大跨斜拉桥损伤识别的数值模拟与试验研究
|
摘要
随着科学技术和社会经济的快速发展,大跨度桥梁结构在工程中应用越来越多,而这些结构主要在复杂的环境中服役,另外还有材料的老化、交变荷载的疲劳效应等因素的耦合作用,这些都会造成结构的损伤,从而导致结构抗力的衰减,加大了结构发生事故的危险。当前,结构健康检测与损伤识别已经成为土木工程学科的热点研究领域,结构损伤识别问题就是根据结构表现出的一些性态去判别结构损伤的出现、位置和程度。
本文针对大跨度桥梁结构,以山东滨州黄河大桥为背景,以数值仿真和实验为手段,研究基于结构柔度和模态应变能变化的损伤识别,以及神经网络方法的损伤识别。
柔度法与模态应变能法是分别基于位移模态和应变模态的损伤识别方法,本文通过数值模拟分析说明,基于位移模态的柔度法只能识别出损伤的位置,但同时又具有一定的抗燥能力,基于应变模态的模态应变能法不仅能识别出损伤的位置还能识别出损伤的程度,是一种比较优秀的损伤识别方法。本文在此基础上引入BP神经网络,以结构模态应变能变化为样本训练了一个三次神经网络,并对损伤模拟的结果进行仿真,得到较好的结果。其次,本文在对滨州黄河大桥实验室缩尺模型的实例分析基础上,验证了这三种方法的可行性。
最后给出了本文的结论和本课题未来研究工作的展望。
With the fast development of technology and economy, more and more large-span bridges are used in engineering. However, these structures are mainly in service in the complex environment. The coupling action of material aging and fatigue effect of alternating loads can also cause structure damage, which will result in the decrease of structure bearing capacity and enhance the possibility of structure events. Currently structural health monitoring and damage identification have become the hot research field. Structural damage identification is defined that the commencement, the location and the degree of structural damage are identified according to the behavior of structure.
This paper presents the damage identification of large span structure based on structural compliance and the change of modal strain energy as well as the one of neural network method. The results are all based on modeling and test under the background of the Shandong Binzhou Yellow River highway bridge. This paper is divided into four chapters as follows:
Flexibility method and the modal strain energy method is damage identification methods based on each displacement mode and the strain mode, the paper adopted by the numerical simulation analysis, flexibility method can only identify the location of the damage ,which is based on displacement mode, but at the same time it has a certain capacity to resist noise; based on the strain mode, the modal strain energy method can not only identify the location of the damage but also identify the extent of the damage, and it is a relatively good damage identification methods. In this thesis, based on the introduction of BP neural network to structural changes in the modal strain energy for the training samples three times a neural network and simulation of damage simulation results, to achieve better result. Second, this article in the Binzhou Yellow River highway Bridge in the laboratory scale model based on the analysis of the case, to verify the feasibility of the three methods.
Finally, this paper presents the conclusion and the prospect of research work in the future.
本文针对大跨度桥梁结构,以山东滨州黄河大桥为背景,以数值仿真和实验为手段,研究基于结构柔度和模态应变能变化的损伤识别,以及神经网络方法的损伤识别。
柔度法与模态应变能法是分别基于位移模态和应变模态的损伤识别方法,本文通过数值模拟分析说明,基于位移模态的柔度法只能识别出损伤的位置,但同时又具有一定的抗燥能力,基于应变模态的模态应变能法不仅能识别出损伤的位置还能识别出损伤的程度,是一种比较优秀的损伤识别方法。本文在此基础上引入BP神经网络,以结构模态应变能变化为样本训练了一个三次神经网络,并对损伤模拟的结果进行仿真,得到较好的结果。其次,本文在对滨州黄河大桥实验室缩尺模型的实例分析基础上,验证了这三种方法的可行性。
最后给出了本文的结论和本课题未来研究工作的展望。
With the fast development of technology and economy, more and more large-span bridges are used in engineering. However, these structures are mainly in service in the complex environment. The coupling action of material aging and fatigue effect of alternating loads can also cause structure damage, which will result in the decrease of structure bearing capacity and enhance the possibility of structure events. Currently structural health monitoring and damage identification have become the hot research field. Structural damage identification is defined that the commencement, the location and the degree of structural damage are identified according to the behavior of structure.
This paper presents the damage identification of large span structure based on structural compliance and the change of modal strain energy as well as the one of neural network method. The results are all based on modeling and test under the background of the Shandong Binzhou Yellow River highway bridge. This paper is divided into four chapters as follows:
Flexibility method and the modal strain energy method is damage identification methods based on each displacement mode and the strain mode, the paper adopted by the numerical simulation analysis, flexibility method can only identify the location of the damage ,which is based on displacement mode, but at the same time it has a certain capacity to resist noise; based on the strain mode, the modal strain energy method can not only identify the location of the damage but also identify the extent of the damage, and it is a relatively good damage identification methods. In this thesis, based on the introduction of BP neural network to structural changes in the modal strain energy for the training samples three times a neural network and simulation of damage simulation results, to achieve better result. Second, this article in the Binzhou Yellow River highway Bridge in the laboratory scale model based on the analysis of the case, to verify the feasibility of the three methods.
Finally, this paper presents the conclusion and the prospect of research work in the future.
引文
1朱子.基于振动特性的结构损伤识别理论与方法研究.清华大学硕士毕业论文, 2006.
2 M. H. Richardson, M. A. Mannan, Correlating Minute Structural Faults with Changes in Modal Parameters. the. 11th International Modal Analysis Conference’93, 1993,2:893-898
3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):1~10
4张华,闫贵平.基于柔度矩阵的结构损伤识别方法.铁道建筑, 2003, 6:62~63.
5邵云飞.桁架结构损伤识别方法研究.兰州理工大学硕士毕业论文. 2007.
6刘小民,刘与行.土木工程结构损伤诊断研究进展.陕西建筑, 2006, 127:30~34
7谢汝海.桥梁结构损伤识别技术研究.山东大学硕士毕业论文. 2006.
8谭冬梅,姚三,瞿伟廉.振动模态的参数识别综述,华中科技大学学报(城市科学版), 2002, 19(3):73~78
9史治宇,吕令毅.由模态应变能法诊断结构破损的实验研究.东南大学学报, 1999, 29(2):134~138
10马宏伟,杨贵通.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
11于开平,邹经湘,庞世伟.结构系统模态参数识别方法研究进展.世界科技研究与发展,专题:工程技术, 2005:22~30
12冯新,李国强,周晶.土木工程结构健康诊断中的统计识别方法综述.地震工程与工程振动, 2005, 25(2):105~113
13周宗红,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
14于德介,雷慧,程军圣.基于BP神经网络与柔度变化的结构破损诊断.振动工程学报, 2001, 14(3):345~348
15师本强.基于动柔度变化结构损伤监测.工程力学增刊, 2001:291~297
16陈志刚.基于结构振动的损伤识别技术研究进展.山西建筑, 2007,33(6):326~327
17杨华.基于柔度矩阵法的结构损伤识别.长春理工大学学报, 2005, 28(4):22~25
18史治宇,罗绍湘,张令弥.结构破损定位的单元模态应变能变化率法.振动工程学报, 1998, 11(3):356~360
19 S. Hassiotis,Identification of Damage Using Natural Frequencies and Markov Parameters. Computers and Structures, 2000, 74:365±373
20 Y. Xia, H. Hao. Statistical Damage Identification Of Structures with Frequency Changes. Journal of Sound and Vibration, 2003, 263:853–870
21 A. Messina. Structural Damage Detection By A Sensitivity And Statistical-based Method. Journal of Sound and Vibration, 1998, 216(5):791~808
22 J. E. Mottershead. M. I. Friswell. Model Updating in Structural Dynamics:a survey. Journal of Sound and Vibration, 1993, 167(2):347~375
23 A. Alvandi, C. Cremona. Assessment of Vibration-based Damage Identification Techniques. Journal of Sound and Vibration, 2006, 292:179~202
24 Y. J. Yan, L. Cheng, Z. Y. Wu, L. H. Yam. Development in Vibration-based Structural Damage Detection Technique. Mechanical Systems and Signal Processing. 2007, 21:2198~2211
25 W. L. Bayissa, N. Haritos. Structural Damage Identification in Plates Using Spectral Strain Energy Analysis. Journal of Sound and Vibration, 2007, 307:226~249
26董聪,刘西拉.广义BP算法及网络容错性和泛化能力的研究.控制与决策, 1998, 13(2):120~124
27潘旦光,董聪.局部损伤梁动力问题的近似计算方法.应用力学学报, 2005, 22(1):119~122
28董聪.现代结构系统可靠性理论及其应用[M].北京:科学出版社, 2001
29 A. K. Pandey, M. Biswas. Samman M.M. Damage detection from change in curvature mode shape[J], Journal of Sound and Vibration, 1991, 145(2):321~332
30李国强,李杰.工程结构动力检测理论与应用.北京:科学出版社, 2002
31姜绍非.基于神经网络的结构优化与损伤检测.北京:科学出版社, 2002
32 J. Zhao, J. N. Ivan and J. T. Dewolf. Structure Damage Detection Using Artificial Neural Networks[J]. Journal of Infrastructure Systems, 1998,4:93~101
33 A. K. Pandey, M. Biswas. Damage Detection in Structures Using Changes in Flexibility. Journal of Sound and Vibration. 1994, 169(1):3~17
34郭杏林,陈建林.基于神经网络技术的结构损伤探测.大连理工大学学报. 2002, 42(3):269~273
35 H. W. Hu, B. T. Wang, C. B. Wu. Application of Modal Strain Energy Index to the Damage Detection of Cantilever Beams.
36李佳升,颜东煌,田仲初.三塔斜拉桥整体模型试验的实施.长沙交通学院学报, 1999, 15(3):34~37
37布占宇,吕忠达,徐爱敏,叶贵如,谢旭.考虑索局部振动的斜拉桥动力特性研究, 2005, 39(1):143~147
38蔺鹏臻,刘凤奎.拉索对斜拉桥体系面内弯曲频率的影响分析.城市道桥与防洪. 2005, 2:41~43
39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
40谭冬梅,姚三,瞿伟廉.振动模态的参数识别综述.华中科技大学学报. 2002, 9(19):73~78
41 J. S. Lew. Using Transfer Function Parameter Changes for Damage Detection of Structures, American Institute of Aeronautics and Astronautics Journal. 1995, 33(11):2189~2193
42 C. David, Zimmerman. Structural Damage Detection Using Frequency Response Function. Proceedings of 13th International Miniature Aerobatic Club, 1995, 179~184
43 Q. Fu, Y. Deng, L. Mao. Wireless Measurement System of Cable Tension Force Based on LabVIEW. SICE Annual Conference 2004, Aug 4-6 2004[C]. Sapporo, Japan: Society of Instrument and Control Engineers (SICE), Tokyo, 113, Japan. 2004:161～164
44 H. N. Cho, Y. M. Choi, S. C. Lee, et al. Critical Threshold Value for Monitoring and Management of Cable Tension Force in Cable-stayed Bridge. Proceedings of the 11th Asian Pacific Conference on Nondestructive Testing, Nov 3-7 2003[C]. Jeju Island, South Korea: Trans Tech Publications Ltd, Zurich-Ueticon, CH-8707, Switzerland. 2004:1977～1982
45 G. Zheng, J. M Ko, Y. Q. Ni. Multimode-Based Evaluation of Cable TensionForce in Cable-Supported Bridges. Smart Systems for Bridges, Structures, and Highways-Smart Structures and Materials 2001-, Mar 5-7 2001[C]. Newport Beach, CA:Society of Photo-Optical Instrumentation Engineers. 2001:511～522
46 Q. Fu, Y. Deng, T. Qiao, et al. Virtual Test System of Cable Tension Force Based on Lab VIEW. Fifth International Symposium on Instrumentation and Control Technology, Oct 24-27 2003[C]. Beijing, China: The International Society for Optical Engineering. 2003:512～515
2 M. H. Richardson, M. A. Mannan, Correlating Minute Structural Faults with Changes in Modal Parameters. the. 11th International Modal Analysis Conference’93, 1993,2:893-898
3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):1~10
4张华,闫贵平.基于柔度矩阵的结构损伤识别方法.铁道建筑, 2003, 6:62~63.
5邵云飞.桁架结构损伤识别方法研究.兰州理工大学硕士毕业论文. 2007.
6刘小民,刘与行.土木工程结构损伤诊断研究进展.陕西建筑, 2006, 127:30~34
7谢汝海.桥梁结构损伤识别技术研究.山东大学硕士毕业论文. 2006.
8谭冬梅,姚三,瞿伟廉.振动模态的参数识别综述,华中科技大学学报(城市科学版), 2002, 19(3):73~78
9史治宇,吕令毅.由模态应变能法诊断结构破损的实验研究.东南大学学报, 1999, 29(2):134~138
10马宏伟,杨贵通.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
11于开平,邹经湘,庞世伟.结构系统模态参数识别方法研究进展.世界科技研究与发展,专题:工程技术, 2005:22~30
12冯新,李国强,周晶.土木工程结构健康诊断中的统计识别方法综述.地震工程与工程振动, 2005, 25(2):105~113
13周宗红,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
14于德介,雷慧,程军圣.基于BP神经网络与柔度变化的结构破损诊断.振动工程学报, 2001, 14(3):345~348
15师本强.基于动柔度变化结构损伤监测.工程力学增刊, 2001:291~297
16陈志刚.基于结构振动的损伤识别技术研究进展.山西建筑, 2007,33(6):326~327
17杨华.基于柔度矩阵法的结构损伤识别.长春理工大学学报, 2005, 28(4):22~25
18史治宇,罗绍湘,张令弥.结构破损定位的单元模态应变能变化率法.振动工程学报, 1998, 11(3):356~360
19 S. Hassiotis,Identification of Damage Using Natural Frequencies and Markov Parameters. Computers and Structures, 2000, 74:365±373
20 Y. Xia, H. Hao. Statistical Damage Identification Of Structures with Frequency Changes. Journal of Sound and Vibration, 2003, 263:853–870
21 A. Messina. Structural Damage Detection By A Sensitivity And Statistical-based Method. Journal of Sound and Vibration, 1998, 216(5):791~808
22 J. E. Mottershead. M. I. Friswell. Model Updating in Structural Dynamics:a survey. Journal of Sound and Vibration, 1993, 167(2):347~375
23 A. Alvandi, C. Cremona. Assessment of Vibration-based Damage Identification Techniques. Journal of Sound and Vibration, 2006, 292:179~202
24 Y. J. Yan, L. Cheng, Z. Y. Wu, L. H. Yam. Development in Vibration-based Structural Damage Detection Technique. Mechanical Systems and Signal Processing. 2007, 21:2198~2211
25 W. L. Bayissa, N. Haritos. Structural Damage Identification in Plates Using Spectral Strain Energy Analysis. Journal of Sound and Vibration, 2007, 307:226~249
26董聪,刘西拉.广义BP算法及网络容错性和泛化能力的研究.控制与决策, 1998, 13(2):120~124
27潘旦光,董聪.局部损伤梁动力问题的近似计算方法.应用力学学报, 2005, 22(1):119~122
28董聪.现代结构系统可靠性理论及其应用[M].北京:科学出版社, 2001
29 A. K. Pandey, M. Biswas. Samman M.M. Damage detection from change in curvature mode shape[J], Journal of Sound and Vibration, 1991, 145(2):321~332
30李国强,李杰.工程结构动力检测理论与应用.北京:科学出版社, 2002
31姜绍非.基于神经网络的结构优化与损伤检测.北京:科学出版社, 2002
32 J. Zhao, J. N. Ivan and J. T. Dewolf. Structure Damage Detection Using Artificial Neural Networks[J]. Journal of Infrastructure Systems, 1998,4:93~101
33 A. K. Pandey, M. Biswas. Damage Detection in Structures Using Changes in Flexibility. Journal of Sound and Vibration. 1994, 169(1):3~17
34郭杏林,陈建林.基于神经网络技术的结构损伤探测.大连理工大学学报. 2002, 42(3):269~273
35 H. W. Hu, B. T. Wang, C. B. Wu. Application of Modal Strain Energy Index to the Damage Detection of Cantilever Beams.
36李佳升,颜东煌,田仲初.三塔斜拉桥整体模型试验的实施.长沙交通学院学报, 1999, 15(3):34~37
37布占宇,吕忠达,徐爱敏,叶贵如,谢旭.考虑索局部振动的斜拉桥动力特性研究, 2005, 39(1):143~147
38蔺鹏臻,刘凤奎.拉索对斜拉桥体系面内弯曲频率的影响分析.城市道桥与防洪. 2005, 2:41~43
39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
40谭冬梅,姚三,瞿伟廉.振动模态的参数识别综述.华中科技大学学报. 2002, 9(19):73~78
41 J. S. Lew. Using Transfer Function Parameter Changes for Damage Detection of Structures, American Institute of Aeronautics and Astronautics Journal. 1995, 33(11):2189~2193
42 C. David, Zimmerman. Structural Damage Detection Using Frequency Response Function. Proceedings of 13th International Miniature Aerobatic Club, 1995, 179~184
43 Q. Fu, Y. Deng, L. Mao. Wireless Measurement System of Cable Tension Force Based on LabVIEW. SICE Annual Conference 2004, Aug 4-6 2004[C]. Sapporo, Japan: Society of Instrument and Control Engineers (SICE), Tokyo, 113, Japan. 2004:161～164
44 H. N. Cho, Y. M. Choi, S. C. Lee, et al. Critical Threshold Value for Monitoring and Management of Cable Tension Force in Cable-stayed Bridge. Proceedings of the 11th Asian Pacific Conference on Nondestructive Testing, Nov 3-7 2003[C]. Jeju Island, South Korea: Trans Tech Publications Ltd, Zurich-Ueticon, CH-8707, Switzerland. 2004:1977～1982
45 G. Zheng, J. M Ko, Y. Q. Ni. Multimode-Based Evaluation of Cable TensionForce in Cable-Supported Bridges. Smart Systems for Bridges, Structures, and Highways-Smart Structures and Materials 2001-, Mar 5-7 2001[C]. Newport Beach, CA:Society of Photo-Optical Instrumentation Engineers. 2001:511～522
46 Q. Fu, Y. Deng, T. Qiao, et al. Virtual Test System of Cable Tension Force Based on Lab VIEW. Fifth International Symposium on Instrumentation and Control Technology, Oct 24-27 2003[C]. Beijing, China: The International Society for Optical Engineering. 2003:512～515