Abstract

Over 50% of global pipes have been made of cast iron, and most of them are aging. In order to effectively estimate possibilities of their failures, which is paramount for efficiently managing asset infrastructures, it requires the remaining wall thickness (RWT) of a pipe to be known. In fact, RWT of the cast iron pipes can be primarily measured by the magnetism based nondestructive testing technologies though they are quite slow. To speed up the inspection process, it is proposed to sense RWT of a part of a pipe and then employ a model to predict RWT in the rest. Thus, this letter introduces a 3-D model to efficiently represent RWT of a pipe given measurements collected intermittently on the pipe’s surface. The proposed model first transforms 3-D cylindrical coordinates to 3-D Cartesian coordinates before modeling RWT by Gaussian processes (GP). The transformation allows GP to work properly on RWT data gathered on a cylindrical pipe and effectively predict RWT at unmeasured locations. Moreover, periodicity of RWT along circumference of the pipe is naturally integrated. The effectiveness of the proposed approach is demonstrated by implementation in two real life inservice aging cast iron pipes, where the obtained results are highly promising.

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