Corrosion and Erosion Monitoring of Pipes by an Ultrasonic Guided Wave Method

This paper aims to provide an overview of the experimental and simulation works focused on the detection, localisation and assessment of various defects in pipes by applying fast-screening guided ultrasonic wave techniques that have been used in the oil and gas industries over the past 20 years. Major emphasis is placed on limitations, capabilities, defect detection in coated buried pipes under pressure and corrosion monitoring using different commercial guided wave (GW) systems, approaches to simulation techniques such as the finite element method (FEM), wave mode selection, excitation and collection, GW attenuation, signal processing and different types of GW transducers. The effects of defect parameters on reflection coefficients are also discussed in terms of different simulation studies and experimental verifications.

Section: Common Gw Testing Methodsmentioning

confidence: 99%

Section: Gws’ Propertiesmentioning

confidence: 99%

Section: Gws’ Propertiesmentioning

confidence: 99%

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Detection, Localisation and Assessment of Defects in Pipes Using Guided Wave Techniques: A Review

Ghavamian

Mustapha

Baharudin

et al. 2018

“…Novel techniques have emerged that utilize thickness loss measurements around the circumference of pipes as a tool for more accurate and relatively large-scale assessment of corrosion [ 19 , 20 ]. These techniques frequently utilize high-order guided wave modes that propagate along the circumference of the pipe and are sensitive to changes in wall thickness [ 21 , 22 ]. When these techniques are combined with specialized scanners, they can be used as a rapid pipe cross section screening method, allowing for the real-time generation of wall thickness maps.…”

Section: Introductionmentioning

confidence: 99%

Detection and Classification of Uniform and Concentrated Wall-Thinning Defects Using High-Order Circumferential Guided Waves and Artificial Neural Networks

Cirtautas

Samaitis

Mažeika

et al. 2023

Pipeline structures are susceptible to corrosion, leading to significant safety, environmental, and economic implications. Existing long range guided wave inspection systems often fail to detect footprints of the concentrated defects, which can lead to leakage. One way to tackle this issue is the utilization of circumferential guided waves that inspect the pipe’s cross section. However, achieving the necessary detection resolution typically necessitates the use of high-order modes hindering the inspection data interpretation. This study presents the implementation of an ultrasonic technique capable of detecting and classifying wall thinning and concentrated defects using high-order guided wave modes. The technique is based on a proposed phase velocity mapping approach, which generates a set of isolated wave modes within a specified phase velocity range. By referencing phase velocity maps obtained from defect-free stages of the pipe, it becomes possible to observe changes resulting from the presence of defects and assign those changes to the specific type of damage using artificial neural networks (ANN). The paper outlines the fundamental principles of the proposed phase velocity mapping technique and the ANN models employed for classification tasks that use synthetic data as an input. The presented results are meticulously verified using samples with artificial defects and appropriate numerical models. Through numerical modeling, experimental verification, and analysis using ANN, the proposed method demonstrates promising outcomes in defect detection and classification, providing a more comprehensive assessment of wall thinning and concentrated defects. The model achieved an average prediction accuracy of 92% for localized defects, 99% for defect-free cases, and 98% for uniform defects.

“…However, if the requirement is to detect relatively severe and highly localized defects, the number of point sensors required substantially increases. In these cases, the area monitoring systems such as the field signature method [ 9 ] or dispersive guided wave velocity measurements [ 10 , 11 ] appear to be more attractive. Nonetheless, the area monitoring systems are only sensitive to the average loss of the wall thickness over a monitored area.…”

Section: Introductionmentioning

confidence: 99%

On-Line Corrosion Monitoring of Plate Structures Based on Guided Wave Tomography Using Piezoelectric Sensors

Rao

Ratassepp

Lisevych

et al. 2017

Corrosion is a major safety and economic concern to various industries. In this paper, a novel ultrasonic guided wave tomography (GWT) system based on self-designed piezoelectric sensors is presented for on-line corrosion monitoring of large plate-like structures. Accurate thickness reconstruction of corrosion damages is achieved by using the dispersive regimes of selected guided waves and a reconstruction algorithm based on full waveform inversion (FWI). The system makes use of an array of miniaturised piezoelectric transducers that are capable of exciting and receiving highly dispersive A0 Lamb wave mode at low frequencies. The scattering from transducer array has been found to have a small effect on the thickness reconstruction. The efficiency and the accuracy of the new system have been demonstrated through continuous forced corrosion experiments. The FWI reconstructed thicknesses show good agreement with analytical predictions obtained by Faraday’s law and laser measurements, and more importantly, the thickness images closely resemble the actual corrosion sites.