acoustic emission monitoring - university of delaware

The World Federation of NDE Centers

Acoustic Emission monitoring

Thomas SchumacherUniversity of Delaware

E-mail: schumact@udel.edu

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

Overview of technology (cont.)

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

Overview of technology (cont.)

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)

Overview of technology (cont.)

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.

Overview of technology (cont.)

11

Koeppel, 2002

Overview of technology (cont.)

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

Overview of technology (cont.)

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

Overview of technology (cont.)

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

Overview of technology (cont.)

15

Grosse et al., 2003

Grosse et al., 2003Sansalone, 1997

� Moment Tensor Inversion (MTI) (cont.)

Overview of technology (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)