Completely contactless structural health monitoring of real-life structures using cameras and computer vision

被引:179
作者
Khuc, Tung [1 ]
Catbas, F. Necati [1 ]
机构
[1] Univ Cent Florida, Orlando, FL 32816 USA
基金
美国国家科学基金会;
关键词
monitoring; camera; computer vision; targets; key-point; displacement; CRACK DETECTION; DISPLACEMENT MEASUREMENT; BRIDGE;
D O I
10.1002/stc.1852
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
A newly developed, completely contactless structural health monitoring system framework based on the use of regular cameras and computer vision techniques is introduced for obtaining displacements and vibrations of structures, which are critical responses for performance-based design and evaluation of structures. To provide contactless and practical monitoring, the current vision-based displacement measurement methods are improved by eliminating the physical target attachment. This is achieved by means of utilizing imaging key-points as virtual targets. As a result, pixel-based displacements of a monitored structural location are determined by using an improved detection and match key-points algorithm, in which false matches are identified and discarded almost completely. To transform pixel-based displacements to engineering units, a practical camera calibration method is developed because calibration standard on a physical target no longer exists. Moreover, a framework for evaluating the accuracy of vision-based displacement measurements is established for the first time, which, in return, provides users with the most crucial information of a measurement. The proposed framework along with a conventional sensor network and a data acquisition system are applied and verified on a real-life stadium during football games for structural assessment. The results obtained by the new method are successfully validated with the data acquired from sensors such as linear variable differential transformers and accelerometers. Because the proposed method does not require any type of sensor and target attachment, common field works such as sensor installation, wiring, maintaining conventional data acquisition systems are not required. This advantage enables an inexpensive and practical way for structural assessment, especially for real-life structures. Copyright (C) 2016 John Wiley & Sons, Ltd.
引用
收藏
页数:17
相关论文
共 28 条
[1]  
Alahi A, 2012, PROC CVPR IEEE, P510, DOI 10.1109/CVPR.2012.6247715
[2]   SURF: Speeded up robust features [J].
Bay, Herbert ;
Tuytelaars, Tinne ;
Van Gool, Luc .
COMPUTER VISION - ECCV 2006 , PT 1, PROCEEDINGS, 2006, 3951 :404-417
[3]   BRIEF: Binary Robust Independent Elementary Features [J].
Calonder, Michael ;
Lepetit, Vincent ;
Strecha, Christoph ;
Fua, Pascal .
COMPUTER VISION-ECCV 2010, PT IV, 2010, 6314 :778-792
[4]  
Caprioli A., 2007, IMAC 25
[5]   Structural Identification of Constructed Systems: Collective Effort toward an Integrated Approach That Reduces Barriers to Adoption [J].
Catbas, F. Necati ;
Kijewski-Correa, Tracy .
JOURNAL OF STRUCTURAL ENGINEERING, 2013, 139 (10) :1648-1652
[6]   Sensor Networks, Computer Imaging, and Unit Influence Lines for Structural Health Monitoring: Case Study for Bridge Load Rating [J].
Catbas, F. Necati ;
Zaurin, Ricardo ;
Gul, Mustafa ;
Gokce, Hasan Burak .
JOURNAL OF BRIDGE ENGINEERING, 2012, 17 (04) :662-670
[7]  
Catbas FN, 2009, 27 INT MOD AN C IMAC
[8]  
Elgamal A., 2003, P 4 INT WORKSHOP STR, P123
[9]  
Fraser C.D., 2006, WHATS GOOD GIVING SM
[10]  
Harris C., 1988, ALVEY VISION C, P147151