This chapter has evaluated the performance of dispersive SH guided wave thickness measurements along a line of a plate, representing the propagation around the circumference of a pipe. The temperature compensated group velocity thickness extraction algorithm has been shown to be able to precisely determine the average thickness of a uniformly thick plate between two transducers, using SH guided waves. The experimental data showed that the temperature compensated thickness value had an associated error of 0.04mm and the average thickness along the line could be determined to that precision. When the same thickness extraction algorithm was applied to simulated signals from plates which contained flat bottomed notches spanning the whole width of the plate, an accurate value of the average thickness could be extracted.
When testing the thickness extraction algorithm on signals that had passed through finite width defects (Hann profile defects and part thickness holes), it was clear that the presence of the defect distorted the received signal significantly and that the thickness extraction algorithm was unable to extract the correct value of the average thickness. The interaction of the wave with the defect led to an increase in the measured thickness at the centre of the defect and measured decreases outside the defect width. If the corrosion patch is much wider than the beam width and is relatively flat, then the proposed corrosion monitoring
73 method appears to be sound. However, for the proposed method to be useful in the field, defects of different sizes and profiles must be detectable and ultimately measurable. As the B-scan simulation of the finite width defects has shown, the presence of a defect elicits a detectable/qualitative response. Although, this method could provide a means of screening a pipe for defects or corrosion, it would be difficult to implement as a quantitative monitoring system.
Chapter 4 will describe a parametric study using guided waves to quantitatively evaluate the sensitivity to defects in reflection and transmission. Two analogous setups are studied: monitoring and screening. The study, thereby, will look to quantify the detection ability of guided waves, but not the ability to characterise defects.
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Detectability of Corrosion Damage with
Circumferential Guided Waves
4.1 Introduction
Chapter 3 presented a method, using short range guided waves, to estimate a temperature compensated value of a pipe or plate’s average thickness, over a given propagation distance. It was concluded that the method presented gave inaccurate measurements when a finite width defect was placed within the path of the guided wave. The value of the estimated average thickness is also highly sensitive to the position of the defect due to scattering of the guided wave and subsequent interference effects. It would therefore be possible to measure no thickness change even if a (large) defect is positioned within the width of the beam.
If, however, adjacent measurements are analysed concurrently then the method presented could serve as a qualitative indication that a defect/region of wall loss exists within a pipe, either as a permanently installed monitoring system (using an array of transducers) or a defect screening system (which scans axially along a pipe). Compared to other multi- measurement scanning methods (e.g. c-scan using a raster scanner) the main benefit of this device is the increased coverage area at each measurement. This chapter, therefore, continues to explore the spectrum of area coverage between the spot ultrasonic measurements and long range guided wave techniques as illustrated in Figure 1.5.
This chapter quantifies the idea of using circumferential guided waves as a means of detecting (as opposed to characterising) wall loss due to corrosion. Temperature correction is not considered, and a simple thickness extraction algorithm is used enabling fair comparison between several modes. The potential for defect detection using reflections from the defects will also be considered alongside the transmission method (average thickness estimation). Specifically, this chapter will evaluate and compare the sensitivities of three guided wave modes optimised for either measurement modality (reflection or transmission) to a range of defects.
Similarly, to chapter 3, the single transducer setup used in Figure 4.1a forms the basis of this study, which propagates a guided wave pulse around the circumference of the pipe and
75 detects it at the same location. However, to fully evaluate the sensitivity of the guided waves (in either reflection or transmission) several assumptions must be explicitly stated: The transducer is able to:
a) preferentially excite a guided wave in one direction around the circumference of a pipe, this is a reasonable expectation since directional transducers have been successfully demonstrated in the laboratory [80] and in the field [27].
b) separate out the transmitted and the reflected signals from one another and treat them independently. This enables a fair comparison between the two measurement modalities.
c) operate at a wide range of input toneburst parameters, allowing optimisation of input toneburst characteristics in either transmission or reflection.
In this chapter the two analogous setups in Figure 4.1b and c were investigated. In Figure 4.1b a monitoring setup is shown that consists of an array of transducers each of which transmit a dispersive guided wave around the circumference of the pipe, extracting both: a value of the average thickness around the circumference from the through transmitted signal; and a value of the reflection coefficient from the reflected signal. In Figure 4.1c a rapid screening setup which uses a single transducer which is axially scanned along the pipe extracting the average thickness and reflection coefficient. All the fundamental guided wave modes were evaluated (A0, S0, and SH0) as well as the first shear horizontal mode (SH1). Both setups have an associated pitch - distance between adjacent measurements indicated in Figure 4.1b and c - which governs the coverage area and therefore the sensitivity.
In contrast to the single transducer setup explored in chapter 3 the monitoring and scanning setups combine multiple measurements with varying spatial distribution, depending on the measurement pitch. Therefore, the pitch must be taken into account when assessing the ability of a setup to detect a defect. This chapter uses the concept of the probability of detection (POD) as the metric to assess the sensitivity of a setup.
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Figure 4.1. a) The single transducer setup studied in this chapter, which inputs a directional guided wave pulse at a single location. b) The proposed array setup. c) The proposed short range guided wave rapid scanning or screening setup
This chapter first describes the finite element simulations, followed by a detailed explanation of the two measurement methods used. The selected input toneburst characteristics as well as the reasons for them are then presented. Some example FE simulation results are then shown, before a description of the POD methods, which is used to quantify the sensitivity. The POD results and discussion are then given before conclusions are drawn.
4.1.1 Overview of Guided Wave Reflection Literature
The literature discussed in chapter 3 covers the existing knowledge on the use of dispersive guided waves, whereas the following gives an overview of the literature on the reflection of guided waves, specifically for the purposes of defect detection and characterisation, propagating either circumferentially around or axially along a pipe wall or in a plate. There is also commercial interest in circumferential guided wave systems [92]. The use of circumferential guided wave reflections for the detection of cracks in pipes has been studied by Valle et al. [93] and Fletcher [94], as have through holes [95], part thickness holes [48], [96] and axial slots [97]. Many finite element and experimental studies have simplified pipe geometry to that of a flat plate to further study more complex defects such as irregular defects [36], [98], part thickness ellipses [90] as well as to characterise the effect of sharp edges on defects [88]. Full, albeit very coarse, 3D FE simulation of guided waves have been commonplace since the early 2000s [99], however, current GPU FE software allows for both high fidelity and fast processing of many different defect sizes [100]. It is these recent developments that has allowed this study to model and subsequently probabilistically analyse a large range of defect sizes to ascertain the sensitivity of guided waves to wall thinning.
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