Flaking concrete detection with hammering inspection methodology based on machine learning

Research output: Contribution to conferencePaper

Abstract

Recently, efficient infrastructure maintenance methodologies have been required in Japan, because the number of aged infrastructures, such as bridges, roads, and tunnels, are increasing drastically. Actual maintenance works consist of a visual inspection, hammering test and paper based archiving. However, there are technical issues, such as a rapider education for professional inspection, infrastructure evaluation cost improvement, and shortage of skilled engineers for infrastructure maintenance. In this paper, we aimed to propose an inspection methodology based on machine learning for concrete structure maintenance using Geographic Information Systems (GIS). We also focused on a hammering test for flaking concrete detection as GIS attribute data acquisition on site. The hammering inspection methodology can evaluate health a condition of concrete surface with hammering sounds. In this research, we have applied a machine learning methodology with k-nearest neighbor (k-NN) algorithm for concrete hammering inspection works.

Original languageEnglish
Publication statusPublished - 2017 Jan 1
Event38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017 - New Delhi, India
Duration: 2017 Oct 232017 Oct 27

Other

Other38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017
CountryIndia
CityNew Delhi
Period17/10/2317/10/27

Fingerprint

Learning systems
Inspection
Concretes
Geographic information systems
Concrete construction
Data acquisition
Tunnels
Education
Health
Acoustic waves
Engineers
Costs

Keywords

  • Concrete hammering inspection
  • Flaking concrete
  • Geographic Information Systems
  • Infrastructure maintenance
  • K-nearest neighbor algorithm
  • Machine learning

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Saso, H., Katsuki, F., & Nakagawa, M. (2017). Flaking concrete detection with hammering inspection methodology based on machine learning. Paper presented at 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, New Delhi, India.

Flaking concrete detection with hammering inspection methodology based on machine learning. / Saso, Hayami; Katsuki, Futoshi; Nakagawa, Masafumi.

2017. Paper presented at 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, New Delhi, India.

Research output: Contribution to conferencePaper

Saso, H, Katsuki, F & Nakagawa, M 2017, 'Flaking concrete detection with hammering inspection methodology based on machine learning' Paper presented at 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, New Delhi, India, 17/10/23 - 17/10/27, .
Saso H, Katsuki F, Nakagawa M. Flaking concrete detection with hammering inspection methodology based on machine learning. 2017. Paper presented at 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, New Delhi, India.
Saso, Hayami ; Katsuki, Futoshi ; Nakagawa, Masafumi. / Flaking concrete detection with hammering inspection methodology based on machine learning. Paper presented at 38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017, New Delhi, India.
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