Presentation ph d

Innovative ﬁber optic
sensors: from theory to
applications
Daniele Tosi
PhD presentation
Electronics Engineering
2008-2009

Overview
Sensor networks market
Optical ﬁber sensors
Grating sensors
Low-cost solutions

Principles Results
Processing Potential
Daniele Tosi, daniele.tosi@polito.it

Focus
Sensor for measurement of mechanical and
physical parameters
• Direct: strain, vibrations, temperature, ...
• Indirect: pressure, rotation, resonance, modes, level, ...

Network
Applications
Cost control

Daniele Tosi - daniele.tosi@polito.it

Near future scenario

Wireless Sensor Networks VS Fiber Optic Sensors

Market size
'$!!"

'#!!"
Revenues (M$/year)

+,-"
'!!!" ./,"

&!!"

%!!"

$!!"

#!!"

!"
#!!(" #!!%" #!!)" #!!&" #!!*" #!'!" #!''"


*!"#
)!"# Market growth
Market size
(!"#
'$!!"
'!"#
Wireless
&!"# '#!!" Global market
Revenues (M$/year)

%!"# +,-"
$!"# '!!!" ./,"
Optic
!"#
&!!"
!)# !*# !+# !,# $!# $$#
%!!"

$!!"

#!!"

!"
#!!(" #!!%" #!!)" #!!&" #!!*" #!'!" #!''"


Market 49%
Revenues 51%
size 30%
70%
'$!!"
WSN
'#!!"
FOS
2008 2011
Revenues (M$/year)

+,-" 5%
'!!!" 10% ./,"

&!!"
# units
90% 95%
%!!"

$!!"

#!!"

!"
#!!(" #!!%" #!!)" #!!&" #!!*" #!'!" #!''"


Market size
'$!!"

'#!!"
$6.2B $60
+,-"B
Revenues (M$/year)

'!!!" ./,"
$320M
&!!" $335M
Telecom Sensors
Wi-ﬁ
%!!" Sensors

$!!"

#!!"

!"
#!!(" #!!%" #!!)" #!!&" #!!*" #!'!" #!''"


Near future scenario
H

FOS
Cost

WSN
L

Gen. Target Spec.


Differentiation
FOS WSN

Size ∅ <1mm 6x4x3 cm

Fiber immune to Active and passive
Immunity EMI interference
Distrib. + multiplex Punctual
Distribution + punctual Slow multiplex
0.2 dB/km WiLD < 1km
Attenuation Remote sensing Small cover area


FOS
Sensitivity
Interferometry
10 pm

Doppler/TOF
1 nm
Raman/Brillouin
100 nm
Active ﬁbers
10 µm
CCD/imaging
1 mm POF

$100 $1k $10k $100k $1M Cost

FOS
Sensitivity
Interferometry
10 pm

Doppler/TOF 28%
1 nm
Raman/Brillouin
FBG
100 nm Research papers
Active ﬁbers
10 µm
CCD/imaging
1 mm POF 42%

$100 $1k $10k $100k $1M Cost
Revenues

FBG principles
FBG ➙ refractive index modulation inside the
core of an optical ﬁber - wavelength/selective


FBG principles
Modulation period sensitive to:
- mechanical strain
- thermal expansion Λ

Λ
Strain
Temperature


FBG principles
Peak wavelength (nm)

Strain (με)
ΔL/L
{
1 pm/µε
10 pm/°C

FBG principles
Peak wavelength (nm)

➙ Temperature compensation

Strain (με)
ΔL/L
{
1 pm/µε
10 pm/°C

FBG sensors

Receiver Source

? FBG arrays

Coupling ...


Intensity detection

Receiver Source

FBG arrays

Coupling ...


FBG sensors
Sensitivity
Interferometry
<<1nm
Optical spectrum
Active ﬁbers
1nm
Scanning ﬁlter
FBG analyzer
100nm
Intensity
based
Cost
$1k $10k $100k $1M


Applications

• performance
• environment
• immunity
• safety
• invasiveness


Applications
2%
2% Remote structures
3%
7% Smart structures
Security
13% 35%
Industrial process
Seismic
Aerospace
15%
Military
22%
Medical


FBG sensors
H

FOS
Cost

WSN
L

Gen. Target Spec.


Matched FBGs

Sensing Fixed
∫(·) ➥ power meter

Intensity modulation

Matched FBGs


Matched FBGs
320 µε

0.18 mV/µε


Matched laser


Matched laser
Backreﬂection


Matched laser
6

5 1 mV/µε
Voltage (V)

4

3
10 mV/µε
2 60µε
1

-150 -50 50 150
Strain

FBGA

Commercial FBGA

Performances
M. FBGs M. Laser FBGA
Sensitivity ✓✓ ✓✓✓✓✓ ✓✓
Resolution ✓✓✓✓✓ ✓✓✓✓✓ ✓✓
Range ✓✓✓✓ ✓✓ ✓✓✓
# Sensors ✓✓✓ ✓✓ ✓✓✓✓✓
Stability ✓✓✓ ✓ ✓✓✓✓✓


Performances
M. FBGs M. Laser FBGA
Sensitivity ✓✓ ✓✓✓✓✓ ✓✓
Resolution ✓✓✓✓✓ ✓✓✓✓✓ ✓✓
Range ✓✓✓✓ ✓✓✓ ✓✓
# Sensors ✓✓✓ ✓✓ ✓✓✓✓✓
Dynamic
Stability ✓✓✓ ✓ ✓✓✓✓✓

Static

Performances
Perform. Optical

Min SNR -10 dB

Sensitivity 800 nε

RMSE 2.2 µε

Overhead 0%


Signal processing
Sensitivity
Interferometry
<<1nm
Optical spectrum
Active ﬁbers
1nm
SP Scanning ﬁlter
FBG analyzer
100nm
Intensity
based
Cost
$1k $10k $100k $1M


Signal processing
Noise properties - FBG backreflection
Autocorrelation(a.u.)

PSD
(dB)

f/3kHz
Time(s) με
D. Tosi, M. Olivero, G. Perrone, “Self-mixing based interrogation techniques for high-
Daniele Tosi - daniele.tosi@polito.it reflectivity fibre Bragg grating sensors”, Electronic Letters, vol. 44, 2008.

Signal processing
Adaptive ﬁlter - RLS 40 taps

Training

Acquired

Reference

Filtered


Signal processing
Adaptive ﬁlter - RLS 40 taps

Noise ﬁltering

Acquired

Reference

Filtered
14 dB

Signal processing
Capon power spectral density estimator
J. Capon, “High-resolution frequency-wavenumber spectrum analysis”, Proc. IEEE, vol. 57, 1969.

FFT Param. Capon

SNR -10 dB <-40 dB -25 dB

Resolution 1/N ~<1/N Unlimited

Properties None Required Adaptive


Signal processing
Capon power spectral density estimator
J. Capon, “High-resolution frequency-wavenumber spectrum analysis”, Proc. IEEE, vol. 57, 1969.

FFT Param. Capon

SNR -10 dB <-40 dB -25 dB

Resolution 1/N ~<1/N Unlimited

Properties None Required 15 dB
Adaptive


Performances
Perform. Optical Optical + SP

Min SNR -10 dB -39 dB

Sensitivity 800 nε 5.6 nε

RMSE 2.2 µε 0.4 µε

Overhead 0% <1%


Setup
Circuit

DAQ

Strain
Climatic
chamber


Setup


Temperature
Climatic chamber Outdoor


Temperature
Climatic chamber Outdoor

➙ Temperature compensation


Vibrations

Aluminum bar


Vibrations
FBG POF sensor

13 dB

Surface wall


Vibrations

Wooden board

27.1 Hz


Setup
Matlab sound

WVF generator

Acquisition

DAQ
card FBG

Laser/TEC

Setup
Speaker Receiver

FBG

Voice


Voice recognition
FBG
Input


Voice recognition

Cepstrum ➙ FFT[Capon(voice)]

Metronome
92 bpm 112 bpm 144 bpm

www. metronomeonline.com


Heartbeat
69.9bpm
Criticalities:
- FBG positioning
- signal processing


Potential
2%
2% Remote structures
3%
7% Smart structures
Security
13% 35%
Industrial process
Seismic
Aerospace
15%
Military
22%
Medical


Potential
2%
Smart structures
2%
Distributed7%
sensor networks 3%

Few sensing points, repeated
13% 35%

15%

22%


Potential
2%
Remote structures
2%
3%
7%
Remote sensing 35%
13%
Lower cost solutions

15%
22%


Potential
2%
Medical equipment
2%
3%
7%

13% 35%

Increase smartness capability
15%

Replacement / redundancy
22%


Potential
2%
3% 2%
7%

13%
35% Niche applications
in adjacent ﬁelds

15%
22%


Conclusion
• Fiber optic sensors market: trends and opportunities
• Applications range and requirements
• The proposed solutions - low cost FBG sensors
• The effect of signal processing
• Experimental results and potential developments


References
(1) D. Tosi, M. Olivero, G. Perrone, “Dynamic strain measurement system with
fiber Bragg gratings and noise mitigation techniques”, Measurement Science and
Technology, vol. 20, 2009.
(2) D. Tosi, M. Olivero, G. Perrone, “A low-cost fiber Bragg grating vibro-acoustic
sensor for voice and heartbeat detection”, Applied Optics, vol. 47, 2008.
(3) D. Tosi, M. Olivero, G. Perrone, “Self-mixing based interrogation techniques for
high-reflectivity fibre Bragg grating sensors”, Electronic Letters, vol. 44, 2008.
(4) D. Tosi, M. Olivero, G. Perrone, “Broadband source-based interrogation
scheme of fiber Bragg grating sensors for structural health monitoring”, Key
Engineering Materials, vol. 347, 2007.
(5) D. Tosi, M. Olivero, G. Perrone, “Optical microphone with fiber Bragg gratings
and signal processing techniques”, Proc. SPIE, vol. 7098, 2008.
(6) D. Tosi, M. Olivero, G. Perrone, “Low-cost fiber Bragg grating-based static and
dynamic strain system for structural monitoring”, Proc. SPIE, vol. 7098, 2008.


References
(7) Y. J. Rao, “In-fibre Bragg grating sensors”, Measurement Science and Technology,
vol. 8, 1997.
(8) A. Othonos, K. Kalli, Fiber Bragg Gratings: Fundamentals and Applications in
Telecommunications and Sensing, Artech House, 1999.
(9) W. W. Morey, “Distributed fibre grating sensors”, Proc. OFS Conference, 1997
(10) F. A. Bezombes, M. J. Lalor, D. R. Burton, “Contact microphone using optical fibre
Bragg grating technology”, J. Phys. Conf. Ser., vol. 76, 2007.
(11) A. Zaknich, Principles of Adaptive Filters and Self-Learning Systems, Springer, 2000.
(12) J. Capon, “High-resolution frequency-wavenumber spectrum analysis”, Proc. IEEE,
vol. 57, 1969.
(13) D. B. Huff, M. S. Lebby, “Fiber optic sensing technology: emerging markets and
trends”, Proc. SPIE, vol. 6619, 2007.
(14) www.smartech.ch
(15) www.bayspec.com
(16) www.xbow.com

Acknowledgments
Guido Perrone Barry Posner
Massimo Olivero Kevin Holmes
Rena to Orta Nick Kurns
Alb erto Vallan Terri Grifﬁth
Ivo Mo ntrosset Mary Furlong
rancesco Profumo
F
accone
Claudio M
+o thers... John Canning
Gaetano Pelli
Mattias Aslund cano
Antonio Strum Barbara Pizze
ia Kevin Cook lla
Silvio Abrate Maria Grazia
Mike Stevenson Quieti
Julia Gillard
Tracy Harris Armen Berjikly
Sebastian Sabogal Jake Wall


End
Thank you for your interest

Spectral response


Signal processing
Data modelling
RMSE
reconstruction:

11.4με ➙ 0.32με

(6 iterations)

15 dB
D. Tosi, M. Olivero, G. Perrone, “Dynamic strain measurement system with ﬁber Bragg
Daniele Tosi - daniele.tosi@polito.it gratings and noise mitigation techniques”, Measurement Science and Technology, vol. 20, 2009.

FBG inscription


Matched FBGs

∫(·)


Matched FBGs

Power(strain)

∫(·)


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