Effect of Laser Induced Tin Oxide (SnO2) Nano particle
Chen Liu_Laser scanning damage detection - Copy
1. Numerical and Experimental Investigation
of Laser-induced Optoacoustic Wave
Propagation for Damage Detection
Student：Chen Liu
Dr. Yongming Liu, Chair
Arizona State University
July 15, 2016
2. Outline
Background
Experimental investigation of laser-induced optoacoustic wave
propagation
Setup
Experimental process
Parametric study
Numerical investigation using finite element method
Finite element model
Laser-induced loading function
Results analysis and comparison
Wave mode study
Conclusions and future work
2
3. Background -1
• Cracks exist in various different kinds of materials
• Cracks in rail, aircraft and heavy-duty machines are
not easy to be detected
Damage
detection
methods
Traditional
method
Non-
destructive(NDE)
evaluation
methods
Attaching
sensors
Wave-
based
method
Laser-
induced
optoacoustic
wave
Lamb wave
Acoustic wave
…
Laser---sensor
Sensor---laser
Laser---laser
Figure 1 Crack in aircraft component[1]
3
[1] Holly Jordan, “Sensor Provide Real-Time Data on Aircraft Component Fatigue,”
http://www.wpafb.af.mil/news/story.asp?id=123306759.
crack
4. 4
Laser-induced optoacoustic wave propagation for damage detection, it is applied
on laser scanning nondestructive testing(NDT), which is used to verify the
structural integrity of materials. Laser beam that generate ultrasound are
scanned across the testing surface.
Works by a mechanism called thermo-elastic expansion
-- directly shoot at the surface
-- laser beam is absorbed
-- create a localized heating
-- induce a stress wave
Figure 2 Laser scanning schemes for ultrasonic
wave-field image construction[2]
[2] Y.-K. An, B. Park, and H. Sohn, “Complete noncontact laser ultrasonic imaging
for automated crack visualization in a plate,” Smart Mater. Struct., vol. 22, no. 2,
p. 025022, 2013.
Background -2
5. • In most studies[2][3] YAG laser is used as emission terminal
• Few studies[4] set the emission terminal as high frequency
MOPA(Master Oscillator Power Amplifier) laser and receiving terminal is
attached piezo sensor
Laser type Power density Repetition rate
MOPA laser Low High(1.6kHz-1000kHz)
YAG laser high Low (10Hz-20Hz)
5
[2] Y.-K. An, B. Park, and H. Sohn, “Complete noncontact laser ultrasonic imaging for automated crack visualization in a plate,”
Smart Mater. Struct., vol. 22, no. 2, p. 025022, 2013.
[3] R. F. Anastasi, A. D. Friedman, and M. K. Hinders, “APPLICATION OF LASER BASED ULTRASOUND FOR NDE OF DAMAGE IN
THICK STITCHED COMPOSITES,” 1997.
[4] S. Yashiro, N. Toyama, J. Takatsubo, and T. Shiraishi, “Laser-Generation Based Imaging of Ultrasonic Wave Propagation on
Welded Steel Plates and Its Application to Defect Detection,” Mater. Trans., vol. 51, no. 11, pp. 2069–2075, 2010.
Background -3
6. Numerical computational techniques have been developed for wave
propagation studies.
• Define the whole model as thermal-mechanical coupled model[5] , apply heat
flux on the laser hitting point.
• Define the laser hitting point as thermal-mechanical coupled and the rest of the
model as pure mechanical model, apply heat pulse on the coupled elements.
6
[5] A. Soni and R. K. Patel, “Two Dimensional Finite Element Modeling Of
Single Pulse Laser Drilling,” vol. 2, no. 3, pp. 389–396, 2013.
Background – numerical simulation
7. 7
Motivation and novelty
• Development of a new laser source-induced acoustic wave
propagation
• Development of a new efficient multi-physics simulation
framework for mechanism investigation of the proposed
experimental setup
• Perform parametric study (both experimentally and
numerically) for optimized parameter determination
• Demonstration for structural components of local property
change detection
9. 9
The objective of this test is to get the time of arrival between signals.
Laser beam is the emission terminal and sensor is the receiving terminal.
• PC controls function generator
and laser machine
• Oscilloscope collects the signals
received from sensor and
synchronized from function
generator
Figure 3 Schematic diagram for the test
Experimental objective
10. 10
Setup
• Fiber Laser (IPG YLPM-1-4X200-20-
20)
• Laser head
• Aluminum plate (4.375” X 12” X
0.0625”)
• Oscilloscope (Tektronix DPO 2024B)
• Function generator (RIGOL
DG1022)
• PC
• Remote control (IPG YLP-RC-USB)
Function generator control laser
machine to form a pulse signal, and
set the pulse durationFigure 4 Experimental setup
Laser head
Fiber laser
Aluminum
plate
Remote
control
Oscilloscope
Function
generator
PC
11. 11
Experimental process
1. Horizontal path test
- change the horizontal position of the laser beam
2. Effect of number of magnets test
- change the number of magnets
3. Vertical path test
- change the vertical position of the laser beam
1
2
3
4
5
1 2 3 4 5
9.525cm9.525cm
Figure 5 (a) Specimen of single path test (b) Specimen of multiple path test
(a) (b)
12. Parametric study
Figure 6 (a)There is no signal received from the sensor (b) There is signal received but not very clear (c) There is
signal received (d) There is signal received and it is the clearest signal
(a) (b) (c) (d)
12
13. 13
• Number of pulse: 1
• Laser pulse duration: 200ns
• Laser pulse period: 10μs (100kHz)
• Laser fire duration: 0.5ms (1000Hz)
• Sampling rate: 62.5 MHz
Figure 7 Parameter setup
Figure 8 Signal plotted by raw data
Parameter setup
14. Figure 9 Filtered signal
Butterworth Bandpass filter:
Laser signal: Highpass: 1500Hz
Lowpass: 500Hz
Received signal: Highpass: 120kHz
Lowpass: 80kHz
14
Signal processing - 1
15. 15
Hilbert-Huang transformation
Hilbert-Huang
transformation
Empirical mode
decomposition
Hilbert spectral
analysis
Intrinsic mode
functions
Extract
characteristics
Hilbert-Huang transformation is used to analyze nonlinear and non-stationary signals.
Widely used in damage detection fields:
• Damage in plate structures[6]
• Digital image splicing detection[7]
• Damage identification of a benchmark buildings[8]
[6] A. I. Zemmour, “The Hilbert-Huang Transform for Damage Detection in Plate Structures,” 2006.
[7] D. Fu, Y. Q. Shi, and W. Su, “Detection of image splicing based on Hilbert-Huang transform and moments of characteristic
functions with wavelet decomposition,” Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics),
vol. 4283 LNCS, pp. 177–187, 2006.
[8] S. Lin, J. N. Yang, and L. Zhou, “Damage identification of a benchmark building for structural health monitoring,” Smart Mater.
Struct., vol. 14, pp. S162–S169, 2005.
16. 16
Figure 10 Decomposed received signal
Hilbert-Huang transformation to decompose the filtered signal to different modes
Signal processing - 2
18. Finite element model
Figure 11 (a) Finite element model in front view (b) 3D finite element (c) FE model in side view
(a) (b) (c)
Define the material properties of laser beam area and test plate separately:
Laser hitting point: Linear isotropic; Thermal expansion coefficient; Density
Rest part of the specimen: Linear isotropic; Density
18
Magnets
Laser hitting
points
Piezo
sensor
Magnets
19. Figure 12 Whole model after meshing Figure 13 Meshed model of laser hitting point and magnet
Element edge size:
Laser hitting point --- 0.0005m
Rest of the model --- 0.001m
19
Magnets
Laser hitting point
Meshed model
20. Laser-induced loading function
Temperature =
273.15𝐾 0 𝑚𝑠 < 𝑡 < 0.1𝑚𝑠
274.35K 0.1𝑚𝑠 < 𝑡 < 0.6𝑚𝑠
273.15𝐾 0.6𝑚𝑠 < 𝑡 < 1𝑚𝑠
Figure 14 Loading function
Hypothesis for this simplified loading function:
• Synchronize with laser firing profile and light
speed is ignored
• The opto-thermal conversion efficiency is
assumed to be a constant
Boundary condition:
Fix the upper side of the specimen
All DOFs = 0
Temperature applied on the specimen is estimated as 1.2K[5] during 0.5ms
273
273.2
273.4
273.6
273.8
274
274.2
274.4
274.6
0 0.0002 0.0004 0.0006 0.0008 0.001 0.0012
Temperature(K)
Time(s)
20
[9] S. Safdar, L. Li, M. A. Sheikh, and Zhu Liu, “Finite element simulation of laser tube
bending: Effect of scanning schemes on bending angle, distortions and stress distribution,”
Opt. Laser Technol., vol. 39, no. 6, pp. 1101–1110, 2007.
21. Figure 17 Time history profile for von Mises stress
Blue line ----laser signal which starts from 0.1ms to 0.6ms
Purple line ----receiving signal from the piezo sensor 21
Time of arrival
Time history profile for simulation
24. 2. Horizontal path test
2.00E-04
2.50E-04
2.00E-04
2.50E-04
1.50E-04
1.87E-04
1.69E-04
2.35E-04
2.41E-04
2.03E-04
0.00E+00
5.00E-05
1.00E-04
1.50E-04
2.00E-04
2.50E-04
3.00E-04
0 2 4 6
TimeofArrival(s)
Horizontal position
Simulation test
4.76E+02
3.94E+02
5.08E+02
4.32E+02
7.62E+02
5.21E+02
5.84E+02
4.33E+02
4.48E+02 6.28E+02
0.00E+00
1.00E+02
2.00E+02
3.00E+02
4.00E+02
5.00E+02
6.00E+02
7.00E+02
8.00E+02
9.00E+02
0 1 2 3 4 5 6
Speed(m/s)
Horizontal position
Simulation test
Figure 19 (a)Time of arrival in horizontal move (b) Speed in horizontal move
(b)(a)
24
Results and comparison - 2
25. 3. Effect of number of magnets test
3.00E-05
2.00E-04
2.50E-04
2.80E-04
3.00E-04
4.92E-05
1.87E-04
2.40E-04
3.02E-04
4.59E-04
0.00E+00
5.00E-05
1.00E-04
1.50E-04
2.00E-04
2.50E-04
3.00E-04
3.50E-04
4.00E-04
4.50E-04
5.00E-04
0 1 2 3 4 5 6
Timeofarrival(s)
Number of magnets
simulation test
3.18E+03
4.76E+02
3.81E+02 3.40E+02 3.18E+02
2.10E+03
5.21E+02
4.07E+02
3.18E+02 2.08E+020.00E+00
5.00E+02
1.00E+03
1.50E+03
2.00E+03
2.50E+03
3.00E+03
3.50E+03
0 1 2 3 4 5 6
Speed(m/s)
Number of magnets
simulation test
Figure 20 (a)Time of arrival with increasing magnets (b) Speed in horizontal move with increasing magnets
(b)(a)
25
Results and comparison - 3
26. 26
Wave mode study
Figure 16 Extracted x, y displacement of
the finite element
(a) schematic representation of the Lamb
wave mode and
(b) the extracted x,y displacement[10]
[10] T. Peng, a. Saxena, K. Goebel, Y. Xiang, and Y. Liu, “Integrated experimental and numerical investigation for
fatigue damage diagnosis in composite plates,” Struct. Heal. Monit., vol. 13, no. 5, pp. 537–547, 2014.
Bottom node ——
Top node ——
Bottom node ——
Top node ——
Figure 15 Extracted (a) x displacement (b) y displacement of the simulation
(a) (b)
Dominant wave mode —— S0 mode (symmetric mode)
27. 27
Conclusions and future work - 1
Conclusions
This research developed an integrated experimental and simulation
framework for a novel optoacoustic wave propagation for damage detection.
• Using a low-power high frequency MOPA laser is feasible
• Local mass change has a large influence on wave propagation; implementation for
small damage detection
• Butterworth bandpass filter and Hilbert-Huang transformation can extract the time
of arrival information accurately
• Laser firing parameters have significant effect on the generated signals; A 100kHz
pulse frequency with 200ns pulse duration can generate clear acoustic wave signals
28. Future work
• Noise reduction is required for more accurate analysis
• Automated scanning for large area detection
• Inverse imaging reconstruction for the detection of damage shape and
location
• Laser-induced optoacoustic wave propagation for damage detection in
composite materials
28
Conclusions and future work - 2
29. 29
Acknowledgements
• My deepest gratitude is to my thesis advisor Dr. Yongming Liu for
the continuous support of my study and research throughout my
Master’s period. His patience and guidance helped me to overcome a
lot of difficulties and finish this thesis.
• I would also like to thank my committee members: Dr. Liping Wang
and Dr. Yang Jiao, for their insightful comments and questions.
• Last but not the least, my sincere thank goes to my fellow labmates
in Arizona State University, especially to Tishun Peng, for
enlightening me with the help of the experiment and simulation.
