акустика / gan_ws_acoustical_imaging_techniques_and_applications_for_en

Figure 9.2 Measuring size and angular position of a flat defect from the edge-wave transit times, when scanned with a sharp beam: (a) with longitudinal waves; (b) with transverse waves (Krautkramer¨ and Krautkramer¨ [19] © Springer-Verlag)

(depending on the quality of bond at both interfaces) within the range from a complete disband to a well-bonded joint. The is often the only reliable method for distinguishing a poor quality bond from a good bond.

9.2Automated Ultrasonic Testing

9.2.1Introduction

Automated ultrasonic testing (AUT) involves the use of a robot to carry out the inspection work instead of working manually. It has become popular during the last 20 years. It is often used when inspecting large areas. When large engineering structures are inspected, the amount of data produced can be enormous, and a bottleneck can arise at the manual interpretation stage. Boredom and fatigue of operators can lead to unreliable and inconsistent results, where significant defects are not reported. Besides this, manual testing results in many limitations: a high training cost and a long training procedure. In order to improve their performance, it is recognized that there are gains to be derived from automating the ultrasonic inspection process by using a manipulator.

AUT is the latest innovation in the inspection of welding in onshore and offshore pipeline constructions and has distinct advantages over traditional radiography testing (RT) methods. AUT is replacing radiography for pipeline girth weld inspection world wide.

The advantages of conventional AUT over radiography are as follows:

1.No radiation hazard.

2.Better process control of welding, giving lower reject rates.

3.Larger defect acceptance using Engineering Critical Assessment (ECA), also giving lower reject rates.

4.Faster inspections.

5.Rapid and reliable data interpretation from special output display.

6.Overall, onshore mechanized ultrasonics offers a better inspection solution with lower reject rates than radiography.

Contemporary gas and oil pipeline projects have stringent time, budget and planning requirements. The changing dynamics and importance of key pipelines projects drive the industry to prefer faster yet more reliable AUT over the traditional radiography testing. It has multidimensional advantages, which include superior risk analysis, reliability, time effectiveness, cost savings, sizing abilities, safety and weld defect detecting and trending. Modern pipeline requires testing methods that can match high production rates at many different spreads concurrently. The testing method must have a flexible operation design so that it can be customized to the diverse and complex requirements of different projects. The selection of AUT for large projects offers significant advantages over RT due to its fast testing time and the immediate availability of results at the weld site. It enhances productivity. Additionally with automated method, ultrasonic testing (UT) quality is able to provide a high level of NDT service to the many work fronts with limited numbers of crew, which is a significant advantage over RT. It does not interfere with any activity on the ‘Right of Way’; it offers superior Probability of Detection (POD); and has proven itself as a successful tool for unsound weld verification.

AUT is more effective than RT in its ability to detect planar defects such as lack of fusion. The UT scan system can scan an entire weld in one circumferential scan. To do this, the wall thickness is first divided into zones and a probe technique is selected to inspect each zone individually. Pulse/echo and pitch and catch techniques are used to target the weld preparation as perpendicularly as possible. The through-transmission technique is used to verify the proper acoustic coupling of the probes to the pipe surface and for the detection of transverse indications.

AUT also provides a superior processing analysis and data on the inspection and quality of the weld. The UT scan’s data computers are paired with a unique data archive and weld management software system called ‘Plursweld’, which automatically collects all AUT process parameters and weld testing results. An auto-update repair list is generated.

The ‘live’ and auto-reporting system generates inspection reports at the end of each day or on demand. Weld numbers, GPS location, time and date are automatically recorded for each weld. The UT scan can also provide permanent records for each inspected joint, whereas radiography film can only be saved for 10–15 years.

9.2.2Testing Procedure

In AUT, due to the huge area to be covered, and to speed up the scanning process, the robot and array transducers have to be used.

In the AUT of pipeline girth welds, a series of phased array probes is mounted on a band strapped around the pipe adjacent to the weld and driven around the pipe’s circumference. As the probes travel around the pipe, ultrasonic data is collected from the weld and the software enables flaw sizes and positions to be displayed. Very fast, scanning speeds ( 100 mm/s) are required to keep pace with construction, and it is necessary to complete a weld inspection every 2–4 minutes.

9.2.3Example of an AUT System

An example of an AUT system is the PipeWIZARD of Olympus NDT. It is a cam that crawls along the surface of the pipe and, at the same time, carries out the scanning work controlled by the computer. The advantage of this system over conventional AUT systems is that it utilizes phased arrays. The major advantages of using phased arrays for AUT over conventional UT are as follows:

1.Scan time is reduced by several seconds due to the narrower probe pan.

2.Increased number of zones for better detection and vertical sizing.

3.Smaller probe pans, reducing the length of pipe coating that has to be cut back.

4.Any weld profile, pipe diameter or wall thickness can be accommodated by recalling the appropriate setup files.

5.Arrays can be programmed to check the coupling automatically using the back wall.

6.One PipeWIZARD can scan pipes ranging in diameter from 2 to 56 in.

7.The standard PipeWIZARD can scan pipewalls from 6 to 50 mm.

A demonstration of the performance of the PipeWIZARD is shown in Figure 9.3.

In the PipeWIZARD computer screen shown, the vertical plots are the signals associated with specific zones of the weld (cap, body and root) on the upstream and downstream sides of the weld. Each zone is approximately 2 mm deep and is scanned by selecting an appropriate focal law that controls the phasing of the array. The screen display essentially ‘opens out’ the weld from the root. Flaw lengths are estimated from circumferential position markers and depths from the number of zones affected. The red zones are above the threshold. The central grey area is a time of flight diffraction (TOFD) plot.

Figure 9.3 Demonstration of the performance of the PipeWIZARD (Picture courtesy of Absolute NDE as found on the Olympus website at http://www.olympus-ims.com/en/pipewizard/)

2.Standard deviation: The measure of dispersion or scatter of values of a random variable above the mean. If the values tend to be concentrated near the mean, the variance is small; but if the values tend to be distributed away from the mean, the variance is large.

3.Pearson correlation: The measure of the linearity of the data.

4.Dispersion uniformity degree: The dispersion uniformity degree (DUD) is defined as

DUD = Maximum − μ

σ

where ‘maximum’ is the maximum value in the data set, μ is the mean value of the data set, and σ is the standard deviation.

The next step is to choose the best set of features that discriminate the classes most effectively; that is, enhance the separability among the different classes while increasing homogeneity within the repeated class at the same time [5]. Because the signal is rectified, the frequency information becomes blurred, and little separability is shown by the AR coefficient. The three AR coefficients are therefore eliminated, and only the standard deviation σ , the Pearson correlation and the DUD are left as features. This reduces the computation complexity.

After the feature space is obtained, the next step of a pattern recognition system is classification. The goal of a classifier is to consign objects of interest to one of a number of categories or classes [6]. There are many methods to do the classification task, and a neural network is the most common way for engineering purposes. However, for recognizing peaks, the classification tree is the best method.

The automatic peak detection algorithm can detect peaks of very little difference better than a human operator. When the gain is too high, the signal will be very noisy, and even a human operator can recognize all the peaks properly. In practice, almost all the test procedures define the gain range.

The automatic calibration procedure and the automatic shaft testing procedure can both be implemented by software. An example of the automatic defects detection for an aluminium shaft is shown in Figure 9.6.

9.3Guided Waves Used in Acoustical Imaging for NDT

There are two standard types of guided waves: Rayleigh waves (or surface waves) and Lamb waves.

Rayleigh waves have the unique feature that they will follow complex curvatures that can often provide a path to defect areas that are virtually inaccessible by other waveforms. These unique characteristics justify their usage in certain situations in ultrasonic inspection. The energy of the surface wave is restricted to the surface, which is an advantage as it can travel along a curved path during inspection. However, this also becomes a disadvantage as it is severely affected by ordinary anomalies that appear on machines and structural parts, such as pits on castings, tool marks, and so on. Figure 9.7 shows the cross-sectional view of a surface wave.

The other type of guided wave is the Lamb wave. Unlike surface waves, whose propagation is restricted only to one surface, Lamb waves can propagate in situations where there are

y

x

t

O z

l

w

Figure 9.8 Plate for Lamb wave excitation (Bray and Stanley [21])

Ultrasonic pulses are composed of a number of frequencies and each frequency component in the excited pulses will travel at a varying phase velocity, as shown in Figure 9.9(a).

However, due to transducer characteristics, the amplitudes of the frequency components decrease away from the probe central frequency f0. Also, components having different phases may tend to cancel. The overall result is that contributions to the pulse amplitude are diminished for components away from f0. An additional effect is due to the fact that frequency components, different from the central frequency, will travel at different phase speeds. The result is a group velocity determined by the frequency components containing the dominant energy. The components nearer to the central frequency would contribute most to the shape and group velocity of the pulse. The effect observed would be that of a dispersive pulse, which is often observed as a cluttered arrival pattern that creates difficulty in the interpretation of ultrasonic test results in bars and plates. Despite these complications, Lamb waves are useful in ultrasonic nondestructive evaluation (NDE), and in the inspection of metals and composite plate for horizontal separation.

Overall, the guided wave modes, like Rayleigh waves and Lamb waves, have limited but rather specialized applications in NDE. A Lamb wave is particularly used for inspecting the long dimension of samples up to few metres in length. The particular advantage of Rayleigh waves is their ability to follow the curvature of a part to an expected defect location. In certain situations, this same advantage also exists for Lamb waves, but the dispersive nature of these waves makes their application difficult.

These guided wave modes can be also used in acoustical imaging in ultrasonic NDE works.

9.4Ultrasonic Technologies for Stress Measurement and Material Studies

9.4.1Introduction

The scope of nondestructive evaluation (NDE) includes the efficient design of the machines and their satisfactory maintenance service in various industries, such as aerospace, automotive, rail tracks, oil and gas, semiconductor, and so on. This will require an in-depth knowledge of the properties of the material being used, such as the nature of the internal stresses, in addition to studying the isotropy, homogeneity, texture, grain size determination, and the inspection of multilayered material for interfacial defects. The ability to nondestructively investigate for

abnormal material conditions would allow the engineer not only to optimize the design but also to optimize the maintenance cycle.

9.4.2Internal Stress Measurements

Stress is considered to be incipient damage, and usually gives rise to cracks and defects. Hence, stress measurement is an eventual essential procedure of NDE. There are various ultrasonic methods for measuring stress, but in this chapter we shall focus only on methods related to acoustical imaging.

We shall be dealing with stress measurement using the scanning acoustical microscope (SAM). This, which is also known as quantitative acoustical microscopy, and is concerned not only with the measurement of the applied stress but also with the residual stress spreading in the solids.

9.4.2.1 The Use of V (z) Curve Technique for Stress Measurement

The propagation of both bulk and surface acoustic waves is affected by the presence of static stresses in the solids. This phenomenon is known as the acousto-elastic effect. The Rayleigh velocity, or surface acoustic wave velocity, is reduced in the presence of stress. Stress cannot be measured directly when using elastic waves but can be calculated from the Rayleigh velocity. In certain cases, the presence of stress can be ascertained unambiguously from velocity measurements. Since this difference in velocity vanishes in an unstressed material, this phenomenon can provide a direct indication of the presence of stress and can be employed to map stress distribution in materials [4–8]. Since the effect of stress on velocity is small, we must be sure that a measured velocity change is indeed due to stress and not simply to inaccurate values for the elastic constants.

We shall first need to derive the equation for the period of the oscillation of the V (z) curve. An example of a V (z) curve is showed in Figure 9.10.

Stress can provide information on incipient damage, which is the process before the actual fatigue or crack occurs. Also, heat damage generates stresses and from stress measurement one can obtain information of heat damage on materials – for instance, aerospace materials. We call this quantitative acoustical imaging.

Heat damage can be investigated by taking the C-scan acoustical images of the change in grain size due to heat damage, but this is qualitative imaging and is unable to give the exact dimension of the grain size. We call this quantitative acoustical imaging as it can give the quantitative change in the values of the elastic modulus due to heat damage.

For a derivation of the equation for the determination of Rayleigh (surface wave) velocities an understanding of the V (z) effect is crucial to an understanding of the contrast in the acoustic microscope. For this derivation we use the ray model shown in Figure 9.11.

This represents a microscope with a specimen in which the Rayleigh wave can be excited and is defocused towards the lens. Most rays from the lens are reflect specularly from the specimen and then pass through the lens with an inappropriate angle to contribute significantly to the excitation of the transducer (ray aa ). There are two important rays, one is bb which propagates along the axis of the lens (taken to be normal to the specimen surface), is reflected, then propagates back along the same path. The second important ray, cc , is incident on the