This study is interested in evaluating several ultrasonic techniques for detecting and measuring corrosion in pipelines. Due to the scale of pipeline infrastructure, particular attention will be given to the spatial coverage of each technique, as well as the sensitivity of individual sensors to the presence of corrosion. This requires two characteristics of corrosion to be simultaneously considered: corrosion morphology and corrosion distribution. The primary interest of this thesis is corrosion monitoring, which is defined as frequent readings/measurements made at exactly the same location(s) (usually via a permanently installed sensor) [35]. This is in contrast with inspections, which are carried out at intervals by an operator and can be performed over an area of pipe, rather than a single location. A screening technique is considered alongside a monitoring technique in chapter 4.
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1.3.1 Corrosion Morphology
The morphology of the corrosion will affect how sensitive a single sensor is to detecting and measuring a single incident of corrosion. For example, [36] illustrates how guided wave reflection sensitivity varies with defect shape as well as size, however, given that LRGWs provide 100% coverage, the placement of the defect relative to the sensor is not considered. Two corrosion morphologies are studied in this thesis: uniform and pitting corrosion. As the name suggests, uniform corrosion occurs either over the entire surface, or at least over a large proportion of a surface, of a component. Multiple electrochemical cells (anodes and cathodes) form on the surface at any given time [1]. Examples of metals susceptible to uniform corrosion are copper and pre-weathered/COR-TEN steel [37]. As discussed above, uniform corrosion is likely to have a rough surface profile.
When corrosion is highly localised it is known as pitting corrosion. Pitting can occur in isolation or in clusters, and, although there is much less mass/metal loss compared to uniform corrosion, is potentially much more dangerous, as it can cause difficult-to-detect isolated points of weakness. A lone pit can easily be the root cause of failure of an entire component. All metals are at risk of pitting because a slight variation in the homogeneity of the metal’s surface can cause it to become anodic with respect to the rest of the surface [1]. For example, a small amount of surface damage may lead to a higher corrosion rate [38]. In addition, many materials are coated in a passive oxide layer (e.g. Aluminium [39]) which, if it breaks down in a single location, can lead to increased corrosion rates of the unprotected bulk metal underneath [40]. Pitting corrosion covers a wide range of dimensions and aspect ratios, from narrow and deep defects to wide and shallow defects which border on areas of uniform corrosion. Figure 1.3 shows several different pitting cross-sections. The three pit profiles/cross-sections studied in this thesis are b) narrow and deep, c) elliptical and hemispherical, and d) shallow and wide. Each of these can be defined by two parameters: depth and diameter.
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Figure 1.3 Example pits with different aspect ratios defined by depth and diameter (a): b) narrow and deep c) elliptical or hemispherical d) shallow and wide e) subsurface f) undercutting, and pit governed by g) horizontal or h) vertical microstructure [1]
1.3.2 Corrosion Distribution
When selecting a suitable monitoring technique to detect and track corrosion it is necessary to consider the spatial distribution as well as the morphology of the individual corrosion patches. The ratio of the corroded area to non-corroded area is an important factor that needs to be considered [35]. If the area ratio is high (i.e. a large proportion of the inner pipe surface is corroded - Figure 1.4a) then this can be detected using a sparse array of UT spot/point wall thickness measurements, for example. If, however, the isolated corrosion occurs on the inner pipe wall with a low corroded to non-corroded area ratio, then a distributed array of spot sensors is unlikely to detect the corrosion. A greater danger is that the spot sensor may only measure a portion of the corroded area (Figure 1.4b), leading to positive identification of corrosion but the perception of a slow corrosion rate. In this scenario, a monitoring or screening technique with 100% area coverage is required, such as LRGWs. It is also important to consider sensor density. It is possible to cover an entire pipe with spot sensors, however, the cost and complexity of powering, installing and multiplexing between the sensors will make it commercially unviable.
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Figure 1.4 Corrosion distributions with a a) high and b) low corroded to non-corroded area ratio
1.3.3 Coverage Against Sensitivity Trade Off
Currently it is possible for inspections to create a 2D thickness map of a pipe by performing a series of spot measurements systematically scanned over the area under test (known as a c-scan). This technique requires a skilled operator to perform the measurements and is time consuming, leading to a search for more efficient methods. Conventional LRGW systems excite a wave packet in the pipe or plate at one location and rely on the reflection of the wave from a defect. This enables large areas of oil and gas infrastructure to be screened at any one time (e.g. up to 50m either side of an array of transducers [27]) from a single location/access point on a pipe. However, the defects in the pipe must be sufficiently deep and sharp for a detectable reflection to occur (5% cross sectional area loss is commonly quoted [27] as minimum size that can be detected if the defect shape causes a reflection). Therefore, this system is likely to miss smaller areas of wall thinning that might be of concern. Spot wall thickness monitoring systems accurately measure the thickness of a pipe or plate at a precise location (with a WT sensitivity of around 20μm [41]), using the pulse echo or pitch catch method. These spot measurements constantly monitor the average thickness of a pipe (approximately 1cm2 directly under the sensor) and relay the information
back to the plant operator. However, even though multiple sensors can be installed on the same pipe, this system is only able to relay a discretised thickness map of the pipe or plate, thereby potentially missing defects which are not directly under a sensor. The sensitivity/coverage area trade-off is demonstrated in Figure 1.5, illustrating that the current in-service technology occupies either end of the sensitivity/area spectrum. It is therefore the objective of this study to evaluate several techniques which lie between these extremes, with the aim of evaluating both their coverage and sensitivity.
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Figure 1.5 Current ultrasonic corrosion monitoring and screening techniques plotted ona sensitvity-coverage area curve.