Technical Papers
Jan 28, 2020

Developing Novel Monocular-Vision-Based Standard Operational Procedures for Nondestructive Inspection on Constructed Concrete Cracks

Publication: Journal of Performance of Constructed Facilities
Volume 34, Issue 2

Abstract

To mitigate the limitations in traditional concrete crack-measuring methods such as low degree in automation and high cost, this study aims to develop a novel method with standard operational procedures (SOP) for nondestructive inspection and automeasure on bridge concrete cracks based on monocular vision and the Harris algorithm. Through experiments in four scenarios using commercially available software as the programming and imaging-processing interface, a novel method, named Mono-Harris, with high automation, high detection speed, and high precision for nondestructive inspection and automeasure of bridge concrete cracks based on monocular vision and the Harris algorithm was developed. There were three main criteria in the experiments, including the shooting angle (parallel and not parallel), shooting distance (far and near), and checkerboard target positioning. Results revealed positively that the combination of monocular vision and image processing technique could effectively measure bridge concrete cracks and the Mono-Harris method developed in this study was efficient and effective.

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Data Availability Statement

All data, models, and code generated or used during the study appear in the published article.

Acknowledgments

Authors are grateful to the Tongjiang Scholar Special Funding for financial support through grant number (605-50X17234), Quanzhou science and technology bureau for financial support through grant number (2018Z010), and Huaqiao University through grant number (17BS201).

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Published In

Go to Journal of Performance of Constructed Facilities
Journal of Performance of Constructed Facilities
Volume 34Issue 2April 2020

History

Received: Apr 29, 2019
Accepted: Aug 28, 2019
Published online: Jan 28, 2020
Published in print: Apr 1, 2020
Discussion open until: Jun 28, 2020

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Authors

Affiliations

Lifang Zhang [email protected]
Research Fellow, Intelligence and Automation in Construction Fujian Province Higher-Educational Engineering Research Centre, College of Civil Engineering, Huaqiao Univ., Xiamen 361021, China. Email: [email protected]
Distinguished Professor and Director of Intelligence and Automation in Construction Fujian Province Higher-Educational Engineering Research Centre, College of Civil Engineering, Huaqiao Univ., Xiamen 361021, China (corresponding author). ORCID: https://orcid.org/0000-0001-7892-3575. Email: [email protected]
Assistant Professor, Dept. of Surveying, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kajang, Selangor 43000, Malaysia. ORCID: https://orcid.org/0000-0003-4332-0031. Email: [email protected]
Chair Professor, Dept. of Building and Real Estate, Hong Kong Polytechnic Univ., Hong Kong 999077, Hong Kong. ORCID: https://orcid.org/0000-0002-3187-9041. Email: [email protected]

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