MONITORING CRACK GROWTH IN PRESSURE VESSELS BY ACOUSTIC EMISSION TECHNIQUE
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MONITORING CRACK GROWTH IN PRESSURE VESSELS BY ACOUSTIC EMISSION TECHNIQUE
ENGINEERING DEPARTMENT OF MECHANICAL
COLLEGE OF ENGINEERING TRIVANDRUM
AE-Analysis is an extremely powerful technology that can be deployed within a wide range of usable applications of non-destructive testing: metal pressure vessels, piping systems, reactors, and similar. The growing discontinuities in pressure vessels and structures under load can be detected by monitoring their acoustic emission signals. Acoustic emission (AE) examination is a rapidly maturing non-destructive testing method used to monitoring structural integrity, detecting leak and incipient failures in mechanical equipment. It is a high sensitivity technique for detecting active microscopic events in a material.
Acoustic emission differs from most other NDT methods in two key respects. First, the signal has its origin in the material itself, not in an external source. Second, acoustic emission detects discontinuity movement, while most other methods detect the existing geometrical discontinuities.
Joseph Kaiser from Germany reported the first comprehensive investigation into the phenomenon of acoustic emission. His objectives of research were to determine the tensile tests of conventional engineering materials what noises are generated from within the specimen, the acoustic process involved, the frequency level found and the relations between stress-strain curve of the materials. His most significant discovery however was irreversibility, which is known as Kaiser effect. Acoustic emission technique slowly gathered ground as tool for Non-destructive testing applications and the applications spread to different fields such as aerospace and nuclear industries, chemical plants etc.
In this seminar and presentation the Acoustic Emission Signature during crack growth in 304L Stainless Steel material is discussed in detail. In this study the Acoustic Emission signals generated from different types of Compact Test specimens viz. plain, welded with pre-crack under tensile loading are explored.
MONITORING CRACK GROWTH IN PRESSURE VESSELS BY ACOUSTIC EMISSION TECHNIQUE.rar (Size: 601.56 KB / Downloads: 129)
No material is perfect or without interruption in its physical structure. Such interruptions at microscopic levels are called discontinuities. Every discontinuity need not be a defect but all defects are discontinuities. Significance of a defect depends on the requirements of the final product. Planar flaws like cracks, lack of fusion, lack of penetration, undercut, etc. are considered to be severe than volumetric defects like inclusions, porosities and cavities. A planar flaw produces high stresses locally, introduces triaxial stresses at the flaw and increases the stress intensity factors to a threshold value above which stable or even unstable crack growth occurs. Design techniques have improved to define the stress intensities accurately in presence of flaws. Material testing techniques are evolved to evaluate the tolerable stress intensity levels that can cause stable as well as unstable crack growth. Finally this helps in defining tolerant flaw sizes that are in turn detected by NDE techniques like Acoustic Emission (AE) and screened out or repaired.
AE TECHNIQUE FOR REAL TIME MONITORING
The acoustic Emission Technique (AET) is a relatively recent entry into the field of non-destructive evaluation, which has particularly shown a very high potential for material characterization and damage assessment in conventional as well as non-conventional material. Acoustic Emission (AE) phenomenon where transient elastic waves are generated by the rapid release of energy from localized sources within a material. In other words acoustic emission refers to the stress waves generated by dynamic processes in materials. Emission occurs as a release of a series of short impulsive energy packets. The energy thus released travels as a spherical wave front and can be picked from the surface of a material using highly sensitive transducers, usually electro mechanical type placed on the surface of the material. The mechanical wave thus picked up is converted into electrical signal, which on suitable processing and analysis can reveal valuable information about the source causing the energy release.
In the conventional NDT methods, some form of energy is fed into the material which interacts with flaws and defects in the material and gives description of these defects existing in the material. Where as, in the case of AE technique, active defects themselves speak about their existence and condition. Because of this AE technique is termed s active NDT to detect active defects. This technique provides us the dynamic characteristics of a flaw or defect such as its growth rate, criticality and intensity. On the contrary even if a flaw is very large in size, AE cannot directly indicate its presence unless it becomes active.
SOURCES OF AE
All solid materials have certain elasticity. They become strained or compressed under external forces and spring back when released. The higher the force and, thus, the elastic deformation, the higher is the elastic energy. If the elastic limit is exceeded a fracture occurs immediately if it is a brittle material, or after a certain plastic deformation. If the elastically strained material contains a defect, e.g. a welded joint defect, a non- metallic inclusion, incompletely welded gas bubble or similar, cracks may occur at heavily stressed spots, rapidly relaxing the material by a fast dislocation. This rapid release of elastic energy is what we call an AE event. It produces an elastic wave that propagates and can be detected by appropriate sensors and analyzed. The impact at its origin is a wideband movement (up to some MHz). The frequency of AE testing of metallic objects is in the range of ultrasound, usually between 100 and 300 kHz.
Everybody knows the sound of breaking glass but it is not as widely known, that tiny cracks in steel or other solid materials emit very intense ultrasound bursts. AE testing detects and interprets the acoustic events resulting from these crack processes and can identify, locate, and display a beginning damage to the tested object within very short time.
During plastic deformation, dislocations move through the crystal lattice. These movements also produce AE but most of these processes (except for twinning) only have very low amplitudes, which can be measured reliably only at a short sensor distance and in laboratory environment. Most of these processes produce continuous signals rather than short bursts. Bursts are pulses or short wave packets; the type of signals AE testing is based on.
AE testing is a active, receptive technique analyzing the ultrasound pulses emitted by a defect right in the moment of its occurrence. In contrast to the ultrasound technique one does not measure the response to an artificial and repeatable acoustic excitation of the test object. Instead, the sound signals produced by defects are evaluated, every growth of a defect is a unique event and can’t be exactly reproduced again.
The AE analysis is a dynamic technique. AE occurs when a crack grows or when crack borders rub against each other, e.g. when a crack closes after relaxation of the test object.
Also corrosion, e.g. at the bottom of oil tanks, produce burst AE that propagates through the liquid oil to the tank wall, where it can be detected. With leakages, AE is e.g. produced by turbulent flow in the leak itself or by particles rebounding from the tank support. Burst AE from leakages will occur mainly at high pressure. Small pressure differences mainly cause laminar flow that emits continuous AE with low amplitudes and small propagation distances.
Also, if due to mechanical loading composites de-laminate, glue joints detach, fiber reinforcements break, etc. AE is produced, which can be analyzed for testing or monitoring these structures.
PROPAGATION OF AE SIGNALS
A short, transient AE event is produced by a very fast release of elastic energy, actually a local dislocation movement. This local dislocation is the source of an elastic wave that propagates into all directions and cannot be stopped any more. It is similar to an earthquake, with the epicenter at the defect, but with microscopic dimensions.
On flat surfaces, the wave propagates in terms of concentric circles around its source and can be detected by one or more sensors. During propagation, the wave is attenuated. The maximum distance, where an AE event still can be detected depends on various parameters, e.g. on the material properties, the geometry of the test object, its content and environment, etc. On flat or cylindrical metal surfaces, events can still be detected at a distance of several meters, which is one of the great advantages of this technique. In liquid filled pipelines the maximum distance AE events can be detected is usually longer than in gas filled tubes, because the AE signal attenuates less in the liquid volume than in the thin tube wall.
THE AE PROCESS CHAIN
A process chain always exists at AE testing. The process chain basically consists of the following links:
1. Test object and application of load: Produce mechanical tensions
2. Source mechanisms: Release elastic energy
3. Wave propagation: From the source to the sensor
4. Sensors: Converting a mechanical wave into an electrical AE signal
5. Acquisition of measurement data: Converting the electrical AE signal into an electronic data set
6. Display of measurement data: Plotting the recorded data into diagrams
7. Evaluation of the display: From diagrams to a safety-relevant interpretation
Mechanical stress has to be produced within the test object, which is usually done by applying external forces. The behavior of the material and the starting point of the release of elastic energy, e.g. by crack formation, are influenced by the material properties and the environment conditions.
The elastic wave propagating through the material is detected and converted into the electrical AE signal by the AE sensors.
The AE System processes the AE signal, converts the received wave packets into feature data sets, determines the source locations, calculates statistics, and displays them graphically and numerically.
So-called parametric channels measure the environmental conditions as well as the external load as reference parameters for the detected AE.
In very few cases, AE testing is based on only a few bursts. In general, some hundreds or thousands of bursts are recorded for statistic evaluation. Statistical evaluation of waveforms themselves is difficult, but certain features of waveforms can be evaluated statistically. One has to determine the most important parameters of each waveform in order to compare the results of the structure under test with those of defect- free test object and with those of a defective test object. The most commonly used features are (see figure 5):
Arrival time (absolute time of first threshold crossing)
Rise-time (time interval between first threshold crossing and peak amplitude)
Signal duration (time interval between first and last threshold crossing)
Number of threshold crossings (counts) of the threshold of one polarity
Energy (integral of squared (or absolute) amplitude over time of signal duration)
RMS (root mean square) of the continuous background noise (before the burst)
AE bursts are not only produced by the defects we are looking for but can also originate from drop-ins such as peak values of the background noise, which sometimes exceed a low threshold. Therefore, it is very important to determine those characteristics that distinguish the wanted from the unwanted bursts.
The peak amplitude is one of the most important burst features. Crack signals show medium to high amplitudes and have durations of some 10 s, depending on the test object’s properties.
In most cases, bursts with less than 3 threshold crossings and durations less than 3 s can be regarded as unwanted signals. Most of the bursts with low amplitudes and long duration are friction noise. Very short signals may indicate electrical noise peaks, especially, if they arrive at all channels at the same time.
With logical filters one can separate bursts on the basis of those burst features in a flexible way. This must be done carefully: Always make sure not to miss inadvertently important bursts.
THE AE SENSORS
Piezo-electric sensors have proved to be most appropriate for AE testing. They are robust and more sensitive than other sensor techniques, e.g. capacitive, electro-dynamic, or laser-optical sensors.
When testing metal vessels for integrity, frequencies between 100 and 300kHz are usually most interesting. The sensors used for this frequency range have a resonance at about 150 kHz and cover the range of 100 – 300 kHz with a variation of sensitivity of about 6 dB. The resonance frequency determines indirectly the spatial range of the sensor
High frequencies attenuate faster, so they have a smaller detection distance. Background noise coming from longer distances consist only of frequency components below 100 kHz, so they have only small influence on the measurement chain tuned to 100 – 300 kHz.
For testing tank bottoms, sensors with a high sensitivity in the range down to 25 kHz are required, because signals run over long distances. Hence it is very important to find and turn off potential noise sources.
Often the sensors already contain a preamplifier and are attached to the objects using magnetic holding devices. The amplified AE signal is transmitted to the AE system via a signal cable. Usually, the 28VDC power supply for the pre-amplifiers is fed through the signal cable. The signal cable can have a length of several 100 m.
AE DATA ACQUISITION SYSTEM
A basic Data Acquisition system consists of the following equipments
1. AE Sensor
2. The Sensor to Preamplifier cable
3. AE Preamplifier
4. Preamplifier to System Cable
5. Frequency Filter
6. The A/D Converter
7. The Transient Recorder
8. The Data Buffer
9. Personal Computer and Software
Pre-amplifier:-The AE preamplifier can be either a separate device or is integrated into the sensor. It amplifies the AE signal and drives the cable between sensor and AE system. Important characteristics:
Low input noise to distinguish smallest sensor signals from electronic noise
Large dynamic range to process high amplitudes without saturation
Large range of operating temperature for applications in the neighborhood of low temperature vessels as well as above the transition temperature from brittle to ductile behavior
Usual voltage supply: 28 V DC via signal cable
Optional frequency filter
Calibration pulse can be routed through to the sensor
Frequency Filter:-The frequency filter is used to eliminate unwanted frequency ranges (noise sources) and matches the measurement chain to the requirements of the application.
20 - 100kHz for tank bottom tests (leakage, corrosion)
100-300kHz for integrity testing metallically components
Above 300kHz for reduced range (smaller distance between sensors).
A/D converter: The A/D converter is used to digitize the AE signal that has passed the frequency filter. A huge measurement dynamic is required, as very strong bursts from nearby produce much higher amplitudes than weak ones from a big distance.
Transient Recorder:- In order to better understand the AE signals and to display the curve like in the picture above, sometimes the complete waveform is stored, even if this requires a large memory. The propagation of the wave can be extremely complex. Further research and improvements for future applications of the AE testing technique can only be done using those complete waveforms recorded by transient recorders. An enormous potential of improvement of the AE technology is already within sight today.
Data buffer:- The data buffer prevents data loss in case the CPU is busy with other tasks and temporarily not ready to accept more data. Today’s Windows PCs are extremely powerful but they are not made for strict real-time processing. Therefore external buffers are very important for those systems that use the advantages of standard Windows operating systems
Personal Computer and Software:-Modern AE systems use computers providing a menu-driven parameter input and system control. An online help system provides quick access to help texts explaining the use of the software.
First the result of a data acquisition is just a file containing the features of all the bursts of all the sensors as well as the external parameters, such as test pressure, temperature, and others. If the complete waveform is to be stored, another file is created. During the test the measured data is online analyzed and displayed, so the operator may immediately recognize the possible development of defects within the test object. He may then halt the load increase (e.g. pressurization at pressure tests) in order to minimize possible danger to man, environment, and the tested object.
The tasks of the PC are:
Data acquisition and storage (all data are stored)
Data analysis, online / offline
Logical filtering (plausibility)
Location calculation and clustering
Display of the results (graphically and numerically)
Self test of the system hardware
Sensor coupling test, recording of the sensor frequency response
LOCATING CRACKS BASED ON TIME DIFFERENCES
The determination of the source location of each event is an essential element of AE testing. The distance difference between a source (defect) and different sensors are equal to Arrival Time Difference, Sound Velocity. Location calculation is based on the evaluation of the arrival time differences of the AE signal propagating from its source to different sensors as illustrated in the two-dimensional example shown in Figure 10. An AE wave is propagating in concentric circles from its source and arrives at different sensors with certain delays. The delay is proportional to the distance between the sensor and the source. In this example the wave first reaches sensor 1, then 4, 2 and, at last, sensor 3.
In figure 9 the waveforms of a breaking pencil lead on an acrylic glass plate with four sensors, configured similar to figure 10, are displayed. The zero of the time axis marks the arrival time at the sensor 1, that was hit first in this example. The arrival time differences between channel 1 and the channels 2, 3, and 4 can be read at the time axes of the waveform diagrams.
All points having a constant difference between their distances to two fixed points form a hyperbola. Figure 12 shows three hyperbolae, each representing all points with the calculated distance difference to two sensors. At the point of intersection of the three hyperbolae, the three distance differences are equivalent to the measured time differences. So, this is the wanted source position. As can be seen in this example, the arrival time at three sensors is required to find the point of intersection. If an AE event only arrives at two sensors, there is only one couple of sensors and, thus, only one hyperbola, which is not sufficient for this method to calculate the planar location. Hyperbola diagrams (like in figure 10) are mainly used to check the plausibility of certain selected location results. Mostly, the calculation is based on an inverse method, which, in addition to the location results, provides a measure of the reliability of the location calculation, if more than three sensors have been hit by the event.
Compared to the early days of AE testing, nowadays an excellent location technique is available to the AE tester. Anyway there is still room for improvements to be developed. Today, the AE tester himself has to take care of influences causing location errors and rate them in a correct way.
Some of the influences on the location accuracy are:
A different wave mode than the assumed one determines the arrival time
A wave takes a different propagation path than assumed by the algorithm
Multiple waves overlap at the sensor
Sources emit signals in such a quick succession, that there is not enough time for the signals in the structure to decay, therefore do not represent a “new” hit.
One of the problems is, that from the AE signal one can’t know whether it was produced by a real defect and, if so, how big e.g. the crack growth was. One has to build up know-how by investigating the emission behavior of materials by tensile tests in the laboratory. Doing so, one has to consider, that e.g. the propagating conditions for mechanical waves in real test objects and small samples are different. All these aspects may make the un-experienced feel uncertain about the AE technology. But the theoretical and practical knowledge of the AE behavior of materials and structures increases steadily and will soon be taught at universities and made available to everyone in technical books.
We have to be especially aware of location errors if there is inhomogeneous wave propagation, which e.g. is the case close to manholes, nozzles, etc. Materials with anisotropic wave propagation do not allow for precise location.
CHARACTERIZATION OF AE SOURCES
Some of the characterization criteria have already been explained in connection with some of the charts above. Here is a summary of important characterization criteria:
Dr. Joseph Kaiser’s dissertation (about. 1950) at the Institute for Metallurgy at the Technical University Munich was named: „Examination about the occurrence of sound at tensile tests”. At this dissertation Dr. Kaiser indicates irreversible processes during plastic deformation under strain which can be shown by using a piezoelectric crystal. Due to his dissertation and continuing research until his decease 1958, the Technical University Munich is known as the origin of the AE-Technology. A friend and colleague of Dr. Kaiser, the Munich Professor Hans Maria Tensi, called the phenomenon Irreversibility of the AE-behavior in materials the “Kaiser Effect”.
Nowadays the expression “Kaiser Effect” has a wider meaning. According to EN1330-9-2000 it describes the “absence of detectable acoustic emission until the previous maximum applied load has been exceeded”.
If a specimen is loaded heavily for the first time, the stress generated by the external load is added to the internal stresses, e.g. originating from the production process. During this phase, irreversible relaxation and settlement processes may take place, stabilizing the material. These processes produce AE. If now the specimen is relieved from stress and then stressed again, acoustic emissions will occur not before the maximum previous stress is exceeded.
In steel this effect fades out after about one year. For this reason AE-testing of metal vessels should not be repeated after less than one year, to be sure that weak spots emit AE during a new test pressurization.
Because AE-testing should not be repeated after a short delay, a sufficient number of sensors and AE channels, depending on the size of the test object, must be available. It is neither allowed to repeat the pressurization with another sensor placement, nor to perform a trial pressurization prior to the AE-test.
If a structure, after relief and during a second loading, emits AE before the maximum of the first loading is reached, thereby violating the Kaiser-Effect, this may indicate a defect. On the other hand, sources of interference have always to be taken into account. So, usually, a final judgement can only be given after the pressure increase is stopped and the AE has been monitored during the pressure-hold phase, during which the AE activity should calm down. Sources which cannot be definitely identified, are not acceptable within the pressure-hold phase. So, if there is unexplainable AE activity during the pressure-hold phase, the pressure must be decreased and the AE test aborted.
Clustering always indicates a source, which repeatedly emits acoustic signals. Occasionally, these sources are easily to be identified (e.g. abrasion marks, annexes, etc.). If the source cannot be identified, a real defect must be assumed. Therefore paying attention to the activity and intensity of a cluster is important.
Intensity (Mean Values of Amplitudes or Energy)
Intensity parameters (amplitude, energy) increasing with external load indicate a defect.
Increase of Activity
A defect is also indicated by a disproportionate increase of activity under load (number of hits or located events).
High Amplitudes, also Single Signals (Big Bang, Forced Rupture)
Depending on the test object (e.g. juggling joints at liquid vessels) even a few single signals of high amplitudes may refer to severe defects requiring an immediate pressure decrease. With this type of test objects it is very important to calibrate the measured amplitude with respect to the distance, i.e. to take into account the attenuation of the acoustic signal depending on the distance to the sensor.
Activity during Phases of Constant Pressure
This type of activity may be a sign of a beginning or continuous destruction process.
A flat decay of the cumulative amplitude distribution means, that a considerably high number of high amplitudes have been detected, which may be caused by defects.
ANALYSIS OF AE SIGNALS
Frequency Domain Analysis
The AE system was operated under Transient analysis mode to record the AE signal wave forms. Post processing analysis viz. Fast Fourier Transforms (FFT), Power spectral density (PSD) were performed on the captured AE wave forms. The dominant frequencies can be found out.
Time Domain Analysis
In this various time domain parameters such as Rise time, Ring down counts, Event duration, peak amplitude etc. are plotted versus time in real time.
This investigates the AE generated from various crack propagation steps in compact tension specimens made from pressure vessel steels, and to study the AE characteristics of the crack propagation in different zones like the base metals, the
weld seam and the heat affected zone (HAZ).
The specimen materials used in these tests are 304L stainless steel and P265GH Carbon–Manganese steel. The choice of materials was based on the steels most used in the manufacture of pressure vessels in service are 304L and P265GH. These specimens are designated A, B and C. Specimen A was not welded, whereas specimens B and C were welded from top to bottom on the side and in the middle of the notch, respectively.
The specimens were fatigue pre-cracked, the crack being introduced into different zones for the different CT specimens. In specimen A the crack was in the base metal, whereas in specimens B and C the crack was, respectively, in the heat affected zone (HAZ) and the weld seam. Fig.13 shows the different CT specimens. The specimen thickness is 6 mm.
Fig.13.Different kinds of specimens used during the tensile tests.
Courtesy: Journal Ref.No.1
The acoustic emission measuring system used during these tests is shown in Fig. 14. The Acoustic signals were detected by two kinds of piezoelectric sensors: a wide band sensor (100– 900 kHz) and sensors with a resonance frequency of 180 kHz. The sensor was placed near the tip of the fatigue pre-crack. The acquired AE signals were amplified by a 40 dB fixed gain preamplifier. The threshold selected was 40 dB, which was well above machine noise level.
Fig.14. Schematic set up of equipment.
Courtesy: Journal Ref.No.1
The Acoustic emission analysis shown in Fig.15 gives the separation of each mechanism operating during the different stages of crack propagation.
Fig.15. Acoustic emission analysis of specimen C (P265GH).
Courtesy: Journal Ref.No.1
1. Acoustic emission from plastic deformation: dislocation motion
Slip is the principal source of AE during the plastic deformation of the two kinds of steel tested.
Plasticity of the 304L steel:
The data indicated that there is very little AE generated by slip in our 304L stainless steel. For example, the maximum amplitude recorded during this stage for the A specimen is 51 dB.
Plasticity of the P265GH steel:
The plastic deformation in CT specimens (B and C) of P265GH is characterized by an important acoustic emission. The analyses of the signals recorded during this deformation prove the presence of two sources of this AE.
• Plasticity 1 is the first source of acoustic emission. The first motion of dislocations produces a low amplitude continuous emission (64 dB).
• Plasticity 2 is characterized by an important acoustic emission, which is produces a number of events of significant amplitude (90 dB in the case of the welded specimen). This emission, caused by the energy liberated by the movement of dislocations, leads to peaks of signals. These peaks of acoustic activity correspond to simultaneous movements of dislocations.
In all specimens (304L steel and P265GH steel), during plastic deformation, the most important acoustic emission was produced during the deformation in the weld seam. This means that the signature of this deformation depends of the heterogeneity and the ductility of the metals. The heterogeneity makes the movement of dislocations more difficult and more emissive because of the presence of a significant number of
inclusions. The ductility reduces the periods of plastic instability, which constitute the principal sources of AE.
2. Acoustic emission from a micro crack in the plastic zone
The source of the AE during this stage is the fracture and/or decohesion of the inclusions because they are generally very brittle, so they should fracture very quickly.
Microcrack in 304L steel:
Microcracking is low at the beginning, increases during the test to reach its maximum during stable crack propagation. The appearance and the growth of these microscopic cracks, in the three zones, involve an increase in the acoustic parameters (the amplitude, the energy and the average frequency). This evolution is not the same in the three types of specimens (A, B and C). So a multi-parametric analysis allows the AE events emitted by the microcrack propagation to be separated from the other events. Microcracking is characterised by the highest average frequency and a low duration.
Microcrack in P265GH steel:
Acoustic signature depends on the zone of the microcracking. During microcracking of the weld seam, we have recorded a decrease in many acoustic parameters. For example the energy passed from 1225 aJ during plasticity 2 to 322 aJ.
In contrast to the weld, the acoustic signature of the microcracking of the HAZ is characterized by an important increase of the amplitude and energy.
The results for the two kinds of steel show that the acoustic emission signature of the microcracking mechanism depends on the microstructure of the propagation zone.This difference are marked by several acoustic parameters such as amplitude, energy, duration and count.
3. Stable crack propagation
The crack propagation proceeds primarily from microvoid coalescence (stable crack propagation) in AISI 304L stainless steel and P265GH carbon steel (Fig.16). This mechanism forms the principle source of the AE recorded during this stage of crack propagation.
Fig.16. crack propagation.
Courtesy: Journal Ref.No.1
Stable crack propagation in 304L steel:
The mechanisms intervening during the stable propagation in the three types of specimens generate an increase in the acoustic emission. The acoustic signature of stable propagation is not identical for the three types of CT specimens. Here the specimen C becomes more emissive than the others, with maximum amplitude of 97 dB.
Stable crack propagation in P265GH steel:
The acoustic signature of stable propagation depends on the zone of Propagation (in the HAZ or the welding), but during this stage the weld is more emissive than the HAZ. The acoustic emission of this stage is characterized by an increase in the amplitude (97 dB) of the signals recorded from specimens C. The AE of the stable propagation in the weld is very important, regarding energy. The maximum energy can reach 2571 aJ, whereas for specimen B, it is only 232 aJ.
The AE measured during crack growth in the weld seam is characterised best by amplitude and energy, which are the most important features. These results are available for the 304L steel and the P265GH steel. Stable propagation is characterized by the coalescence of microscopic cracks in the matrix between two cavities. The
Acoustic energy emitted during this stage depends on this zone and its mode of rupture. The smaller is this zone, the more the rupture is brittle and more the emitted signals are energetic. The difference between the energy emitted by stable propagation in the HAZ and that in the weld is due to the difference in the size of the broken zones.
Fig.17. Distribution of the maximum amplitude in the base metal,
in the HAZ and in the weld of the 304L steel.
Courtesy: Journal Ref.No.1
Fig.18. Distribution of the maximum counts in the base metal,
in the HAZ and in the weld of the 304L steel.
Courtesy: Journal Ref.No.1
Fig.19. Distribution of the maximum amplitude in the base metal,
in the HAZ and in the weld of the P265GH steel.
Courtesy: Journal Ref.No.1
Comparison of the acoustic signature of the two steels
The acoustic signature of the plasticity of the two types of steel is different. The plasticity of P265GH steel is more emissive and more energetic than for the 304L steel. In contrast to the carbon steel, the plasticity of the stainless steels starts with very little acoustic activity and this increase progressively with crack propagation. This difference is due to the nature of the plasticity, which is a homogeneous deformation for 304L steel and a heterogeneous plastic deformation for carbon steel (P265GH).
The number of acoustic events recorded during the test of the carbon steel CT specimens is higher than those recorded for 304L steel, which is true in the weld or the HAZ. Moreover, the highest value acoustic parameters were recorded during cracking of the carbon steel specimens. This phenomenon is due to the fact that 304L steel is much more ductile than carbon steel. The stainless steel amplifies the phenomena of plastic deformation and the resistance of the CT specimens. It has a toughness superior to that of P265GH steel. This increase of toughness is accompanied by an important distinction with regard to acoustic emission, because the periods of plastic instability, which constitute the principal sources of AE, are absent.
The conclusion of this case study is that the count, the amplitude, the rise time, the average frequency and the duration are the important parameters for AE identification of the different crack propagation mechanism. The analyses show that we can also identify the zone of defect propagation, but the AE parameter used for that depends on the kind of steel. For P265GH steel the duration of plasticity and the amplitude ratio between plasticity 2 and microcracking are the principal AE parameters to identify if crack propagation is in the HAZ or in the weld seam.
The results of this work provide a database allowing the identification of defects in pressure vessels monitored by AE. The correlation between the results of laboratory specimens with those of structures is possible. It allows the understanding of the behaviour of defects in complex structures. The following three are the examples of defects in pressure vessels monitored by AE.
1. ELONGATION OF PRESSURE VESSEL IN BOTTOM
Fig 20: AE signal for elongation of pressure vessel in bottom.
Courtesy: ISNDT course note
2. LEAKAGE OF PRESSURE VESSEL
Fig 21: AE signal for leakage of pressure vessel.
Courtesy: ISNDT course note
3. Comparison of AE performance for a good and defective pressure vessel
ADVANTAGES AND LIMITATIONS OF AE
Numerous test objects ranging from spherical natural or liquid gas tanks to petrochemical reactors have been tested successfully during the last years using the AE testing method. AE testing is done to complement the water pressure test (hydro test) and, increasingly, also the gas pressure test (pneumatic test).
AE monitoring of a pneumatic test can be used to ensure a safe test. In addition to its use as a NDT method, AE testing can be used as early-warning system for developing and/or growing defects. Thereby a test can be stopped before a critical situation occurs.
Using an AE controlled pneumatic test, the following drawbacks of the hydro test can be avoided:
The pressure systems and their supports must be sufficiently dimensioned for the water loading (weight), which in some cases means a considerable over-dimensioning. So, often absurd solutions are required, such as replacing a simple support by a support ring etc.
Long downtimes are required, caused by the removal of the working medium as well as the cleaning of the vessel before the water delivery. Also, releasing rest gases may be hazardous to the environment.
The humidity remaining in the vessel after draining may cause various effects ranging from corrosion via hydrogen-induced-crack (HIC) formation to a complete system breakdown. The drying processes used to remove the humidity are, if feasible at all, quite expensive and, thus, applied rather seldom.
The water used for pressurizing the object gets polluted and must be thoroughly purified before being released into the environment.
During the testing of chemical reactors, the catalysts become unusable. Exchanging them causes enormous extra expenses and environmental stress.
The hydro test only provides the information no blowing-up, no leakage, and no noticeable deformation. It does not provide any indication of whether a defect has been initiated or expanded during the test, which may cause a later failure of the vessel.
In addition to the disadvantages of the hydro test mentioned above, the pressurization using the storage medium (gas or liquid) provides other advantages:
In many cases the pressure system can be tested almost under standard operating conditions, e.g. with low-temperature applications, the material will be tested in the appropriate temperature range. With warm reactors, the test temperature can be kept above the transition temperature between ductile and brittle behavior.
AE testing can also detect corrosion, so in most cases there is no reason for an internal inspection of the pressure system and it can be taken into operation again without being opened.
More advantages compared to other NDT methods arise from the basic principles of AE testing:
It monitors the dynamic reaction of the test object upon the applied load passively and without intervention.
It often allows detecting sources over a distance of several meters to the sensor.
It allows 100% pressurized wall monitoring.
It allows real-time monitoring of the growth of known and unknown defects at a given load, even remotely by data transmission e.g. by using a modem/internet.
It can monitor a structure under operating conditions.
Despite all the advantages of AE testing, we have to clearly point out, that it cannot be applied always and everywhere.
Defects, which are neither growing nor moving do not produce AE and, thus, cannot be detected.
According to the Kaiser-Effect, only those defects are detected without exceeding the highest preceding load, which are already active at the actual load level and are endangering the component anyway. Only by increasing the load above the previous maximum load level defects can be found, which do not grow at standard load.
Evaluation criteria do not exist in form of commonly accessible data, i.e. the rating of AE-results is set firmly to the knowledge and experience of the service provider.
AE testing is sensitive to process noise exceeding the detection threshold. In case the process noise cannot be stopped, the detection threshold has to be increased, which requires smaller distances between the sensors and, accordingly, more sensors and channels. Above a certain noise level, AE testing is no longer efficient.
APPLICATION OF ACOUSTIC EMISSION TESTING
AE-Analysis is an extremely powerful technology that can be deployed within a wide range of usable applications like-
• Non-destructive testing of components or complete structures.
•Composite structures / pressure vessels.
•Nuclear Power plants.
•Material research e.g. Investigation of properties, break down mechanisms and damage behavior.
•Leak detection in valves and long pipes.
•Detection of high voltage partial discharge in large transformers.
•Health monitoring of Bridges.
•Geological and micro-seismic research.
•In process machining monitoring.
The high level of modern computer technology, measurement techniques, and software has generated an enormous increase of the range of applications, the reliability, and the significance of the AE testing method. Especially, the real-time location calculation provides a big advantage, as in many cases it allows to locate and to eliminate sources of interference or to distinguish their signals from those generated by defects. Because of its capability to detect defects right at the moment of their growth, the AE testing method may also be used as a real-time monitoring and warning system to avoid a failure of the structure under test with possibly disastrous consequences. This capability also allows to use the storage medium, e.g. liquid gas or natural gas, for pressurization. So, the removal of the storage medium as well as the filling with water as medium for pressurization are no longer required. This drastically reduces the costs as well as harmful impacts on both, equipment and environment
1. Monitoring crack growth in pressure vessel steels by acoustic emission and the method of potential difference from International Journal of Pressure vessels and piping 83 (2006) 197-204.
2. Guide to Non-Destructive Testing (Acoustic Emission Technique) prepared by M.R.Bhat, T. Jayakumar, S.V. Subba Rao
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28-04-2011, 12:45 PM
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