Crack detection with 2D wall mapping for building safety inspection

Authors

• Jose Martin Z. Maningo, De La Salle University, Manila
• Argel A. Bandala, De La Salle University, Manila
• Rhen Anjerome R. Bedruz, De La Salle University, Manila
• Elmer Jose P. Dadios, De La Salle University, Manila
• Ralph Joseph N. Lacuna, De La Salle University, Manila
• Andrea Bianca O. Manalo, De La Salle University, Manila
• Paolo Luis E. Perez, De La Salle University, Manila
• Neil Patrick C. Sia, De La Salle University, Manila

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Conference Proceeding

Source Title

2020 IEEE Region 10 Conference (TenCon)

Publication Date

11-2020

Abstract

In the Philippines, the number of earthquakes occurring has risen to an alarming rate. ’The Big One’ is one of the biggest expected catastrophes that is undoubtedly going to occur in the next decade, as said by various experts. Buildings that were able to withstand the upcoming earthquakes are to be inspected by engineers without knowing if the safety of the building is compromised. Thus, there is a need for a system that can inspect the cracks on the wall for faster and safer inspection. The objective of this study is to develop a crack-detecting system capable of analyzing the physical characteristics of cracks and mapping the surface of the wall. The model to be used for classifying and determining what cracks are, was trained with the use of Faster R-CNN machine learning architecture. Trained using the SDNET2018 combined with actual data generated by the proponents, the resulting system can detect cracks with an accuracy of 90% and classify the cracks according to the shape. The system also calculates its physical properties and has a recommender system that provides remarks on what necessary actions can be done.

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Recommended Citation

Maningo, J. Z., Bandala, A. A., Bedruz, R. R., Dadios, E. P., Lacuna, R. N., Manalo, A. O., Perez, P. E., & Sia, N. C. (2020). Crack detection with 2D wall mapping for building safety inspection. 2020 IEEE Region 10 Conference (TenCon) Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/15191

Disciplines

Electrical and Computer Engineering | Operations Research, Systems Engineering and Industrial Engineering

Keywords

Concrete—Cracking—Inspection; Walls—Cracking—Inspection; Building inspection

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