Identification of Pipeline Axial Tensile Stress Using Geometric and ACSM In-Line Inspection Data

Accurate identification of high-stress axial tensile sections in pipelines remains a significant challenge for stress in-line inspection (ILI) technology. To address this, we designed and conducted dynamic calibration tests for Alternating Current Stress Measurement (ACSM), alongside a pull test combining geometric and ACSM stress ILI sensors. Results demonstrate approximately linear correlation between applied axial stress and the mean ACSM signal, characterized by a distinct baseline downshift under tensile loading. However, irregular high-frequency fluctuations compromise quantitative accuracy, obscuring the distinction between actual stress variations and environmental noise. To mitigate this, a new analysis method is proposed, integrating geometric deformation data with ACSM signals. This approach effectively attributes signal variations to axial tensile deformation, significantly enhancing assessment reliability. Furthermore, we conducted an integrated analysis of ACSM and geometric ILI data for an in-service D813 oil pipeline. The synergistic variation between geometric deformations and ACSM signals was validated at pipe sections exhibiting localized stress alterations induced by dents and wall thickness transitions. By leveraging Poisson’s effect in conjunction with geometric ILI data, we identify and analyze ACSM stress concentration signals. Thereby, the adverse impacts of weld seams, mechanical noise, and other interferences in signal fidelity are mitigated. This study confirms that integrated analysis of geometric and ACSM ILI data is beneficial for high axial stress identification of in-service pipeline.

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Publication Details

Journal
Sensors
Published
2026-09-10
DOI
https://doi.org/10.3390/s26185748
Primary Topic
Non-Destructive Testing Techniques
Type
article
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article

Identification of Pipeline Axial Tensile Stress Using Geometric and ACSM In-Line Inspection Data

Rui Li, Zhengqiang Lei, Guangyong Yang, Yanbing Wang
Sensors
Non-Destructive Testing Techniques
article

Identification of Pipeline Axial Tensile Stress Using Geometric and ACSM In-Line Inspection Data

Rui Li, Zhengqiang Lei, Guangyong Yang, Yanbing Wang
article en

Abstract

Accurate identification of high-stress axial tensile sections in pipelines remains a significant challenge for stress in-line inspection (ILI) technology. To address this, we designed and conducted dynamic calibration tests for Alternating Current Stress Measurement (ACSM), alongside a pull test combining geometric and ACSM stress ILI sensors. Results demonstrate approximately linear correlation between applied axial stress and the mean ACSM signal, characterized by a distinct baseline downshift under tensile loading. However, irregular high-frequency fluctuations compromise quantitative accuracy, obscuring the distinction between actual stress variations and environmental noise. To mitigate this, a new analysis method is proposed, integrating geometric deformation data with ACSM signals. This approach effectively attributes signal variations to axial tensile deformation, significantly enhancing assessment reliability. Furthermore, we conducted an integrated analysis of ACSM and geometric ILI data for an in-service D813 oil pipeline. The synergistic variation between geometric deformations and ACSM signals was validated at pipe sections exhibiting localized stress alterations induced by dents and wall thickness transitions. By leveraging Poisson’s effect in conjunction with geometric ILI data, we identify and analyze ACSM stress concentration signals. Thereby, the adverse impacts of weld seams, mechanical noise, and other interferences in signal fidelity are mitigated. This study confirms that integrated analysis of geometric and ACSM ILI data is beneficial for high axial stress identification of in-service pipeline.

SensorsVol. 26(18)
China University of Petroleum, Beijing (CN)
Openalex Percentile: Top 20%
Non-Destructive Testing Techniques
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Identification of Pipeline Axial Tensile Stress Using Geometric and ACSM In-Line Inspection Data — Rui Li, Zhengqiang Lei, et al. · Sensors (2026) | TGRS Research Map | TGRS