Analysis improvements of acoustic emission data in evaluation of concrete beam
Structural health monitoring (SHM) is known as an assessment on damage detection in structural engineering. Nowadays, the application of SHMhas been widely used especially on the continuous real time monitoring system with minimum labour involvement. One of the most excellent tools in SHM for real t...
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| Main Authors: | , , , , , |
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| Format: | Conference or Workshop Item |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/6595/ http://eprints.uthm.edu.my/6595/1/353.pdf |
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| Summary: | Structural health monitoring (SHM) is known as an assessment on damage detection in structural engineering. Nowadays, the application of SHMhas been widely used especially on the continuous real time monitoring system with minimum labour involvement. One of the most excellent tools in SHM for real time monitoring system is an Acoustic Emission (AE). AE waves are high frequency stress wave generated by rapid release of energy from localised sources within a material, such as crack initiation and growth. High sensitivity to crack growth, the ability to locate source, passive nature and the possibility to perform real time monitoring are some of the attractive features of AE technique. In spite of these advantages, challenges still exist in using AE technique for monitoring applications especially in analysing recorded AE data as large volume of data are usually generated during monitoring.In this research works, AE parameter, which are Signal Strength and Absolute Energy were selected to be used in determination of damage quantifications by means of Felicity and Calm. Laboratory experimental work was performed on a beam size 150x250x1900mm with concrete gred40. The beams were tested under cyclic loading with four points bending. In conclusion, AE data parameters analyses were prove to be reliable in determining the damage classification in concrete structure in accordance with the real observations during increased loading cycle |
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