Vision-Based Damage Detection Using Inclination Angles and Curvature

Chidiebere B. Obiechefu*, Rolands Kromanis, Fouad Mohammad, Zakwan Arab

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Downloads (Pure)


This paper presents damage detection techniques for structural health monitoring of horizontal structures using computer vision. A technique based on the derivation of curvature from the second order polynomial equations of the deflection curve is introduced. The technique, as well as inclination angles, and the primary deflection data are applied for damage detection on a simply supported laboratory beam subjected to a point load at its midspan. The beam is loaded and unloaded at intact and damaged states. Measurements are obtained with a smartphone. The measurement resolution is 1 mm/px—a relatively low value. Measurements are pre-processed for measurement noise. Results show that damage can be detected using all three responses analysis techniques. The curvature and inclination angle techniques outperform the deflection technique, especially for damage identification.

Original languageEnglish
Title of host publicationCivil Structural Health Monitoring
Subtitle of host publicationProceedings of CSHM-8 Workshop
EditorsCarlo Rainieri, Giovanni Fabbrocino, Nicola Caterino, Francesca Ceroni, Matilde A. Notarangelo
Place of PublicationCham
Number of pages13
ISBN (Electronic)978-3-030-74258-4
ISBN (Print)978-3-030-74257-7
Publication statusPublished - 25 Aug 2021
Event8th Civil Structural Health Monitoring Workshop, CSHM-8 2021 - Virtual, Online
Duration: 31 Mar 20212 Apr 2021

Publication series

NameLecture Notes in Civil Engineering
ISSN (Print)2366-2557
ISSN (Electronic)2366-2565


Conference8th Civil Structural Health Monitoring Workshop, CSHM-8 2021


  • Computer vision
  • Curvature
  • Damage detection
  • Inclination angle
  • Static response


Dive into the research topics of 'Vision-Based Damage Detection Using Inclination Angles and Curvature'. Together they form a unique fingerprint.

Cite this