Research on Ultrasonic Guided Wave Damage Detection in Internally Corroded Pipes with Curved Random Surfaces

To accurately simulate the progression of pipeline corrosion, this paper proposes a three-dimensional corrosion modeling method for curved random surfaces based on spatial frequency composition. It applies this method to the inner surface of layered pipelines to emulate both the morphological characteristics and the evolution of internal corrosion. Combined with ultrasonic guided wave technology, the approach enables quantitative assessment of internal corrosion in layered pipelines. First, trigonometric series expansion and nonlinear polynomial superposition are used to characterize the roughness and curvature of the corroded surface, respectively, establishing a mathematical model capable of accurately representing complex corrosion morphologies. Next, a COMSOL–ABAQUS co-modeling approach is employed to build a finite element model of a three-layer composite pipeline consisting of a steel pipe, an insulating layer, and an anti-corrosion layer, with curved random-surface corrosion on the inner surface of the steel pipe. Finally, a wavelet packet decomposition algorithm is applied to extract features from the guided wave echo signals, creating a damage index matrix to correlate the corrosion area with the damage index quantitatively. The results show that the damage index increases steadily with the corrosion area, confirming the effectiveness of the proposed method. This study provides an alternative technical approach for high-fidelity modeling and precise assessment of pipeline corrosion detection.

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Publication Details

Journal
Applied Sciences
Published
2025-11-21
DOI
https://doi.org/10.3390/app152312372
Citations
1
Primary Topic
Ultrasonics and Acoustic Wave Propagation
Type
article
Field-Weighted Citation Impact
0.86
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article

Research on Ultrasonic Guided Wave Damage Detection in Internally Corroded Pipes with Curved Random Surfaces

Ying Li, Qihao Liang, Fu He
1 citations
Applied Sciences
Ultrasonics and Acoustic Wave Propagation
0.86
article

Research on Ultrasonic Guided Wave Damage Detection in Internally Corroded Pipes with Curved Random Surfaces

Ying Li, Qihao Liang, Fu He
article en
1 citations

Abstract

To accurately simulate the progression of pipeline corrosion, this paper proposes a three-dimensional corrosion modeling method for curved random surfaces based on spatial frequency composition. It applies this method to the inner surface of layered pipelines to emulate both the morphological characteristics and the evolution of internal corrosion. Combined with ultrasonic guided wave technology, the approach enables quantitative assessment of internal corrosion in layered pipelines. First, trigonometric series expansion and nonlinear polynomial superposition are used to characterize the roughness and curvature of the corroded surface, respectively, establishing a mathematical model capable of accurately representing complex corrosion morphologies. Next, a COMSOL–ABAQUS co-modeling approach is employed to build a finite element model of a three-layer composite pipeline consisting of a steel pipe, an insulating layer, and an anti-corrosion layer, with curved random-surface corrosion on the inner surface of the steel pipe. Finally, a wavelet packet decomposition algorithm is applied to extract features from the guided wave echo signals, creating a damage index matrix to correlate the corrosion area with the damage index quantitatively. The results show that the damage index increases steadily with the corrosion area, confirming the effectiveness of the proposed method. This study provides an alternative technical approach for high-fidelity modeling and precise assessment of pipeline corrosion detection.

Applied SciencesVol. 15(23)
Institute of Disaster Prevention (CN), China Earthquake Administration (CN)
Openalex Percentile: Top 22%
Ultrasonics and Acoustic Wave Propagation
0.86
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Research on Ultrasonic Guided Wave Damage Detection in Internally Corroded Pipes with Curved Random Surfaces — Ying Li, Qihao Liang, et al. · Applied Sciences (2025) | TGRS Research Map | TGRS