Acoustic Emission monitoring - University of Delaware

The World Federation of NDE Centers

Acoustic Emission monitoring

Thomas SchumacherUniversity of Delaware

E-mail: [email protected]

Short course on NDE for the infrastructureBurlington Vermont, July 16th and 17th, 2011

� Overview of fundamental basis

� Overview of technology

� Review of latest developments

� Strengths of method

� Limitations of method

� NDE application: case studies

� Summary and conclusions

Overview of presentation

2

� Acoustic Emission (AE) is the term used for transient elastic waves generated by the release of energy within a material or by a process (EN, 2000).

� Irreversible process� Source time, location, and mechanism

unknown� Passive technique� Sensing via surface-mounted piezo-

electric transducers� Similarity to earthquakes, i.e. nano-

seismic activity� Frequency range of AE in concrete:

~10 to 500 kHz

Overview of fundamental basis

3

Medium

Sensor

to DAQSource

External load

� Primary sources� Micro-cracking (distributed)� Macro-cracking (localized)� Compression failure (crushing)� Yielding and fracture� De-bonding between materials

� Secondary sources� Sliding/friction between interfaces

� Artificial sources� Calibration sources (pencil lead break, ball drop, pulse)

� Noise� From bearings, supports� Background: ambient traffic, vibrations� From electrical circuit, cell phones

Overview of fundamental basis (cont.)

4

Schumacher, 2008

Angerinos et al., 1999

� Elastic waves in finite media (non-dispersive)

� Reflected/diffracted waves� Guided waves in plate-like members (dispersive)

� Plate waves� Lamb waves

� Wave attenuation� Geometrical� Scattering� Internal friction

Overview of fundamental basis (cont.)

5

Compression wave (fastest) Shear wave Surface wave (slowest)

Frequency, f [kHz]

Nor

mal

ized

am

plitu

de [-

]

0 100 200 300 400 5000.0

0.2

0.4

0.6

0.8

1.076 mm (3 in.)

Frequency, f [kHz]0 100 200 300 400 500

152 mm (6 in.)

Frequency, f [kHz]0 100 200 300 400 500

305 mm (12 in.)

Frequency, f [kHz]0 100 200 300 400 500

1143 mm (45 in.)

Increasing travel distance

Adapted from Wood: http://www.geo.mtu.edu/

Schumacher, 2008

� Measurement process

Overview of technology

6

Source: Ch. Grosse, TUM

b-Value

� Model of the measurement process

Source signal, S(t)�

Stress wave�

Propagation�

Surface motion � voltage�

Amplification�

Filtering Response function�

Digitization/storage on PC�

Response signal, R(t)

Overview of technology (cont.)

7

Pre-amplifier, tfR(ω)

Source, S(ω)

Stress wave front, p-wave

Sensor , tfS(ω)

Data acquisition system , tfR(ω)

Medium, tfG(ω)

( ) ( ) ( ) ( ) ( )G S RR S tf tf tfω ω ω ω ω= ⋅ ⋅ ⋅

( ) ( ) ( ) ( ) ( )G S RR t S t tf t tf t tf t= ∗ ∗ ∗⇕

Adapted from Schumacher, 2008

� Sensors� Piezo-electric (PZT) devices � Voltage output proportional to surface motion� Resonant vs. broadband� Coupling

� Pre-amplifiers� Amplify small sensor output

� Transient recorder� 14 to 18-bit dynamic range typical� Recording rates ≤ 40 MHz (practical ≤ 10 MHz)� Analog filters� Parameter extraction� Full waveform storage� Independent recording using trigger criteria


8Source: Vallen Systeme GmbH

Schumacher, 2008

1)Fowler et al., 1989, 2)Ohtsu et al., 2002, 3)Gutenberg & Richter, 1949,4)Grosse, 1996, 5)Geiger, 1910, 6)Aki & Richards, 1980

� Overview methods of analysis


9

Stored AE signals, R(t)

AE event forming

Qualitative Quantitative

Source parameters5):- Location

- Time

AE parameters- Hit rates/energy/…

Waveform analysis:- Comparisons4)

Moment Tensor Inversion6)

- Historic-severity1)

- Load-Calm ratio2)

- b-Value analysis3)

� Qualitative� Statistical analysis of AE parameters� Does not relate observations with physical parameters (source mechanisms)� Can be performed with as few as 1 sensor� Readily available and implemented in commercial AE systems� Relative measure, only comparable if exact same conditions� Depend on selected acquisition and threshold criteria

� Developed methods� Load-Calm ratio (Ohtsu, 2002)� Historic-Severity index (Fowler, 1989)� b-Value analysis (Gutenberg &

Richter, 1952)


10

Source: ASTM E602 (1982)

� Qualitative (cont.)� Kaiser Effect (Kaiser, 1950): In most metals, AE are not observed

during the reloading of a material until the stress exceeds its previous high value.

� Felicity Ratio (Fowler, 1986): Break down of Kaiser Effect due to material instability where AE start to occur before its previous high value is reached.


11

Koeppel, 2002


12

� Qualitative (cont.)� NDIS-2421 (Ohtsu, 2002)

� Historic-Severity Index (Fowler, 1989)

� Problem: selection of triggerinfluences results!

Golaski et al., 2002

Ohtsu, 2002

Schumacher, 2008


13

� Qualitative (cont.)� b-Value analysis (Gutenberg & Richter, 1949)

� Waveform correlation (Grosse, 1996)

2 2.5 3 3.5 4 4.5

0

0.5

1

1.5

2

AE Magnitude [AdB/20]

log(

Cum

ulat

ive

AE

Hits

) [-

]

Frequency distribution of hit amplitudes

Estimated b-value (slope of this line)± one standard deviation of data

Data mean value

50 hits

Amax

Grosse, 1996

Magnitude-squared coherence

� Quantitative� Relates observations with physical parameters (source mechanisms)� Requires a network of sensors (≥ 6 for moment tensor inversion)� Requires data with high signal-to-noise ratio� Difficult to apply (complicated procedures, still in research stage)

� Source Locations� Arrival time difference method (Geiger, 1910)� ≥ 4 sensors� Accuracy from outside sources low


14

81

23

4

5

6

7

p-wave front

1st hit sensor

AE source

600 650 700 750 800 850 900 950 1000-0.8

-0.7

-0.6

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

Sample # [-]

Sig

nal a

mpl

itude

[m

V]

/ A

IC f

unct

ion

valu

e [-

]

Original Signal

Filtered Signal

AIC Function (on Filtered SignalFloating Threshold Picker

AIC Picker

Schumacher, 2008

� Moment Tensor Inversion (MTI) (Aki & Richards, 1980)� Source mechanism� Requires ≥ 6 sensors� Pre-requisite: accurate

locations (to computeGreen’s functions)

� Radiation pattern inferredthrough surface observations

� Problematic for crackedspecimens (high non-homogeneity)

� Knowledge of responsecharacteristics of systemcomponents required

� Need to use high-fidelity sensors


15

Grosse et al., 2003

Grosse et al., 2003Sansalone, 1997

� Moment Tensor Inversion (MTI) (cont.)


16

Grosse et al., 2001

Shigeishi et al., 2003

� Development of high-fidelity sensors (e.g. Glaser-NIST)

� Sensitive, extreme broad-band, absolutely calibrated

� Wireless sensor networks� Array techniques� High accuracy outside sources

Review of latest developments

17

Grosse et al., 2004McLaskey et al., 2007

Source: KRN Services

� More robust hybrid Moment Tensor Inversion (Linzer, 2001)

� Combines absolute and relative MTI(relative: No need to compute Green’s functions)

Review of latest developments (cont.)

18

Linzer, 2001

Linzer, 2001

� Probability based source location algorithms (Schumacher, 2010)

� Use of seismology based methods for quantitative analyses� New location methods, MTI, moment magnitude, tomography

Review of latest developments (cont.)

19

Schumacher, in review

Strengths of method

Advantages:� Applied during testing/loading� No disturbance during application� Real-time feedback� Detection AND characterization of

internal fracture processes as theyoccur

� Covers volume (distributed sensing)

Useful for:� Monitor progression of existing damage (e.g. crack propagation)� Real-time detection of occurring overloads (alarm system)� Continuous (long-term) monitoring of critical components� Verification of retrofits and repairs (before/after)� Complimentary for in-service load testing (Acoustic Emission Testing)

20

Katsaga et al., 2007

Limitations of method

21

� Very few standards available for infrastructure (NDIS-2421, RILEM)� Large variability in structures (type, geometry, material properties)� Complexity of structures and components � Changing boundary conditions (e.g. cracking or sensor coupling)� Tests not truly reproducible due to nature of AE

� Cannot tell current state such as existing cracks, only change in state

� Background noise can be significant = low signal-to-noise ratio� High variability of signal strengths

� Quantitative analyses often difficult to apply in real-world situations� No long-term monitoring experience with this method

NDE application 1: pressure vessels

� Well established, confidence high� Large pool of samples – baseline data available� Well-defined problem (geometry, material properties)� Loading protocol established� Loading known –

applied pressurecan be easilycontrolled

� Analysis method:historic-severityindex (Fowler, 1989)

22

Catty, 2010

NDE application 2: laboratory RC beam

� Large-scale experiment on RC beam using quantitative analyses(Katsaga et al. 2008)

� Source parameters� Moment Tensor analysis� Insight into development

of fracture during loading� More shear type sources

in the later loading stages

23

Katsaga et al., 2008

NDE application 3: wire breaks on bridge

� Continuous monitoring of post-tensioned bridge (Fricker & Vogel, 2006)

� Monitoring for steel wire breaks� Verified by induced breaks

(after bridge decommissioned)

� Ideal application: sources ofinterest1) high energy comparedto other sources2) and noise

� Example of alarm system

24

1) 2)

Fricker & Vogel, 2006

Fricker & Vogel, 2006

� RC deck girder bridge in Cottage Grove, OR (Schumacher, in preparation)

NDE application 4: in-service load test

25

Crack displ.

AE sensors

Strain gage

� RC deck girder bridge in Cottage Grove, OR (cont.)

NDE application 4: cont.

26

Qualitative Quantitative

NDE application 5: retrofit of steel bridge� Noisy bearing of swing bridge in Reedsport, Oregon

� AE activity during operation before/after replacement of bearing

27

Summary and conclusions� Passive method for monitoring of fracture processes� Applied during testing/normal operation – real-time feedback

� Useful for monitoring and as alarm system:� Prestressed concrete beams� Crack progression monitoring� Location of mechanical noise

during operation� Fracture monitoring during

experiments

� Promote use of principlesfrom seismology forquantitative AE

28

Source: ITI, Northwestern University (website)

Acoustic Emission monitoring - University of Delaware

Documents

Transcript of Acoustic Emission monitoring - University of Delaware