Reddy, Ranjan Ganguli. Structural damage detection in a helicopter rotor blade using radial basis function neural networks[J], Smart Mater. Struct,2003, 12:232-241.
[109]Yeung W T, Smith J W. Damage detection in bridges using neural networks for pattern recognition of vibration signatures [J]. Journal of Engineering Structures, 2005,27:685-698.
[110]Mehrjoo M, Khaji N, Moharrami H, et al. Damage detection of truss bridge joints using Artificial Neural Networks. Expert Systems with Applications 2008[C] 35: 1122-1131.
[111]Jong Jae Lee, Jong Won Lee, and Jin Hak Yi, et al. Neural networks-based damage detection for bridges considering errors in baseline finite element models [J], Journal of Sound and Vibration,2005,280:555-578.
[112]Holland J H. Adaptation in natural and artificial system[M]. University of Michigan Press,1975.
[113]Friswell M I, Penny J E T, Garvey S D. A combined genetic and eigensensitivity algorithm of the location of damage in structures [J]. Computers and Structures,1998, 69(5):547-556.
[114]易伟建,刘霞.基于遗传算法的结构损伤诊断研究.工程力学.2001,18(2),64-71.
[115]Mares C, Surace C. An application of genetic algorithms to identify damage in elastic structures. Journal of Sound and Vibration,1996,195(3):195-215.
[116]Chiang D Y, Lai W Y. Structural damage detection using the simulated evolution method[J]. AIAA Journal,1999,37(10):1331-1333.
[117]Koh C G. Distributive GA for large system identification problems. NDE for Health Monitoring and Diagnostics, San Diego,2002[C]:4702-4752.
[118]Mohammad-Taghi, Vakil Baghmisheh, Mansour Peimani. Crack detection in beam-like structures using genetic algorithms [J], Applied Soft Computing,2008,8:1150-1160.
[119]He R S, Hwang S F. Identifying damage in spherical laminate shells by using a hybridreal-parameter genetic algorithm[J]. Composite Structures,2006, 21(4):131-149.
[120]Jung-Huai Chou, Jamshid Ghaboussi. Genetic algorithm in structural damage detection[J]. Computers & Structures,2001,79:1335-1353.
[121]Rao M A, Srinivas J, Murthy B S N. Damage detection in vibrating bodies using genetic algorithms. Computers and Structures,2004,19(3):963-968.
[122]袁颖,林皋,柳春光,周爱红.遗传算法在结构损伤识别中的应用研究[J],防灾减灾工程学报,2005,25(4)：369-374.
[123]黄维平,王晓燕.基于改进CHC遗传算法的结构损伤诊断研究[J].振动、测试与诊断,2007,27(3)：232-235.
[124]朱劲松,肖汝诚,基于定期检测与遗传算法的大跨度斜拉桥损伤识别.土木工程学报,2006,39(5)：85-89.
[125]程远胜,区光达,谭国焕等.基于分级遗传算法的结构损伤识别方法.华中科技大学学报,2002,30(8)：73-75.
[126]邹大力,屈福政,孙铁兵.基于混合遗传算法的子结构损伤识别.农业机械学报,2005,36(8)：31-35.
[127]袁颖,林皋,柳春光等.遗传算法在结构损伤识别中的应用研究.防灾减灾工程学报,2005,25(4)：369-374.
[128]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,2007.
[129]Nello Cristianini, John Shawe Taylor. Support Vector Machine can do the Kernel-Based Learning Methods[M]. London:Cambridge University Press,2000.
[130]Vapnik V.Estimation of dependencies based on empirieal data[M]. NewYork: SpringerVerlag,1982.
[131]邓乃扬,田英杰.数据挖掘中的新方法一一支持向量机[M].北京：科学出版社,2004
[132]张学工.关于统计学习理论的支持向量机[J].自动化学报,2000,26(1)：32-42.
[133]Sebald D J, Bucklew J A. Support vector machine techniques for nonlinear equalizeanon [J]. Signal Processing,2000,48 (11):3217-3226.
[134]Shi Z, Han M. Support Vector Echo-State Machine for Chaotic Time-Series Prediction[J]. Neural Networks,2007,18 (2):359-372.
[135]Vapnik V.The Nature of Statistieal Learning Theory [M].New York: SpringerVerlag,1995.
[136]刘胜,李妍妍.基于支持向量机的锅炉过热系统建模研究[J].热能动力工程,2007,22(1)：38-41.
[137]Cortes C,Vapnik V. Support vector networks[J]. Machine Learning,1995, 20:273-297.
[138]Paula F. Viero. Ney Roytman. Application of some damage identification method in offshore platforms[J]. Marine Struetures,1999,2(12):107-126.
[139]Daniel Karunakaran, Mortern Barheim, Nile Spidsoe. Full-scale measurements from a large deepwater jack-up platform [J]. Marine Structures,1999,12(4):255-275.
[140]Coppolino R N and Rubin S. Detectability of structural failures in offshore platforms by ambient vibration monitoring [J].1980.OTC 3865.
[141]Hyoung M K, Theodore J Bartkowicz. An experimental study for damage detection using a hexagonal truss [J]. Computers and Structure,2001,2(79):173-182.
[142]Matias E. Wojnarowski, Stanley G. Stiansen and NeilE. Reddy. Structural integrity evaluation of a fixed platform using vibration criteria [J].1977. OTC 2909.
[143]Lalu Mangal, Idichandy V G, Ganapathy C, et al. Structural monitoring of offshore platforms using impulse and relaxation response [J]. Ocean Engineering,2001, 28(6):689-705.
[144]Etube L S, Brennan F P, Dover W D. Modeling of jack-up response for fatigue under simulated service condition [J]. Marine Structures,1999,12(4):327-348.
[145]Begg R D, Mackenzie A C, Dodds C J, et al. Structural Integrity Monitoring Using Digital Processing of Vibration Signals. Proc.8th Annual Offshore Technology Conference, Houston, TX,1976[C],305-311.
[146]Loland O and Dodds J C. Experience in developing and operating integrity monitoring system in north sea. Proc. of the 8th Annual Offshore Technology Conference.1976 [C], 313-319.
[147]Osegueda R A, Dsouza P D, and Qiang Y. Damage evaluation of offshore structures using resonant frequency shifts. Serviceability of Petroleum, Process, and Power Equipment, ASME PVP239/MPC 33,1992[C],31-37.
[148]Swamidas A S and Chen Y. Damage detection in a tripod tower platform (TTP) using modal analysis, ASME Offshore Technology,1992[C],1-B,577-583.
[149]Ambient Kondo, T. Hamamoto. Local damage detection of fFlexible offshore platforms using vibration. Proc. of the 4th International Offshore and Polar Engineering Conference.1994[C],4,400-407.
[150]Brincker R, Kirkegaard P H, Anderson P, et al. Damage Detection in an Offshore Structure. Proc. of the 13th International Modal Analysis Conference,1995[C], I,661-667.
[151]Icirn J T and Stubbs N. Assessment of the relative impact of model uncertainty on the accuracy of global nondestructive damage detection in Structures[R]. Report prepared for New MexicoState University,1993.
[152]Hansen K and Gudmestad O T. Reassessment of jacket type of platforms subject to wave-in-deck forces:current practice and future development. Society of Offshore and Polar Engineers,2001[C], California:482-489.
[153]Asgarian B, Amiri M, Ghafooripour A. Damage detection in jacket type offshore platforms using modal strain energy. Structural Engineering and Mechanics, 2009,33 (3):325-337.
[154]董聪,丁辉,高嵩.结构损伤识别和定位的基本原理与方法[J].中国铁道科学,1999,20(3)：89-94.
[155]Pandey M, Biswas, Samman M M. Damage detection from changes in curvature mode shapes [J]. Journal of Sound and Vibration,1991,145(2):321-332.
[156]张汝清,殷学刚,董明.计算结构力学[M]重庆：重庆大学出版社,1987.
[157]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,(2)：224-227.
[158]李长明.导数与微分[M].北京：科学出版社,1987.
[159]易大义,陈道琦.数值分析引论[M].浙江：淅江大学出版社,2000.
[160]薛毅,耿美英.数值分析[M].北京：北京工业大学出版社,2003.
[161]王勖成 有限单元法[M].北京：清华大学出版社,2003.
[162]金咸定赵德有船体振动学[M]上海：上海交通大学出版社,2000.
[163]孙卫泉.基于支持向量机的梁桥损伤识别[D].成都：西南交通大学,2008.
[164]王茂强.基于支持向量机的大跨度连续刚构桥损伤识别[D].成都：西南交通大学,2009.
[165]刘天怡.基于支持向量机和振动特性的结构损伤识别方法研究[D].武汉：武汉理工大学,2008.
[166]林丽,赵德有.导管架海洋平台结构模型裂纹扩展声发射特征提取[D].大连：大连理工大学,2009.
[167]Holland J H. Adaptation in natural and artificial system. [M] University of Michigan Press,1975.
[168]Duan Q Y, Gupta V K. Effective and efficient global optimization for conceptual rainfall-runoff models[J]. Water Resourses,1992.28(4):1015-1031.
[169]De Jong. Analysis of the Behaviour of a Class of Genetic Adaptive Systems. PhD Thesis.Depart. Of computer and Communication Sciences, University of Michigan, AnnArbor,1975.
[170]周尚明,关于现代工业自动化中的计算智能和信息处理问题的研究,in铁道部科学研究院博士后研究工作报告.1998.
[171]Matsumura T, Nakamura M, Okech J, et al. A parallel and distributed genetic algorithm on loosely-coupled multiprocessor systems. IEICE Trans. Fundam. Electron. Commun. Comput 1998. E81-A(4):540-546.
[172]陈国良,王熙法,庄镇泉等.遗传算法及其应用[M].北京：人民邮电出版社,1996.
[173]Beckers M L M, Derks E, Melssen W J, et al. Using Genetic Algorithms for Conformational Analysis of Biomacro molecules[J]. Comput Chem,1996.20(4):449-457.
[174]Easton F F, Mansour N. A Distributed Genetic Algorithm for Determ Inistic and Stochastic Labor[J]. Scheduling Problems European Of Operational Research,1999,118(3):505-523.
[175]Dengiz B, Altiparmak F, Smith A E. Local Search Genetic Algorithm for Optimal Design of Reliable Networks [J]. IEEE Transactionson Evolutionary Computation 1,1997.1(3): 179-188.
[176]Mayer M K. A Network Parallel Genetic Algorithm for The One Machine Sequencing Problem[J].Computers & Mathematics with Applications,1999.37(3):71-78.
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