One-class SVM based outlier detection strategy to detect thin interlayer debondings within pavement structures using Ground Penetrating Radar data

Todkar, Shreedhar Savant; Baltazart, Vincent; Ihamouten, Amine; Dérobert, Xavier; Guilbert, David

doi:10.1016/j.jappgeo.2021.104392

Cited by 22 publications

(9 citation statements)

References 15 publications

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“…In order to verify the prediction effect of isolation forest on cigarette outflow, this paper uses Python language to compare the classification results of data sets by applying isolation forest (IF), logistic regression (LR) [3], one class svm [4] (O-SVM) and random forest [5] (RF) respectively. In the experi-ment, precision and recall are used as the evaluation indexes of the model.…”

Section: Resultsmentioning

confidence: 99%

Research and application of cigarette trans-regional outflow risk prediction model based on data element value discovery

Yang¹,

Wang²,

Yan³

2023

Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022)

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Due to the particularity of tobacco as a commodity, the problem of cigarette trans-regional outflow has always been a difficult problem in the standardized management of the tobacco market supervision, mainly manifested in the lack of detection means, low identification accuracy, lagging early warning results and so on. To solve the above problems, this paper proposes a detection model TMSS (Tobacco Market Scientific Supervision), which can accurately identify the risk points related to tobacco operating by constructing an isolation forest algorithm, combining principal component analysis and grid search techniques, using multisource data fusion. This paper focuses on the working principle and algorithm design of the model TMSS. The accuracy and reliability of the TMSS are verified by selecting relevant application scenarios in Shiyan city, Hubei province. Through experimental verification, TMSS can effectively identify the risk points cause the transregional outflow phenomenon in the tobacco operation process in advance, which provides a significant breakthrough method and tool in the field of scientific supervision of tobacco market.

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Section: Resultsmentioning

confidence: 99%

Research and application of cigarette trans-regional outflow risk prediction model based on data element value discovery

Yang¹,

Wang²,

Yan³

2023

Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022)

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“…The dielectric property remains constant for a relatively thin and new AC layer, between 4 and 7 ( 5–7 , 15 , 26 ). However, this study shows that this is not the case for a field-aged thick AC layer.…”

Section: Resultsmentioning

confidence: 99%

“…Recently, simulation of GPR waves using a finite-difference time domain (FDTD) algorithm is gaining popularity among pavement engineers. Todkar et al ( 15 ) used FDTD simulation and a one-class support vector machine to determine debonding in pavement layers. Ma et al ( 16 ) also used FDTD simulation and peaks in the GPR signal to identify stripping damage in asphalt pavements.…”

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confidence: 99%

Backcalculation of Thickness and Dielectric Properties of Asphalt Concrete Using Numerical Simulation of Ground Penetrating Radar

Khan

Tarefder

Bairgi

et al. 2023

Transportation Research Record: Journal of the Transportation R

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Ground penetrating radar (GPR) is an essential tool for the non-destructive evaluation of pavement conditions. The accuracy of GPR analysis depends on the correct prediction of the layer dielectric property. In this study, a finite-difference time domain simulation-based two-step backcalculation algorithm was developed to determine the layer thickness and dielectric constant from air-coupled GPR data. The two-step backcalculation algorithm was developed by combining a surrogate-based global optimizer and artificial neural network for efficiency and accuracy. The GPR backcalculated results were compared with the field conditions of three pavement sections. The results show that the backcalculation algorithm could predict the layer thicknesses with almost 95% to 99.7% accuracy, whereas the prediction accuracy of the dielectric constants was between 90% and 98.5%. Furthermore, it was observed that the variations of dielectric constants in each lift of the asphalt concrete layer could be used to predict the presence of probable distress in the field.

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“…Over the last two decades, machine learning techniques have been applied to identify targets. Commonly used methods include support vector machines [10], genetic particle swarm optimization algorithms [11], and clustering K-SVD dictionary learning [12].…”

Section: Introductionmentioning

confidence: 99%

3D imaging and temporal evolution recognition of concrete internal defects based on GPR

Wang,

Li,

Lei

et al. 2024

Meas. Sci. Technol.

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Periodic inspections and recognition of temporal evolution for concrete internal defects are important for the long-term operation of civil engineering infrastructures. This study proposes a method integrating convolutional neural network (CNN) with maximum intensity projection (MIP) for 3D imaging and temporal evolution recognition of concrete internal defects. The proposed method utilizes MIP to process multiple ground penetrating radar (GPR) B-scans and generates 2D projected GPR B-scans containing spatial information. SegNet coupled with the Lovász softmax loss function is introduced to reconstruct 2D defects from projected GPR B-scans. Subsequently, 3D imaging result is reconstructed from 2D imaging results by 3D reconstruction module. Finally, the defect change extraction module realizes recognition of defect changes based on 3D imaging results at different time. The superiority of proposed method is validated based on both synthetic and real GPR data, which presents better recognition results and less time consumption than existing 3D CNN-based method.

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One-class SVM based outlier detection strategy to detect thin interlayer debondings within pavement structures using Ground Penetrating Radar data

Cited by 22 publications

References 15 publications

Research and application of cigarette trans-regional outflow risk prediction model based on data element value discovery

Research and application of cigarette trans-regional outflow risk prediction model based on data element value discovery

Backcalculation of Thickness and Dielectric Properties of Asphalt Concrete Using Numerical Simulation of Ground Penetrating Radar

3D imaging and temporal evolution recognition of concrete internal defects based on GPR

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