Video camera-based vibration measurement of infrastructure

Functional infrastructure-including transportation, energy, and buildings and other facilities - is key to the economic production of a country and the daily lives of its people. Due to deterioration and potential damage, timely inspections and repairs are necessary to keep infrastructure functioning at full capacity. Visual testing is one of the oldest and most widely used methods for condition assessment; however, this technique is limited since it is based on an inspector's subjective rating rather than on an objective quantitative measure of structural condition. Quantitative alternatives to visual testing have emerged over time. These include vibration analysis, in which a structure's operational resonant frequencies and mode shapes are measured and compared against a healthy baseline to detect changes. Typically, contact sensors such as accelerometers have been used to measure vibrations. When physical access to a structure is limited or the placement of contact sensors is too time-consuming, new technologies that allow for non-contact measurements can be used. Video cameras, where each pixel is effectively a sensor, can remotely collect a large amount of data from a structure. The challenge is then to interpret these videos into quantitative vibration data. In this research, newly developed computer vision techniques for analyzing small motions in videos and their application to the vibration measurement and condition assessment of infrastructure are presented. These techniques allow for qualitative visualizations of normally imperceptible motions as a form of enhanced visual testing, and quantitative measurements of the displacements and vibrations of structures as a basis for condition assessment. Computer vision algorithms for processing video are described and the technique is experimentally validated against traditional sensors. The methodology is demonstrated with a series of laboratory measurements of simple representative structures and field measurements of civil infrastructure, including the WWI Memorial Bridge in Portsmouth, New Hampshire.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Civil and Environmental Engineering.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2016

Author dc:creator

• Chen, Justin Gejune

Advisor dc:contributor.advisor

• Oral Büyüköztürk.

• Civil and Environmental Engineering.

Statement dc:rights

• M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/104119

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/104119