Migration-based automated rebar picking for condition assessment of concrete bridge decks with ground penetrating radar

Dinh, Kien; Gucunski, Nenad; Duong, Trung H.

doi:10.1016/j.ndteint.2018.04.009

Cited by 42 publications

(15 citation statements)

References 14 publications

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“…When dealing with a GPR bridge inspection, a large amount of data are produced and extensive manual processing is required to extract useful information, in which the manual identification and localization of rebar is time-consuming and labor intensive. In such a context, some authors have developed algorithms for the automatic detection of rebar [157,173,174,[176][177][178][179][180][181][182] and cracks/delamination [165,177,178].…”

Section: Concrete Bridgesmentioning

confidence: 99%

“…The typical post-processing includes time-zero correction (set ground surface), background removal (remove horizontal banding), band pass filtering (remove high-and lowfrequency noise), and gain (amplify the received signal across depth range). Migration is also recommended when identifying the rebar in a concrete slab in order to reduce or eliminate hyperbolic diffraction patterns in the data [180]. Thus, each pixel in the original GPR images will be migrated focusing energy on the true rebar locations; hence, the intensity values of the pixels at a true object location will end up having the sum intensity value of all the pixels on the hyperbolic signature (the energy will be focused therefore on those pixels).…”

Section: Concrete Bridgesmentioning

confidence: 99%

“…There is a large variety of computational methods that can be applied, such as interpolation functions, a histogram of oriented gradients (HOG), a feature descriptorsbased multi-layer perceptron (MLP) classifier, a support vector machine (SVM), a convolutional neural network (CNN), the limited and simplified hyperbolic summation (LSHS) technique, partial differential equations (PDEs), the hidden Markov model (HMM), a genetic algorithm, and the fuzzy logic approach. These computational methods are described and applied in some relevant and recent studies [177][178][179][180][181] and, in most cases, with accuracies greater than 95.0%. On the other hand, algorithms are also implemented to extract the GPR amplitudes automatically from both the whole GPR signals and the rebar peaks detected [165], [171], [174], generally after applying a migration procedure.…”

Section: Concrete Bridgesmentioning

confidence: 99%

See 2 more Smart Citations

A Review of GPR Application on Transport Infrastructures: Troubleshooting and Best Practices

2021

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The non-destructive testing and diagnosis of transport infrastructures is essential because of the need to protect these facilities for mobility, and for economic and social development. The effective and timely assessment of structural health conditions becomes crucial in order to assure the safety of the transportation system and time saver protocols, as well as to reduce excessive repair and maintenance costs. Ground penetrating radar (GPR) is one of the most recommended non-destructive methods for routine subsurface inspections. This paper focuses on the on-site use of GPR applied to transport infrastructures, namely pavements, railways, retaining walls, bridges and tunnels. The methodologies, advantages and disadvantages, along with up-to-date research results on GPR in infrastructure inspection are presented herein. Hence, through the review of the published literature, the potential of using GPR is demonstrated, while the main limitations of the method are discussed and some practical recommendations are made.

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Section: Concrete Bridgesmentioning

confidence: 99%

Section: Concrete Bridgesmentioning

confidence: 99%

Section: Concrete Bridgesmentioning

confidence: 99%

See 1 more Smart Citation

A Review of GPR Application on Transport Infrastructures: Troubleshooting and Best Practices

2021

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“…The proposed algorithm was validated on many real GPR images. More recently Dinh et al [52] presented an automated rebar picking algorithm for GPR data of concrete bridge decks. The algorithm is based on the limited and simplified hyperbolic summation technique.…”

Section: Review Of the Gpr Literature Related To Bridge Deck Conditiomentioning

confidence: 99%

Bridge deck condition assessment by using GPR: a review

2018

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Bridge deck deterioration includes delamination, corrosion of rebars, vertical cracking and concrete degradation. Ground Penetrating Radar based inspection technique was used for mapping bridge deck in order to monitor the health of this vital structure. Beginning from the 1970‘s, research has focused on identification of bridge deck deterioration which causes severe deficiencies by reducing seriously strength. The main purpose of this work was to review the literature existing in the field of bridge deck diagnosis by means of Ground Penetrating Radar. This enabled to survey detailed evolution of this technique, to understand the effects of key intervening parameters and to determine the kind of material disorders that this device could be used for. Bridge deck condition assessment can then be performed more successfully, based on the huge progress experienced by this particular method of inspection.

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“…Normalised Cross-Correlation (NCC) is a signal processing technique [7] used as a similarity measure to determine the matching point between template and image [8]. Although this technique is computationally slow, NCC is robust under uniform illumination changes [9] where it is less sensitive to linear changes in the amplitude of illumination between two matched images [10].…”

Section: Introductionmentioning

confidence: 99%

Interpretation of Ground Penetrating Radar Dataset using Normalised Cross-Correlation Technique

Wahab¹,

Zakaria²,

Omar³

et al. 2019

IJEAT

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Ground Penetrating Radar (GPR) is one of the latest non-destructive geophysical technology and most widely used in detecting underground utilities. GPR can detect both metal and non-metal, however, it is unable to identify the type of underground utility object. Many researchers come out with their techniques to interpret the GPR image. The current method requires experience in interpretation. Thus, in this study, a new method to detect underground utility utilizing the Normalised Cross-Correlation (NCC) template matching technique is proposed. This technique will reduce the dependency on experts to interpret the radargram, less time consuming and eventually save cost. Upon detection, the accuracy of the system is assessed. From the accuracy assessment performed, it is shown that the system provides accurate detection results for both, depth and pipe size. The Root Mean Square Error (RMSE) for the buried pipe depth obtained by using the proposed system is 0.110 m, whereas the highest percentage match obtained is 91.34%, the remaining 8.66% mismatched might be due to the soil condition, velocity or processing parameter that affected the radargram. Based on the assessment, the developed system seems capable to detect the subsurface utility if the radar image and template image used is acquired using the same antenna frequency, point interval, and similar GPR instrument

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Migration-based automated rebar picking for condition assessment of concrete bridge decks with ground penetrating radar

Cited by 42 publications

References 14 publications

A Review of GPR Application on Transport Infrastructures: Troubleshooting and Best Practices

A Review of GPR Application on Transport Infrastructures: Troubleshooting and Best Practices

Bridge deck condition assessment by using GPR: a review

Interpretation of Ground Penetrating Radar Dataset using Normalised Cross-Correlation Technique

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