Journal of AE, Volume 25, 2007 (ca. 26 MB) - AEWG

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tant goal of AE testing [6, 23]. Weather-induced noise can be a serious obstacle in field tests. A recent study is a good reference on this topic [24]. Fig. 3 The power-law AE correlation of N ∝ K In for the case of n = 4 and the CP formulation of AE “energy” E ∝ [(τ’ – t)/τ’] –γ , with the fracture (critical) time τ’, time t and an universal critical exhibitor without dimension, γ (1, 0.25, 0.1 and 0.025 shown). Materials Effects Structural materials affect the attenuation of AE waves and determine the effective range of detection frequency and sensor spacing. In typical metallic alloys, the attenuation is low and primary AE signals at 100 kHz-2 MHz can be routinely utilized. Buttle and Scruby showed the distinction among fatigue cracks, fretting and noise requires MHz-signals, using their special conical sensors extending to 7 MHz [25]. It is often found that secondary AE signals have their main contents below 100 kHz, allowing frequency-based discrimination [26]. In large metallic tanks, pressure vessels and pipes filled with liquids, the usable range is reduced to 30-100 kHz. This comes from the loss of wave energy dissipated into liquid via dispersion and absorption. Heterogeneous concrete, bricks and rocks have high attenuation and the detection frequency is at 10-60 kHz [27]. Even at this range, Shiotani et al. [28] showed the frequency-based discrimination is possible between cracking and fretting signals. Geological materials have high attenuation and their typically large sizes further limit the usable frequency to sub-kHz range. In the low-frequency range, however, 3-axis sensing becomes practical and this allows detailed evaluation of sources [29]. In geological cases, the large size of propagation media allows the use of body waves. This is in contrast to industrial structures, where guided waves are common and boundaries wield strong effects on the signals reaching sensors. Until the work of Gorman and Prosser [30], the guided waves were long ignored in AE studies, especially in field AE testing, in part due to the difficulties of analyzing them. By now, Lamb (plate) waves have proven the utility in field inspection as well and even cylindrical waves are beginning to be used [31]. Expanded uses of guided-wave analysis should be seriously considered in AE testing. Wide-frequency signals in low-attenuation materials can provide more detailed waveform information, allowing better source characterization [25]. Reverberation presents a challenge in 4
sorting out the original signals, especially in smaller shapes. By combining with source location, exact waveform analysis is possible and source parameters can be determined (Suzuki et al. [32]). Such laboratory-scale scheme is difficult to scale up to the industrial level, but increased capability of Lamb-wave simulation should enable this to happen. In structures with highattenuation materials, limited sound transmission forces the use of lower detection frequency. Low frequency implies wavelength larger than the scale of inhomogeneity, reducing attenuation. While longer transmission becomes possible, low-frequency waveforms carry less information regarding the sources and limit the capability of source characterization. In principle, this can be compensated by increasing the number of sensors, as demonstrated in laboratory studies [14, 16]. Fig. 4 Two classes of AE signal observed during fatigue of riveted coupon. High frequency AE (attributed to crack advance) (a) AE waveform; (b) Fourier transform. Fretting-AE signal observed periodically; (c) AE waveform; (d) Fourier transform. Buttle and Scruby [25]. 3. Evaluation Tools Kaiser effect enables the detection of the prior loading level and in assessing the state of structural damages. AE emitted below the prior load (Felicity effect) implies the presence of damages, although other measures are needed to verify the damages. In metallic structures, a clear re-start of AE is usually indicated in the absence of flaws. Crack-face cohesion and fretting provide under-preload AE indication of the crack presence, especially under cyclic loading. 5
Page 3 and 4: JOURNAL OF ACOUSTIC EMISSION VOLUME
Page 5 and 6: 25-194 ACOUSTIC EMISSION SOURCE LOC
Page 7 and 8: Volume 25 (2007) AUTHORS INDEX DIMI
Page 9 and 10: YUICHI TOMODA, 25-021 T. TOUTOUNTZA
Page 11 and 12: Notes for Contributors 1. General T
Page 13 and 14: In Memoriam H. Reginald Hardy, Jr.
Page 15 and 16: STRUCTURAL INTEGRITY EVALUATION USI
Page 17: The power-law AE behavior was recen
Page 21 and 22: Wood [36] in Australia has been usi
Page 23 and 24: One needs to appreciate the difficu
Page 25 and 26: In geotechnical applications, the p
Page 27 and 28: methods include the use of combined
Page 29 and 30: should take. Past attempts for stru
Page 31 and 32: 11. Suzuki, T., Ohtsu, M., Aoki, M.
Page 33 and 34: 40. http://en.wikipedia.org/wiki/Ma
Page 35 and 36: Abstract ACOUSTIC EMISSION TECHNIQU
Page 37 and 38: Fig. 1 Damage qualification by the
Page 39 and 40: After adding the data of a tested s
Page 41 and 42: Fig. 8 Sketch of a reinforced concr
Page 43 and 44: (3) Corrosion Process of Reinforced
Page 45 and 46: analysis. Corrosion cracking was si
Page 47 and 48: ACOUSTIC EMISSION MONITORING OF REI
Page 49 and 50: which - contrary to current beliefs
Page 51 and 52: Fig. 4. Applied load (actuator 1) a
Page 53 and 54: concrete and the jacket. Visual ins
Page 55 and 56: Based on conventional analysis, AE
Page 57 and 58: 2. Experimental The model pipe syst
Page 59 and 60: pressure, respectively. This is ana
Page 61 and 62: Fig. 6: Power spectra from fast Fou
Page 63 and 64: small leaks (below 0.1 mm diameter)
Page 65 and 66: ACOUSTIC EMISSION TECHNIQUE APPLIED
Page 67 and 68: parameters in time domain and (c) m
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above the threshold level of 40 dB
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energy, i.e., high amplitude and lo
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An optical microscopy observation o
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Continuous WT (CWT) is defined as a
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Fig. 8. Typical AE waveforms, their
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followed by abrupt jumps in the det
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E. Landis (1999), “Micro-macro fr
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EVALUATION OF REPAIR EFFECT FOR DET
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Fig. 2 Sensor array for tomography
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2 [ ] 2 k 3 9 2 2 1 f () 0 f ()
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At these depths, a complicated and
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The number of AE hits after repair
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damage indices of Calm and Load rat
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PVDF is a semicrystalline polymer,
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After these preliminary tests, the
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of PVDF sensors does not seem to ha
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Fig. 10. Evolution of a typical PAD
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Fig. 17. Evolution of a typical dur
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I-G. Kim, H-Y. Lee and J-W. Kim (20
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Pencil-lead breaks are monopoles an
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Fig. 1 Displacement vs. time, sourc
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Fig. 5 Displacement vs. time, sourc
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Fig. 8 Displacement versus time for
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Fig. 10 Displacement vs. time. Sour
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Fig. 14 Signal amplitude versus tim
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To better relate these PLB and FEM
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HIGH-TEMPERATURE ACOUSTIC EMISSION
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thickness of 9 μm. The AlN element
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Fig. 5 Experimental setup for AE mo
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scales (and possibly salt cracks at
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DAMPING, NOISE, AND IN-PLANE RESPON
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The sharper resonance in Fig. 1c is
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i 2 RMS VDCC0 k BT = , g m 2 i
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ecause in-plane motion mostly produ
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4. B. Bahreyni, C. Shafai, Fabricat
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We first introduce our new quadridi
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Fig. 4 Amplitude profile as a funct
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Fig. 6 Change of room temperature (
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3) There are slight time lags in th
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Function Generator (FG) The functio
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Table 1 Results for continuous sens
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Fig. 7 pulse response XXX, filter :
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Fig. 11: Noise spectrum VS30-SIC-46
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waves propagate in a plate like str
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0.15 0 100kHz Driving pulse 10 100k
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0.45 0 100kHz Driving pulse 30 100k
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the sensor response to different fr
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CHARACTERISTICS OFACOUSTIC EMISSION
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Results and Discussion Shrinkage pr
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sapwood. Norway spruce wood consist
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most of the cells reached the fiber
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CHARACTERIZATION OF TITANIUM HYDRID
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Growth behavior of hydrides We stud
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were determined by the tensile test
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Figure 9 shows the Mode-I cracks in
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Results obtained are summarized as
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process of hydrogen destruction of
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Amplitude [dB] 60 55 50 45 40 35 30
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(Fig. 7) relative to the material a
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is shown in Table 1. Test specimens
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Fig. 4 Two types of AE signals dete
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the charging solution at 25 o C, by
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ANALYSIS OF ACOUSTIC EMISSION FROM
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nearly same waveforms for the first
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values). Most (11 of 14) of the rec
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Type-D (at 3.45 ms). In this sample
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NEURAL NETWORK BURST PRESSURE PREDI
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temperature, while the remaining se
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not properly set). This results in
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Conclusions Table 3 Summary of trai
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accurate source locations could be
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Fig. 1 Group velocities versus freq
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plane source orientation. But the l
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Fig. 9 Out-of-plane displacement vs
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Fig. 11 WTs of Fig. 8 with superimp
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Fig. 13 WTs of Fig. 10 with superim
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Table 3 At 102 kHz, WT peak arrival
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Fig. 17 Frequency of maximum WT int
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Fig. 18 Arrangement of sensors (#1,
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location calculation result that yi
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NOVEL ACOUSTIC EMISSION SOURCE LOCA
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tion resolution. It should be noted
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The specimen with numerous holes wa
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Fig. 5. Comparison of location meth
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Conclusions Delta-T source location
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Our approach This conceptual view c
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Voronoi Construction: Taking a case
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Fig. 6: Source location on a clamp
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PROBABILITY OF DETECTION FOR ACOUST
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POD is determined at the convergenc
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Fig. 2: Setup for illustrative runs
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Fig. 7: Probability of location (PO
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AE signals were filtered by high-pa
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Fig. 3 Accuracy and variations of a
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Fig. 7 Accuracy and variations of a
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eference data. The absolute values
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REAL-TIME DENOISING OF AE SIGNALS B
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600 500 400 300 200 kHz700 Frequenc
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the STFT result (Fig. 4(b)). Theref
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MONITORING THE EVOLUTION OF INDIVID
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the type of filtering, number of su
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was observed for either actuator. F
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Conclusions An experimental methodo
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the onset of pulses, consequently,
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zeros. The locations where a patter
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The reliability of the additional p
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AE MONITORING OF SOIL CORROSION OF
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Fig. 2 Cumulative AE counts with ap
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cumulative event counts and amplitu
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AE was monitored using three types
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Our conclusion from these tests is
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measurements with an Exxon Nuclear
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equipment manufacturer), CISE (AE t
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Automatic testing of receptacles du
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The finalized standards are: • EN
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14. Tscheliesnig P., Lackner G., He
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Fig. 1. Typical high-temperature cr
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• Emission rates are much higher
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Fig. 4. Results of AE monitoring of
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examination at 2000-5000X was able
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samples extracted from the beam aft
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The relative comparison of the size
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Fig. 3. Schema of VB Application fo
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Fig. 5. Microstructural observation
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Fig. 7 AE source locations for diff
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Fig. 9 CT images and corresponding
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A.M. Brandt, G. Prokopski, J. Mater
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conducted with AE technique. The AE
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After location of the events, inter
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The transit times of the individual
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6) B. Schechinger, T. Vogel, Acoust
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greater than the available anchorag
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location uncertainty and is the roo
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Figures 4 and 5 illustrate all loca
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ig cracks form, localization of AE
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ased on magnetic induction, while i
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Fig. 3. AE sensors positioning on b
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As a further evaluation of the degr
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EARLY FAULT DETECTION AT GEAR UNITS
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Acoustic Emission Analysis at Rotat
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The fixed bearing at the beginning
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The time-frequency components of a
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Additionally, the gear test bench h
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APPLICATION OF ACOUSTIC EMISSION IN
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Measurements of the acoustic backgr
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Fig. 6. RMS for different ranges of
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which indicate the transition from
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surface condition. It has already b
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( 2 1) 2) ! kx1 ! k c ! x + c ! k (
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Fig. 6: Signal above normal and def
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DAMAGE ASSESSMENT OF GEARBOX OPERAT
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The waveform streaming can be trigg
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Extracting features using different
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The classifier was used to identify
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ASL spectral energy is further calc
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2 #_ of _ Sensors 2 2 2 ( x ) (
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Simulated Failure Plane One hundred
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It has been documented that the ini
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(a) (b) (c) (d) 95% _ 98% 98% _ 100
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IMPACT IMAGING METHOD TO MAP DAMAGE
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e) Step d) was repeated until the a
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Panel A Panel B Panel C Panel D Fig
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Journal of AE, Volume 25, 2007 (ca. 26 MB) - AEWG

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