A wavelet-based denoising method for pipeline dent assessments

Abstract

Strain-based assessments of dents in buried steel oil and gas pipelines are commonly carried out in practice. Dent signals obtained from the caliper inspection tool contain noises that can have a large impact on the accuracy of the estimated strain. This paper proposes a novel wavelet-based denoising method for dent signals based on the overcomplete expansion with the corresponding dictionary constructed using the stationary and hyperbolic wavelet transforms. The proposed method is validated based on noise-free and noisy dent signals generated from elasto-plastic finite element analyses of a pipe segment subjected to an indenter and shown to be more effective than the commonly used wavelet transform-based hard- and soft-thresholding methods in terms of the root mean square error and the accuracy of the effective dent strain estimated from the denoised signal. The proposed method is further employed to denoise 42 real dent signals from in-service pipelines to illustrate its effectiveness and potential practical application to facilitate strain-based dent assessments.