基于反馈控制与统计分析的结构损伤识别技术研究
|
摘要
随着航空、航天、海洋、桥梁和军事装备等领域的重要大型工程结构的不断修建及已建结构的大批老化,从上个世纪70年代开始,无损检测技术的研究受到国内外学术和工程界越来越多的关注,并已进行了一些工程实践探索。其中,基于振动的结构损伤识别技术具有信号便于提取、易于实现自动化等优点,其工程应用前景良好,已成为研究的核心内容之一。然而,随着研究的深入和实际工程应用的需求,许多基于振动的损伤识别方法显露出了一些不足。
本文首先对基于振动的结构损伤识别技术的基本理论和研究方法进行了总结和分析,在此基础上重点对如何提高噪声环境下损伤指标对损伤的灵敏度与采用结构振动的时域响应数据进行损伤识别进行了研究。主要研究工作包括:
(1)从理论上证明了反馈控制能够提高频率对刚度的灵敏度。在此基础上,采用基于模态空间控制的反馈控制合理配置系统极点,提高了多自由度耦合系统的特征频率对结构刚度变化的灵敏度。以损伤前后闭环系统特征频率构造损伤识别指标,采用假设检验法判断损伤是否发生。假设检验法能够克服随机噪声对识别准确性的影响,并且由于采用反馈控制提高了频率对损伤的灵敏度,该方法对于噪声环境下较小程度损伤的存在性识别具有一定的优势。
(2)在提高频率对损伤灵敏度的基础上,采用统计模式识别方法进行损伤定位的研究。采用基于模态空间控制的反馈控制法合理配置系统极点;然后以损伤前后闭环系统特征频率构造特征向量;通过矩阵摄动理论,推导了对该特征量进行归一化的方法,最后采用多元统计分析的Mahalanobis距离作为判别函数来识别损伤位置。
(3)提出了一种采用随机载荷作用下的结构时域响应数据进行损伤识别的新方法。其主要原理是建立基于自回归参数的损伤灵敏度矩阵,该矩阵建立了由单元损伤导致的自回归参数的变化与损伤系数变化之间的关系;通过求解损伤系数向量来识别损伤位置和损伤程度。该方法与其它基于时域响应的损伤识别方法相比,其最大优势在于能够仅利用单个传感器的响应信号进行损伤识别,因此对于传感器位置和数量的选择上有较大的灵活性,尤其对于大型的复杂结构如海洋平台结构,该方法能够降低损伤识别的难度和测试成本。
(4)推导了自回归参数对单元刚度损伤系数的灵敏度表达式。提出通过合理配置系统极点能够在一定程度上提高自回归参数对结构刚度变化的灵敏度,从而提高损伤识别正确率的新思路。其基本过程为,建立闭环系统加速度响应的时序模型,以自回归参数建立均值控制图,通过监测自回归参数的统计性变化判断结构是否发生损伤。该方法仅需结构的时域响应数据,并且由于反馈控制使得自回归参数灵敏度的提高,因此对于早期损伤能够及时诊断,适用于结构的健康监测系统。
(5)以一梁结构为实验对象,测量了完好梁和损伤梁的传递函数和模态频率,并分析了损伤前后系统特性的变化。实验验证了采用控制图进行损伤存在性识别的有效性和可行性。
本文将控制理论和统计方法综合运用于结构的损伤识别,从理论和方法上进行了较深入地研究。其研究成果为提高损伤识别方法的抗噪声能力、提高损伤识别指标对损伤的灵敏度以及基于时域响应的损伤识别方法的研究提供了新的研究思路和途径。
With the continuous construction of large engineering structures in aerospace, civil, ocean, and mechanical engineering communities and the aging of existing structures in these communities, development of technology to monitor a structure and detect damage is becoming increasingly important. During the last 30 years, non-destructive examination (NDE)method has received considerable attention both in the academic and engineering communities. As the one kind of NDE vibration-based structural damage detection has become a hot research area because of its simplicity and minimum interaction with users and has promising applicability. However, with the development of research and acquirement of its practical application, many techniques of the vibration-based damage identification have shown some limitations.
This thesis first presents a comprehensive summary and the state-of-the-art review on development of vibration-based structural damage detection. In the study, emphases are placed on how to enhance sensitivity of the damage indicator to damage and how to utilize time-domain response data of structure for detecting damage. The main works presented in the thesis are as follows:
(1)The principle and feasibility of the sensitivity-enhancing feedback control for damage detection is further explored. Feedback control based on independent modal space control is first used to assign the pole of the system under detection intentionally. Then the prescribed characteristic frequencies of closed-loop system, which are more sensitive to damage, are obtained and further employed to constitute a sensitivity-enhanced damage indicator (SEDI). To overcome the effect of measurement noise on modal frequencies, a hypothesis test involving the t-test that utilizes the SEDI is employed to estimate the occurrence of damage. The combination of sensitivity-enhancing feedback control and statistical analysis is expected to improve the capability of the frequencies of the closed-loop system for identifying small damage and to lower the sensitivity to measurement noise.
(2)A statistical pattern recognition technique is used for locating damage with the characteristic frequencies of the closed-loop system. Feedback control based on independent modal space control is used to assign the pole of the system under detection intentionally, and then the frequencies of the closed-loop system are used to construct feature vector. Based on perturbation theory, the feature vectors are normalized in order to eliminate the effect of damage extent on damage localization. Finally, mahalanobis distance of multivariate statistical analysis is used for locating damage.
(3)A novel method using time-domain response data under random loading for detecting structural damage is proposed. A time series model with a fitting order is first constructed using the time domain response data with measurement noise. A sensitivity matrix consisting of the first differential of the autoregressive coefficients of the time series models with respect to the stiffness of the structural elements is then obtained. The locations and severities of the damage may be finally estimated by solving for the damage vector whose components are the damage degrees of the structural elements. A unique aspect of this method is that acceleration history data obtained from only one or a few sensors are required for detection and more feasibility for sensor arrangement is obtained accordingly. This advantage is helpful to reduce the difficulty and cost of testing of damage detection especially for large-scale complex engineering structures such as offshore platform structures.
(4)The sensitivity of autoregressive coefficient to element stiffness is deduced, and it is concluded that assignment of pole of system under detection can be employed to enhance the sensitivity of autoregressive coefficient to element stiffness to improve the accuracy of damage detection. Principal component analysis is first carried out on all response time series of closed-loop system for data compression. A time series model with a fitting order is then constructed using the fist principal component. Finally, an X-bar control chart is constructed based on the mean value of autoregressive coefficient. The identification of damage occurrence is performed by monitoring the statically significant change of the control chart. Because only time-domain responses data are demanded and the sensitivity of autoregressive coefficient is enhanced by feedback control, the presented approach is efficient for the identification of early small damage and is very attractive for online structural monitoring system.
(5)In order to demonstrate the effectiveness and feasibility of using control chart for damage detection, a beam structure with damage is tested in laboratory. Transfer function and modal frequencies of the damage and undamaged beams are measured. An analysis about the change of vibration characteristics of structures is carried out according to the measurement data. The process using control chart for the identification of damage occurrence is performed based on acceleration samples of the beam. High success rates are obtained.
In this thesis, statistical approach combined with control theory are utilized for structural damage detection in an effort to enhance the sensitivity of damage feature indicator with measurement noise, and several key techniques and basic theories are studied. These research findings can be employed to supply novel ideas and approaches for improvement of robust ability of vibration-based damage identification, enhancement of the sensitivity of damage feature indicator to damage and the use of time-domain response data applied to damage detection.
本文首先对基于振动的结构损伤识别技术的基本理论和研究方法进行了总结和分析,在此基础上重点对如何提高噪声环境下损伤指标对损伤的灵敏度与采用结构振动的时域响应数据进行损伤识别进行了研究。主要研究工作包括:
(1)从理论上证明了反馈控制能够提高频率对刚度的灵敏度。在此基础上,采用基于模态空间控制的反馈控制合理配置系统极点,提高了多自由度耦合系统的特征频率对结构刚度变化的灵敏度。以损伤前后闭环系统特征频率构造损伤识别指标,采用假设检验法判断损伤是否发生。假设检验法能够克服随机噪声对识别准确性的影响,并且由于采用反馈控制提高了频率对损伤的灵敏度,该方法对于噪声环境下较小程度损伤的存在性识别具有一定的优势。
(2)在提高频率对损伤灵敏度的基础上,采用统计模式识别方法进行损伤定位的研究。采用基于模态空间控制的反馈控制法合理配置系统极点;然后以损伤前后闭环系统特征频率构造特征向量;通过矩阵摄动理论,推导了对该特征量进行归一化的方法,最后采用多元统计分析的Mahalanobis距离作为判别函数来识别损伤位置。
(3)提出了一种采用随机载荷作用下的结构时域响应数据进行损伤识别的新方法。其主要原理是建立基于自回归参数的损伤灵敏度矩阵,该矩阵建立了由单元损伤导致的自回归参数的变化与损伤系数变化之间的关系;通过求解损伤系数向量来识别损伤位置和损伤程度。该方法与其它基于时域响应的损伤识别方法相比,其最大优势在于能够仅利用单个传感器的响应信号进行损伤识别,因此对于传感器位置和数量的选择上有较大的灵活性,尤其对于大型的复杂结构如海洋平台结构,该方法能够降低损伤识别的难度和测试成本。
(4)推导了自回归参数对单元刚度损伤系数的灵敏度表达式。提出通过合理配置系统极点能够在一定程度上提高自回归参数对结构刚度变化的灵敏度,从而提高损伤识别正确率的新思路。其基本过程为,建立闭环系统加速度响应的时序模型,以自回归参数建立均值控制图,通过监测自回归参数的统计性变化判断结构是否发生损伤。该方法仅需结构的时域响应数据,并且由于反馈控制使得自回归参数灵敏度的提高,因此对于早期损伤能够及时诊断,适用于结构的健康监测系统。
(5)以一梁结构为实验对象,测量了完好梁和损伤梁的传递函数和模态频率,并分析了损伤前后系统特性的变化。实验验证了采用控制图进行损伤存在性识别的有效性和可行性。
本文将控制理论和统计方法综合运用于结构的损伤识别,从理论和方法上进行了较深入地研究。其研究成果为提高损伤识别方法的抗噪声能力、提高损伤识别指标对损伤的灵敏度以及基于时域响应的损伤识别方法的研究提供了新的研究思路和途径。
With the continuous construction of large engineering structures in aerospace, civil, ocean, and mechanical engineering communities and the aging of existing structures in these communities, development of technology to monitor a structure and detect damage is becoming increasingly important. During the last 30 years, non-destructive examination (NDE)method has received considerable attention both in the academic and engineering communities. As the one kind of NDE vibration-based structural damage detection has become a hot research area because of its simplicity and minimum interaction with users and has promising applicability. However, with the development of research and acquirement of its practical application, many techniques of the vibration-based damage identification have shown some limitations.
This thesis first presents a comprehensive summary and the state-of-the-art review on development of vibration-based structural damage detection. In the study, emphases are placed on how to enhance sensitivity of the damage indicator to damage and how to utilize time-domain response data of structure for detecting damage. The main works presented in the thesis are as follows:
(1)The principle and feasibility of the sensitivity-enhancing feedback control for damage detection is further explored. Feedback control based on independent modal space control is first used to assign the pole of the system under detection intentionally. Then the prescribed characteristic frequencies of closed-loop system, which are more sensitive to damage, are obtained and further employed to constitute a sensitivity-enhanced damage indicator (SEDI). To overcome the effect of measurement noise on modal frequencies, a hypothesis test involving the t-test that utilizes the SEDI is employed to estimate the occurrence of damage. The combination of sensitivity-enhancing feedback control and statistical analysis is expected to improve the capability of the frequencies of the closed-loop system for identifying small damage and to lower the sensitivity to measurement noise.
(2)A statistical pattern recognition technique is used for locating damage with the characteristic frequencies of the closed-loop system. Feedback control based on independent modal space control is used to assign the pole of the system under detection intentionally, and then the frequencies of the closed-loop system are used to construct feature vector. Based on perturbation theory, the feature vectors are normalized in order to eliminate the effect of damage extent on damage localization. Finally, mahalanobis distance of multivariate statistical analysis is used for locating damage.
(3)A novel method using time-domain response data under random loading for detecting structural damage is proposed. A time series model with a fitting order is first constructed using the time domain response data with measurement noise. A sensitivity matrix consisting of the first differential of the autoregressive coefficients of the time series models with respect to the stiffness of the structural elements is then obtained. The locations and severities of the damage may be finally estimated by solving for the damage vector whose components are the damage degrees of the structural elements. A unique aspect of this method is that acceleration history data obtained from only one or a few sensors are required for detection and more feasibility for sensor arrangement is obtained accordingly. This advantage is helpful to reduce the difficulty and cost of testing of damage detection especially for large-scale complex engineering structures such as offshore platform structures.
(4)The sensitivity of autoregressive coefficient to element stiffness is deduced, and it is concluded that assignment of pole of system under detection can be employed to enhance the sensitivity of autoregressive coefficient to element stiffness to improve the accuracy of damage detection. Principal component analysis is first carried out on all response time series of closed-loop system for data compression. A time series model with a fitting order is then constructed using the fist principal component. Finally, an X-bar control chart is constructed based on the mean value of autoregressive coefficient. The identification of damage occurrence is performed by monitoring the statically significant change of the control chart. Because only time-domain responses data are demanded and the sensitivity of autoregressive coefficient is enhanced by feedback control, the presented approach is efficient for the identification of early small damage and is very attractive for online structural monitoring system.
(5)In order to demonstrate the effectiveness and feasibility of using control chart for damage detection, a beam structure with damage is tested in laboratory. Transfer function and modal frequencies of the damage and undamaged beams are measured. An analysis about the change of vibration characteristics of structures is carried out according to the measurement data. The process using control chart for the identification of damage occurrence is performed based on acceleration samples of the beam. High success rates are obtained.
In this thesis, statistical approach combined with control theory are utilized for structural damage detection in an effort to enhance the sensitivity of damage feature indicator with measurement noise, and several key techniques and basic theories are studied. These research findings can be employed to supply novel ideas and approaches for improvement of robust ability of vibration-based damage identification, enhancement of the sensitivity of damage feature indicator to damage and the use of time-domain response data applied to damage detection.
引文
[1]高维成,刘伟,邹经湘.基于结构振动参数变化的损伤探测方法综述.振动与冲击, 2004, 23(4): 1-9
[2]张丽卿,韩兵康,李春祥.基于振动的土木工程结构损伤诊断研究进展期.自然灾害学报, 2004, 13(5): 136-143
[3] C. R. Farrar, T. A. Duffey, S. W. Doebling, et al. A statistical pattern recognition paradigm for vibration-based structural health monitoring. In: Proceedings of the 2nd International Workshop on Structural Health Monitoring, Stanford, California, USA, 2000, 764-773
[4] Y. J. Yan, L. Cheng, Z. Y. Wu, et al. Development in vibration-based structural damage detection technique. Mechanical Systems and Signal Processing, 2007, 21(5): 2198-2211
[5] O. S. Salawu. Detection of structural damage through changes in frequencies: a review. Engineering Structures, 1997, 19(9): 718-723
[6] S. W. Doebling. A summary review of vibration based damage identification methods. The Shock and Vibration Digest, 1998, 30(2): 92-105
[7]马宏伟,杨桂通.结构损伤探测的基本方法和研究进展.力学进展, 1999, 29(4): 513-527
[8]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.振动与冲击, 2002, 21(2): 1-6,10
[9]宗周红,任伟新,阮毅.土木工程结构损伤诊断研究进展.土木工程学报, 2003, 36(5): 105-110
[10]王术新,姜哲.基于结构振动损伤识别技术的研究现状及进展.振动与冲击, 2004, 23(4): 99-104
[11] E. P. Carden, P. Fanning. Vibration based condition monitoring: a review. Structural Health Monitoring, 2004, 3(4): 355-377
[12] A. Rytter. Vibration based inspection of civil engineering structures: [PhD.Dissertation]. Denmark: Department of Building Technology and Structural Engineering, Aalborg University, 1993
[13]张德文,魏阜旋.模型修正和破损诊断.北京:科学出版社, 1999
[14] P. Cawley, R. D. Adams. The location of defects in structures from measurements of natural frequencies. Journal of Strain Analysis, 1979, 14(2): 49-57
[15] N. Stubbs, R. Osegueda. Global non-destructive damage evaluation in solid. International Journal of Analytical and Experimental Modal Analysis, 1990, 5(2): 67-79
[16] F. K. Choy, R. Liang, P. Xu. Fault identification of beams on elastic foundation. Computers and Geotechnics, 1995, 17(2): 157-176
[17] S. Alamphalli, G. Fu, I. A. Aziz. Modal analysis as a bridge inspection tool. In: Proceedings of the 10th International Modal Analysis Conference, San Diego, California, 1992, 1359-1366
[18] A. E. Aktan, K. L. Lee, C. Chuntavan, et al. Modal testing for structural identification and condition assessment of constructed facilities. In: Proceeding 12th International Modal Analysis Conference, Honolulu, Hawaii, 1994, 2251: 462-468
[19] H. L. Chen, C.C. Spyrakos, G. Venkatesh. Evaluating structural deterioration by dynamic response. Journal of Structural Engineering, 1995, 121(8): 1197-1204
[20] C. R. Farrar, W. E. Baker, T. M. Bell, et al. Dynamic characterization and damage detection in the I-40 bridge over the Rio Grande. Los Alamos National Laboratory Report LA-12767-MS, Los Alamos National Laboratory, P.O. Box 1193, Los Alamos, NM, 87544, USA. 1994
[21] S. S. Law, H. S. Ward, G. B Shi, et al. Dynamic assessment of bridge load-carrying capacities. Journal of Structural Engineering, 1995, 121(3): 478-487
[22] R. D. Adams, D. L. Brown. A correlation coefficient for modal vector analysis. In: Proceeding of the first International Modal Analysis Conference, Orlando, 1982: 110-116
[23] T. Wolff, M. Richardson. Fault detection in structures from changes in their modal parameters. In: Proceedings of the 7th International Modal Analysis Conference, Las Vegas, Nevada, 1989: 87-94
[24] A. K. Pandey, M. Biswas, M. M. Samman. Damage detection from changes in curvature mode shapes. Journal of Sound and Vibration, 1991, 145(2): 321-332
[25] M. M. A. Wahab, G. D. Roeck. Damage detection in bridges using modal curvatures: applications to a real damage scenario. Journal of Sound and Vibration, 1999, 226(2): 217-235
[26] O. S. Salawn, C. Eilliams. Damage location using vibration mode shapes. In: Proceedings of the 12th International Modal Analysis Conference, Honolulu, Hawaii, 1994, 933-939
[27] A. Z. Khan, A. B. Stanbridge, D. J. Ewins. Detecting damage in vibrating structures with a scanning LDV. Optics and Lasers in Engineering, 1999, 32(6): 583-592
[28] M. Raghavendrachar, A. E. Aktan. Flexibility by multireference impact testing for bridge diagnostics. Journal of Structural Engineering, 1992, 118(8): 2186-2203
[29] J. Zhao, J. T. DeWolf. Sensitivity study for vibrational parameters used in damage detection. Journal of Structural Engineering, 1999, 125(4): 410-416
[30] A. K. Pandey, M. Biswas. Damage detection in structures using changes in flexibility. Journal of Sound and Vibration, 1994, 169(1): 3-7
[31] A. K. Pandy, M.Biswas. Experimental verification of flexibility difference method for locating damage in structures. Journal of Sound and Vibration, 1995, 184(2): 311-328
[32]孙国,顾元宪.连续梁结构损伤识别的改进柔度阵方法.工程力学, 2003, 20(4): 50-54,198
[33]曹晖, M. I. Friswell.基于模态柔度曲率的损伤检测方法.工程力学, 2006, 23(4): 33-38
[34]唐小兵,沈成武,陈定方.结构损伤识别的柔度曲率法.武汉理工大学学报, 2001, 23(8): 18-20,26
[35]张谢东,张治国,詹昊.基于曲率模态和柔度曲率的结构多损伤识别.武汉理工大学学报, 2005, 27(8): 35-37,55
[36] J. S. Lew. Using transfer function parameter changes for damage detection of structures. AIAA Journal, 1995, 33(11): 2189-2193
[37] N. M. M. Maia. Location of damage using curvature of the frequency responsefunctions. In: Proceedings of the 15th International Modal Analysis Conference, Florida, 1997: 942-946
[38] H. Y. Kim. Vibration-based damage identification using reconstructed FRFS incomposite structures. Journal of Sound and Vibration, 2003, 259(5): 1131-1146
[39] M. Palacz, M. Krawczuk. Vibration parameters for damage detection in structures. Journal of Sound and Vibration, 2002, 249(5): 999-1010
[40] N.G. Park, Y.S. Park. Identification of damage on a substructure with measured frequency response functions. Journal of Mechanical Science and Technology, 2005, 19(10): 891-1901
[41] A. Furukawa, H. Otsuka, J. Kiyono. Structural damage detection method using uncertain frequency response functions. Computer-Aided Civil and Infrastructure Engineering, 2006, 21(4): 292-305
[42] S. W. Doebling, C. R. Farrar. Statistical damage identification techniques applied to the I-40 bridge over the Rio Grande River. In: Proceedings of the 16th International Modal Analysis Conference, Santa Barbara, CA, 1998, 3243: 1717-1724
[43] L. Hermans, D. A. H. Van, L. Mevel. Health monitoring and detection of a fatigue problem of a sports car. In: Proceedings of the 17th International Modal Analysis Conference, Kissimmee, FL, USA, 1999, 1: 42-48
[44] D. W. Allen, H. Sohn, K. Worden, et al. Utilizing the sequential probability ratio test for building joint monitoring. In: Proceedings of SPIE - The International Society for Optical Engineering, 2002, 4704: 1-11
[45] Y. Xia, H. Hao. Statistical damage identification of structures with frequency changes. Journal of Sound and Vibration, 2003, 263(4): 853-870
[46]谢峻,韩大建,周毅姝.整合统计的结构损伤动力诊断三步法.振动与冲击, 2004, 23(4): 119-122
[47]王柏生,刘承斌,何国波.用统计神经网络进行结构损伤存在检测.土木工程学报, 2004, 37(8): 24-27
[48] R. F. Charles, A. D. Thomas, W. D. Scott, et al. A statistical pattern recognition paradigm for vibration-based structural health monitoring. In: Proceedings of the 2nd International Workshop on Structural Health Monitoring, Stanford, CA, 1999,8-10
[49] H. Sohn, C. R. Farrar, N. F. Hunter, et al. Structural health monitoring using statistical pattern recognition techniques. Journal of Structural and Engineering, 2000, 123(11): 1336-1356
[50] H. Sohn, C. R Farrar. Damage diagnosis using time series analysis of vibration signals. Smart Materials and Structures, 2001, 10(3): 446-451
[51] Y. Lu, F. Gao. A novel time-domain auto-regressive model for structural damage diagnosis. Journal of Sound and Vibration, 2005, 283(3-5):1031-1049
[52] H. Sohn, K. Worden, C. R Farrar. Statistical damage classification under changing environmental and operational conditions. Journal of Intelligent Material Systems and Structures, 2003, 13(9): 561-574
[53] H. Sohn, D. W. Allen, K. Worden, et al. Structural damage classification using extreme value statistics. Journal of Dynamic Systems, Measurement and Control, 2005, 127(1): 125-132
[54] G. Park, A. C. Rutherford, H. Sohn, et al. An outlier analysis framework for impedance-based structural health monitoring. Journal of Sound and Vibration, 2005, 286(1-2): 229-250
[55] K. K. Nair, A. S. Kiremidjian, K. H. Law. Time series-based damage detection and localization algorithm with application to the ASCE benchmark structures. Journal of Sound and Vibration, 2006, 291(1-2): 349-368
[56] Q. W. Zhang. Statistical damage identification for bridges using ambient vibration data. Computer and Structures, 2007, 85(7-8): 476-485
[57] M. L. Fugate, H. Sohn, C. R. Farrar. Vibration-based damage detection using statistical process control. Mechanical Systems and Signal Processing, 2001, 15(4): 707-721
[58] H. Sohn, J. A. Czarnecki, C. R. Farrar. Structural health monitoring using statistical process control. Journal of Structural Engineering, 2000, 126(11): 1356-1363
[59] J. Kullaa. Damage detection of the z24 bridge using control charts. Mechanical Systems and Signal Processing, 2003, 17(1): 163-170
[60] Z. Sun, C. C. Chang. Statistical wavelet-based method for structural health monitoring. Journal of Structural Engineering, 2004, 130(7): 1055-1062
[61]李天匀,刘士光,李喆,等.振动功率流方法诊断梁的损伤.振动工程学报, 2000, 13(4): 638-643
[62]李天匀,刘理,刘土光.周期梁结构破损诊断的振动功率流特性.声学学报, 1999, 24(2): 143-148
[63] T. Y. Li, T. Zhang, J. X. Liu, et al. Vibration wave analysis of infinite damaged beam using structure-born power flow. Applied Acoustics, 2004, 65(1): 91-100
[64] T. Y. Li, J. X. Liu, T. Zhang. Vibrational power flow characteristics of circular plate structures with peripheral surface crack. Journal of Sound and Vibration, 2004, 276(3-5): 1081-1091
[65]朱翔,李天匀,赵耀,等.含轴对称裂纹的圆柱壳输入功率流特性.中国舰船研究, 2006, 1(8): 21-25
[66]李天匀,朱翔,赵耀,等.含环向表面裂纹管道功率流特性与裂纹识别.海洋工程, 2007, 25(2): 57-63
[67] D. R. Mahapatra, S. Gopalakrishnan. Spectral finite element analysis of coupled wave propagation in composite beams with multiple delaminations and strip inclusions. International Journal of Solids and Structures, 2004, 41(5-6): 1173-1208
[68]王丹生,朱宏平.基于波传播和阻抗特性的裂纹梁损伤识别.振动、测试与诊断, 2005, 25(3): 186-189
[69]杨秋伟,刘济科.损伤识别一种改进的残余力向量法.固体力学学报, 2006, 27(1): 83-85
[70] J. He. Analytical stiffness matrix correction using measured vibration modes. Nodal Analysis, 1986, 1(3):9-14
[71]吴琼.基于数学模型的结构破损定位方法研究: [硕士学位论文].南京:南京航空航天大学, 1997
[72] M. F. Elkourdy, K. C. Chang, G. C. Lee. Neural networks trained by analytically simulated damage states. Journal of Computing in Civil Engineering, 1993, 7(2): 130-145
[73] N. Mitsuru, S. F. Masri, G. Anatassios, et al. A method for nonparametric damage detection through the use of neural networks. Earthquake Engineering andStructural Dynamics, 1998, 27: 997-1010
[74]何萍,李东升,王德禹.基于小波分析的结构损伤检测发展现状与展望.噪声与振动控制, 2007, 2: 1-5
[75] Z. Hou, M. Nonri. Wavelet-based approach for ASCE structural health monitoring benchmark studies. In: Proceedings of the 3th International Workshop on Structural Health Monitoring, Stanford University, Stanford, CA, 2001, 12-14
[76]李洪泉,懂亮,吕西林.基于小波变换的结构损伤识别与实验分析.土木工程学报, 2003, 36(5): 52-57
[77] Z. Sun, C. C. Chang. Structural damage assessment based on wavelet packet transforms. Journal of Structural Engineering, 2002, 128(10): 1354-1361
[78] N. E. Huang, Z. Shen. The empirical mode decomposition and Hilbert spectrum for nonlinear and non-stationary time series analysis. In: Proceedings of the Royal Society of London, Series A. 1998, 454: 903-995
[79] J. N. Yang, Y. Lei, S. Lin, et al. Hilber-Huang based approach for structural damage detection. Journal of Engineering Mechanics, 2004, 130(1): 85-95
[80]石志晓,李昕,周晶.损伤检测的经验模态分解法.大连理工大学学报, 2005, 45(3): 401-404
[81] J. N. Yang, Y. Lei, N. E. Huang. Hilbert-Huang based approach for structural damage detection. Journal of Engineering Mechanics, 2004, 130(1): 85-95
[82]熊飞.基于HHT方法的时变结构参数识别: [硕士学位论文].武汉:华中科技大学, 2007
[83] J. H. Chou, J. Ghaboussi. Genetic algorithm in structural damage detection. Computers & Structures, 2001, 79(14): 1335-1353
[84]尹涛,朱宏平,余岭.运用改进的遗传算法进行框架结构损伤识别.振动工程学报, 2006, 19(4): 525-531
[85] L. R. Ray, L. Tian. Damage detection in smart structures through sensitivity enhancing feedback control. Journal of Sound and Vibration, 1999, 227(5): 987-1002
[86] L. R. Ray, S. Marini. Optimization of control laws for damage detection in smartstructures. In: Proceedings of SPIE-the International Society for Optical Engineering, Newport Beach, CA, USA, 2000, 3984: 395-402
[87] J. S. Lew, J. N. Juang. Structural damage detection using virtual passive controllers. Journal of Guidance, Control, and Dynamics, 2002, 25(3): 419-424
[88] B. H. Koh, L. R. Ray. Localization of damage in smart structures through sensitivity enhancing feedback control. Mechanical System and Signal Processing, 2003, 17(4): 837-855
[89] B. H. Koh, L. R. Ray. Feedback controller design for sensitivity-based damage localization. Journal of Sound and Vibration, 2004, 273(1-2): 317-335
[90] B. H. Koh. Damage identification in smart structures through sensitivity enhancing control [PhD. Dissertation]. Hanover: Thayer School of Engineering, Dartmouth college, 2003
[91] J. A. Solbeck, L. R. Ray. Damage identification using sensitivity-enhancing control and identified models. Journal of Vibration and Acoustics, 2006, 128: 210-220
[92]程远胜,王怀群,汪刚.用受控结构的动力特性诊断结构的损伤.中国造船, 2004, 45(增): 134-138
[93]程远胜,杨振宇,汪刚.基于受控结构振型的损伤定位分步方法.工程力学, 2006, 23(6): 54-60
[94]程远胜,汪刚,杨振宇.基于多个控制力作用下结构动力特性的损伤定位.振动与冲击, 2006, 25(5): 186-190
[95]程远胜,吕磊,王真.基于结构柔度灵敏度的损伤定位.华中科技大学学报(自然科学版), 2007, 35(9): 5-7
[96]欧进萍,段忠东,肖仪清.海洋平台结构安全评定-理论、方法与应用.北京:科学出版社, 2003
[97]石德新,王晓天,唐立强,等.潜艇结构材料低周疲劳的损伤力学分析.哈尔滨工程大学学报, 1999, 20(4): 1-7
[98] A. Zubaydi, M. R. Haddara, A. S. J. Swamidas. Damage identification in a ship’s structure using neural networks. Ocean Engineering, 2002, 29: 1187-1200
[99] A. Budipriyanto, M. R. Haddara, A. S. J. Swamidas. Identification of damage onship’s cross stiffened plate panels using vibration response. Ocean Engineering, 2007, 34: 709-716
[100] L. Mangal, V. G. Idichandy, C. Ganapathy. Structural monitoring of offshore platforms using impulse and relaxation response. Ocean Engineering, 2001, 28(6): 689-705
[101]杨和振,李华军,黄维平.基于振动测试的海洋平台结构无损检测.振动工程学报, 2003, 16(4): 480-484
[102]张兆德,王德禹.基于固有频率的海洋平台损伤检测方法的改进.海洋工程, 2004, 22(3): 9-13
[103] Y. S. Diao, H. J. Li, X. Shi. Experiment verification of damage detection for offshore platforms by neural networks. China Ocean Engineering, 2006, 20(3): 351-360
[104]刁延松,李华军,王树青,等.基于不完备模态信息的海洋平台损伤诊断研究.海洋工程, 2006, 24(2): 14-20
[105] A. S. J. Swamidas, Y. Chen. Monitoring crack growth through change of modal parameters. Journal of Sound and Vibration, 1995, 186(2): 325-343
[106]顾仲权,马扣根,陈卫东.振动主动控制.北京:国防工业出版社, 1997
[107] R. W. Clough, J. Penzien. Dynamics of Structures. New York: McGraw-Hill, c1993
[108]陈国铭,崔延铨. SQC-4统计质量控制-控制图.北京:中国石化出版社, 1995
[109]刘锦萼,等.概率论与数理统计.北京:科学出版社, 2001
[110] E. A. Johnson, H. F. Lam, L. S. Katafygiotis, et al. Phase I IASC-ASCE structural health monitoring benchmark problem using simulated data. Journal of Engineering Mechanics, 2004, 130(1): 3-15
[111]杨光正,吴岷,张晓莉.模式识别.合肥:中国科学技术大学出版社, 2001
[112]陈塑寰.结构动态设计的矩阵摄动理论.北京:科学出版社, 1999
[113] L. Majumder, C. S. Manohar. A time-domain approach for damage detection in beam structures using vibration data with a moving oscillator as an excitation source. Journal of Sound and Vibration, 2003, 268(4): 699-716
[114] S. Choi, N. Stubbs. Damage identification in structures using the time-domainresponse. Journal of Sound and Vibration, 2004, 275(3-5): 577-590
[115] U. Galvanetto, G. Violaris. Numerical investigation of a new damage detection method based on proper orthogonal decomposition. Mechanical Systems and Signal Processing, 2007, 21(3): 1346-1361
[116] D. S. Li, Z. D. Zhang, D.Y. Wang. Damage detection methods for offshore platforms based on wavelet packet transform. China Ocean Engineering, 2005, 19(4): 701-710
[117]杨叔子,吴雅,等.时间序列分析的工程应用.武汉:华中理工大学出版社, 1992
[118]周亚军.导管架海洋平台结构振动智能主动控制研究: [博士学位论文].大连:大连理工大学, 2004
[119] D. Wang, A. Haldar. Element-level system identification with unknown input information. Journal of Engineering Mechanics, 1994, 120(1): 159-176
[120]傅志方,华宏星.模态分析理论与应用.上海:上海交通大学出版社, 2000
[121]于秀林,任雪松.多元统计分析.北京:中国统计出版社, 1999
[122]张公绪.两种质量诊断理论及其应用.北京:科学出版社, 2001
[2]张丽卿,韩兵康,李春祥.基于振动的土木工程结构损伤诊断研究进展期.自然灾害学报, 2004, 13(5): 136-143
[3] C. R. Farrar, T. A. Duffey, S. W. Doebling, et al. A statistical pattern recognition paradigm for vibration-based structural health monitoring. In: Proceedings of the 2nd International Workshop on Structural Health Monitoring, Stanford, California, USA, 2000, 764-773
[4] Y. J. Yan, L. Cheng, Z. Y. Wu, et al. Development in vibration-based structural damage detection technique. Mechanical Systems and Signal Processing, 2007, 21(5): 2198-2211
[5] O. S. Salawu. Detection of structural damage through changes in frequencies: a review. Engineering Structures, 1997, 19(9): 718-723
[6] S. W. Doebling. A summary review of vibration based damage identification methods. The Shock and Vibration Digest, 1998, 30(2): 92-105
[7]马宏伟,杨桂通.结构损伤探测的基本方法和研究进展.力学进展, 1999, 29(4): 513-527
[8]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.振动与冲击, 2002, 21(2): 1-6,10
[9]宗周红,任伟新,阮毅.土木工程结构损伤诊断研究进展.土木工程学报, 2003, 36(5): 105-110
[10]王术新,姜哲.基于结构振动损伤识别技术的研究现状及进展.振动与冲击, 2004, 23(4): 99-104
[11] E. P. Carden, P. Fanning. Vibration based condition monitoring: a review. Structural Health Monitoring, 2004, 3(4): 355-377
[12] A. Rytter. Vibration based inspection of civil engineering structures: [PhD.Dissertation]. Denmark: Department of Building Technology and Structural Engineering, Aalborg University, 1993
[13]张德文,魏阜旋.模型修正和破损诊断.北京:科学出版社, 1999
[14] P. Cawley, R. D. Adams. The location of defects in structures from measurements of natural frequencies. Journal of Strain Analysis, 1979, 14(2): 49-57
[15] N. Stubbs, R. Osegueda. Global non-destructive damage evaluation in solid. International Journal of Analytical and Experimental Modal Analysis, 1990, 5(2): 67-79
[16] F. K. Choy, R. Liang, P. Xu. Fault identification of beams on elastic foundation. Computers and Geotechnics, 1995, 17(2): 157-176
[17] S. Alamphalli, G. Fu, I. A. Aziz. Modal analysis as a bridge inspection tool. In: Proceedings of the 10th International Modal Analysis Conference, San Diego, California, 1992, 1359-1366
[18] A. E. Aktan, K. L. Lee, C. Chuntavan, et al. Modal testing for structural identification and condition assessment of constructed facilities. In: Proceeding 12th International Modal Analysis Conference, Honolulu, Hawaii, 1994, 2251: 462-468
[19] H. L. Chen, C.C. Spyrakos, G. Venkatesh. Evaluating structural deterioration by dynamic response. Journal of Structural Engineering, 1995, 121(8): 1197-1204
[20] C. R. Farrar, W. E. Baker, T. M. Bell, et al. Dynamic characterization and damage detection in the I-40 bridge over the Rio Grande. Los Alamos National Laboratory Report LA-12767-MS, Los Alamos National Laboratory, P.O. Box 1193, Los Alamos, NM, 87544, USA. 1994
[21] S. S. Law, H. S. Ward, G. B Shi, et al. Dynamic assessment of bridge load-carrying capacities. Journal of Structural Engineering, 1995, 121(3): 478-487
[22] R. D. Adams, D. L. Brown. A correlation coefficient for modal vector analysis. In: Proceeding of the first International Modal Analysis Conference, Orlando, 1982: 110-116
[23] T. Wolff, M. Richardson. Fault detection in structures from changes in their modal parameters. In: Proceedings of the 7th International Modal Analysis Conference, Las Vegas, Nevada, 1989: 87-94
[24] A. K. Pandey, M. Biswas, M. M. Samman. Damage detection from changes in curvature mode shapes. Journal of Sound and Vibration, 1991, 145(2): 321-332
[25] M. M. A. Wahab, G. D. Roeck. Damage detection in bridges using modal curvatures: applications to a real damage scenario. Journal of Sound and Vibration, 1999, 226(2): 217-235
[26] O. S. Salawn, C. Eilliams. Damage location using vibration mode shapes. In: Proceedings of the 12th International Modal Analysis Conference, Honolulu, Hawaii, 1994, 933-939
[27] A. Z. Khan, A. B. Stanbridge, D. J. Ewins. Detecting damage in vibrating structures with a scanning LDV. Optics and Lasers in Engineering, 1999, 32(6): 583-592
[28] M. Raghavendrachar, A. E. Aktan. Flexibility by multireference impact testing for bridge diagnostics. Journal of Structural Engineering, 1992, 118(8): 2186-2203
[29] J. Zhao, J. T. DeWolf. Sensitivity study for vibrational parameters used in damage detection. Journal of Structural Engineering, 1999, 125(4): 410-416
[30] A. K. Pandey, M. Biswas. Damage detection in structures using changes in flexibility. Journal of Sound and Vibration, 1994, 169(1): 3-7
[31] A. K. Pandy, M.Biswas. Experimental verification of flexibility difference method for locating damage in structures. Journal of Sound and Vibration, 1995, 184(2): 311-328
[32]孙国,顾元宪.连续梁结构损伤识别的改进柔度阵方法.工程力学, 2003, 20(4): 50-54,198
[33]曹晖, M. I. Friswell.基于模态柔度曲率的损伤检测方法.工程力学, 2006, 23(4): 33-38
[34]唐小兵,沈成武,陈定方.结构损伤识别的柔度曲率法.武汉理工大学学报, 2001, 23(8): 18-20,26
[35]张谢东,张治国,詹昊.基于曲率模态和柔度曲率的结构多损伤识别.武汉理工大学学报, 2005, 27(8): 35-37,55
[36] J. S. Lew. Using transfer function parameter changes for damage detection of structures. AIAA Journal, 1995, 33(11): 2189-2193
[37] N. M. M. Maia. Location of damage using curvature of the frequency responsefunctions. In: Proceedings of the 15th International Modal Analysis Conference, Florida, 1997: 942-946
[38] H. Y. Kim. Vibration-based damage identification using reconstructed FRFS incomposite structures. Journal of Sound and Vibration, 2003, 259(5): 1131-1146
[39] M. Palacz, M. Krawczuk. Vibration parameters for damage detection in structures. Journal of Sound and Vibration, 2002, 249(5): 999-1010
[40] N.G. Park, Y.S. Park. Identification of damage on a substructure with measured frequency response functions. Journal of Mechanical Science and Technology, 2005, 19(10): 891-1901
[41] A. Furukawa, H. Otsuka, J. Kiyono. Structural damage detection method using uncertain frequency response functions. Computer-Aided Civil and Infrastructure Engineering, 2006, 21(4): 292-305
[42] S. W. Doebling, C. R. Farrar. Statistical damage identification techniques applied to the I-40 bridge over the Rio Grande River. In: Proceedings of the 16th International Modal Analysis Conference, Santa Barbara, CA, 1998, 3243: 1717-1724
[43] L. Hermans, D. A. H. Van, L. Mevel. Health monitoring and detection of a fatigue problem of a sports car. In: Proceedings of the 17th International Modal Analysis Conference, Kissimmee, FL, USA, 1999, 1: 42-48
[44] D. W. Allen, H. Sohn, K. Worden, et al. Utilizing the sequential probability ratio test for building joint monitoring. In: Proceedings of SPIE - The International Society for Optical Engineering, 2002, 4704: 1-11
[45] Y. Xia, H. Hao. Statistical damage identification of structures with frequency changes. Journal of Sound and Vibration, 2003, 263(4): 853-870
[46]谢峻,韩大建,周毅姝.整合统计的结构损伤动力诊断三步法.振动与冲击, 2004, 23(4): 119-122
[47]王柏生,刘承斌,何国波.用统计神经网络进行结构损伤存在检测.土木工程学报, 2004, 37(8): 24-27
[48] R. F. Charles, A. D. Thomas, W. D. Scott, et al. A statistical pattern recognition paradigm for vibration-based structural health monitoring. In: Proceedings of the 2nd International Workshop on Structural Health Monitoring, Stanford, CA, 1999,8-10
[49] H. Sohn, C. R. Farrar, N. F. Hunter, et al. Structural health monitoring using statistical pattern recognition techniques. Journal of Structural and Engineering, 2000, 123(11): 1336-1356
[50] H. Sohn, C. R Farrar. Damage diagnosis using time series analysis of vibration signals. Smart Materials and Structures, 2001, 10(3): 446-451
[51] Y. Lu, F. Gao. A novel time-domain auto-regressive model for structural damage diagnosis. Journal of Sound and Vibration, 2005, 283(3-5):1031-1049
[52] H. Sohn, K. Worden, C. R Farrar. Statistical damage classification under changing environmental and operational conditions. Journal of Intelligent Material Systems and Structures, 2003, 13(9): 561-574
[53] H. Sohn, D. W. Allen, K. Worden, et al. Structural damage classification using extreme value statistics. Journal of Dynamic Systems, Measurement and Control, 2005, 127(1): 125-132
[54] G. Park, A. C. Rutherford, H. Sohn, et al. An outlier analysis framework for impedance-based structural health monitoring. Journal of Sound and Vibration, 2005, 286(1-2): 229-250
[55] K. K. Nair, A. S. Kiremidjian, K. H. Law. Time series-based damage detection and localization algorithm with application to the ASCE benchmark structures. Journal of Sound and Vibration, 2006, 291(1-2): 349-368
[56] Q. W. Zhang. Statistical damage identification for bridges using ambient vibration data. Computer and Structures, 2007, 85(7-8): 476-485
[57] M. L. Fugate, H. Sohn, C. R. Farrar. Vibration-based damage detection using statistical process control. Mechanical Systems and Signal Processing, 2001, 15(4): 707-721
[58] H. Sohn, J. A. Czarnecki, C. R. Farrar. Structural health monitoring using statistical process control. Journal of Structural Engineering, 2000, 126(11): 1356-1363
[59] J. Kullaa. Damage detection of the z24 bridge using control charts. Mechanical Systems and Signal Processing, 2003, 17(1): 163-170
[60] Z. Sun, C. C. Chang. Statistical wavelet-based method for structural health monitoring. Journal of Structural Engineering, 2004, 130(7): 1055-1062
[61]李天匀,刘士光,李喆,等.振动功率流方法诊断梁的损伤.振动工程学报, 2000, 13(4): 638-643
[62]李天匀,刘理,刘土光.周期梁结构破损诊断的振动功率流特性.声学学报, 1999, 24(2): 143-148
[63] T. Y. Li, T. Zhang, J. X. Liu, et al. Vibration wave analysis of infinite damaged beam using structure-born power flow. Applied Acoustics, 2004, 65(1): 91-100
[64] T. Y. Li, J. X. Liu, T. Zhang. Vibrational power flow characteristics of circular plate structures with peripheral surface crack. Journal of Sound and Vibration, 2004, 276(3-5): 1081-1091
[65]朱翔,李天匀,赵耀,等.含轴对称裂纹的圆柱壳输入功率流特性.中国舰船研究, 2006, 1(8): 21-25
[66]李天匀,朱翔,赵耀,等.含环向表面裂纹管道功率流特性与裂纹识别.海洋工程, 2007, 25(2): 57-63
[67] D. R. Mahapatra, S. Gopalakrishnan. Spectral finite element analysis of coupled wave propagation in composite beams with multiple delaminations and strip inclusions. International Journal of Solids and Structures, 2004, 41(5-6): 1173-1208
[68]王丹生,朱宏平.基于波传播和阻抗特性的裂纹梁损伤识别.振动、测试与诊断, 2005, 25(3): 186-189
[69]杨秋伟,刘济科.损伤识别一种改进的残余力向量法.固体力学学报, 2006, 27(1): 83-85
[70] J. He. Analytical stiffness matrix correction using measured vibration modes. Nodal Analysis, 1986, 1(3):9-14
[71]吴琼.基于数学模型的结构破损定位方法研究: [硕士学位论文].南京:南京航空航天大学, 1997
[72] M. F. Elkourdy, K. C. Chang, G. C. Lee. Neural networks trained by analytically simulated damage states. Journal of Computing in Civil Engineering, 1993, 7(2): 130-145
[73] N. Mitsuru, S. F. Masri, G. Anatassios, et al. A method for nonparametric damage detection through the use of neural networks. Earthquake Engineering andStructural Dynamics, 1998, 27: 997-1010
[74]何萍,李东升,王德禹.基于小波分析的结构损伤检测发展现状与展望.噪声与振动控制, 2007, 2: 1-5
[75] Z. Hou, M. Nonri. Wavelet-based approach for ASCE structural health monitoring benchmark studies. In: Proceedings of the 3th International Workshop on Structural Health Monitoring, Stanford University, Stanford, CA, 2001, 12-14
[76]李洪泉,懂亮,吕西林.基于小波变换的结构损伤识别与实验分析.土木工程学报, 2003, 36(5): 52-57
[77] Z. Sun, C. C. Chang. Structural damage assessment based on wavelet packet transforms. Journal of Structural Engineering, 2002, 128(10): 1354-1361
[78] N. E. Huang, Z. Shen. The empirical mode decomposition and Hilbert spectrum for nonlinear and non-stationary time series analysis. In: Proceedings of the Royal Society of London, Series A. 1998, 454: 903-995
[79] J. N. Yang, Y. Lei, S. Lin, et al. Hilber-Huang based approach for structural damage detection. Journal of Engineering Mechanics, 2004, 130(1): 85-95
[80]石志晓,李昕,周晶.损伤检测的经验模态分解法.大连理工大学学报, 2005, 45(3): 401-404
[81] J. N. Yang, Y. Lei, N. E. Huang. Hilbert-Huang based approach for structural damage detection. Journal of Engineering Mechanics, 2004, 130(1): 85-95
[82]熊飞.基于HHT方法的时变结构参数识别: [硕士学位论文].武汉:华中科技大学, 2007
[83] J. H. Chou, J. Ghaboussi. Genetic algorithm in structural damage detection. Computers & Structures, 2001, 79(14): 1335-1353
[84]尹涛,朱宏平,余岭.运用改进的遗传算法进行框架结构损伤识别.振动工程学报, 2006, 19(4): 525-531
[85] L. R. Ray, L. Tian. Damage detection in smart structures through sensitivity enhancing feedback control. Journal of Sound and Vibration, 1999, 227(5): 987-1002
[86] L. R. Ray, S. Marini. Optimization of control laws for damage detection in smartstructures. In: Proceedings of SPIE-the International Society for Optical Engineering, Newport Beach, CA, USA, 2000, 3984: 395-402
[87] J. S. Lew, J. N. Juang. Structural damage detection using virtual passive controllers. Journal of Guidance, Control, and Dynamics, 2002, 25(3): 419-424
[88] B. H. Koh, L. R. Ray. Localization of damage in smart structures through sensitivity enhancing feedback control. Mechanical System and Signal Processing, 2003, 17(4): 837-855
[89] B. H. Koh, L. R. Ray. Feedback controller design for sensitivity-based damage localization. Journal of Sound and Vibration, 2004, 273(1-2): 317-335
[90] B. H. Koh. Damage identification in smart structures through sensitivity enhancing control [PhD. Dissertation]. Hanover: Thayer School of Engineering, Dartmouth college, 2003
[91] J. A. Solbeck, L. R. Ray. Damage identification using sensitivity-enhancing control and identified models. Journal of Vibration and Acoustics, 2006, 128: 210-220
[92]程远胜,王怀群,汪刚.用受控结构的动力特性诊断结构的损伤.中国造船, 2004, 45(增): 134-138
[93]程远胜,杨振宇,汪刚.基于受控结构振型的损伤定位分步方法.工程力学, 2006, 23(6): 54-60
[94]程远胜,汪刚,杨振宇.基于多个控制力作用下结构动力特性的损伤定位.振动与冲击, 2006, 25(5): 186-190
[95]程远胜,吕磊,王真.基于结构柔度灵敏度的损伤定位.华中科技大学学报(自然科学版), 2007, 35(9): 5-7
[96]欧进萍,段忠东,肖仪清.海洋平台结构安全评定-理论、方法与应用.北京:科学出版社, 2003
[97]石德新,王晓天,唐立强,等.潜艇结构材料低周疲劳的损伤力学分析.哈尔滨工程大学学报, 1999, 20(4): 1-7
[98] A. Zubaydi, M. R. Haddara, A. S. J. Swamidas. Damage identification in a ship’s structure using neural networks. Ocean Engineering, 2002, 29: 1187-1200
[99] A. Budipriyanto, M. R. Haddara, A. S. J. Swamidas. Identification of damage onship’s cross stiffened plate panels using vibration response. Ocean Engineering, 2007, 34: 709-716
[100] L. Mangal, V. G. Idichandy, C. Ganapathy. Structural monitoring of offshore platforms using impulse and relaxation response. Ocean Engineering, 2001, 28(6): 689-705
[101]杨和振,李华军,黄维平.基于振动测试的海洋平台结构无损检测.振动工程学报, 2003, 16(4): 480-484
[102]张兆德,王德禹.基于固有频率的海洋平台损伤检测方法的改进.海洋工程, 2004, 22(3): 9-13
[103] Y. S. Diao, H. J. Li, X. Shi. Experiment verification of damage detection for offshore platforms by neural networks. China Ocean Engineering, 2006, 20(3): 351-360
[104]刁延松,李华军,王树青,等.基于不完备模态信息的海洋平台损伤诊断研究.海洋工程, 2006, 24(2): 14-20
[105] A. S. J. Swamidas, Y. Chen. Monitoring crack growth through change of modal parameters. Journal of Sound and Vibration, 1995, 186(2): 325-343
[106]顾仲权,马扣根,陈卫东.振动主动控制.北京:国防工业出版社, 1997
[107] R. W. Clough, J. Penzien. Dynamics of Structures. New York: McGraw-Hill, c1993
[108]陈国铭,崔延铨. SQC-4统计质量控制-控制图.北京:中国石化出版社, 1995
[109]刘锦萼,等.概率论与数理统计.北京:科学出版社, 2001
[110] E. A. Johnson, H. F. Lam, L. S. Katafygiotis, et al. Phase I IASC-ASCE structural health monitoring benchmark problem using simulated data. Journal of Engineering Mechanics, 2004, 130(1): 3-15
[111]杨光正,吴岷,张晓莉.模式识别.合肥:中国科学技术大学出版社, 2001
[112]陈塑寰.结构动态设计的矩阵摄动理论.北京:科学出版社, 1999
[113] L. Majumder, C. S. Manohar. A time-domain approach for damage detection in beam structures using vibration data with a moving oscillator as an excitation source. Journal of Sound and Vibration, 2003, 268(4): 699-716
[114] S. Choi, N. Stubbs. Damage identification in structures using the time-domainresponse. Journal of Sound and Vibration, 2004, 275(3-5): 577-590
[115] U. Galvanetto, G. Violaris. Numerical investigation of a new damage detection method based on proper orthogonal decomposition. Mechanical Systems and Signal Processing, 2007, 21(3): 1346-1361
[116] D. S. Li, Z. D. Zhang, D.Y. Wang. Damage detection methods for offshore platforms based on wavelet packet transform. China Ocean Engineering, 2005, 19(4): 701-710
[117]杨叔子,吴雅,等.时间序列分析的工程应用.武汉:华中理工大学出版社, 1992
[118]周亚军.导管架海洋平台结构振动智能主动控制研究: [博士学位论文].大连:大连理工大学, 2004
[119] D. Wang, A. Haldar. Element-level system identification with unknown input information. Journal of Engineering Mechanics, 1994, 120(1): 159-176
[120]傅志方,华宏星.模态分析理论与应用.上海:上海交通大学出版社, 2000
[121]于秀林,任雪松.多元统计分析.北京:中国统计出版社, 1999
[122]张公绪.两种质量诊断理论及其应用.北京:科学出版社, 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 |