Analysing method for acoustic emission clustering system on reinforced concrete beam

• Main Author: Saiful Bahari, Nur Amira Afiza
• Format: Thesis
• Language: English; English; English
• Published: 2018
• Subjects: TA401-492 Materials of engineering and construction. Mechanics of materials
• Online Access: http://eprints.uthm.edu.my/355/

Acoustic Emission (AE) is a non-destructive testing (NDT) method used for damage detection in structural engineering. Nowadays, NDT is widely used especially on continuous real-time monitoring systems with minimum labour involvement. It could also be used to discriminate the different types of damage occurring in reinforced concrete (RC) beam. In spite of these advantages, difficulties still exist in using the AE technique for monitoring applications particularly in analysing recorded AE data due to the large quantity of data involved. Other than that, the main problem associated with data analysis is the discrimination between different AE sources and the analysis of AE signals in order to identify the most critical damage mechanism. Clustering analysis is a technique in which a set of objects are assigned to a group called cluster. The need for effective data analysis in the clustering system can be linked to three main objectives in this research; (1) to determine the type of failure on reinforced concrete beams through the AE system; (2) to identify and discriminate the AE data parameters via crack classification (tensile and shear movement); (3) to verify the crack classification of Rise Amplitude (RA) clustering by using the NI LabVIEW clustering algorithm. Hence, the purpose of this research is to obtain the crack classification by using the RA clustering analysing (RAC) method. It was found that, the result by using RAC analysing method was reliable system to cluster the cracking on RC beam. In addition, these analysing system could use in any different sizing of beam.