High resolution acoustic identification of clusters of small blockages in fluid-filled pipe using maximum likelihood estimation

Abstract

This paper presents a method for identifying a cluster of small blockages (i.e., blockages with length on the order of centimeters and radial extent on the order of millimeters and separated by a distance on the order of few centimeters) in pressurized fluid-filled pipes using sound waves. This focus on defects with small scale, and, thus, small scattering strength is exploited to develop a Neumann series solution for the scattered acoustic wave field. The probing waves are such that the Helmholtz number (ratio of blockage longitudinal length scale and probing acoustic wavelength) is of order 1 or larger. A high resolution inverse technique for identifying a cluster of small blockages based on the maximum likelihood estimation principle is developed. The proposed technique uses two-dimensional search space to resolve each blockage in the cluster and requires a single measurement point only. The method is successfully tested through both numerical and laboratory experiments. The proposed methodology allows an early identification of a cluster of small defects and leads to reliable condition assessment of pipelines, which is necessary to inform decisions as to when remedial actions are required.

Adaptive anadromic regularization method for the Cauchy problem of the Helmholtz equation

“…Early identification and remediation of such nascent defects are crucial for preventing them from escalating into serious operational challenges and causing significant damage to the pipeline structure. A number of high-resolution imaging techniques for defect detection in pipeline systems have been developed, as outlined in [30]. However, their implementation at an old pipe system will create the blueprint for how to integrate (i.e.…”

“…Addressing this issue holds substantial relevance in practical scenarios. For instance, it assists in detecting anomalies in pipeline infrastructures [29,30] and accurately locating acoustic sources in the domain of oceanography [9].…”