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EARLY WARNING AND FAILURE DETECTION IN BRIDGE USING WIRELESS VIBRATION SENSOR

  • Faculty of Civil
  • Institut Teknologi Sepuluh Nopember

Research output: Contribution to journal › Conference article › peer-review

Abstract

Infrastructure of transportation has become an important aspect in Indonesia. Indonesia needs to maintain this infrastructure. The bridge is one of the important infrastructure need proper maintenance. Indonesia has over 89,000 bridges with a total length of 1,050 km. In order to maintain all the bridges, an integrated structural health monitoring system (SHMS) needs to be built. The aim of this system is to provide early warning for degradation of bridge. Hence, Kutai Kartanegara bridge failure will never repeat. The aim of this research is to detect failure in a bridge and provide adequate warning using wireless vibration sensor. Vibrations information of a bridge is main purpose of this study which enables to determine health of a bridge. A device has been built for this task from accelerometer sensors. Vibration from an accelerometer has been used to find out bridge behavior. Research of this has been done in the laboratory and field. Finite element methods and propose spectral finite element methods have been applied in this research. The finding shows that the vibration information of a bridge has a lot of important information, such as spectral type of vibrations, frequencies, damping and mode shape of structures. Several conditions in laboratory and field have been analyzed. This study shows that vibration information can be used for early warning of bridge health and failure or damage in bridge.

Original languageEnglish
Pages (from-to)425-430
Number of pages6
JournalProceedings of International Structural Engineering and Construction
Volume2
Issue number1
DOIs
Publication statusPublished - 2015
Event8th International Structural Engineering and Construction Conference, ISEC-08 2015 - Sydney [state] NSW, Australia
Duration: 23 Nov 2015 → 28 Nov 2015

Keywords

  • Accelerator Sensor
  • SFEM
  • SHMS

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