Toward Automatic Subsurface Pipeline Mapping by Fusing a Ground-Penetrating Radar and a Camera

Li, Haifeng; Chou, Chieh; Liu, Fan; Li, Binbin; Wang, Di; Song, Dezhen

doi:10.1109/tase.2019.2941848

Cited by 33 publications

(11 citation statements)

References 28 publications

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“…The authors of Li et al [ 65 ] further improved the performance of GPR in underground pipeline mapping by fusing the GPR scans in the form of hyperbolic responses with camera images. The inspection was implemented using a robot consisting of a GPR sensing unit, a camera and an on-board computer for data fusion.…”

Section: Pipeline Failure Detection Methodsmentioning

confidence: 99%

“…This method is effective in differentiating multiple overlapping pipelines in the same region of interest. Authors of [ 65 ], in their experimental setup, were able to produce a reconstructed 3D image of the underground pipeline network with a localisation accuracy of 4.47 cm and orientation errors of 1.73

and 0.73

for the two pipe orientation angles present in the network.…”

Section: Pipeline Failure Detection Methodsmentioning

confidence: 99%

“…The effectiveness of the algorithm used in the reconstruction process affects the quality of the image in terms of the clarity, resolution and contrast. While GPR provides near real-time visualisation of the condition of a pipeline, unless a computerised approach such as that in [ 65 ] is used, human intervention is required since the decision-making process is based on one’s perception of the indicators of water loss events in the GPR image.…”

Section: Pipeline Failure Detection Methodsmentioning

confidence: 99%

“…The failure detection methods covered in this paper are non-exhaustive and are, to the best of our knowledge at the point of writing, include non-destructive technologies that have been practically validated in the industry either in the form of modern wireless sensor networks or human-operated devices. Acoustic Reflectometry Time-of-flight; phase change; power reflection ratio; spectral analysis; synthetic aperture radar; acoustic resonance technology; ultrasonic phased array [6][7][8][42][43][44][45][46] Guided Wave Inspection Time-of-flight; ultrasonic transducer ring; phase change; spectral analysis; transmission/reflection coefficient analysis; non-linear modulation; guided microwave inspection [9,[47][48][49][50][51][52][53][54] Ultrasonic Gauging Time-of-flight; time-series cross-correlation; Gaussian model-based estimation; temperature compensation [55][56][57][58][59] Ground Penetrating RaDAR (GPR) Back-projection; back-propagation; GPR-camera fusion; Bayern approximation [2,[60][61][62][63][64][65] Impact Echo (IE) Sustained duration; resonance analysis; correction factor validation; Edge reflection analysis; noise removal [19,[66][67][68][69][70] Acoustic Emission (AE)/ Vibration Analysis Frequency analysis; vibrational amplitude and fluid transient analysis; time-difference cross-correlation; wavelet entropy analysis; machine learning classification [1,[9]…”

Section: Pipeline Failure Detection Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems

Wong

McCann

2021

Sensors

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Pipeline networks have been widely utilised in the transportation of water, natural gases, oil and waste materials efficiently and safely over varying distances with minimal human intervention. In order to optimise the spatial use of the pipeline infrastructure, pipelines are either buried underground, or located in submarine environments. Due to the continuous expansion of pipeline networks in locations that are inaccessible to maintenance personnel, research efforts have been ongoing to introduce and develop reliable detection methods for pipeline failures, such as blockages, leakages, cracks, corrosion and weld defects. In this paper, a taxonomy of existing pipeline failure detection techniques and technologies was created to comparatively analyse their respective advantages, drawbacks and limitations. This effort has effectively illuminated various unaddressed research challenges that are still present among a wide array of the state-of-the-art detection methods that have been employed in various pipeline domains. These challenges include the extension of the lifetime of a pipeline network for the reduction of maintenance costs, and the prevention of disruptive pipeline failures for the minimisation of downtime. Our taxonomy of various pipeline failure detection methods is also presented in the form of a look-up table to illustrate the suitability, key aspects and data or signal processing techniques of each individual method. We have also quantitatively evaluated the industrial relevance and practicality of each of the methods in the taxonomy in terms of their respective deployability, generality and computational cost. The outcome of the evaluation made in the taxonomy will contribute to our future works involving the utilisation of sensor fusion and data-centric frameworks to develop efficient, accurate and reliable failure detection solutions.

show abstract

Section: Pipeline Failure Detection Methodsmentioning

confidence: 99%

and 0.73

for the two pipe orientation angles present in the network.…”

Section: Pipeline Failure Detection Methodsmentioning

confidence: 99%

Section: Pipeline Failure Detection Methodsmentioning

confidence: 99%

Section: Pipeline Failure Detection Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems

Wong

McCann

2021

Sensors

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show abstract

“…However, the positioning information in their reconstructed object model is not mentioned in the above methods. Similarly, Prof. Dezhen Song's group at Taxes A&M University published a series of papers on automatic subsurface pipeline mapping and 3D reconstruction by fusing a GPR and a Camera [9], [10]. They proposed a robotic underground pipeline mapping model to facilitates GPR-based 3D reconstruction.…”

Section: Introductionmentioning

confidence: 99%

Towards 3D Metric GPR Imaging Based on DNN Noise Removal and Dielectric Estimation

Feng,

Yang,

Xiao

2021

Preprint

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Ground Penetrating Radar (GPR) is one of the most important non-destructive evaluation (NDE) devices to detect the subsurface objects (i.e. rebars, utility pipes) and reveal the underground scene. Due to the background noise and unknown dielectric property of subsurface media, the reconstruction of the subsurface objects with metric information remains the main challenge in GPR inspection. In this letter, a novel metric GPR imaging method is proposed consisting of three steps to address the above challenge. Firstly, a noise removal segmentation model is introduced to clear the GPR raw data; furthermore, a DielectricNet is proposed to predict the dielectric properties of media from each GPR B-scan data and the depth of a target; at the last step, we optimize the back-projection (BP) algorithm by using free motion pattern, thus to obtain the 3D metric BP result. We use both the field and synthetic data to verify the proposed method, experimental results show that our proposed method is able to achieve at least 10% improvement in reconstruction accuracy compared with the conventional BP methods.

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Coal Mine Rescue Robots: Development, Applications and Lessons Learned

Zhu

Tang

et al. 2022

Proceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021)

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Toward Automatic Subsurface Pipeline Mapping by Fusing a Ground-Penetrating Radar and a Camera

Cited by 33 publications

References 28 publications

Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems

Failure Detection Methods for Pipeline Networks: From Acoustic Sensing to Cyber-Physical Systems

Towards 3D Metric GPR Imaging Based on DNN Noise Removal and Dielectric Estimation

Coal Mine Rescue Robots: Development, Applications and Lessons Learned

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