Abstract
Increase in span of cable-stayed bridges generally makes the bridge more flexible and prone to vibrate under environmental and operational loadings. Stay cables in some cable-stayed bridges have large amplitude vibration under the simultaneous occurrence of rain and wind, which is called rain-wind induced vibration (RWIV). The upper rivulet oscillating circumferentially on the inclined cable surface during RWIV is believed to play an important role in this phenomenon. However, its small size and high sensitivity to wind flow make the measurement of the rivulet movement challenging. Distribution of the rivulet along the entire cable hasn't been measured yet. This paper proposes a digital image processing method to measure the movement of the upper rivulet during RWIV. With this method, only a digital video camera is needed to record a video clip during the test. The video clip is transferred into a series of still images, from which the upper rivulet at each time instant is then identified by image processing. Subsequently the dynamic movement of the upper rivulet along the entire cable is obtained. The oscillation amplitude, equilibrium position, and dominant frequency of the rivulet are also presented. The results demonstrate that this non-contact, non-intrusive measurement method has good resolution and is cost-effective.
Original language | English |
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Title of host publication | SHMII 2015 - 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure |
Publisher | International Society for Structural Health Monitoring of Intelligent Infrastructure, ISHMII |
Publication status | Published - 1 Jan 2015 |
Event | 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2015 - Torino, Italy Duration: 1 Jul 2015 → 3 Jul 2015 |
Conference
Conference | 7th International Conference on Structural Health Monitoring of Intelligent Infrastructure, SHMII 2015 |
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Country/Territory | Italy |
City | Torino |
Period | 1/07/15 → 3/07/15 |
ASJC Scopus subject areas
- Building and Construction
- Civil and Structural Engineering
- Artificial Intelligence