期刊文献+

基于固有频率向量的结构损伤检测实验研究 被引量:7

EXPERIMENTAL INVESTIGATION OF STRUCTURAL DAMAGE DETECTION BASED ON THE NATURAL FREQUENCY VECTOR
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摘要 引入固有频率向量及固有频率向量置信准则的概念,提出基于固有频率向量的结构损伤检测方法。以一个8层剪切框架模型的损伤检测为例,阐述用该方法进行损伤检测的原理和步骤。首先根据修正后结构的动力学模型,用局部刚度减小的方法,模拟结构不同位置和不同程度的损伤,计算出损伤结构序列的固有频率,并组成固有频率向量作为损伤数据库。然后实验测试出带损伤实物模型的固有频率,并组成固有频率向量,再根据该实测固有频率向量与损伤数据库中固有频率向量之间的固有频率向量置信准则,对损伤程度和位置进行检测。对框架结构的损伤检测实验结果表明,文中的方法可以准确地识别出损伤的位置,并可以较准确地检测出损伤的程度,而且实验结果证明文中方法还具有较强的抗测量噪声的能力。 Based on the fact that for structure with small damage, its natural frequencies will have some changes compared to its primary intact state, the concept of natural frequency vector is introduced and a new method to detect small damage of structure is prop- osed. The principle of damage detection method is described and an 8-story shear frame smleture is used to demonstrate the damage detection procedure. In the detection, the natural frequency veetor assurance criterion (NFVAC) is also intredueed and used as the damage index. The damage detection results show that based on the concept of natural fi:equency vector, the damage location and extents of the frame structure can be detected with good aceuracy and this method is robust to measuring noise.
出处 《机械强度》 EI CAS CSCD 北大核心 2008年第6期897-902,共6页 Journal of Mechanical Strength
基金 教育部新世纪优秀人才支持计划(NCET-04-0965) 航空科学基金(04I53072) 高等学校博士学科点专项科研基金(20060699001)资助课题~~
关键词 损伤检测 固有频率向量 固有频率向量置信准则(natural FREQUENCY VECTOR ASSURANCE criterion NFVAC)损伤位置 框架结构 Damage detection Natural firequency vector Natural frequency vector assurance criterion (NFVAC) Damage location Frame structure
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参考文献8

  • 1Alvandi A, Cremona C. Assessment of vibration-based damage identification techniques[J]. Journal of Sound and Vibration, 2006, 292: 179- 202.
  • 2Dilena M, Morassi A. Damage detection in discrete vibrating systems[J]. Journal of Sound and Vibration, 2006, 289: 830-850.
  • 3Dilena M, Morassi A. The use of antiresonances for crack detection in beams[J]. Journal of Sound and Vibration, 2004, 276: 195-214.
  • 4Yang Q w, Liu J K. A coupled method for structural damage identification[J]. Journal of Sound and Vibration, 2006, 296: 401-405.
  • 5罗武,赵美英,万小朋.基于模态应变能比与神经网络的复合材料结构损伤辨识[J].机械强度,2006,28(1):146-149. 被引量:7
  • 6王修勇,陈政清.基于柔度矩阵和神经网络的结构损伤识别法[J].机械强度,2002,24(2):164-167. 被引量:12
  • 7Allernang R J, Brown D L. A correlation coefficient for modal vector analysis[C]//Proceeding of the 1 st International Modal Analysis Confer- ence: Orlando, Florida, USA: 1982. Orlando: Society for Experimental Mechanics (SEM), 1982: 110-116.
  • 8王乐,杨智春,李斌,谭光辉,刘江华.基于固有频率向量的模型修正方法[J].西北工业大学学报,2008,26(1):93-98. 被引量:8

二级参考文献15

  • 1李斌,杨智春,孙浩.改进的基于附加已知质量的模型修正方法[J].振动工程学报,2004,17(3):311-316. 被引量:9
  • 2黄方林,顾松年.用残余能量法诊断结构故障[J].机械强度,1996,18(4):5-8. 被引量:6
  • 3Seth Kessler S,Mark Spearing S.Damage detection in composite materials using frequency response methods.Journal of Composites,2002,33(part B):87-95.
  • 4Sampaio R P C,Maia N M M,Silva J M M.Damage detection using the frequency response-function curvature method.Journal of Sound and Vibration,1999,226(5):1029-1046.
  • 5马丁.哈森,霍华德.旦姆斯.神经网络设计.北京:机械工业出版社,2002.
  • 6Hu J S L, Li Huajun, Wang Shuqing. Cross-Model Cross-Mode Method for Model Updating. Mechanical Systems and Signal Processing, 2007, 21(4):1690-1703
  • 7Link M, Friswell M. Working Group 1: Generation of Validated Structural Dynamic Models-Results of a Benchmark Study Utilizing the GARTEUR SM-AG19 Test-Bed. Mechanical Systems and Signal Processing, 2003, 17(1): 9-20
  • 8Allemang R J, Brown D L. A Correlation Coefficient for Modal Vector Analysis. In Proceeding of the 1st International Modal Analysis Conference: Orlando, Florida, USA: 1982. Orlando: Society for Experimental Mechanics (SEM), 1982:110-116
  • 9Ewins D J. Modal Testing. Theory and Practice. New York: Wiley, 1985
  • 10Goge D, Link M. Assessment of Computational Model Updating Procedures with Regard to Model Validation. Aerospace Science and Technology, 2003, 7:47-61

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同被引文献48

引证文献7

二级引证文献18

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