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

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y three orders of magnitude [53]. Hamstad and co-workers have conducted extensive finiteelement modeling analysis of Lamb wave propagation (see [55] and references included). His most recent study shows among others the value of using pencil-lead break (PLB) sources on edge to represent buried dipole sources and the danger of surface, out-of-plane PLB to assess realistic wave modes. For very high attenuation media, embedded waveguides provide an effective means of narrowing the zone of AE activity. Waveguides are also used in tests under extreme environment, but often cause severe waveform distortion [56]. Fig. 12 An AE signal in a brass tube detected at 20 cm from the source (left). Its wavelet coefficient at 190 kHz showing two cylindrical wave modes. Yamada et al. [52]. Fig. 13 Wave attenuation in a water-filled buried pipeline. Vahaviolos et al. [54]. 5. Source Characterization Many methods of source characterization are used. The most rigorous one relies on signals from several sensors on a small sample and conducts deconvolution or simulation analysis to obtain the source rise time and magnitude for Mode-I cracks [9]. This applies to idealized cases only and is of little use for large structures. More practical and appropriate approach must be selected. This also means that identification of AE sources relies on complementary knowledgebase on possible failure mechanisms from fracture mechanics and from experience. Typically, materials study accompanies AE examination and empirical deduction leads to AE characterization (although some people are prone to proclaim mechanisms by intuition). The AE analysis 12
methods include the use of combined AE parameters, signal amplitude and distribution, signal frequency, waveform analysis and moment tensor analysis. However, selected AE parameters (hit rates, amplitude, and their time history, being the typical) are the most common approach used in combination with a source location scheme [3-8]. Various evaluation tools discussed in Section 3 are employed in combination. These have been combined with empirical database of post-test inspection and used in grading tested structures. The highly successful CARP procedures, developed initially for composite vessels, combined AE cluster grading with zone location [5, 17]; cf. Fig. 7. Here, grading utilized severity and historic indices representing cumulative intensity and sudden AE activity jump. A similar (but almost unknown outside Japan) system was actually operational in 1978 [4]. Some have since been packaged into commercial inspection technology products, e.g., MONPAC ® and TANKPAC ® . Signal frequency remains controversial as to its effectiveness in source characterization, but it has been used with much success in (high-pass) filtering out background/frictional noise from higher frequency cracking AE signals [26]. This has a firm support from a rigorous experiment (see Fig. 4 and [25]). It is tempting to assign an AE mechanism to its characteristic frequency. It should be pointed out that the direct signal characterization methods have clearly shown that source rise times of a given type of cracking vary by a factor of ten or more so that a single “characteristic frequency” of cracking does not exist [9]. Moment tensor analysis (MTA) is useful in characterizing the nature of AE sources. This identifies the magnitude and orientation of displacement vector of an AE source. From its geological origin, Ohtsu and Ono [57] set forth this method in AE context initially using theoretical simulation. They set a framework for deducing the crack characteristics using only surface AE observations. Ohtsu [58] developed the MTA further, applying to real AE observations in Fig. 14 Loading curve of a center-notched concrete beam, and results of MT analysis within yellow shading. Double arrows are tensile crack and X are shear cracks. Shiotani et al. [59]. 13
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 and 18: The power-law AE behavior was recen
Page 19 and 20: sorting out the original signals, e
Page 21 and 22: Wood [36] in Australia has been usi
Page 23 and 24: One needs to appreciate the difficu
Page 25: In geotechnical applications, the p
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
Page 69 and 70: above the threshold level of 40 dB
Page 71 and 72: energy, i.e., high amplitude and lo
Page 73 and 74: An optical microscopy observation o
Page 75 and 76: 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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