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Condition Monitoring and Predictive Modelling of Coating Delamination within Remote and Stationary Assets.

Latif, J., Khan, Z. A., Nazir, M. H., Stokes, K. and Plummer, J., 2019. Condition Monitoring and Predictive Modelling of Coating Delamination within Remote and Stationary Assets. Structural Health Monitoring, 18 (4), 1056-1073.

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CorrModel_Finalv_V12_Accepted Version.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial No Derivatives.


DOI: 10.1177/1475921718773524


The ambiguous nature of meteorological parameters in uncontrolled environmental conditions makes it difficult to determine the structural integrity of stationary and mobile assets. The weather conditions for large vehicles, at The Tank Museum at Bovington United Kingdom, which are operating under controlled and uncontrolled environmental conditions are investigated through weather history and corrosion monitoring techniques applied to large military vehicles by using linear polarisation resistance method. Corrosion reactions were found on several occasions during the operation of large vehicle within uncontrolled environment due to critical level of metrological parameters including salinity, relative humidity and rainfall. Comprehensive solutions have been proposed to detect damage initiation at the earliest possible stage to prompt maintenance professionals to take necessary actions to avoid damage. Early detection techniques will help to prolong the service life of large vehicles or metal structures which are operating or installed remotely. The analysis of diffusion of salt particles into coating during summer and winter season is also presented by estimating the salt concentration by taking linear relationship between wind speed and salt deposition rate based on ISO classification of airborne salinity. The proposed solutions can be applied to valuable assets operating in both non- coastal and coastal regions, near the sea, to predict and estimate the damage.

Item Type:Article
Uncontrolled Keywords:Corrosion; Coating delamination; Condition monitoring; Diffusion; Predictive modelling
Group:Faculty of Science & Technology
ID Code:30552
Deposited By: Symplectic RT2
Deposited On:09 Apr 2018 11:16
Last Modified:14 Mar 2022 14:10


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