1. Daniele Tosi
Fiber Optic Sensors for Digital Monitoring:
Opportunities and Challenges
Zhejiang University - 17/11/2011

2. Roadmap
1. Technology overview
2. The problem
3. Lab-in-a-fiber
4. Signal processing
5. Applications and opportunities

3. 1. Technology overview

4. Optical fiber sensors
Sensors embedded into optical fiber devices
All physical parameters transduced into fiber
Strain
Vibrations
Pressure
Temperature
Distributed strain
Chemical concentrations
Biomedical parameters

5. Why optical fibers
με, nε, pε sensing
★ Super performance 0.01°C accuracy
1 ppm chemical
★ Miniature size 50 km distance
★ Distribution
★ Safety/immunity

6. Why optical fibers
με, nε, pε sensing
★ Super performance 0.01°C accuracy
1 ppm chemical
★ Miniature size 50 km μm
10/125 distance
Lightweight
Embeddable
★ Distribution
★ Safety/immunity

7. Why optical fibers
με, nε, pε sensing
★ Super performance 0.01°C accuracy
1 ppm chemical
★ Miniature size 50 km μm
10/125 distance
Lightweight
Embeddable
Punctual
★ Distribution Multiplexed
Distributed
★ Safety/immunity

8. Why optical fibers
με, nε, pε sensing
★ Super performance 0.01°C accuracy
1 ppm chemical
★ Miniature size 50 km μm
10/125 distance
Lightweight
Embeddable
Punctual
★ Distribution Multiplexed
Distributed
EMI compatible
★ Safety/immunity Fire-safe
Passive

9. Fiber Bragg Grating
FBG = in-fiber selective mirror

10. FBG sensor
Strain
Vibrations
Pressure
Temperature
Mechanical strain
λ(ε, ΔT)= λ0+kεε+kTΔT
Thermal expansion

11. FBG response
Strain: 1 pm/με Temperature: 10 pm/°C

12. FBG response
LINEAR response
TEMPERATURE compensation
Strain: 1 pm/με Temperature: 10 pm/°C

13. Chirped FBG
FBG with non-uniform modulation
➯ Shortly distributed pressure sensor (2-5 cm)

14. Chirped FBG
Pressure
Spectrum

15. Chirped FBG
Pressure
Spectrum
Delta pressure
d

16. Evanescent field sensors
Interfacing an optical fiber with surrounding
environment (gas, chemical, biomedical)
>> Hold the tail to whack the dog <<
Tail
Dog
Evanescent field

17. Evanescent field sensors
(1) Side-polish

18. Evanescent field sensors
(2) Recoating

19. Evanescent field sensors
(3) Doping

20. Evanescent field sensors
Gas concentration >> refractive index >> transmittance

21. Evanescent field sensors
Single dopant
Interaction
Interpenetrating polymer
network + nanoparticles

22. Surface plasmon resonance
Multiple SPR

23. Surface plasmon resonance
Multiple SPR

24. Dopants
Dopant Sensitive to
Absorption Palladium Hydrogen
SPR Silver (Ag) H2S
Trapping Hydrophobic sol-gel Oxygen (O2)
matrix
SPR Titanium dyoxide Tyrosine
nanoparticles
Immobilization Acetylcholinesterase Clorphyripos
(AChE) (pesticide)
Enzymatic dep. FITC-labelled dNTP Telomerase

25. Information
Information is encoded into spectrum
Short bandwidth for FBG/CFBG (1-5 nm)
Wide bandwidth for EFT/SPR (50-800 nm)
How to demodulate?
Cost, sensitivity, frequency

26. Spectrometric
LED Spectro
(white) meter
FBG1 ... FBGn
λ
LED Spectro
(white) meter
EFT1 ... EFTn

27. Spectrometric
LED Spectro
(white) meter
FBG1 ... FBGn
Absorption
λ
LED Spectro
(white) meter
EFT1 ... EFTn

28. Spectrometric
LED Spectro
(white) meter
FBG1 ... FBGn
Strain
Temperature
λ
LED Spectro
(white) meter
EFT1 ... EFTn

29. Spectrometers
> $50k $5k
10 pm 1 pm
1 Hz 1 Hz
2000 nm 40 nm
Optical Spectrum Analyzer FBG Analyzer
$35k $20k
0.1-1 pm 10 pm
1 Hz - 5 kHz 1 Hz
60 nm 500 nm
FBG Interrogator Spectrometer

30. Intensity
Power detectors do not resolve spectrum
>> Need to transduce spectrum into power <<
Solution: sweeping laser, synchronized photodetector
Bonus: cheap
$25-100k
vs

31. Intensity
$2.2k !
D. Tosi, G. Perrone, “Low-cost, high sensitivity, signal processing-
enhanced fiber Bragg grating sensing system for condition-based
maintenance application”, Sensor Letters, 2011

32. Intensity
Fixed-wavelength
MHz frequency
Laser noise
$2.2k !
D. Tosi, G. Perrone, “Low-cost, high sensitivity, signal processing-
enhanced fiber Bragg grating sensing system for condition-based
maintenance application”, Sensor Letters, 2011

33. Intensity
$10.5k
D. Tosi, M. Olivero, A. Vallan, G. Perrone, “Weigh-in-motion through
fibre Bragg grating optical sensors,” Electronic Letters, 2010

34. Intensity
Swept laser
100 Hz
Laser noise
$10.5k
D. Tosi, M. Olivero, A. Vallan, G. Perrone, “Weigh-in-motion through
fibre Bragg grating optical sensors,” Electronic Letters, 2010

35. 2. The problem

36. FOS vs WSN
(M$)
FOS WSN
1200
1000
800
600
400
200
0
2006 2007 2008 2009 2010 2011
2005
2007 forecast

37. FOS vs WSN
(M$)
FOS WSN
1200
1000
800
600
400
200
0
2006 2007 2008 2009 2010 2011
2005
Real picture

38. The pain
Expensiveness
(Cost ≥ WTP * 5)
Scalability
(Every sensor is a prototype)

39. Expensiveness
Accuracy
1pε Niche
1nε
Spectrom.
1με WSNIntensity
WSN high
1mε low
$100 Cost
$1k $10k $100k
>> Hi-end market overview (no consumer) <<

40. Expensiveness
Accuracy
1pε Niche
Demand
1nε OFS Spectrom.
Demand
1με WSN WSNIntensity
WSN high
1mε low
$100 Cost
$1k $10k $100k

41. Scalability
Every unit is a prototype...
Architecture Calibration Packaging
Self-calibration Embedment into
Plug&play
development composite
Create LIFA building Agile calibration Packaging of building
blocks development blocks
Remove wavelength Minimize installation
Auto recalibration
constraints efforts

42. Re-targetting FOS
Target Commercial R&D
Strain 1 nε 1 με 0.1 nε
Temperature 0.2 °C 0.5 °C 0.1 °C
Bio/chem. 10 ppm ~0.1% ~0.01%
Cost/sensor $500 > $5k > $5k
Scalability Complete Prototype None
# Sensors 20 100 100

43. 3. Lab in a fiber

44. Sensing capabilities
Strain/vibration +
Temperature +
Pressure +
Differential pressure +
Gas/chemicals +
Biomedical =
Lab-in-a-fiber (LIFA)

45. LIFA unit
Strain FBG
SPR
Temp. FBG
EFS
Chirped FBG

46. Selection - 1
Strain + chemical
...
Strain +
vibrations + EFS a/or SPR
temperature 1-2 substance
(compensation) detection

47. Selection - 2
Biomedical detection
Temperature Medical
compensation detection
Differential
pressure

48. Selection - 3
Multi-chemical
Differential
Multiple SPR pressure
Chemical detection
Gas
compensation

49. LIFA spectrum
...
EFS SPR
Accumulates EFS/SPR
curves of all LIFA units
on each channel

50. LIFA spectrum
...
Discriminates each FBG/ FBG CFBG
CFBG, each encoded by
wavelength

51. Single matrix
LIFA matrix
...
...
. . .
. . .
. . ... .

52. Single matrix
Switching LIFA matrix
...
...
. . .
. . .
. . ... .
SLED
Spectrom.
FBGA

53. Single matrix
Switching LIFA matrix
...
...
. . .
. . .
. . ... .
SLED
Integrated
Spectrom.
LIFA
source
FBGA

54. Double matrix
Switching LIFA matrix
...
...
. . .
. . .
. . ... .
Laser array
Photodetector
Laser
. controller
.
.

55. Kudos
LIFA matrix
...
...
. . .
. . .
. . ... .
1 2 N
Each LIFA block is encoded
SCALABILITY
No “custom-made” blocks
LOW-COST
Ease of fiber fabrication

56. Kudos
LIFA matrix
...
...
. . .
. . .
. . .
MORE All EFS/SPR are the same!
SCALABILITY Pre-fabrication equal for all blocks

57. Kudos
Source/receiver is the
main cost of single
matrix architecture
INTEGRATION
SLED
Integrated
Spectrom.
LIFA
source
FBGA

58. Kudos
Lasers wavelength encoded
SCALABILITY
as LIFA (optimization)
LOW-COST
Laser array
Lasers are cheap
Laser
Laser controller isn’t controller
.
.
.

59. Kudos
Switching LIFA matrix
...
...
. . .
. . .
. . ... .
Laser array
Photodetector
Laser
. controller
Processing .
DSP .

60. Kudos
Switching LIFA matrix
...
Shift COMPLEXITY to
...
SIGNAL PROCESSING
.
.
.
.
.
.
. . ... .
Laser array
Photodetector
Laser
. controller
Processing .
DSP .

61. 4. Signal processing

62. Standard chain
Data
Interpretation
Storage +
Processing
Interrogation
Unit

63. Abstraction layer
Data
CONCRETE Interpretation
Storage +
SEMI-ABSTRACT Processing
Interrogation
ABSTRACT Unit

64. Abstraction layer
Data
CONCRETE Interpretation
Storage +
SEMI-ABSTRACT Processing
Interrogation
ABSTRACT Unit

65. Ineffectiveness
PROBLEM: Data are processed on high
levels of abstraction
➙ No use of a priori physical information
Same for WSN, but FOS have higher
performance and margin!

66. Embedded DSP
Data Data
Fusion + Reduction
Processing
DSP
Interrogation
Unit

67. Closing the gap
SOLUTION: Process data onboard
➙ Data are processed on low level of
abstraction
BEST use of a priori information on
output data!

68. Frequency analysis Adaptive filtering
Processing
DSP
AI
Data fusion
Machine learning

69. Example IFBG
IFBG
Cost = $2.2k; #10 sensors
Stand-alone RLS + MVE RLS&Kalman
+ KLT/MVE
Strain res. 1 με 1 nε <1 pε
Min SNR -10 dB -39 dB -69 dB
Frequency 25 kHz 25 kHz 25 kHz
Proc. time 0.1 s 10 s 4 min

70. Example IFBG
800m
D. Tosi, M. Olivero, G. Perrone, “Low-cost fiber Bragg grating vibroacoustic sensor for
voice and heartbeat detection,” Applied Optics, 2008

71. 5. Applications and
opportunities

72. Multipoint FOS market
2%
2% Remote structures
3% Smart structures
7%
Security
13%
35% Industrial process
Seismic
Aerospace
15% Military
Medical
22%
Oil&Gas - Renewables - Biomedical???

73. 1.2 skyscrapers/week
500Mdata/s/Shanghai
+15% lifecycle
+21% prediction

74. Smart structures
Cloud structures
Venezia, Scola Grande
Torino, Cappella Guarini
I. Ivascu, D. Tosi, M. Olivero, G. Perrone, N. N. Puscas, “Low-cost FBG
temperature sensor for application in cultural heritage preservation,”
Torino, Passerella Olimpica Journal of Optoelectronics and Advanced Materials

75. Gain = ηT - C
Gain = (η+Δη)(T+ΔT) - (C+ΔC)
+10% lifecycle
+ 10% efficiency
(Vestas)

76. 4D sensors
mapping

77. Perimeter
Anti-terrorism
Biohazard

78. Strain
Temperature ref.
Leak/corrosion
Strain + Temperature + Oxygen
DTS integrated

79. Vibrations
Propulsion
Redundancy

80. Urodynamic diseases

81. Fracture healing
monitoring
(Fiberlogix)

82. Thank you