Evidence map›Paper›PMID 41013065›Full record

ArticleSensors (Basel, Switzerland)2025

Localization of Buried Polyethylene Gas Pipelines Using Compressional Wave Migration Stacking Imaging.

Ao Zhang, Junfeng Liao, Disheng Zhong, He Li, Ping Han, Zhenting Song

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ao ZhangSchool of Mechanical Engineering, Shenyang Jianzhu University, Shenyang 110168, China.ORCID 0000-0001-7713-2050
Junfeng LiaoSchool of Mechanical Engineering, Shenyang Jianzhu University, Shenyang 110168, China.
Disheng ZhongSchool of Mechanical Engineering, Shenyang Jianzhu University, Shenyang 110168, China.
He LiKey Laboratory of Vibration and Control of Aero-Propulsion System, Ministry of Education, Northeastern University, Shenyang 110819, China.
Ping HanKey Laboratory of Vibration and Control of Aero-Propulsion System, Ministry of Education, Northeastern University, Shenyang 110819, China.
Zhenting SongSchool of Mechanical Engineering, Shenyang Jianzhu University, Shenyang 110168, China.ORCID 0009-0007-0456-0469

Funding

Department of Education of Liaoning Province JYTQN2023397Key Laboratory of Vibration and Control of Aero-Propulsion System, Ministry of Education, Northeastern University VCAME202403Natural Science Foundation of Liaoning Province 2024-BS-127
6 · The paper itself

Abstract

Buried polyethylene (PE) gas pipelines are widely used in urban construction. Precise localization of these pipelines is essential for regular maintenance. To address the issue of insufficient accuracy in existing localization techniques, this paper proposes a localization method based on compressional wave migration stacking imaging. The pipeline excitation approach is utilized to avoid interference from reflected waves, and the wavelet decomposition method is employed to suppress environmental noise and improve the signal-to-noise ratio. A pipe-soil coupling model was established using COMSOL6.3 Multiphysics to analyze elastic wave propagation induced by pipeline excitation. The results revealed a distinct velocity disparity between compressional wave and shear wave, with compressional wave velocity exhibiting significant superiority. Leveraging this propagation characteristic, we propose a novel pipeline localization method based on compressional wave migration stacking imaging. The method's accuracy was validated through simulations and field experiments. Experimental results showed that the horizontal localization error was below 0.5%, and the depth error was below 4.25%, demonstrating a reliable localization accuracy. Furthermore, the pipeline direction was intuitively identified using 3D imaging technology, effectively distinguishing it from other foreign objects in the soil. This study provides a high-precision, low-interference solution for the trenchless detection of buried PE pipelines in complex soil environments.

Indexed as

compressional wavePE pipeline localizationpipeline excitation methodstacking imagingwavelet decomposition

Identifiers

PMID41013065
PMCPMC12473232

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.