DocumentCode :
2187604
Title :
New developed testing system of defect in cementitious material with Neural Network
Author :
Saechai, Saowanee ; Kusalanggoorawat, Phatra ; Kongprawechnon, Waree ; Sahamitmongkol, Raktipong
Author_Institution :
Sirindhorn Int. Inst. of Technol., Thammasat Univ., Pathumthani, Thailand
fYear :
2011
fDate :
17-19 May 2011
Firstpage :
565
Lastpage :
568
Abstract :
A developed testing system of defect detection in mortar is introduced. Base on this development, more information of the defection could be obtained. Machine Learning algorithm, named Artificial Neural Network (ANN)with pattern recognition, is used to verify the results. As a result, the medium with and without defects could be identified. More over, the number of defects could be indicated. This study shows the methodology for implementing the system, factors to be considered, and verifying the results. Classification examples are given to demonstrate the performance of the network by using the data set from different mediums. The result shows the effectiveness of this classifier and possibility of further development.
Keywords :
cements (building materials); learning (artificial intelligence); mortar; neural nets; pattern recognition; ultrasonic materials testing; artificial neural network; cementitious material; defect detection; machine learning algorithm; neural network; pattern recognition; testing system; Acoustics; Frequency control; Frequency domain analysis; Mortar; Artificial Neural Network; Defect Detection; Pattern Recognition; Ultrasonic Wave;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2011 8th International Conference on
Conference_Location :
Khon Kaen
Print_ISBN :
978-1-4577-0425-3
Type :
conf
DOI :
10.1109/ECTICON.2011.5947901
Filename :
5947901
Link To Document :
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