The Corrosion Under Insulation (CUI) Monitoring: Prediction of CUI Using Electromagnetic Wave

Authors

  • Vun Kiat, Clement Yong FKMP
  • azzura ismail Universiti Tun Hussein Onn Malaysia

Keywords:

Corrosion under insulation, Non-destructive evaluation, Corrosion rate

Abstract

Corrosion Under Insulation is a major problem for oil-and-gas industries, as it costs loss of billions of dollars annually. The problems associated with CUI are that the corrosion occurred beneath the insulation layer, thus not visible for human eye and visual inspection. The objectives of this study are to identify the amount of water ingress in insulation and to identify the corrosion rate of low carbon steel pipe under insulation over a period of 6 months. The scopes of the study are limited to low carbon steel pipe, with length of 2m, pipe thickness of 10mm, and the range of wireless network among electromagnetic sensors are 20m, and the study is carried out at an uncontrolled environment. The material of the pipe used is low carbon steel pipe, while the insulation material is rockwool. The cladding, which is the weather barrier is made of zinc. The method used to detect the amount of water ingress in insulation is by using a pair of electromagnetic sensors, by using pipe-guided wave. The data gathered from the pipe-guided wave was then transferred and stored at a PC through wireless connection. The fourth sentence presents key findings and trends that can be observed from the data. The findings through 128 days observation have shown that the average amount of water ingress in insulation was -50.25mℓ, CUI rate of 0.36 mm/year, and maximum estimated wall loss was 0.47mm. The findings on the amount of water ingress in insulation and CUI rate allowed maintenance staff at oil-and-gas facilities to forward planning the maintenance work and the study may be carried out under controlled environment for future work.

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Published

19-01-2022

Issue

Section

Articles

How to Cite

Yong, V. K. C., & Ismail, A. (2022). The Corrosion Under Insulation (CUI) Monitoring: Prediction of CUI Using Electromagnetic Wave. Research Progress in Mechanical and Manufacturing Engineering, 2(2), 1063-1068. https://penerbit.uthm.edu.my/periodicals/index.php/rpmme/article/view/5158