Comparing Conventional AUT and Phased Array AUT Corrosion Mapping

Introduction

For assets in oil and gas and related industries, utilizing automated ultrasonic testing (AUT) for corrosion mapping to detect and quantify damage can play an important role in an effective mechanical integrity program. Material thickness is measured by calculating the time it takes for the sound wave to reflect back to the transducer after encountering the backwall or an indication in the material. By quantifying material thickness across the entirety of an asset, the data can highlight patterns of degradation and be used to determine the corrosion rate for reliability/maintenance, plan repairs, monitor known damage, and assist with asset remaining life decisions. Responsible maintenance and planning can increase asset life and maintain stable and safe operations.

Corrosion can be generalized, i.e., uniform across sections or the entirety of an asset, or localized, specific to certain locations on an asset [1]. Generalized corrosion is often predictable and easy to detect, whereas localized corrosion is not always detectable, especially when performing on-stream inspections to ascertain the internal condition of the equipment from the outside. Corrosion is typically the oxidation of a metallic surface that causes it to degrade. Erosion is a mechanical wearing away of the metal and is often localized. Mechanisms include, but are not limited to, erosion corrosion, microbiologically influenced corrosion (MIC), and stress corrosion cracking [1]. An internal visual inspection is typically one of the most cost-effective ways to detect localized corrosion but even this approach can miss areas that are precluded from inspection due to attachments and other equipment.

The prevailing corrosion inspection procedure for tanks, piping, pressure vessels, and other metallic assets (not to mention applications with non-metallic components) is to measure the material thickness and/or detect and quantify the presence of mid-wall indications [2]. This is usually accomplished by using flaw detectors. However, there is a growing need for corrosion mapping in order to understand the condition of the entire asset as opposed to point-level readings at corrosion monitoring locations (CMLs).

Corrosion mapping involves plotting individual point-level material thickness readings in a grid. Traditionally, this process is performed manually with hand-drawn grids. The inspector spot checks for wall thickness at particular points on the equipment within the grid, then the readings are entered manually into a spreadsheet correlating to the grid. The advent of AUT in the early 1990s, as well as recent advances in robotics and software in nondestructive testing (NDT) have helped to further automate this process. Independent of the inspection technique utilized, automation allows for full asset coverage and, when paired with software solutions, produces two- or three-dimensional corrosion maps for immediate repair planning and predictive analytics.

There are several AUT techniques for corrosion mapping, but this article will discuss the differences in technology and data between conventional UT and phased array applications. Conventional UT utilizes a single beam to report one thickness reading at a time, whereas phased array UT reports an array of thickness readings. In this article, results from a test scan of an Olympus D790 conventional probe on a demonstration block are compared to those from a dual linear array (DLA) Olympus Rex1 probe on the same block. While both techniques can provide a detailed corrosion map, the dual linear phased array probe provides higher productivity, accuracy, data density, and probability of detection (POD) than conventional UT.

Please note: the purpose of the article is to compare the two most common off-the-shelf AUT technologies used for corrosion mapping. It is not intended to account for the myriad of solutions that can be engineered through conventional probe design and simulation to achieve similar results to the off-the-shelf phased array probe tested here.