A prediction model for oil and gas pipeline deformation based on ACM inspection signal waveforms

Abstract

Deformation is one of the leading causes of oil and gas pipeline accidents, affecting pipeline transportation efficiency and operational safety. This paper proposes a pipeline deformation detection method and prediction models based on alternating current magnetisation (ACM) technology. Firstly, the mechanism of pipeline deformation detection based on ACM technology is introduced and mathematical models are proposed to evaluate the deformation length and height using magnetic detection signals. Next, finite element models of detection signals for deformations with various lengths and heights are analysed and original signal waveforms are obtained. Furthermore, linear and polynomial fitting mathematical models are developed to invert the deformation length and height using the measured peak signal and L' (distorted signal length) value. Finally, experiments are conducted to demonstrate that the length and depth of a deformation can be estimated by linear and polynomial models with tolerable errors. The proposed approach combining ACM and a prediction model is verified to size deformation in pipeline inspection quantitatively.