SHM with Long-gauge Fiber Optic Sensors

Report
IBS Workshop, June 14, 2011
SHM with Long-gage Fiber Optic Sensors
Z.S. Wu, J. Zhang, Y.S. Tang, W. Hong, L. Huang
Southeast University, Nanjing, China
Ibaraki University, Hitachi, Japan
Content
1
Background
2
Distributed sensing technique
Distributed long-gage FBG sensors
Utilizing distributed strain measurement for SHM
3
IBS Bridge
Sensor placement
Global parameter identification
Damage detection
1. Single Point Based Sensors
1. Single Point Based Sensors
Damaged!
• Strain Gauge
No damage!
OK?!
Too Local!
Huge Limitation!
2. Distributed long-gage FBG sensors
C o m posite package
S M C : single -m ode optical fib er cable
S M F : single -m ode optical fiber
F B G : fiber B ragg grating
Tube
FB G
C onnector
SM F
SM C
G auge length
(sensing part)
C onnector
125
250
500
B raid buffer layer
S heath
A packaged long -gage F B G sensor
1000
1 -1 C ross sectio n
unit: μ m
2. Distributed long-gage FBG sensors
C o m posite package
S M C : single -m ode optical fib er cable
S M F : single -m ode optical fiber
F B G : fiber B ragg grating
Tube
FB G
C onnector
SM F
SM C
G auge length
(sensing part)
C onnector
125
250
500
B raid buffer layer
S heath
A packaged long -gage F B G sensor
1000
1 -1 C ross sectio n
unit: μ m
2. Distributed long-gage FBG sensors
C o m posite package
S M C : single -m ode optical fib er cable
S M F : single -m ode optical fiber
F B G : fiber B ragg grating
Tube
FB G
C onnector
SM F
SM C
G auge length
(sensing part)
C onnector
125
250
500
B raid buffer layer
S heath
A packaged long -gage F B G sensor
1000
1 -1 C ross sectio n
unit: μ m
Distributed sensing technique provides both the local information
and the global information of the structure!
2. Distributed long-gage FBG sensors
Distributed sensing does not
means simple measurements!
How to realize a nervous system of structures
1)Very dense distribution of using smart point sensors –useful ?
2)Continuous or partially continuous wiring of using line Macro
strain sensors including long –gauge sensors – natural !
2. Packaged Long-gage FBG Sensors
(a) C arbon fiber tow
Design of Long-gage FBG sensor
B
800
Wavelength variation (pm)
700
Sε=1.2pm/με
600
500
400
bare FBG
300
packaged FBG1
200
packaged FBG2
100
packaged FBG3
0
0
50
100
150
200
250
300
350
400
450
500
550
600
Strain variation (µε)
Long-gage FBG sensor specimen
Packaged with BFRP has no influence on
strain sensitivity.
Long-gage FBG sensor and its mechanical property
2. Distributed Strain Measurement for SHM
(a)
(a) Acceleration
Magnitude of strain FRF (/N)
(i) Global Information
6
5
Mode 1
4
Mode 3
3
Mode 2
2
1
0
0
25
50
75
Frequency (Hz)
(b) Strain
100
125
(ii) Distribution of deformation from static strain distribution
Conjugated beam method
Distribution of deformation can be expressed by macro(long-gage)
Deformation
the first joint and
of the
pth element
strainat distribution
in mid-span
an explicit
formula!
(iii) Damage Detection based on normalized modal
macro-strain concept
MMS of a target sensor,
Si
Data set at period t3
Best line of fit
Data set at period t3
Data set at period t2
Best line of fit
Set of data at period t1
Feature = slope
MMS of a reference sensor, SR
Interpretation
No damage within sensor Si between t1 and t2
Increase in slope indicates damage within sensor Si
between t2 and t3
3. Wayne Bridge: Sensor Layout
Totally 44 sensors were installed on the 3rd and 6th girders.
3. Wayne Bridge: Sensor Layout
Fixing end
Fiber sheath
Connector
Plastic tube
FBG
Fixing end
Connector
Gage length
(a)
Fixing end
Gage length
Fixing end
Connector
Connector
(b)
3. Wayne Bridge Test Results: Global Information
Time history
Time window 2
Time window 1
Time window 2
3. Wayne Bridge Test Results: Global Information
25 0 00
20 0 00
15 0 00
10 0 00
F1
F2
F3
F4
F5
F6
F7
F8
F9
F10
F11
F1 2
F13
F14
F1 5
F16
F17
2.81 Hz
5 00 0
0
2
2 .2
2 .4
2.6
2 .8
3
3 .2
3 .4
-5 00 0
Gird 3
Time history
7000
1.0E-04
2.82 Hz
|fft|
8.0E-05
6000
5000
6.0E-05
4000
4.0E-05
3000
2.0E-05
F1
F2
F3
F4
F5
F6
F7
F8
F9
F10
F11
F12
F13
F14
F15
F16
F17
2.81 Hz
2000
0.0E+00
1000
2
2.5
3
3.5
Frequency (Hz)
Acceleration (Drexel University)
0
-1000
2
2.2
2.4
2.6
2.8
3
3.2
Gird 6
Measured Strain
3.4
150
140
130
120
110
100
90
80
70
60
50
40
30
20
10
0
y = 1.0696x - 0.3627
R² = 0.9957
MMS of F7
MMS of F6
3. Wayne Bridge Test Results: Damage Detection
0
15
30
45
60
75
90
105
120
160
150
140
130
120
110
100
90
80
70
60
50
40
30
20
10
0
y = 1.1408x - 0.7698
R² = 0.9958
0
135
15
30
75
90
105
120
135
90
105
120
135
180
y = 1.1699x - 0.7834
R² = 0.9943
160
y = 1.2116x - 0.7081
R² = 0.9948
140
120
MMS of F9
MMS of F8
60
MMS of F4
MMS of F4
160
150
140
130
120
110
100
90
80
70
60
50
40
30
20
10
0
45
100
80
60
40
20
0
0
15
30
45
60
75
90
105
120
135
0
15
MMS of F4
No damage if slope is stable
Increase in slope indicates damage
30
45
60
MMS of F4
75
3. Wayne Bridge Test Results: Global Information
Variance
Slope
F1
0.9915
0.7305
F2
0.9961
0.8438
F3
0.9968
0.9821
Sensor
F4
1
F5
0.9959
1.0111
F6
0.9957
1.0694
F7
0.9958
1.1408
F8
0.9943
1.1698
F9
0.9948
1.2117
F10
0.9952
1.2439
F11
0.9956
1.2757
F12
0.9931
1.3182
F13
0.9916
1.3117
F14
0.985
1.2058
F15
0.9841
1.2119
F16
0.9829
1.2255
F17
0.9815
1.1661
1.2
1
0.8
0.6
0.4
0.2
0
0
5
10
15
20
25
30
35
Fig. Magnitude relationship
3. Wayne Bridge Test Results: Neutral Axis Determination
 (t )
M
X
 (t )
Neutral Axis Determination from
dynamic strain measurement
150
130
Height (cm)
110
25000
90
20000
W1
70
W10
15000
50
F9
30
10000
10
5000
-10
-50
0
50
100
150
200
MMS of Sensor (F9,W1,W10)
250
300
0
2
-5000
2.2
2.4
2.6
2.8
3
3.2
3.4
3. Wayne Bridge Test Results: Neutral Axis Determination
150
150
130
130
110
110
90
90
Height (cm)
Dynamic
Height (cm)
Static
(Drexel Univ)
70
50
70
50
30
30
10
10
-10
-10
-50
0
50
100
150
200
250
300
-50
MMS of Sensor (F10,W2,W9)
Element
Height
9
128
10
122
0
50
100
150
200
250
MMS of Sensor (F11,W3,W8)
11
132
12
117
13 DREXEL
123 122
300
4. Conclusion
Distributed long-gage FBG sensors can be
used for both global and local information
monitoring
Distributed strain measurement can be used for
damage detection by utilizing developed damage
index (like slopes, neural axis locations)
2
More interesting topics will be investigated by
analyzing the measured distributed strains,
e.g., comparing distributed strain time
histories with traditional strain sensor outputs
Thank you for your
attention!

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