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Proceedings Paper

Vibration studies of simply supported beam based on binocular stereo vision
Author(s): Chaojia Liang; Huaxia Deng; Jin Zhang; Liandong Yu
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Paper Abstract

That sensors are used to collect experimental data is still prevalent nowadays. A common way to analyze the mode of vibration of a structure, lots of sensors may required to be installed on the structure in order to ensure completeness of data. However, if these data can be obtained based on machine vision, the effects caused by sensors on the beam would be removed. A new kind of non-contact method will be used to measure the mode of vibration of simply supported beam. In this paper, the basic theory of the simply supported beam and machine vision will be introduced. It is different from traditional way that is based on a large number of sensors to collect experimental data. Two cameras record the vibration process of simply supported beam while the beam is vibrating caused by an exciter. After those images that have recorded the vibration process of simply supported beam are processed, calibration and registration included, those data collected by sensors also are reconstructed by traditional modal test method for comparison. Through comparing the machine vision method and sensor based method, errors caused by the process of reconstruction might be analyzed. The first order modal vibration modes by using two ways and combining with finite element method to produce can also be analyzed what their differences are.

Paper Details

Date Published: 6 March 2015
PDF: 9 pages
Proc. SPIE 9446, Ninth International Symposium on Precision Engineering Measurement and Instrumentation, 94463M (6 March 2015); doi: 10.1117/12.2181390
Show Author Affiliations
Chaojia Liang, Hefei Univ. of Technology (China)
Huaxia Deng, Hefei Univ. of Technology (China)
Jin Zhang, Hefei Univ. of Technology (China)
Liandong Yu, Hefei Univ. of Technology (China)

Published in SPIE Proceedings Vol. 9446:
Ninth International Symposium on Precision Engineering Measurement and Instrumentation
Junning Cui; Jiubin Tan; Xianfang Wen, Editor(s)

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