International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org
ISSN 2319 - 4847
Special Issue for International Technological Conference-2014
Towards Minimal Noise Infrared Absorption
Based Gas Sensing
Suryakanta R. Patil1, Nadir Charniya2, Shivangi Chourasia3, Alok Verma4
1
VES Institute of Technology, Mumbai
1
surya_patil88@rediffmail.com,
2
VES Institute of Technology, Mumbai
2
nncharniya@gmail.com
3
S.A.M.E.E.R, IIT Bombay, Mumbai
3
shivangi7988@gmail.com,
4
S.A.M.E.E.R, IIT Bombay, Mumbai
4
alok@sameer.gov.in
ABSTRACT
In this paper, we propose an approach to develop trace gas sensor that can be used to detect Carbon monoxide (CO) gas by using
a wavelength tuned Distributed Feedback-Quantum Cascade LASER (DFB-QCL). Trace gas sensor design is based on principle
of infrared absorption spectroscopy. The characteristics of wavelength tunable DFB-QCL has been analyzed. The source is
capable of providing a wavelength tuning from 4.586 to 4.59μm where R (8), R (9), R (17) and R (18) rotational-vibrational bands
of CO gas present. We optimised the detection limit of the sensor using variable multipass gas cell. We are studing the various
noise sources present in system affects detection limit of trace gas sensor. We are improving the sensitivity and response time, and
reducing the various noise present in the gas sensor using signal processing with the help of NI LabVIEW software and hardware.
Keywords: Infrared spectroscopy, Quantum cascade lasers, Gas detection, Noise.
1. INTRODUCTION
Carbon monoxide (CO) has an important impact on atmospheric chemistry through its reaction with hydroxyl (OH) for
troposphere ozone formation and also can affect the concentration level of greenhouse gases. Furthermore, CO even at
low concentration levels is dangerous to human life and therefore must be accurately and precisely monitored it in real
time [1]. Infrared Absorption based gas sensing using Multi-pass Cell techniques provides high accuracy and detection
limit ranges from part per billion (ppb) and part per million according to detection technique applied and gas spectral
lines. Accuracy and detection limits of the chemical gases are possible due to fundamental vibrational bands in the midinfrared (3 to 24 µm regions) and selective detection due to absorption of light by rotational-vibrational transition of
these bands.
The large wavelength coverage of quantum cascaded LASER provides mid-infrared LASER absorption spectroscopy
with ultra-high resolution and sensitivity. The high quantum cascaded LASER power allows use of advanced detection
techniques improving sensing limits and decreasing complexity and size of trace gas sensor. The detection limit of
Infrared Absorption based gas sensor is limited due to various noise sources, such as, flicker noise, detector noise,
acquisition non-linearity. Our prime objective is to detect the noise sources and their methods of removal and determines
the extent to which the noise has been suppressed using LabVIEW based systems.
2.
LINE SELECTION FOR CARBON MONO-OXIDE NEAR 4.58 MICRO METER
Detection of carbon monoxide in the mid-IR around 4.58 μm, R (9), allows high sensitivity measurement, not possible
with near-IR CO sensors, and the potential for measurements with significantly shorter absorption path lengths. The
transitions in the CO fundamental band are extremely well characterized in terms of spectroscopic parameters (line
position, line strength, and line broadening parameters), which allows direct interpretation of measurements.
Organized By: Vivekananda Education Society’s Institute of Technology
International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Line Strength (cm-1/ molecule cm-2)
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ISSN 2319 - 4847
Special Issue for International Technological Conference-2014
Fig.1. Simulated spectra for CO at P= 1 atm, T= 300K using HITRAN (2008) database [2].
The fundamental rotational-vibrational bands are present near 4.58 μm, R (9). The Fig.1 shows the simulated spectra of
different isotopes of CO using HITRAN database [2].
3.
LASER ABSORPTION SPECTROSCOPY
LAS (LASER Absorption Spectroscopy) of target gas species, which is based on the Beer-Lambert absorption law,
effectively determines real-time gas Concentrations. Beer Lambert law given by equation (1) [3],
I(ν) = I0 · e−α(ν)·L
(1)
Where ‘I’ is the intensity of light passing through the absorbing medium, ‘I0’ is the input intensity, ‘L’ is the optical path
length, ‘ν’ is the radiation frequency, and ‘α(ν)’ is the absorption coefficient of a specific target species. The product
‘α(v).L’ represents the spectral absorbance ‘A(v)’ given by equation (2),
A(v) = α(v).L
(2)
The spectral absorption coefficient for a single rotational-vibrational transition of some specified gas ‘g’ can be written
as,
α(ν) = P χi Si(T) Φi (v)
(3)
Where P [atm] is the pressure of the medium, Si (T) [cm-2 atm-1] is the line strength, Φi (v) [cm-1] is the lineshape function,
‘χi’ is the mole fraction of the absorbing species, and the L[cm] is the path length through which the radiation passes.
Hence the spectral peak absorbance for a single rotational-vibrational transition of gas can be written as:
A (v)peak= P χi Si(T) L Φi (v)peak
(4)
Where Φi (v)peak is the peak value of the lineshape function.
There are three type of lineshape function Gaussian lineshape function, Lorentzian lineshape function, Voigt lineshape
function.
4.
EXPERIMENTAL SETUP FOR WAVELENGTH TUNING OF DFB-QCL
A schematic diagram for Wavelength tuning of DFB-QCL depicted in Fig.2. A distributed feedback Quantum Cascade
LASER (QCL) operating near 4.58 μm (HHL-11-28, AdTech optics, Inc) is employed as the light source [4]. The QCL is
mounted in ILX light wave LASER housing. A TEC (thermo electrically cooled) temperature controller (HamamatusC11330-01) [5] is used to tune and control the LASER temperature which is driven by a regulated DC power supply
(L3205) of 24 V and 8A capable of providing a tuning from 4.586 to 4.598 μm.
The QCL is driven by a high compliance LASER diode current source (ILX LDX-3232) of 15V and 4A current [6]. The
variable length multi-pass cell; path length varies from 1 to 16 m in steps of 1m. Multi-Pass cell is connected to Nitrogen
Organized By: Vivekananda Education Society’s Institute of Technology
International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org
ISSN 2319 - 4847
Special Issue for International Technological Conference-2014
gas cylinder and vacuumed pump for analyzing results of detection. The transmitted output is coupled to the spectrum
analyzer (Bristol-721) [7] for analyzing the spectra near the desired wavelength.
LASER Diode
Current
Source
PC
DFB-QCL
IR Source
Multi-Pass
Gas Cell
TEC
Temperature
Controller
CO Gas
Spectrum
Analyzer
Fig.2. A block diagram for Wavelength Tuning of DFB-QCL LASER.
Power (Linear)
4.1 Result of Wavelength tuning of DFB-QCL
The temperature of the QCL is changed in steps of 2 oC and the wavelength is monitored by using spectrum analyzer. The
wavelength tuning is found to be 0.46 nm per oC. Fig.3. and Fig.4. depicts the variation of wavelength on increasing
temperature of QCL. The wavelength obtained is 4587.60 nm at 18 oC, 4588.21 nm at 20 oC.
Wavelength (nm)
Power (Linear)
Fig.3. Plot between wavelength and intensity, peak wavelength of 4587.60 nm at T= 18 oC
Wavelength (nm)
Fig.4. Plot between wavelength and intensity, peak wavelength of 4588.21 nm at T= 20 oC
5.
EXPERIMENTAL SETUP FOR DETECTION OF CO GAS
For detection of CO gas 4587 nm wavelength is selected, where R(9) transition of carbon monoxide gas is present and
DFB-QCL is tuned at 4587 nm wavelength. The output of the QCL is coupled through Chopper (MC1F10) [8] to the
variable length multi-pass cell; path length varies from 1 to 16 m in steps of 1m.
Organized By: Vivekananda Education Society’s Institute of Technology
International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org
ISSN 2319 - 4847
Special Issue for International Technological Conference-2014
NI USB
6351
LASER
Diode
Current
MCT
Detector
PC
Source
DFB-QCL
IR Source
TEC
Temperature
Chopper
Multi-Pass
Gas Cell
Beam
Splitter
Spectrum
Analyzer
Mass Flow
Meter
Controller
CO Gas
Fig.5. Block diagram for detection of CO gas.
Multi-Pass cell is connected to CO gas cylinder and vacuumed pump for analyzing results of detection of CO gas at
different atmospheric pressure and different CO gas concentration. As light passes through a gas cell, fragments of the
light energy will be absorbed by the gas molecules resulting in distinctive absorption bands in the absorption spectrum
which enables recognition of the chemical species. The transmitted output was coupled through Beam Splitter to the
spectrum analyzer (Bristol-721) [7] for analyzing the spectra near the desired wavelength and MCT (PVI-4TE-5) [9]
detector of operating wavelength 5µm. MCT (PVI-4TE-5) detector signal is acquire using NI USB 6351 [10] hardware
and further signals are processed by NI LabVIEW software. A block diagram for detection of CO gas is shown in Fig.5.
We optimized the variable Multipass gas cell and achieved 62 ppb detection limit for CO gas. We now are aiming to
reduce the detection limit below 10 ppb by eliminating various noises present in the system.
6.
NOISE CONSIDERATION
Various Noise sources in mid infrared region significantly reduce the selectivity of concentration measurements, such as,
non-linearity in data acquisition, detector noise, other gases contributing to a broad absorption spectrum, electronic base
line fluctuation. This section describes way to reduce these noise sources.
6.1 Optical Detector Noise
Optical Detector Noise creates errors (Thermally excited current carriers) in the signal. To reduce optical detector noise
high power signals are require. High power signal suppress background fluctuations, which are unrelated to the laser
radiation, such as, electronic noise or excitation of the detectors by stray radiation [11].
6.2 White Gaussian Noise
The White Gaussian Noise distribution follows a probability density function (PDF) given by equation (5):
f (x, µ, σ) = (1/ σ 2π) exp ((x-µ)2/2.σ2)
(5)
Where ‘σ’ is the standard deviation and ‘μ’ is the mean. When averaging a Gaussian distribution, the sample set size
determines the sample standard deviation and narrows the possible region of the true mean. The sample standard
deviation decreases as a function of √Hz until the other noise sources dominate. Shot noise is created due to random
variation in the rate at which charge carriers are generated and combine. This noise can be reduced by keeping
amplification bandwidth as narrow as possible [11].
6.3 Johnson Noise
Johnson noise is generated by thermal fluctuation in semiconductor material. It is sometimes called as Thermal Noise. It
results from random motion of electrons. In random motion, electrons collide with each other resulting in small current.
The sum of all these current over long period is zero but for small interval it creates Johnson Noise. Johnson Noise can
be reduce by proper cooling of detector.
Organized By: Vivekananda Education Society’s Institute of Technology
International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org
ISSN 2319 - 4847
Special Issue for International Technological Conference-2014
6.4 Gas Absorption Spectrum
Some Gas species have spectral absorption line in the same wavelength as the desire Gas spectral line generating Gas
Absorption Spectrum base line fluctuation. To reduce Gas Absorption Spectrum base line fluctuation is to select
interference free absorption line and pressure broadening should be reduced. One method to normalize the baseline is to
perform a baseline fit to the wings of the spectrum where the absorption of the target gas is zero [11].
6.5 Single-Pulse and Pulse-to-Pulse Fluctuations
In LASERs due to timing jitter, temperature drift, electronic noise, vibration of optical element causes identical LASER
pulses to be different. When the PDFs of these sources are convoluted, the final statistical distribution is close to a
Gaussian distribution (central limit theorem). Thus, a more efficient reduction of noise is accomplished via an increase in
pulse rate or an increase in the number of spectral averages [11].
6.6 Acquisition Noise
Timing jitter is another type of acquisition noise, which is important in synchronous detection schemes. With narrow
detected pulses, the slope of the signal is large; therefore, if the acquisition clock has a large amount of jitter, the noise
will increase. This type of noise is minimized by averaging of a larger number of pulses. However, stable timing sources
are available, and as long as the jitter is much less than the width of the detected pulse, the jitter acquisition noise will be
minimal [11].
7.
SIGNAL PROCESSING FOR NOISE REDUCTION
The raw data is collected from MCT detector and data is acquired using NI USB 6351. Every chemical species has its
own unique absorption spectrum. The presentation of the absorbed radiation at each wavelength, as a function of
wavelength, is called absorption spectrum. Spectral analysis is useful for resolving the absorption spectrum of CO. The
data recorded is never the true spectrum; rather, it is modified by every optical element along the light path, including
lenses, the detector. Each of these elements has its own spectral response. A spectrum recorded with these components
will include their instrumental artifacts. The spectra should be intensity normalized to remove the instrumental
contribution. In final stage recorded absorption spectra is to be analyzed to detect the CO absorption line. The future
work is to reduce above mentioned noise using different signal processing technique in NI software and to improve the
response time of system.
Fig.4. Flow diagram for detection of CO.
8.
CONCLUSION
Experiments were conducted to detect CO trace using QCL. The detection limits were optimized using Multipass gas
cell. Further the various noises were studied to improve the sensitivity of the instrument. Theoretical analysis of all noise
present and ways to reduce these noises in absorption spectroscopy is studied and analyzed. The further work is to
improve the detection limit of system by modifying NI hardware and Lab view software, so as to achieve sensitivity up to
10 ppb (part per billion).
Organized By: Vivekananda Education Society’s Institute of Technology
International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org
ISSN 2319 - 4847
Special Issue for International Technological Conference-2014
REFERENCES
A. Krier; H. H. Gao; V. V. Sherstnev and Y. Yakovlev, “High power 4.6 μm light emitting diodes for CO
detection”, Applied Physics, 32, 1-5, 1999.
[2] “Spectral Analysis”, available at: www.cfa.harvard.edu/hitran/, (Accessed: 2013).
[3] Shivangi Chaurasia, Niyati Chetwal, Indrajit Bairagi, Alok. J. Verma, “QCL based direct absorption for finding the
detection limit of CO trace gas sensor”, Fourth International Conference on Perspectives in Vibrational
Spectroscopy, May, 2013
[4] “DFB-QCL Laser HHL 11-28” available at: http://www.atoptics.com, (Accessed: 2013).
[5] “TEC Temperature Controller Hamamatus-C11330-01” available at: http://www.hamamatsu.com/resourcses /pdf /
lsr/QCLE.pdf, (Accessed: 2013).
[6] “Laser Driver Current Source ILXLDX3232” available at: http://www.boselec.com/products/documents/ILXLDX
3232powersup, (Accessed: 2013).
[7] “spectrum analyzer (Bristol-721)”, http://www.bristol-inst.com/products-and-services/products/721-series laserspectrum-analyzer.htm, (Accessed: 2013).
[8] “Mass Flow Controller” available at: http://www.thorlabs.com/thorproduct.cfm?partnumber= MC1F10, (Accessed:
2013).
[9] “MCT (PVI-4TE-5)” available at:, http://boselec.com/products /VigocatalogWWW4-23-10.pdf, (Accessed: 2013).
[10] “LabVIEW Function and VI Reference Manual”, National Instruments, www.ni.com/pdf/manuals321526b.pdf,
(Accessed: 2013).
[11] Stephen G. So, Gerard Wysocki, J. Patrick Frantz, and Frank K. Tittel, “Development of Digital Signal Processor
Controlled Quantum Cascade LASER Based Trace Gas Sensor Technology”, IEEE sensors journal, vol. 6, no. 5,
1057-1067, October 2006.
[1]
Organized By: Vivekananda Education Society’s Institute of Technology
International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org
ISSN 2319 - 4847
Special Issue for International Technological Conference-2014
AUTHORS
Suryakanta R. Patil was born on 26 February 1988. She received the Bachelor of Engineering degree
in Electronics and Telecommunication from D. N. Patel College of Engineering, Shahada, India, in 2009.
Currently, she is pursuing the Master of Engineering degree in Electronics and Telecommunication from
Vivekanand Education Society’s Institute of Technology, Mumbai, India. She is doing Master of
Engineering project from SAMEER an R&D institute, Govt of India, Mumbai. She has 3 years of
teaching experience and her interests of area are signal processing and optics.
Nadir N. Charniya was born on September 30, 1966. He received the Master of Engineering degree in
electronics from Victoria Jubilee Technical Institute, Mumbai, India, in 1995 and the Ph.D. degree in design
of intelligent sensors using a neural network approach from Sant Gadge Baba Amravati University,
Amravati, India, in 2010. He has about 24 years of teaching experience. He is currently working as a
Professor, Department of Electronics and Telecommunications Engineering, VES Institute of Technology,
Chembur, Mumbai, India. He has papers published in refereed international journals and international
conference proceedings. He has chaired various conferences and delivered expert talk on signal processing
techniques and their applications at various engineering colleges. His areas of interest include intelligent
sensors and systems, neuro-computing techniques, signal processing, and their applications. Dr. Charniya
is a member of the Institute of Electronics and Telecommunication Engineers, the Indian Society for
Technology in Education, India, International Association of Computer Science and Information
Technology. He is recipient of various research and laboratory development grants from AICTE, New Delhi
and Universities. He has been invited to work as a reviewer for papers submitted to the IEEE transactions
and Elsevier international journals in relation to his field of interest. A project on robotics guided by him
received the First Prize and the “Maharashtra State Engineering Design Award” from the ISTE, India. His
Ph.D. work on intelligent sensors received the First Prize under Post P.G. category in the Maharashtra State
Interuniversity Research Project Exhibition “AVISHKAR—2008”.
Shivangi Chaurasiya was born on 7th September 1988. She received the Bachelor of Engineering degree in
Electronics and Telecommunication from Rajiv Gandhi Proudyogiki Vishwavidyalaya, Bhopal, India, in
2010 with first position in Branch. She received Master of Technology degree in optoelectronics from Shri
Govindram Seksariya Institute of Technology and Science, Indore (M.P), India in 2013 with first position in
Branch. She has done specialization in optical communication. She joined SAMEER an R&D institute,
Govt of India in 2013 as Research Scientist.
Alok J. Verma received his Master' in Electronic Science from Dayalbagh Educational Institute, Agra, UP
in 1989. He then taught in a state engineering college for two years. He was associated with IIT Delhi for
his research work from 1992 and received his PhD degree on Optoelectronics in 1997. He joined
SAMEER an R&D institute under Ministry of Communication & IT, Govt of India in 1997 as Scientist. He
has handled many projects in the areas of Development of Optical components and Photonics Packaging.
His current research interests are Laser Spectroscopy for Space, Environmental monitoring, Homeland
Security and Healthcare Health Care applications.
Organized By: Vivekananda Education Society’s Institute of Technology