Assessment of Pipeline Condition Using Heterogeneous Input Data

An inverse analysis model was developed which provides a mathematical framework for interpretation, in terms of the condition of a buried pipeline, of survey data in the presence of random noise. A boundary-element forward model was coupled with a weighted nonlinear regression algorithm to obtain pipe surface properties from two types of survey data: soil-surface potentials and local values of current flowing through the pipe. The model was demonstrated for synthetic data generated for a section of a coated underground pipeline electrically connected to a vertical sacrificial anode. The success of the regression was sensitive to the relative weighting applied in the objective function to the respective types of data. A generalized weighted and scaled objective function is proposed.

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