In order to minimize the costs, risks, and disruptions associated with structural inspections, robotic systems have increasingly been studied as an enhancement to current inspection practic...

Review of Robotic Infrastructure Inspection Systems

Unmanned aerial systems (UASs) have become of considerable private and commercial interest for a variety of jobs and entertainment in the past 10 years. This paper is a literature review of the state of practice for the United States bridge inspection programs and outlines how automated and unmanned bridge inspections can be made suitable for present and future needs. At its best, current technology limits UAS use to an assistive tool for the inspector to perform a bridge inspection faster, safer, and without traffic closure. The major challenges for UASs are satisfying restrictive Federal Aviation Administration regulations, control issues in a GPS-denied environment, pilot expenses and availability, time and cost allocated to tuning, maintenance, post-processing time, and acceptance of the collected data by bridge owners. Using UASs with self-navigation abilities and improving image-processing algorithms to provide results near real-time could revolutionize the bridge inspection industry by providing accurate, multi-use, autonomous three-dimensional models and damage identification.

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Bridge inspection: human performance, unmanned aerial systems and automation

The coupling of waves between the piezoelectric generators, detectors, and propagating media is challenging due to mismatch in the acoustic properties. The mismatch leads to the reverberation of waves within the transducer, heating, low signal-to-noise ratio, and signal distortion. Acoustic impedance matching increases the coupling largely. This article presents standard methods to match the acoustic impedance of the piezoelectric sensors, actuators, and transducers with the surrounding wave propagation media. Acoustic matching methods utilizing active and passive materials have been discussed. Special materials such as nanocomposites, metamaterials, and metasurfaces as emerging materials have been presented. Emphasis is placed throughout the article to differentiate the difference between electric and acoustic impedance matching and the relation between the two. Comparison of various techniques is made with the discussion on capabilities, advantages, and disadvantages. Acoustic impedance matching for specific and uncommon applications has also been covered.

A Review of Acoustic Impedance Matching Techniques for Piezoelectric Sensors and Transducers.

This paper summarizes the results of traditional image processing algorithms for detection of defects in concrete using images taken by Unmanned Aerial Systems (UASs). Such algorithms are useful for improving the accuracy of crack detection during autonomous inspection of bridges and other structures, and they have yet to be compared and evaluated on a dataset of concrete images taken by UAS. The authors created a generic image processing algorithm for crack detection, which included the major steps of filter design, edge detection, image enhancement, and segmentation, designed to uniformly compare different edge detectors. Edge detection was carried out by six filters in the spatial (Roberts, Prewitt, Sobel, and Laplacian of Gaussian) and frequency (Butterworth and Gaussian) domains. These algorithms were applied to fifty images each of defected and sound concrete. Performances of the six filters were compared in terms of accuracy, precision, minimum detectable crack width, computational time, and noise-to-signal ratio. In general, frequency domain techniques were slower than spatial domain methods because of the computational intensity of the Fourier and inverse Fourier transformations used to move between spatial and frequency domains. Frequency domain methods also produced noisier images than spatial domain methods. Crack detection in the spatial domain using the Laplacian of Gaussian filter proved to be the fastest, most accurate, and most precise method, and it resulted in the finest detectable crack width. The Laplacian of Gaussian filter in spatial domain is recommended for future applications of real-time crack detection using UAS.

https://www.mdpi.com/2412-3811/4/2/19/pdf

Benchmarking Image Processing Algorithms for Unmanned Aerial System-Assisted Crack Detection in Concrete Structures

/pdf/benchmarking-image-processing-algorithms-forunmanned-aerial-z4r5uvjl0e.pdf

Benchmarking Image Processing Algorithms forUnmanned Aerial System-Assisted Crack Detectionin Concrete Structures

The information presented in this report provides a detailed assessment of the condition of the Arlington Memorial Bridge (AMB) deck. The field-data collection was obtained by both the RABIT™ Bridge Inspection Tool and a number of semi-automated non-destructive evaluation (NDE) tools. The deployment of the semi-automated NDE tools was performed to inspect the AMB deck condition and also to validate data obtained by the RABIT™ Bridge Inspection Tool. Data mining and analysis were accomplished through enhanced data interpretation and visualization capabilities using advanced data integration, fusion, and 2D rendering. One of the major challenges that the research team had to overcome in assessing the condition of the AMB deck was the presence of an asphalt overlay on the entire bridge deck.

Nondestructive evaluation inspection of the Arlington Memorial Bridge using a robotic assisted bridge inspection tool (RABIT)

The past decade has seen new, emerging innovation of Ultrasonic Testing (UT). Specifically, multiple manufacturers have produced Phased Array Ultrasonic Testing (PAUT) systems. The PAUT systems embed a matrix of multiple (some up to 128) single transducers into one probe used for scanning elastic materials. Simultaneously exciting multiple transducers offers distinct advantages; depending on the sequencing of transducer excitation, the ultrasonic beam could be steered within the material and multiple beams help develop extra dimensional data to assist with visualization of possible flaws including the discontinuity size, shape and location. Unfortunately, there has not been broad acceptance of PAUT in the bridge fabrication industry because it is currently not a recognized inspection technology in AWS D1.5. One situation in which the technology would excel would be inspection of Complete Joint Penetration (CJP) butt welds. Currently, AWS D1.5 required CJP welds subjected to tensile or reversal stresses only be inspected by Radiographic Testing (RT). However, discontinuities normally seen by RT can also be seen with PAUT. Until specification language is adopted into D1.5, there will continue to be hesitancy to use PAUT for the inspection of CJP butt welds. Developmental work must first be performed to develop the acceptance criteria and the specification language. The developmental work from the inspections carried out on butt-weld specimens and transition butt-weld specimens are presented in this paper. Specific scan plans were developed using the ES-Beam simulation software for each of the test specimens. In depth analysis of PAUT data obtained to determine exact location and sizing information of the defects was performed. The results also present the comparison of results from PAUT to those obtained using conventional UT and radiography.

Shane D. Boone

Papers

Nondestructive evaluation inspection of the Arlington Memorial Bridge using a robotic assisted bridge inspection tool (RABIT)

Development of phased array ultrasonic testing in lieu of radiography for testing complete joint penetration (CJP) welds