acoustic emission testing of highly loaded … · published in ommi, 2009, volume 6, issue 1,...

Published in OMMI, 2009, Volume 6, Issue 1, April. www.ommi.co.uk

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ACOUSTIC EMISSION TESTING OF HIGHLY LOADED COMBUSTOR LINER TILES FOR GAS TURBINES

C. Mende1*, E. Heits1, A. Schulz1, H.-J. Bauer1, A. Wanner2

1Lehrstuhl und Institut für Thermische Strömungsmaschinen, Universität Karlsruhe (TH), Kaiserstraße 12, 76128 Karlsruhe, Germany

2Institut für Werkstoffkunde I, Universität Karlsruhe (TH), Kaiserstraße 12, 76128 Karlsruhe, Germany

* Address all correspondence to this author. [email protected]

Dipl.-Ing. Carsten Mende Research in the fields of heat transfer and non destructive testing of combustor liner tiles, flow investigations of turbochargers [email protected]

Enno Heits Deals with acoustic emission testing within a student research project [email protected]

Dr.-Ing. Achmed Schulz Research for more than 20 years in the fields of heat transfer, film cooling, and new materials for gas turbine engines. Expertise in experimental techniques as well as theoretical modelling of complex flow with heat transfer. [email protected]

Prof. Dr.-Ing. Hans-Jörg Bauer Research in various fields of gas turbines and jet engines, i.e.:

- Analysis of auto-ignition, flashback, and aeroacoustics. - Development of advanced instrumentation systems for

reacting and two-phase flows (sprays, shear driven liquid films).

- Aerodynamics, heat transfer and cooling. - Contactless seals, pre-swirl nozzle systems and bearing

chambers. - Aerodynamics of radial turbomachines and fluid flow

structure interaction. - Application of micro turbines for distributed energy

supply and combined heat and power generation. [email protected]

Prof. Dr.rer.nat. Dipl.-Ing. Alexander Wanner, Deals with the mechanics, failure analysis, non-destructive evaluation, and lifetime assessment of engineering materials, especially metallic alloys and metal matrix composites. [email protected]


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Abstract The redistribution of internal stresses in a material, for example, as a consequence of mechanical loading, causes the emission of acoustic waves, which are called acoustic emission (AE). The detection of acoustic emission is a common non-destructive testing method and mainly used in pressure vessel testing and structural health monitoring of large structures as, for example, bridges. In this paper the application of acoustic emission testing (AET) to combustor liner tiles (CLT) of gas turbines is presented. These combustor tiles are exposed to thermal cycles under engine-like conditions while acoustic emission testing is applied. A thermal cycle consists of dwell times at low and high temperatures, and heating and cooling phases. The paper first presents basic knowledge of acoustic emission testing and of the experimental rig at the “Institut für Thermische Strömungsmaschinen (ITS)”. Then the adaptation of the measurement technique to the hot combustor environment, which is done by so-called waveguides, is elucidated. Finally some test data are given, which confirm the capability of AET for online damage detection in the thermally loaded CLT. These data show not only a correlation between AE and individual phases of the thermal cycles but allow also a planar localisation of the acoustic emission sources on the CLT. Keywords: acoustic emission testing, combustor liner tiles, non-destructive testing Nomenclature

Abbreviations & symbols: AE acoustic emission AET acoustic emission testing CLT combustor liner tile d waveguide diameter HDT high temperature - high pressure facility l length LCF low-cycle fatigue Δt time difference

1 Introduction Modern aircraft engine combustors are equipped with complex cooling systems to protect the liners from the hot combustion gases. A common way to accomplish the required protection of the combustor casing is the use of film-cooled combustor liner tiles acting as heat shields. These tiles are typically bolted to the liner like shown in Figure 1 for a section of an annular combustion chamber of a Rolls-Royce “Trent” jet engine. In spite of an appropriate cooling under normal operating conditions Low-Cycle Fatigue (LCF) occurs, since the loading of aircraft combustor liners is a complex combination of creep, fatigue, and oxidation. Due to the transient service of the combustor, damage from thermal-mechanical fatigue and from fatigue-creep interaction is especially pronounced. In conjunction with material deterioration like aging of precipitation hardened nickel-based superalloys, the varying operating conditions during a flight make lifetime predictions difficult. As a consequence, jet engines are bound to frequent inspections, ensuring the required reliability of the aircraft engine. Some authors, therefore, tried to assess the lifetime of combustor components by cyclic testing under realistic operating conditions and comparative installation situations (Hughes et al. [1], Mende et al. [2], Corman et al. [3] or Verrilli et al. [4]). Of course, in-situ detection gives the most information about the nonlinear damage evolution. Because of the pressurized hot gas environment within the combustor, typically in-situ measurement techniques like boroscope visualization or thermography require optical accesses. This is the major drawback of these methods, since the mechanical properties of the windows prevent complete monitoring of the whole structure. Furthermore, developing invisible defects, e.g. micro-pores, are not detectable. To deepen the knowledge of damage evolution in CLT within a realistic combustor environment other non-destructive testing methods are needed.


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Figure 1: Section of an annular combustion chamber with film-

cooled combustor liner tiles. Courtesy of Rolls-Royce plc

One possibility is the application of acoustic emission testing (AET). It offers not only an online and in-situ detection of developing damage, but also the opportunity to be applied as a structural health monitoring device during combustor service life. AET is a common measuring technique in various fields of research (e.g. Spielmannová et al. [5], Wevers et al. [6], Laschimke et al. [7]) and industrial applications (Scheer et al. [8], Geng [9], Baxter et al. [10]). Its basic principle is the measurement of acoustic waves emitted in a solid when internal stresses are redistributed, i.e. stored elastic energy is released. These waves, so called acoustic emissions (AE), spread within the solid and can be detected at accessible positions. Although this can be done by non-contacting devices like interferometers, contacting piezoelectric sensors are widely used due to their outstanding sensitivity. The operational temperature of these sensors is comparatively low, thus limiting their application to temperatures below about 423 K. To overcome this limitation Kirk et al. [11] successfully developed piezoelectric sensors from lithium niobate composites for higher temperatures. Today sensors working up to 773 K are available (but with comparatively low sensitivity). Since CLT surface temperatures of over 1273 K are common in gas turbine combustor walls, a direct mounting of the sensors is not possible. Several authors, for example Yen & Tittmann [12], successfully applied so called waveguides, which provide an acoustic path out of the hot monitoring area to the piezoelectric sensors, installed in a convenient environment. Consequently, acoustic waveguides were applied in this study to monitor the damage evolution during service of combustor liner tiles for the first time. 2 Basic principles of acoustic emission testing Acoustic emissions are either of the burst or the continuous type. Burst type signals are often related to elastic energy release from cracks, whereas continuous emissions mainly originate from frictional processes or background noise. Therefore, the burst type signals are often of major interest. Due to the source mechanism - the sudden release of stresses - their frequency spectra are typically broadband from 100 kHz to several MHz. Consequently, the logging of these frequencies results in high data rates. This led to two different approaches of analysing the stored data. In the classical approach, characteristic features of the measured acoustic emissions are extracted and stored. The analysis is then performed with a comparatively small amount of data. In the newer quantitative approach, the whole transient signals are stored and analysed in the time and frequency domains. Today, both


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approaches are used alternatively, depending on the measurement task. For illustration of the classical examination, typical parameters are given in Figure 2 for an arbitrary burst signal. The threshold crossing defines start and end of the signal. The rise time (i.e. time span between first threshold crossing and peak amplitude) and duration of the signal are considered as indicators for noise. Furthermore, peak amplitude, counts (the number of threshold crossings within a predefined time span after the first crossing), and signal energy are stored for signal classification.

Figure 2: Schematic burst type signal with parameters (classical approach)

AET allows defect localisation when multiple sensors are applied. Then the differences in arrival times of the acoustic waves at the sensors are used to calculate the position of the source. In a plate-like CLT, at least three sensors are necessary for defect localisation. Since elastic waves in plate-like structures are highly dispersive and the amplitude threshold of the measurement system is fixed, the resulting localisation will be imprecise. Therefore, additional sensors are often applied to estimate the uncertainty by evaluating the arrival times for different triples of sensors. It has to be noted, that this localisation method allows only the determination of sources, which lie within the area defined by the sensors. Other approaches, accounting for dispersion experimentally or analytically are reported by, for example Gorman [13, 14]. These approaches evaluate the arrival times of the different wave modes in plates. Thus, they allow localisation with less than three sensors (cp. Jiao et al. [15]). 3 Experimental setup In this study acoustic emission testing was applied to an intensely cooled combustor liner tile loaded with thermal cycles under gas turbine representative conditions. The analysis was done with both the classical and the quantitative approach. Parameter extraction was used for a pre-classification of the numerous AE-signals. For a more detailed analysis, a selection of complete transient signals was investigated with a quantitative approach, based mainly on the time dependent frequency content. Therefore, wavelet transforms of these signals were performed, using the “AGU-Vallen Wavelet R2008.0915” software. In the following paragraphs the test rig, the CLT, and the measurement device are presented. Furthermore, the test procedure is elucidated. 3.1 Low-cycle fatigue test rig The tested CLT was installed in the low-cycle fatigue test rig of the “Institut für Thermische Strömungsmaschinen (ITS)”. It provides an engine-like combustor environment for simultaneously conducting endurance tests of up to three different combustor liner tiles. Similar loading is achieved by comparable size and installation of the CLT, realistic hot gas temperatures and thermal gradients, and oxidizing atmosphere. The test rig itself is supplied with a preheated and pressurized airflow by


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the institute’s high temperature - high pressure facility (HDT). Design and performance of the test rig are described in detail in [2]. It consists of three parts (Figure 3): a natural gas fired combustor, a test section, and an exhaust gas cooler. The combustor supplies hot exhaust gas for the test section where the CLT are installed. It consists of a cylindrical combustion chamber and a staged, lean-premixed, bluff-body stabilized, natural gas burner. The exhaust gases are ducted to the test section, which has a square cross section. Each of the CLT is bolted to a supporting structure, which is used to position the tiles in the test section. Cooling air is supplied to each tile individually through the supporting structure. Due to the governing temperatures, the flow channel is formed by a thick insulating, refractory concrete layer. Therefore, the CLT are only accessible via the supporting structure for AET instrumentation (Figure 3). In the following, the flow path in the test rig will be elucidated. The preheated air from the HDT facility enters a ring-shaped collecting pipe at “1” (see Figure 3). It is circumferentially distributed and flows through 16 pipes into the combustor. The air then flows through the annulus (“2”) to the head of the combustor and is accelerated centripetally. Natural gas is added and mixed at “3”. Subsequently the mixture is accelerated further until the burner exit. The hot exhaust gas leaves the combustion chamber at “5” and passes the test section, where the CLT are installed. Cooling air temperature and pressure are measured in a cavity of the supporting structures at the cooled sides of the CLT. At “6”, water is injected to cool down the hot exhaust gas. Before the exhaust gas leaves the test rig into the chimney at “8”, its total pressure and temperature is measured at “7”. Injected, not evaporated, water can be separated through a condensate outlet.

Figure 3: Low-cycle fatigue test rig at ITS

3.2 Measurement device The acoustic emission testing was done with the “AMSY4” measuring device from Vallen-Systeme GmbH. It featured four independent AE-channels, each having a maximum sampling rate of 10 MHz and a resolution of 16 bit. All channels are equipped with a parameter extraction unit and a transient wave recorder. The sampling rate of the transient wave recorder was set to 5 MHz. The measurements were performed with resonant sensors of the type “VS375-M” from Vallen-Systeme GmbH with resonance frequencies at 375 kHz. The AE-signals were amplified using four “AEP3” preamplifiers. A pilot study showed that the noise produced by the test rig was mainly in a frequency range below 200 kHz. Consequently, the signals were filtered before parameter extraction using a cut-off frequency of 230 kHz. The AMSY4 has an additional analogue low-pass filter (5 MHz), thus enabling frequencies up to 2.5 MHz to be measured. Since attenuation of the AE depends strongly on the ratio between obstacle size and wavelength, high frequencies may be significantly attenuated due to the effusion holes. According to Viktorov [16] the Rayleigh velocity for the CLT’s material can be assumed to be 2879 m/s. As a result, attenuation due to the inclined effusion holes can be expected for frequencies higher than 508 kHz, only. Consequently, the investigated frequency range was limited between 230 kHz and 500 kHz.


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Furthermore, the AMSY4 is equipped with four independent input channels to record external voltage signals, allowing a correlation of AE-signals to simultaneously measured data. One of these channels was connected to a pressure transmitter, logging the pressure level in the rig. This allowed the correlation of AE-signals to different phases of the thermal load cycles. Additionally, temperatures measured via the test rig control could be related by matching the different start times of the AMSY4 and the test rig control. For the first 95 cycles with low thermal loading, the surface temperature could be measured using a thermocouple. Unfortunately, the thermocouple failed at this stage so that the temperature evolution during the following 204 cycles with significantly higher thermal loading, (see Table 2 later), could not be measured. With the measured cooling and exhaust gas quantities, the surface temperature of the CLT can be calculated to approximately 1000 K (with a total film cooling effectiveness of 0.7) at the end of the full load phase. This corresponds to temperature measurements with similar cooled CLT for comparable cycle parameters. 3.3 Device under investigation In order to accelerate the damage evolution, and thus enforce AE-signals, a 2 mm thick CLT made of stainless steel 1.4301 (X5CrNi18-10) instead of a nickel-base superalloy was used within the endurance test. A principal drawing of this CLT, which is bolted to the supporting structure, is given in Figure 4. It is impingement cooled by perpendicular cooling holes in the supporting structure and additionally film cooled by inclined effusion holes (inclination angle: 30°). On the left hand side of Figure 5, a photograph of the hot gas side of the tile is shown. The effusion hole pattern in the middle of the tile, i.e. within the area of measurement, was designed to give high thermal loading and therefore many AE-signals. In contrast, the boundaries are better cooled to guarantee only little disturbing AE from these areas. A detailed description of the cooling design is given in Meinl [17].

Figure 4: Principal drawing of the CLT

Figure 5: Hot gas side (left) and cooling air side (right) of the CLT


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To guide the acoustic waves out of the test rig, cylindrical waveguides with a diameter of 2 mm and a length of 520 mm (l/d = 260) were applied. In plates or rods, like waveguides, acoustic waves spread as Lamb- or Rayleigh-waves, consisting of different modes. These waves are subject to dispersion, i.e. the propagation velocity of the modes depends on their frequencies. Additionally, attenuation is also frequency dependent. Both effects modify the AE-signals on their way from source to sensor. For short waveguides (l/d < 50), a thickness of 6.4 mm is recommended by Ono & Cho [18] for a good waveform fidelity. Sikorska & Pan [19] showed that attenuation of AE-signals increases with waveguide diameter and length. So, the question arises if AE-signals keep their waveform and their amplitude while passing the waveguides used in this study. In order to assess their transmission behaviour, different acoustic path lengths in these waveguides were investigated, using the same resonant sensor and mounting device (Figure 6) as in the later thermal cyclic testing.

Figure 6: Coupling between sensor and waveguide

Figure 7 shows typical transient AE-signals for 200 mm, 400 mm, and 600 mm. As can be seen, the time Δt between the two significant peaks of the AE-signals increases for longer distances due to dispersion. Yet, major characteristics stay unaltered. Furthermore, the measured attenuation of 1.13 dB (reference voltage: 1 μV) of the AE-signals is negligible. Therefore, the measured AE during the thermal cycles should be detectable and not altered significantly by the applied waveguides.


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Figure 7: Transient AE-signals for 200 mm, 400 mm, and 600 mm propagation length

The connection of the waveguides to the CLT was investigated regarding waveform fidelity and attenuation. It was found, that screw fastening is inferior to welding. Consequently, the waveguides were welded to the bolts of the CLT (shown in Figure 5, right hand side). They were guided through holes out of the supporting structure of the CLT, which were sealed with PTFE. The high acoustic impedance mismatch between the PTFE stuffing box and the stainless steel waveguides (same material as the tile) guaranteed minimum interference from AE-signals outside the CLT. Particular care was taken that the waveguides did not contact the supporting structure to avoid AE signals from rubbing or rattling. The sensors were mounted on a flat spacer, which allowed the focussed signal from the waveguide to spread over the whole diameter of the piezoceramic sensor. Both, plate and sensor were pressed on the waveguide through PVC plates, which were clamped on a soldered bushing (cp. Figure 6). Additionally, a fifth waveguide (d: 0.5 mm) was applied, which allowed to couple artificial AE-signals into the tile. This enables the in-situ calibration of the sensor coupling efficiency, and the determination of the (temperature dependent) speed of sound. 4 Test procedure After the sensors were mounted on the waveguides, the quality of the acoustic coupling was tested by artificial AE signals. These were coupled into the installed CLT via the fifth waveguide, from which small pieces were cut off to produce the artificial AE signals. Then the test rig was brought to idle condition, in order to determine the threshold of the AMSY4 by setting the trigger several dB over the measured flow noise. The subsequent measurements were performed with the settings of the AMSY4 given in Table 1. After this, the temperature dependence of the speed of sound was determined for the CLT. Therefore, the rig was operated stationary at different thermal loads and AE was coupled into the


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CLT again. Then, the thermal cycles were adjusted with particular concern to keep the maximum material temperatures of the CLT rather low. Otherwise fatal damage right at the first load cycle due to thermal shock could have been occurred. The temperature level chosen was considered to allow cycle phase resolved monitoring of damage, which in case of CLT is a combination of fatigue, creep, and corrosion.

Table 1: Channel settings of AMSY4 during the endurance test of the CLT

Channel setting: Sampling rate parametric input channel 4 Hz Threshold (reference: 1μV) 46.1 dB Rearm time 0.2 ms Duration discrimination time 150 μs Amplification 49 dB Filter (high-pass/low-pass) 230/5000 kHz Software filter: Only AE with more than 5 counts

These thermal cycles led to crack initiation and propagation in the supporting structure, which are shown in Figure 8. Therefore, the AET had to be interrupted.

Figure 8: Cracked supporting structure of the CLT

Nevertheless, AE-signals from the evolving damage were measured. This is shown in Figure 9 where the surface temperature of the tile is displayed along with the corresponding AE-signals. It reveals that AE occurs at the end of the full load phase (grey diamonds), when the temperature reaches a maximum, and at the beginning of the cooling phase of the thermal load cycles (black triangles). Note, that the maximum temperatures of these cycles are lower than those of the later thermal cycles, which were performed after the repair of the supporting structure. Additionally a thermal barrier coating was applied to the structure, allowing higher thermal loading of the CLT. After the repair, AET was continued by additional 204 thermal load cycles. Some of the then applied parameters are given in Table 2.


10

0

200

400

600

800

1000

1200

1400

1600

12330 12380 12430 12480 12530 12580 12630 12680 12730

Time [s]

Surf

ace

tem

pera

ture

of t

he C

LT [K

]

45

50

55

60

65

Am

plitu

de [d

B]

Surface temperature of CLT AE during cooling down AE during full load

Full load Cooling down

Figure 9: AE-signals during the thermal cycles

Table 2: Phase resolved parameters of the last 204 thermal load cycles during AET of the CLT

Averaged measured quantity: Idle Full load Transient (Heating/Cooling) Pressure 8.7 bar 6.7 bar - Exhaust gas mass flow 364 g/s 701 g/s - Cooling air mass flow 8.4 g/s 16.5 g/s - Exhaust gas temperature 982 K 1985 K - Cooling air temperature 556 K 562 K - Duration of phase 30 s 30 s 30 s/30 s Mean hot gas temperature gradient - - 41 K/s/-43 K/s Max. hot gas temperature gradient - - 467 K/s/-312 K/s 5 Results Within all 299 cycles no visible damage of the CLT occurred. Nevertheless, numerous AE-signals were measured. This made it impractical to store all transient waveforms in all thermal load cycles. Consequently, transient data were stored only during a limited number of cycles spread over the whole test campaign. The subsequent qualitative analysis of the measured AE could be done for these cycles only, while the classical approach was used for the entire AET. In the following paragraphs, the results of the quantitative analysis are presented. Since the settings of the measurement device, especially the threshold has to be chosen prior to the AET, they influence the measured data. For example, the integrated localisation algorithm of AE-sources provided by the AMSY4 can be inaccurate, since the recorded arrival time Δt of an AE-signal may be erroneous due to attenuation. This can be seen in Figure 10 for the transient waveforms of the


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same signal detected by two sensors. It shows that a fixed threshold leads to a later measured arrival time. In order to improve the localisation, the arrival times were corrected manually. Thus, a wavelet transformation was performed on the transient AE-signals. Then, by using a narrow band-pass filter (around 350 kHz), the true arrival time of this frequency could be determined, allowing the calculation of the real arrival time differences. So, a localisation with only little uncertainty was possible.

Figure 10: Inaccurate arrival time measurement due to a fixed threshold setting during AET

Analysing numerous AE-signals, three areas with AE on the CLT could be determined, which are shown in Figure 11. Due to the measurement uncertainty, the located source positions may overlap for a few AE-signals. The wavelet transformation of these signals showed that each located source position had a typical time-frequency characteristic, allowing the correlation between signal and source position. These wavelet transforms are given in Figure 12. There, the magnitude of the wavelet coefficient (as an indicator for the presence of the certain frequency) is plotted as a function of time and frequency for each source. Displayed is only the beginning of these signals. Since reflections of the acoustic waves interfere with reverberations of the sensors, a further analysis is not possible.

Figure 11: CLT with areas of measured AE


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Figure 12: Wavelet distributions of the different signal types

As can be seen in the figure, type I signals have a clear single peak. It should be noted that the wavelet transformations of all signals of type I look similar, regardless of their absolute amplitude. For signals of type I a short initial wave band between 150-250 kHz was found, which is not visible in Figure 12 due to the applied scale. A similar first peak is also present at signals of type II, but usually broader. Furthermore, a second, weaker peak may be distinguished in this signal class. For all signals of type II, a lasting wave band between 100-250 kHz can be observed, which is also not visible due to the applied scale. This wave band may originate from sliding sources, e.g. fixing of components or from creep within the tile. A changed transfer characteristic between CLT and waveguide could also be responsible. The reason for the presence of the wave band could not be determined within this study. Type III was related to signals with multiple peaks, which get more intense with signal duration but showed no regular pattern. Furthermore, the same short initial wave band (like in type I signals) could be observed for most of these signals. Instead of the ones seen in type I, their magnitudes correspond to the signals amplitudes. They are therefore present in Figure 12. A classical analysis approach indicates a similarity of type I and III signals. Since both signal types are closely located on the tile (Figure 11), the altered appearance could result from different transfer characteristics along the propagation paths. The occurrence of the AE within the different phases of the thermal load cycles was of further interest. The subsequent analysis showed significant AE-activity only during the full load and the cooling


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phases of the thermal cycle. This confirmed the measured crack-induced signals in the supporting structure shown in Figure 9, where AE-activity occurred at the same load conditions. In contrast, idle conditions and heating of the tile led to almost no AE. Compared to Figure 9, the AE-activity was found during almost the whole full load phase. Additionally, each signal type is dominant in a certain time span only. This is schematically shown in Figure 13, where the different signal classes are marked depending on the exhaust gas temperature of the load cycle. As can be seen, type I and type II signals were measured mainly during the full load phase, while type III was predominantly found in the cooling down phase. For type I and II, the signal amplitudes rise with the duration of the cycle phase. This indicates a temperature dependence of the source mechanism, because the temperature of the CLT increases during the complete full phase to a maximum. Since this increase is rather slow, the resulting thermal stresses should be low. AE-activity during this time span therefore could be related to creep and stress relaxation due to the governing temperature level. On the other hand, the amplitudes of type III signals decrease with time. The transient temperature gradients are at their maximum at the beginning of the cycle phase, leading to high thermal stresses. At the same time the strength of the material is lowest due to the temperature level. Consequently, signals of type III should be correlated to fatigue. This time dependence of the signal classes is consistent for the whole endurance test. Thus, intermittent stochastic noise as source for these signals can be excluded.

Figure 13: Occurrence of the different signal types during a thermal load cycle

6 Conclusions In this study, acoustic emission testing (AET) was successfully applied to monitor damage in a cooled combustor liner tile under engine-like conditions for the first time. An endurance test consisting of transient thermal load cycles was performed. Because of the high material temperatures during a cycle, waveguides were applied which allowed the installation of piezoelectric sensors for AET in an appropriate environment. Consequently, the transfer characteristic of these waveguides was investigated first with the help of classical and quantitative analysing techniques. During the endurance test, acoustic emissions from the CLT and from cracks in the supporting structure were measured. By application of a wavelet transformation to the AE from the CLT, the arrival times of these signals were corrected, thus allowing the localisation of three different AE-sources on the tile. Besides the determination of the source area, typical characteristics of these sources were found. A phase resolved analysis of the thermal load cycle suggested, that the determined signal types correlate to creep and fatigue damage evolution. In summary, this study proved AET to be an effective measurement technique for the online damage detection in combustor liner tiles and, therefore, confirmed its potential for structural health monitoring in highly loaded jet engine combustors.


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In future studies, the endurance test will be continued in order to confirm the results of this study for macroscopic cracks. Additionally, the observed low frequency wavebands of type II and III signals will be investigated further. 7. Acknowledgements The partly funding of the test rig used in this study by the Federal Ministry of Economics and Technology of Germany (support code: 20T0309C) and Rolls-Royce Deutschland Ltd. & Co KG within the LuFo-III framework program E3E is gratefully acknowledged. The authors are responsible for the content of this publication. The authors also thank Dr. Miklós Gerendás (Rolls-Royce Deutschland) for providing the photograph of the annular combustion chamber segment. *This paper was previously presented at the 2nd. ECCC International Conference on Creep, April 21st. – 23rd., 2009, Zurich, Switzerland. 8. References [1] Hughes, M., Riccius, O., Moobola, R., Kuehn, I., Schneider, L. (2007): “Cyclic lifetime validation of annular combustor liner segments for heavy duty gas turbines”. ASME Turbo Expo 2007, Montreal, Canada, ASME Paper No. GT2007-27663. [2] Mende, C., Liedtke, O., Schulz, A., Bauer, H.-J. (2008): “Design of a new experimental rig for thermal cyclic testing of combustor liner tiles”. ASME Turbo Expo 2008, Berlin, Germany, ASME Paper No. GT2008-50300. [3] Corman, G.S., Dean A.J., Brabetz, S., Brun, M.K., and Luthra, K.L., Tognarelli, L., Pecchioli, M. (2000): “Rig and engine testing of melt infiltrated ceramic composites for combustor and shroud applications”. ASME Turbo Expo 2000, Munich, Germany, ASME Paper No. 2000-GT-638. [4] Verrilli, M.J., Martin, L.C., Brewer, D.N. (2002): “RQL sector rig testing of SiC/SiC combustor liners”. NASA/TM-2002-211509, NASA Glenn Research Center, Cleveland, USA. [5] Spielmannová, A., Landa, M., Machová, A., Haušild, P., Lejček, P. (2007): “Influence of crack orientation on the ductile–brittle behavior in Fe–3 wt.% Si single crystals”. Materials Characterization; 58: 892-900. [6] Wevers, M., Van Dijck, G., Desadeleer, W., Winkelmans, M., Van Den Abeele, K. (2004): “Acoustic emission for on-line monitoring of damage in various application fields”. Journal of acoustic emission; 22: 252-263. [7] Laschimke, R., Burger, M., Vallen, H. (2004): “Acoustic emission from transpiring plants – new results and conclusions”. Journal of acoustic emission; 22: 102-109. [8] Scheer, C., Reimche, W., Bach, F.-W. (2007): “Frühzeitige Schadenserkennung und -ortung an Getrieben mittels Schallemissionsanalyse und Wavelet-Transformation“. 16.th. Kolloquium Schallemission 2007, Fürth, Germany. [9] Geng, R. (2006): “Modern acoustic emission technique and its application in aviation industry”. Ultrasonics; 44:e1025-e1029. [10] Baxter, M.G., Pullin, R., Holford, K.M. (2004): DGZfP-Proceedings BB 90-CD, 289-296. [11] Kirk, K.J., Scheit, C.W., Schmarje, N. (2007): “High-temperature acoustic emission tests using lithium niobate piezocomposite transducers”. Insight; 49(3):142-145. [12] Yen, C.E., Tittmann, B.R. (1995): “Guided wave sensor for in-situ high temperature process monitoring”. IEEE Ultrasonic Symposium 1995, Proceedings; 1:799-802. [13] M. R. Gorman and W. H. Prosser (1990): “AE source orientation by plate wave analysis. Journal of Acoustic Emission”; 9: 283-288. [14] M. R. Gorman (1994): “New technology for wave based acoustic emission and acousto-ultrasonics”. ASME AMD, Wave Propagation and Emerging Technologies; 188: 47-59. [15] Jiao, J., He, C., Wu, B., Fei, R., Wang, X. (2004): “Application of wavelet transform on modal acoustic emission source location in thin plates with one sensor”. International Journal of Pressure Vessels and Piping; 81:427-431. [16] Viktorov, I.A. (1967): “Rayleigh and Lamb waves: physical theory and applications”. New York: Plenum Press, 1967.


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[17] Meinl, F. (2006): “Anwendung der Schallemissionsprüfung an thermisch hochbelasteten Brennkammerschindeln“. Master thesis, Institut für Thermische Strömungsmaschinen, Universität Karlsruhe (TH). [18] Ono, K., Cho, H. (2004): “Rods and tubes as AE waveguides“. Journal of acoustic emission; 22: 243-252. [19] Sikorska, J., Pan, J. (2004): “The effect of waveguide material and shape on AE transmission characteristics - Part 2: frequency and joint-time-frequency characteristics”. Journal of acoustic emission; 22: 264-273.

Appendix Settings of AGU-Vallen Wavelet 2008.0915 Frequency range 10-700 kHz Wavelet size 400 Samples Number of samples 500 Offset samples -100 Wavelet table scale factor 1

acoustic emission testing of highly loaded … · published in ommi, 2009, volume 6, issue 1,...

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