Page 85 - Read Online

Wang et al. Intell Robot 2022;2(4):391-406 Intelligence & Robotics
DOI: 10.20517/ir.2022.25

Review Open Access

Intelligent feature extraction, data fusion and

detection of concrete bridge cracks: current
development and challenges

1
Di Wang , Simon X. Yang 2
1
School of Information Science and Engineering, Chongqing Jiaotong University, Chongqing 400074, China.
2
Advanced Robotics and Intelligent Systems (ARIS) Lab School of Engineering, University of Guelph, Guelph ON N1G 2W1,
Canada.
Correspondence to: Dr. Di Wang, School of Information Science and Engineering, Chongqing Jiaotong University, No. 66, Xuefu
Avenue, Nan’an District, Chongqing 400074, China. E-mail: diwang@cqjtu.edu.cn

How to cite this article: Wang D, Yang SX. Intelligent feature extraction, data fusion and detection of concrete bridge cracks:
current development and challenges. Intell Robot 2022;2(4):391-406. https://dx.doi.org/10.20517/ir.2022.25

Received: 10 Aug 2022 First Decision: 3 Oct 2022 Revised: 30 Oct 2022 Accepted: 8 Dec 2022 Published: 23 Dec 2022

Academic Editor: Guang Chen Copy Editor: Ying Han Production Editor: Ying Han

Abstract
As a common appearance defect of concrete bridges, cracks are important indices for bridge structure health
assessment. Although there has been much research on crack identification, research on the evolution mechanism
of bridge cracks is still far from practical applications. In this paper, the state-of-the-art research on intelligent
theories and methodologies for intelligent feature extraction, data fusion and crack detection based on data-driven
approaches is comprehensively reviewed. The research is discussed from three aspects: the feature extraction level
of the multimodal parameters of bridge cracks, the description level and the diagnosis level of the bridge crack
damage states. We focus on previous research concerning the quantitative characterization problems of
multimodal parameters of bridge cracks and their implementation in crack identification, while highlighting some of
their major drawbacks. In addition, the current challenges and potential future research directions are discussed.

Keywords: Intelligent detection, crack detection, deep learning, data fusion, feature extraction

1. INTRODUCTION
As a pivotal project for economic development and residents’ lives and travel, bridges have an irreplaceable
role in modern transportation. Bridge structures inevitably incur defects such as pores and cracks when they

© The Author(s) 2022. Open Access This article is licensed under a Creative Commons Attribution 4.0
International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, sharing,
adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as
long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and
indicate if changes were made.

www.intellrobot.com