非接触式结构动力特性识别方法及试验验证

摘要
图/表
参考文献(14)
相关文章 (15)

全文: PDF (2168 KB) HTML (1 KB)
输出: BibTeX | EndNote (RIS)

摘要针对传统结构振动监测中存在的弊端，比如传感器和线缆布设困难、干扰交通等，提出了一种基于机器视觉技术的非接触式结构动力特性识别方法。发展了基于模板匹配算法的多点结构动态位移计算方法，利用多点结构位移时程信号识别结构动力特性。制作模拟桥塔的钢竖杆并安装LED灯和加速度传感器，同时采用机器视觉位移测量系统和加速度测量系统进行振动监测及动力特性识别比较研究，试验结果表明本文方法和加速度测量方法计算得到的结构动力指标相当吻合，验证了本文方法在结构动力特性识别方面的可行性。

	服务

	把本文推荐给朋友
	加入我的书架
	加入引用管理器
	E-mail Alert
	RSS
	作者相关文章
	董传智
	叶肖伟
	刘坦

关键词 ：振动监测, 结构位移, 机器视觉技术, 模板匹配算法, 模态参数识别

Abstract：

A noncontact structural dynamic characteristics identification method based on machine vision technology was proposed in order to overcome the existent drawbacks of traditional structural vibration monitoring, such as, difficult arrangement of sensors and wires, disturbing traffic, etc. The method of multi-point structural dynamic displacement calculation based on the pattern matching algorithm was developed. Structural dynamic characteristics were identified by using multi-point structural displacement time history signals. A vertical steel bar to analog a bridge tower was fabricated, LED lamps and accelerometers were deployed on it. A comparative investigation for vibration monitoring and dynamic characteristics identification was conducted using the vision-based displacement measurement system and the acceleration measurement system synchronously. The test results demonstrated that the structural dynamic indices with the proposed system and the acceleration measurement system agree well, they verify the feasibility of the proposed method for structural dynamic characteristics identification.

Key words： vibration monitoring structural displacement machine vision technology pattern matching algorithm modal parameter identification

收稿日期: 2015-06-12 出版日期: 2016-12-25

引用本文:

董传智，叶肖伟，刘坦. 非接触式结构动力特性识别方法及试验验证[J]. 振动与冲击, 2017, 36(1): 188-193.
DONG Chuan-zhi, YE Xiao-wei, LIU Tan. Noncontact structural dynamic characteristics identification method and its test verification. JOURNAL OF VIBRATION AND SHOCK, 2017, 36(1): 188-193.

链接本文:

http://jvs.sjtu.edu.cn/CN/ 或 http://jvs.sjtu.edu.cn/CN/Y2017/V36/I1/188

[1] Chatzis M N, Chatzi E N and Smyth A W. An experimental validation of time domain system identification methods with fusion of heterogeneous data [J], Earthquake Engineering & Structural Dynamics, 2015, 44: 523–547.
[2] 樊可清,倪一清,高赞明. 改进随机子空间系统辨识方法及其在桥梁状态监测中的应用[J]. 中国公路学报, 2004, 17(04): 73-76.
FAN Ke-qing, NI Yi-qing and GAO Zan-ming. Improved stochastic system identification approach with its application in bridge condition monitoring [J]. China Journal of Highway and Transport, 2004, 17(4): 73-76.
[3] Kim R E, Moreu F and Spencer. Jr B F. System identification of an in-service railroad bridge using wireless smart sensors [J], Smart Structures and Systems, 2015, 15(3): 683-698.
[4] Au S K, Zhang F L and Ni Y C. Bayesian operational modal analysis: Theory, computation, practice [J], Computers and Structures, 2013, 126: 3-14.
[5] Yang Y, Wang X and Wu Z S. Experimental study of vibration characteristics of FRP cables for long-span cable-stayed bridges [J], Journal of Bridge Engineering, 2015, 20, 04014074.
[6] 李枝军,韩晓林,李爱群,缪长青,冯兆祥.悬索桥桥塔挂缆前后动态特性分析与测试[J].中国公路学报, 2007, 05: 54-58.
LI Zhi-jun, HAN Xiao-lin, LI Ai-qun, MIAO Chang-qing and FENG Zhao-xiang. Dynamic analysis and test of bridge tower of suspension bridge before and after cable installed [J]. China Journal of Highway and Transport, 2007, 05: 54-58.
[7] Ye X W, Ni Y Q, Wai T T, Wong K Y, Zhang X M and Xu F. A vision-based system for dynamic displacement measurement of long-span bridges: algorithm and verification [J], Smart Structures and Systems, 2013, 12(3-4), 363-379.
[8] 叶肖伟,张小明,倪一清,黄启远,樊可清. 基于机器视觉技术的桥梁挠度测试方法[J]. 浙江大学学报(工学版), 2014, 48(5): 813-819.
YE Xiao-wei, Zhang Xiao-ming, NI Yi-qing, WONG Kai-yuen and FAN Ke-qing. Bridge deflection measurement method based on machine vision technology [J]. Journal of Zhejiang University (Engineering Science), 2014, 48(5): 813-819.
[9] Ye X W, Yi T H, Dong C Z, Liu T and Bai H. Multi-point displacement monitoring of bridges using a vision-based approach [J], Wind and Structures, 2015, 20(2): 315-326.
[10] Fukuda Y, Feng M Q, Narita Y, Kaneko S and Tanaka T. Vision-based displacement sensor for monitoring dynamic response using robust object search algorithm [J], IEEE Sensors Journal, 2013, 13(12): 4725-4732.
[11] Busca G, Cigada A, Mazzoleni P and Zappa E. Vibration monitoring of multiple bridge points by means of a unique vision-based measuring system [J], Experimental Mechanics, 2014, 54: 255-271.
[12] Ribeiro D, Calçada R., Ferreira J and Matins T. Non-contact measurement of the dynamic displacement of railway bridges using an advanced video-based system [J]. Engineering Structures, 2014, 75: 164-180.
[13] Gonzalez R C and Woods R E. Digital Image Processing, (3rd Edition) [M], 2008, Pearson Prentice Hall, Upper Saddle River, NJ, USA.
[14] Clough R W and Penzien J. Dynamics of Structures, (3rd Edition) [M], 2003, Computers & Structures, Inc., Berkeley, CA, USA.