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Review
. 2020 Jul 16;20(14):3954.
doi: 10.3390/s20143954.

Review of Non-Destructive Civil Infrastructure Evaluation for Bridges: State-of-the-Art Robotic Platforms, Sensors and Algorithms

Habib Ahmed  1 , Hung Manh La  1 , Nenad Gucunski  2
Affiliations
Review

Review of Non-Destructive Civil Infrastructure Evaluation for Bridges: State-of-the-Art Robotic Platforms, Sensors and Algorithms

Habib Ahmed et al. Sensors (Basel). .

Abstract

The non-destructive evaluation (NDE) of civil infrastructure has been an active area of research in recent decades. The traditional inspection of civil infrastructure mostly relies on visual inspection using human inspectors. To facilitate this process, different sensors for data collection and techniques for data analyses have been used to effectively carry out this task in an automated fashion. This review-based study will examine some of the recent developments in the field of autonomous robotic platforms for NDE and the structural health monitoring (SHM) of bridges. Some of the salient features of this review-based study will be discussed in the light of the existing surveys and reviews that have been published in the recent past, which will enable the clarification regarding the novelty of the present review-based study. The review methodology will be discussed in sufficient depth, which will provide insights regarding some of the primary aspects of the review methodology followed by this review-based study. In order to provide an in-depth examination of the state-of-the-art, the current research will examine the three major research streams. The first stream relates to technological robotic platforms developed for NDE of bridges. The second stream of literature examines myriad sensors used for the development of robotic platforms for the NDE of bridges. The third stream of literature highlights different algorithms for the surface- and sub-surface-level analysis of bridges that have been developed by studies in the past. A number of challenges towards the development of robotic platforms have also been discussed.

Keywords: NDE sensor fusion; concrete crack detection; convolutional neural network (CNNs); electric resistivity (ER) sensors; ground-penetrating radar (GPR); impact echo (IE); infrared (IR) thermography; non-destructive evaluation (NDE); rebar detection and localization; structural health monitoring (SHM).

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Timeline showing some of the bridge accidents in the U.S. in recent decades [1].
Figure 2
Figure 2
Roadmap of the review-based study in order to understand the inter-relationship between the different sections of the paper.
Figure 3
Figure 3
The different steps in the review process for the evaluation of the relevant literature.
Figure 4
Figure 4
Timeline depicting the applications of the different sensors and the development of different platforms for NDE.
Figure 5
Figure 5
Visual representation for the proposed taxonomy used for studies on the NDE for civil infrastructure evaluation.
Figure 6
Figure 6
Proposed taxonomy for NDE robot development for bridge inspection.
Figure 7
Figure 7
The different sensor configurations within the NDE evaluation literature.
Figure 8
Figure 8
Different elements of the IE method for NDE of infrastructure [111].
Figure 9
Figure 9
Data collection using a thermography sensor: (a) the absorption of solar radiation by the different parts of the infrastructure during the day time [133], (b) the emission of radiation from the different parts of the infrastructure during night time [133], (c) the output of the data collection unit in the form of a digital image [134], and (d) the output of the data collection unit. [134].
Figure 10
Figure 10
Principles for the GPR wave transmission: (a) wave transmission with the fixed-offset profiling method for data collection, (b) the use of a common midpoint method for data collection using GPR [149,150] with different visual sensors to provide surface-level information to assess the structural health of bridges [72,74,75,76,77,83,98].
See this image and copyright information in PMC

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