Journal of AE, Volume 27, 2009 (ca. 35 MB) - AEWG

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References Holford, K. and Lark, R. (2005). Acoustic emission testing of bridges. In Fu, G., editor, Inspection and Monitoring Techniques for Bridges and Civil Structures. CRC Press. Hopwood, T. and Prine, D. (1987). Acoustic emission monitoring of in-service bridges. Technical Report UKTRP-87-22, Kentucky Transportation Research Program, University of Kentucky, Lexington, Kentucky. Kentucky Transportation Cabinet (2003). Traffic station counts: Jefferson County, Kentucky. Division of Planning traffic station map. Kosnik, D. and Marron, D. (2007). Acoustic emission evaluation of retrofits on the I-80 Bryte Bend Bridge, Sacramento, California. In Ono, K., editor, Advances in Acoustic Emission: Proceedings of the Sixth International Conference on Acoustic Emission. Acoustic Emission Working Group, Colorado, USA, and Acoustic Emission Group, Encino, California, USA. Marron, D. and Kosnik, D. (2008). Acoustic emission monitoring of a top chord on the John F. Kennedy Memorial Bridge over the Ohio River, Louisville, Kentucky. Technical report, Infrastructure Technology Institute, Northwestern University, Evanston, Illinois. McKeefry, J. and Shield, C. (1999). Acoustic emission monitoring of fatigue cracks in steel bridge girders. Technical Report MN/RC–1999–36, University of Minnesota, Department of Civil Engineering, Minneapolis, Minnesota. Prine, D. (1985). Structural fatigue damage detection with the GARD Acoustic Emission Weld Monitor (AEWM). Technical report, Chamberlain Manufacturing Corp., GARD Division, Niles, Illinois. Prine, D. (1994). Acoustic emission monitoring of the trunnion shafts on Oregon DOT Bridge #1377A, the I-5 Columbia River Bridge east lift span, Portland, Oregon. Technical report, Infrastructure Technology Institute, Northwestern University, Evanston, Illinois. Prine, D. (2001). Acoustic emission monitoring of the Hoan Bridge. Presented at AEWG-44, Montreal, Quebec. Prine, D. (2004). Localization of noise sources in large structures using AE. In Proceedings, EWGAE 2004. 26 th Meeting of European Working Group on Acoustic Emission, Vol. 1, pp. 247- 254, DGfZP, Berlin. 17
Abstract ACOUSTIC EMISSION AS A MONITORING METHOD IN PRESTRESSED CONCRETE BRIDGES HEALTH CONDITION EVALUATION MAŁGORZATA KALICKA Institute of Structural Engineering, ETH Zurich, 8093 Zurich, Switzerland A system, based on acoustic emission (AE) monitoring technique, has been studied at Kielce University of Technology for several years. A reference-signals database has been prepared based on laboratory tests on samples, beams and full-scale girders. The developed reference data has been verified during field monitoring of prestressed and post-tensioned concrete bridges. Some phenomena, which are usually very difficult or even impossible to discover by the traditional methods, were detected by this system. Keywords: Destructive processes (DP) analysis, Prestressed concrete bridges, Structural health monitoring. Introduction Prestressed concrete bridges, which are nowadays in service, were designed to work safely for an average of 50 years. A large number of structures are reaching this age. Throughout 50 years, the traffic has enlarged significantly, both in quantity of vehicles and transferred goods. The actual loads mostly exceeded the design loads applied at the time of construction. To assure both serviceability and safety of structures, inspections are undertaken periodically. However, the assessment relies mainly on visual observations. Material degradation evaluation and nondestructive techniques (NDT) cover simply a limited volume of a structure. Moreover, the condition of a structure is estimated only at the time of an inspection. The history of damage initiation and development is unknown. In most cases, loading conditions as well as environmental factors are also unidentified. As a result, the assessment relies mainly on the inspector’s own experience and subjective decision-making. Road management institutions responsible for infrastructural networks had come to the conclusion that the traditional methods for bridge inspections are insufficient and new assessment methods and damage/deterioration evaluation criteria should be established. Following this challenge in the last decade, European and American engineering grants [1-9] have supported programs related to structural health monitoring, safety of infrastructure, increase of service life, reduction of maintenance costs and smart structural monitoring. These programs resulted in a great number of comments and conclusions. Here are some main remarks regarding structural monitoring. Most important aim is to improve already existing structural monitoring methods and to develop new innovative structural monitoring systems to prevent unexpected structural failures/collapses. To have a better understanding of existing condition, the measurement of the loading variations and its influence on the structural reliability should be controlled globally as well as locally. Moreover, measurement of loading should be carried out together with registering the environmental conditions. To control the initiation and the development of damages and deteriorations, long term (at least 1-2 weeks) and continuous monitoring should be conducted. For the collected monitoring results, a central database management should be created. Prognosis of the structural reliability concerning the decrease of strength of material is the final aim for a complete model of structural health monitoring system. J. Acoustic Emission, 27 (2009) 18 © 2009 Acoustic Emission Group
Page 2 and 3: Journal of Acoustic Emission, Volum
Page 4 and 5: and HISAKAZU MORI 233-240 27-241 EF
Page 6 and 7: JOURNAL OF ACOUSTIC EMISSION Editor
Page 8 and 9: MEETING CALENDAR: EWGAE29 EWGAE-201
Page 10 and 11: eference in that document to see if
Page 12 and 13: AE LITERATURE Chinese Acoustic Emis
Page 14 and 15: Li Guanhai, Liu Shifeng (Tsinghua U
Page 16 and 17: Monitoring during Landing Gear Cont
Page 18 and 19: MONITORING THE CIVIL INFRASTRUCTURE
Page 20 and 21: including stringers, floor beams (i
Page 22 and 23: Fig. 3. A sensor array for monitori
Page 24 and 25: Fig. 7. Maintenance follow-up recom
Page 26 and 27: Fig. 9 Fatigue-prone location on th
Page 28 and 29: ACOUSTIC EMISSION TESTING OF A DIFF
Page 30 and 31: adius of each other in order to pas
Page 32 and 33: Fig. 3. AE transducer arrays. (a) A
Page 36 and 37: Unfortunately, there are neither a
Page 38 and 39: Table 2: Total damage extension of
Page 40 and 41: Some structures, even when visibly
Page 42 and 43: identification processes leading to
Page 44 and 45: ACOUSTIC EMISSION LEAK DETECTION OF
Page 46 and 47: evaluate and to calculate the linea
Page 48 and 49: Further analysis was made on-site u
Page 50 and 51: graph) shows higher activity betwee
Page 52 and 53: Fig. 8. (a) Aerial photo of the com
Page 54 and 55: Fig. 12. ASL measurements at 8.3 ba
Page 56 and 57: Today’s modern AE systems offer i
Page 58 and 59: Fig. 1: Primary AE parameters [6].
Page 60 and 61: Fig. 4: Backpropagation neural netw
Page 62 and 63: does not drop below the set thresho
Page 64 and 65: Fig. 8: Amplitude histogram for a t
Page 66 and 67: Table 2 shows the tests for the 3.8
Page 68 and 69: Fig. 14: Cumulative energy versus c
Page 70 and 71: crack jumps have a higher amplitude
Page 72 and 73: etween these two fatigue life value
Page 74 and 75: Table 5: 25% HCF BPNN testing file.
Page 76 and 77: Fig. 23: Range of data used for 50%
Page 78 and 79: 4. Conclusions and Future Work Acou
Page 80 and 81: [15] Suleman, J., Korcak, A., Barso
Page 82 and 83: on the resin plate hardness or its
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Fig. 4 Schematics of cutting load a
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(a) Line force during idle cutting
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(a) Non-arranged die type, f imax /
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Fig. 11 Sensor position and impact
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Fig. 14 Relationship between Δf im
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DAMAGE ONSET AND GROWTH IN CARBON-C
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(a) (b) (c) Fig. 1. (a-b) Polarized
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Fig. 4(c). The dependency of the th
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Fig. 6 (c) cumulative AE counts at
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as shown schematically in Fig. 8(a)
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(a) (b) (c) (d) Fig. 11. Micro-fail
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FUNDAMENTAL STUDY ON INTEGRITY EVAL
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Fig. 3 UT C-scan images of internal
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Fig. 7 AE signal peak amplitude and
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Fig. 9 Relationship between AE sign
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monotonically with load. As mention
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A phenomenon of stress wave generat
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where plus sign refers to the first
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kHz. The result of filtration is sh
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Sphere radius, R, mm Sphere mass, m
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Regime ρV 2 /Yd (MPa) Approximate
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a b Fig. 6. AE signal at the remote
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a b Fig. 9. AE waveforms from impac
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9. А.А. Harkevich, Spectrums and
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amplitudes in the AE signals. In th
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Fig. 2. Signals from small aperture
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Fig. 4. Signals from small aperture
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during the duration of the direct w
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Fig. 8. Expanded time scale view of
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Fig. 10. Displacement signal result
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Fig. 12. Top surface out-of-plane d
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Fig. 14. Signals from small apertur
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Fig. 16. Filtered signal showing hi
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Fig. 18. WTs of the first 200 µs o
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Summary There are three summary obs
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FRACTURE BEHAVIOR IN BONE CHARACTER
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Fig. 2. Schematic diagram of static
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and AE events during loading were d
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References [1] Hirai T., Katayama T
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where and stand for the strain-hard
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Experimental The samples for mechan
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Fig. 4. Typical AE waveforms and th
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detected just before the upper yiel
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the AE energy in iron upon Lüders-
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The most intriguing issue, which ha
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ACOUSTIC AND ELECTROMAGNETIC EMISSI
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Fig. 2 Sample assembly: (a) setup f
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We have observed that the EME signa
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EME under Repeated Loading Rectangu
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the fact that the AE due to the fri
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Abstract IDENTIFICATION OF AE MULTI
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sensor/sonde/surface units have fla
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Fig. 3. Coherency between a pair of
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These multiplets may be related to
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Fig. 7. Hypocenter location and sou
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Accordingly, semi-supervised or uns
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Indeed, the AE events are also non-
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Fig. 5. Overlap plot of AE events f
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(a) Individual Events Test 1 Test 2
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Fig. 10. The distribution of event
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loading tests of concrete elements
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Fig. 4: Typical cracking of specime
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(a) Plain concrete. (b) Composite.
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3) T. Shiotani, M. Shigeishi and M.
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data cannot be recorded by most exp
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where A and I are the area and mome
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Fig. 3 Loading condition for the si
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4. Simulation Results 4.1 Stress-st
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dilatancy observed in an actual uni
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Fig. 9. Energy-frequency distributi
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After the AE cluster formation, mic
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Fig. 13 Spatial distribution of all
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7. J.F. Hazzard and R.P. Young: Int
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obvious that the calibrating AE sou
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Fig. 2. Geometry and schematic illu
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The boundary conditions for tempera
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Calculations have shown that in ord
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Fig. 9. Example of an AE sensor cal
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Hence, the distinct features and ad
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Developed Sensor Configuration Rela
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In this study, the sensor width was
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Fig. 8 Typical AE waveforms and the
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Fig. 11 Relationship between shell
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CORROSION DETECTION BY FIBER OPTIC
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sensor by an FOD sensor. Due to the
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Corrosion AE Monitoring AE monitori
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operated at the normal condition. S
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EFFECT OF SHOT PEENING ON THE DELAY
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Figure 1 shows the SSI and three-po
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stresses do not give any positive e
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Fig. 7 Examples of Lamb waveforms p
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Figure 10 shows results of an SSI t
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as-received strip. It is noted that
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Almen strips were charged in less a
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more AE transducers. AE events may
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Given the data with , and the new d
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Fig. 4. Projection of AE data: (a)
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Table 2. Feature-discriminated stat
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FLEXURAL FAILURE BEHAVIOR OF RC BEA
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Table 2. Weight loss of rebar after
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(a) Global (b) Close up (only skele
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AE hits. By comparison among corros
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dots). It seems that the ratio of A
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Fig. 1. The scheme of double-bottom
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Fig. 3. The other two at 2 and 7 o
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Fig. 6. Located AE sources with the
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Fig. 10. The intensity of recorded
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STUDY OF IDENTIFICATION AND REMOVAL
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Fig. 4 2D Location result with ch5-
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Fig. 8 Noise removal result with th
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Identification and removal for drop
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It was confirmed that a minimum thi
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A GENERIC TECHNIQUE FOR ACOUSTIC EM
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where ∆t exp are the experimental
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stone disc. Oolitic limestone is a
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CFC plate test, larger errors occur
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ACOUSTIC EMISSION TESTING - DEFININ
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What is the detection performance o
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A.3. Performance analysis - Calcula
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- Planar testing configuration (2.5
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Whereas in the planar testing confi
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We can see that full use of the pla
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B.3. Influence of the minimum numbe
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technique such as GBP in France, au
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Page 149 Elastic Waves in Solids Ro
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A Note from the Editor Kanji Ono Nu
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Page 173 5th Colloquium on AE D. Sc
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S78 S82 S86 S90 S94 On the Applicat
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S247 In-Process Acoustic Emission M
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Page i Appreciation K. Ono / Europe
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Page 83 Number 2 Page 85 Page 93 Pr
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Page 111 Page 119 Page 129 Page 129
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S53 S57 S62 S66 S70 S71 S75 "AE App
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S231 S236 Vessels", S238 S239 "Tool
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Number 4 Page 65 Page 93 Page 99 A
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Page 197 Page 203 Nondestructive Ev
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M. Momayez, F. P. Hassani and H. R.
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Number 3 Page C1-C24 Page 95-99 Pag
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12th International Acoustic Emissio
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Source Simulation Analysis Hiroaki
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Page S70-S79 Page S80-S88 Page S90-
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Page S343 Page i-iii Page iii Page
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A. Tsimogiannis, B. Georgali, and A
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VOLUME 19, 2001 ACOUSTIC EMISSION E
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VOLUME 20, 2002 Contents 20-001 DAM
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20-285 ACOUSTIC EMISSION CHARACTERI
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21-197 New Concept Of Ae Standard:
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22-243 Rods And Tubes As Ae Wavegui
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23-196 Ae And Electrochemical Noise
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Kazuaki Arai, Katsuyuki Kaiho, Hiro
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25-132 A SIMPLE METHOD TO COMPARE T
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25-373 IMPACT IMAGING METHOD TO MAP
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High-Voltage Electric Devices Jan P
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27-212 ELECTROMAGNETIC METHOD OF EL
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Authors Index, Volumes 1-27 (1982-2
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Thomas Bidlingmaier 14-S47 Jacek M.
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S. Y. Chuang 4-S137 S. S. Christian
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J.-P. Favre 9-97 Carol Featherston,
Page 400 and 401:
Y. Haddad 8-S314 M. E. Hager 8-S42
Page 402 and 403:
Y. Ichimura 19-142 Makoto Ichinose
Page 404 and 405:
Kunihisa Katsuyama 11-S27 Harold E.
Page 406 and 407:
MOSHE KUPIEC, 27-077 D. S. Kupperma
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Eric Madaras 23-037 M. R. Madhava 8
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F. Mostert 18-189 Andre Moura 23-10
Page 412 and 413:
Tatsuma Ohnishi 19-109 Tadashi Onis
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M. Raab 20-274 Amani Raad 20-300 Ja
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Keiichi Sato, 4-S240, 8-S213, 9-209
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Wolfgang Stengel 4-S312 D. Stöver
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R.G. Tobin 8-25 Akira Todoroki 26-1
Page 422 and 423:
M. Wevers, 4-S186, 8-S272, 13-79, 1
Page 424:
Daihua Zou 5-S1 Ryszard Zuchowski 2
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Journal of AE, Volume 27, 2009 (ca. 35 MB) - AEWG

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