• Journal of Ocean Engineering and Technology
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• v.27 no.3
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• pp.8-14
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• 2013

Although there are various factors that threaten the security of ships, one of the most harmful is corrosion. It is not easy to find corroding areas and the status of corrosion, even though corrosion causes serious problems such as submergence and marine pollution as a result of leaking oil and polluted water. To monitor the corrosion of ships, non-destructive inspection, weight loss coupons, electrical resistance, linear polarization resistance, zero resistance ammeter, and electrochemical impedance spectroscopy have been developed. However, these methods require much time to detect corrosion, and most are not appropriate for real time monitoring. Coating, sacrificial anode, and impressed current cathodic protection (ICCP) methods have been developed to control corrosion. The ICCP and sacrificial anode methods are the most popular ways to prevent ship corrosion. However, ICCP is only appropriate for the outside of a ship and cannot be used for complex structures such as ballast tanks because these are composed of many separate chambers. Sacrificial anodes have to be replaced periodically. This paper proposes an integrated corrosion monitoring and control system (ICMCS) that can detect corrosion in real time and is appropriate for complex structures such as ballast tanks. Because the system uses titanium for an anode, exhausted anodes do not need to be replaced.

• Corrosion Science and Technology
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• v.19 no.2
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• pp.66-74
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• 2020

In this paper, the author's team has carried out a comparative experimental study on the corrosion characteristics of Q235 steel commonly used in large-scale storage tanks under the specific bottom water environment found with Russian and Daqing crude oil. It was found that there is a certain degree of uniform or local corrosion on the tank floor depending on the kind of bottom water. The bottom water corrosion of Daqing crude oil is a uniform corrosion caused by carbon dioxide. While the Russian crude oil bottom water corrosion is clearly local corrosion caused by co-corrosion of carbon dioxide and hydrogen sulfide, here the corrosion rate is obviously higher than that caused by Daqing crude oil. There are two modes of storage tank inspection and maintenance that have been currently adopted by Chinese refining and chemical enterprises: a regular inspection mode and a API581-2016 risk-based detection mode. These modes have been effectively combined to form an intelligent tank inspection and maintenance mode, software tools to support this intelligent inspection and maintenance management have been developed.

• Proceedings of the Korea Concrete Institute Conference
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• 1996.10a
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• pp.213-217
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• 1996

The electrochemical methods of early detection and analysis of corrosion related deterioration in concrete reinforcement structures are very useful techniques. The generally using procedure for corrosion monitoring of reinforced structures employs a method of half-cell potential measurement. Whilst the technique has provided a useful means of delineating areas of high or low corrosion risk, there are difficulties in its use and interpretation, particularly when assessing corrosion rates of reinforcement. The aim of this study is to describe the AC-impedance method being employed to monitor and assess corrosion rates, to estimate corrosion mechanism of reinfrocement in laboratory conditions. The AC-impedance monitoring technique applies a small amplitude(20mV) AC signal to embedded steel in concrete and reference electrode (Cu/$CuSo_4$). We obtained over a wide frequency range(10MHz~1mHz) to produce a complex plane plot or Nyquist plot.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.784-789
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• 2012

In this paper, a number of anode and reference electrodes that are installed around the target anti-corrosion objects to monitor, appropriate to your situation of a fixed potential and polarization methods can be applied automatically in the system was developed. In particular, this system was configured with a remote electric anti-corrosion automatic control device that have automatically adjust function to uniformal anti-corrosion in all parts of target objects, a corrosion monitoring device to perform the function of corrosion potential detection and a web-based operating program to perform the function of real-time monitoring, control and prediction. Using this system, by preventing oxidative corrosion phenomena can maximize the life of the target anti-corrosion objects.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.657-665
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• 2021

Nondestructive evaluation methods play an important role in ensuring component integrity and safety in many industries. Operator fatigue can play a critical role in the reliability of such methods. This is important for inspecting high value assets or assets with a high consequence of failure, such as aerospace and nuclear components. Recent advances in convolution neural networks can support and automate these inspection efforts. This paper proposes using residual neural networks (ResNets) for real-time detection of corrosion, including iron oxide discoloration, pitting and stress corrosion cracking, in dry storage stainless steel canisters housing used nuclear fuel. The proposed approach crops nuclear canister images into smaller tiles, trains a ResNet on these tiles, and classifies images as corroded or intact using the per-image count of tiles predicted as corroded by the ResNet. The results demonstrate that such a deep learning approach allows to detect the locus of corrosion via smaller tiles, and at the same time to infer with high accuracy whether an image comes from a corroded canister. Thereby, the proposed approach holds promise to automate and speed up nuclear fuel canister inspections, to minimize inspection costs, and to partially replace human-conducted onsite inspections, thus reducing radiation doses to personnel.

• Structural Engineering and Mechanics
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• v.26 no.2
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• pp.179-190
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• 2007

Damage detection based on measured vibration data has received intensive studies recently. Frequently, the damage to a structure may be reflected by a change of some system parameters, such as a degradation of the stiffness. In this paper, we apply a method to nondestructively locate and estimate the severity of damage in corrosion pipeline for which a few natural frequencies or mode shapes are available. The method is based on the strain modal sensitivity ratio (SMSR) and the orthogonality conditions sensitivities (OCS) applied to vibration features identified during the monitoring of the pipeline. The advantage of these methods is that it only requires measuring few modal parameters. The SMSR-based and OCS-based damage detection methods are illustrated using computer-simulated and laboratory testing data. The results show that the current method provides a precise indication of both the location and the extent of corrosion pipeline.

• Corrosion Science and Technology
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• v.19 no.5
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• pp.265-280
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• 2020

External corrosion of buried pipes can be controlled using both coating and cathodic protection. However, deterioration of the coating can occur due to several reasons. The detection reliabilty of coating flaw detection methods is affected by interference such as metal objects connected to rectifiers and copper grids. When performing parallel direct current voltage gradient (DCVG) inspection, a sine wave form without potential reversal in voltage gradient appears in the area where the interference exists. However, this area may be not identified using existing methods. The objective of this study was to determine the effect of analyzing direction on the reliability of coating flaw detection of pipes buried in soil using a multi-electrode detector. DCVG on the buried pipe was measured along the buried pipe. This measurement parallel to the pipe was repeated. Measured data were analyzed for parallel, vertical, and diagonal directions. The reliability of coating flaw detection was improved by up to 46.4% compared to the conventional method.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4481-4490
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• 2022

In this study, a new rupture disk corrosion test (RDCT) method was developed for real-time detection of stress corrosion cracking (SCC) initiation of Alloy 600 in a primary water environment of pressurized water reactors. In the RDCT method, one side of a disk specimen was exposed to a simulated primary water at high temperature and pressure while the other side was maintained at ambient pressure, inducing a dome-shaped deformation and tensile stress on the specimen. When SCC occurs in the primary water environment, it leads to the specimen rupture or water leakage through the specimen, which can be detected in real-time using a pressure gauge. The tensile stress applied to the disk specimen was calculated using a finite element analysis. The tensile stress was calculated to increase as the specimen thickness decreased. The SCC initiation time of the specimen was evaluated by the RDCT method, from which result it was found that the crack initiation time decreased with the decrease of specimen thickness owing to the increase of applied stress. After the SCC initiation test, many cracks were observed on the specimen surface in an intergranular fracture mode, which is a typical characteristic of SCC in the primary water environment.

• Structural Monitoring and Maintenance
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• v.3 no.3
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• pp.297-314
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• 2016

As the study of internal corrosion of pipeline need a large number of experiments as well as long time, so there is a need for new computational technique to expand the spectrum of the results and to save time. The present work represents a new non-destructive evaluation (NDE) technique for detecting the internal corrosion inside pipeline by evaluating the dielectric properties of steel pipe at room temperature by using electrical capacitance sensor (ECS), then predict the effect of pipeline environment temperature (${\theta}$) on the corrosion rates by designing an efficient artificial neural network (ANN) architecture. ECS consists of number of electrodes mounted on the outer surface of pipeline, the sensor shape, electrode configuration, and the number of electrodes that comprise three key elements of two dimensional capacitance sensors are illustrated. The variation in the dielectric signatures was employed to design electrical capacitance sensor (ECS) with high sensitivity to detect such defects. The rules of 24-electrode sensor parameters such as capacitance, capacitance change, and change rate of capacitance are discussed by ANSYS and MATLAB, which are combined to simulate sensor characteristic. A feed-forward neural network (FFNN) structure are applied, trained and tested to predict the finite element (FE) results of corrosion rates under room temperature, and then used the trained FFNN to predict corrosion rates at different temperature using MATLAB neural network toolbox. The FE results are in excellent agreement with an FFNN results, thus validating the accuracy and reliability of the proposed technique and leads to better understanding of the corrosion mechanism under different pipeline environmental temperature.

• Proceedings of the KIEE Conference
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• 1999.07e
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• pp.2374-2376
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• 1999

This paper deals with some experimental results of the ACSR inner corrosion detector which is developed in order to measure local corrosion of transmission line. Tested wire is ACSR $97{mm}^2$. Experimental procedures, desirable test results and normalizing method of corrosion grade are reported. It is shown that the detector is possible to inspect the inner corrosion of ACSR, through testing and experimental studying for artificial corroded samples.