SHINING A
LIGHT ON
TDLAS
Airat Amerov and Nicole Rose, Ametek, USA, evaluate how a tunable
diode laser absorption spectroscopy (TDLAS) gas analyser can effectively
measure carbon monoxide and methane in hydrogen gas.
H
ydrogen is heavily consumed in refineries, by the cryogenics
industry, and in the production of ammonia and methanol.
Petroleum refineries are both consumers of hydrogen and
large producers of hydrogen. Refinery hydrogen is often used
for hydrotreating naphtha, in hydrodesulfurisation, and in cycle oil
hydrogenation.
Traditionally, catalytic reforming has been used to produce
hydrogen as a byproduct of the production of high octane aromatic
compounds used in gasoline, with steam reforming as the dominant
production method. The hydrocarbon feed is mixed with steam at high
temperatures and then passed through catalyst filled tubes to produce
synthesis gas, which is an equilibrium mixture of hydrogen, carbon
monoxide and carbon dioxide. The synthesis gas that exits the reformer
is cooled before entering a shift converter, where more hydrogen is
produced as carbon monoxide and steam are converted to form carbon
dioxide and hydrogen.
Hydrogen gas purity is largely dependent on the purification
method, as residual methane in the hydrogen gas reduces its purity. To
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ENGINEERING
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Table 1. Composition of product hydrogen
Gas component
Wet scrubbing
PSA
Hydrogen, %
95 - 97
99 - 99.99
Methane, %
2-4
Down to 100 ppm
CO and CO2, ppm
10 - 50
10 - 50
Nitrogen, %
0-2
0.1 - 1.0
Figure 1. A calculated spectra of carbon monoxide
and methane, at a temperature of 50˚C and
atmospheric pressure in an optical path of 1 m.
reduce the amount of impurities, wet scrubbing hydrogen plants
commonly use shift converters, in combination with
carbon dioxide removal and methanation. Depending on the
temperature of the shift converter and the reformer steam to
carbon ratio, the amounts of carbon monoxide and methane at
the outlet of a shift converter can vary from 0.5 - 4% and from
2 - 8%, respectively.
In newer plants, wet scrubbing has been replaced by
pressure swing adsorption (PSA), in which adsorbent beds are
used to remove impurities. The composition of the hydrogen
product depends on the technology used. Typical compositions
are shown in Table 1.
Hydrogen management is a critical concern for refiners
because various processes require different levels of hydrogen
purity and pressure. Additionally, the control of the impurities
provides opportunities for optimising the hydrogen production
process, which may result in both time and energy savings, as
well as improvements in the quality of the final product.
Near-infrared tunable diode laser absorption spectroscopy
(TDLAS) has gained much attention for industrial applications.
This technology has three key attributes: specificity for the
analyte, high sensitivity and fast response time. The specificity is
the result of the extremely high spectral resolution achievable.
Emission bandwidths for tunable diode lasers are on the order
of 10-4 - 10-5 cm-1, which results in the ability to isolate a single
ro-vibrational transition line of an analyte species. The second
attribute of TDLAS is the ability to rapidly tune the lasers, so
techniques such as wavelength modulation spectroscopy
(WMS), which typically yield two orders of sensitivity
enhancements over a direct absorption approach, are easily
implemented. Because TDLAS is an optical technique, it offers a
very fast response time. The high specificity, sensitivity and
response time of TDLAS make it very suitable for a variety of
process measurements.
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The specificity of TDLAS for an analyte is dependent on the
sample matrix. For some applications it is difficult to find and
use an absorption line for the analyte species that is free of
interference from all other species in the sample matrix. By
combining TDLAS with chemometric strategies that have been
used in other fields of spectroscopy, new application
possibilities emerge.
The measurement of impurities – carbon dioxide, carbon
monoxide and methane – in product hydrogen gas is an
attractive application area for TDLAS. The measurement of
carbon dioxide is straightforward and has previously been
demonstrated by one of the authors in a similar sample matrix.
However, making reliable measurements of carbon monoxide in
this sample matrix is complicated by the spectral overlapping
with methane in the vicinity of 2334 nm. The use of multivariate
analysis enables resolution of overlapping responses.
The objective here is to characterise a new TDLAS-based
analyser. The analyser was set up to perform an all digital
implementation of WMS. A distributed feedback (DFB) laser,
with an emission centred at 2334 nm, was used to measure the
concentration of carbon monoxide in product hydrogen gas. A
key feature of this instrument was the use of a sealed reference
cell, which contained known amounts of the analytes, for
referencing the emission wavelength of the laser. The use of a
reference cell enabled both the ability to line lock the laser and
continuously validate the analyser performance.
The instrument
The TDLAS analyser evaluated in this work was an
Ametek 5100 HD, which was modified to operate with a
2334 nm DFB laser. Reference spectra of carbon monoxide and
hydrocarbons in the vicinity of 2334 nm, calculated from
Pacific Northwest National Laboratory (PNNL) data, is shown in
Figure 1. Of the three hydrocarbons shown in the figure, only the
methane had any substantial peak structure overlapping with
the carbon monoxide line, which would interfere with
measurements of low concentrations of carbon monoxide.
Figure 1 also demonstrates that, with increased molecular
weight of the hydrocarbon molecule, there is a significant
reduction in the absorbance spectral profile. Corresponding
2F spectra of heavier hydrocarbons results in close to zero levels
and could be neglected.
However, the carbon monoxide line close to 2334 nm has
minimal overlap with methane, as compared to other lines in
this region of the spectrum. This absorption line also has more
than two orders of magnitude higher intensity than carbon
monoxide absorption lines in the vicinity of 1570 nm.
Additionally, the line at 2334 nm has negligible spectral
interference from carbon dioxide, which is another
component of the product hydrogen gas. Scanning the laser
over a range of wavelengths containing peaks for both carbon
monoxide and methane compensates for background
interference.
A schematic representation of the analyser used for the
measurement of carbon monoxide concentrations is shown in
Figure 2. The laser produced an optical power of approximately
3 milliwatts (mW). A Herriott cell provided an optical path
length of 16 m. In addition, a fibre-optic coupled DFB laser and a
gradient refractive index (GRIN) lens based collimator were
used in this configuration. In contrast to the analyser
configurations published previously by this group, the reference
cell is in line with the sample cell.
The reason for this configuration was the absence of
available fibre-optic beam splitters for use at this wavelength.
The sample cell and the reference cell were assembled into one
optically aligned module of the analyser. This module is shown
in Figure 3. At the output of the sample cell, a plate beam
splitter, designed for 45˚ orientation, was used to divide the
optical power in a 50:50 ratio.
One beam was directed through the reference cell, which
was filled with carbon monoxide. The detection of the 2334 nm
energy required the use of extended InGaAs photodiode
detectors. The sample channel photodiode was located close
to the beam splitter. The reference cell signal was used to lock
the laser wavelength on the selected absorption line for carbon
monoxide. The reference cell contained carbon monoxide in an
optical path of 1 cm. Two nested levels of temperature control
were employed to maintain the operation of the DFB lasers at
the proper wavelength. The first level is a simple PID control
loop, which maintained the laser at a target temperature. In the
second level, the outer control loop, the spectra of the analyte
samples in the reference cells were monitored. Minor shifts in
the observed peak positions were used as a feedback signal for
the temperature set point of the inner control loop. The outer
control loop provided a fine adjustment for the inner control
loop.
While this work describes a TDLAS-based analyser
performing WMS, all aspects of the experiment were
performed with a digital implementation of the technology.
The WMS experiment was implemented by using a digitally
sampled sine function, summed with a staircase, and the
resulting signal was used to drive the tunable DFB lasers.
Specifically, the sine function was sampled at 21 discrete points,
evenly spaced across each period. This digitally synthesised
signal provided a very close approximation to an analogue
WMS experiment. Further, signals produced by the detectors
were digitised, prior to applying signal processing (e.g., phase
sensitive detection, smoothing, etc). The duration for the
discrete steps in the waveform was stored as a setup parameter
in the analyser, so the modulation/demodulation frequencies
were software selectable.
Additionally, in contrast with the common practice of
using second harmonic detection (2F), the
detection/demodulation in this instrument was performed at
the laser modulation frequency (i.e. ‘1F’ detection). Using the 1F
detection scheme enabled the analyser to normalise the
spectra, without the need for a separate measurement of the
laser power. Specifically, the magnitude of the power
envelope of the laser output was contained in the spectra
produced by 1F demodulation. After the 1F spectra were
normalised, ‘2F’ spectra were calculated as derivative of the 1F
spectrum.
Methods
Sample gases for this study were prepared using a
programmable gas mixer to blend commercial carbon
monoxide, methane and other background gases to simulate
hydrogen recycle gas of varying compositions. The
concentration ranges for carbon monoxide and methane were
set in agreement with real orders provided by customers.
Figure 2. A schematic diagram of the TDLAS
analyser for carbon monoxide measurements at low
concentration levels.
Figure 3. Sample and reference cells assembly.
Figure 4. Carbon monoxide spectra with a methane
background.
A calibration was developed for the TDLAS instrument
covering a carbon monoxide concentration range of
0 - 100 ppm and a methane concentration range of
0 - 1000 ppm balanced hydrogen. A multivariate regression was
used to establish the calibration models for carbon monoxide.
For the low concentration range of carbon monoxide, a
calibration was developed for the range of 0 - 100 ppm, with
1000 ppm methane and a balance of hydrogen. Following the
calibration, instrument performance was evaluated. The overall
measurement accuracy for carbon monoxide was established,
and corresponding limit of detection (LOD) was determined.
Results and discussion
Solving the multivariate problem was achieved with an
inverse least squares regression (P-matrix calibration). The
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Figure 5. Carbon monoxide readings for a series of
concentration challenges in the range of 0 - 100 ppm.
Figure 6. Analyser zero drift test.
Table 2. Tested analyser performance parameters
Analyser LOD,
ppm
Accuracy,
ppm
Repeatability,
ppm
Drift,
ppm
1
2.8
1.0
0.2
1.1
2
4.5
2.1
0.4
1.0
3
2
0.5
0.2
1.0
response variables used in the regression were the integrated
values observed over three spectral bands in the 2F spectra.
Specifically, a band centred at the peak in the carbon
monoxide spectrum and two additional bands were used. All
concentrations are cited by volume (i.e. ppm and % [V/V]),
and the estimates were calculated as:
3
nn Cj = Σ αj,i Ri
i=l
Where: Cj = concentration estimates for each component;
αj,i = regression coefficients; and Ri = integrated band intensities.
Example spectra collected with the 2334 nm laser are
shown in Figure 4. Each of the spectra in the figure covers a
range of 2333.4 - 2334.1 nm, and is the average of
100 separate scans. In these data, the peak amplitude and
area of the 2F carbon monoxide and methane signals were
proportional to the concentration of carbon monoxide and
methane in the cell. With increasing concentrations of
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carbon monoxide, a peak at 2333.72 nm became more
notable.
Spectra recorded for two separate concentrations of carbon
monoxide (50 and 100 ppm) and methane spectra for a
concentration of 1000 ppm are shown in Figure 4. The methane
spectral features are clearly observed on the long wavelength
side of the spectra. This background spectrum was significant in
comparison with the absorbance of the carbon monoxide at
these concentration levels. Hence, the spectra of the sample
matrix components needed to be built into the calibration
model. The regression vector that was calculated as a result of
the inverse least squares regression is also shown in Figure 4. The
calculated regression vector is analyte specific and corresponds
to regions where the analyte spectra are changing with
concentration.
The calibration procedure for the TDLAS instrument was
conducted, and a multivariate calibration model for the carbon
monoxide measurement was developed. All spectral data were
recorded for gas samples under atmospheric pressure and a
temperature of 60˚C. Spectra were recorded for a series of
different carbon monoxide concentrations, ranging from 0 - 100
ppm, with 1000 ppm methane and a balance of hydrogen.
Analysis of this application was based on the performance of
three separate TDLAS analysers, which have subsequently been
placed in the field. According to stream composition data
provided for these installation sites, the background gas
contained approximately 1000 ppm of methane in a balance of
hydrogen and corresponded to purified hydrogen gas at the
outlet of a purification unit.
Figure 5 shows analyser responses to a series of carbon
monoxide challenges over the concentration range for one of
the selected analysers. The duration for each challenge was
approximately 10 minutes, and the data were acquired at a rate of
2 seconds per measurement. A return to the background gas
baseline was also tested before and after the validation
measurements. A methane-hydrogen gas mixture was used as the
background gas. The response time (T90) was measured to be 48
seconds, which was limited by the larger volume of the sample
cell and the propagation of the gas in the sampling system with a
flow rate of 2 l/min. The results of the drift test for one of the
analysers are shown in Figure 6. Background gas was running
through analyser sample cell during the entire test. The drift was
evaluated as the difference between maximum and minimum
carbon monoxide readings recorded during the test. The results
of the validation and drift testing for all three tested carbon
monoxide analysers are shown in Table 2.
Conclusion
A new TDLAS-based analyser was evaluated for the
measurement of carbon monoxide in product hydrogen gas. A
DFB laser was used in the analyser. Scanning the laser over a
range of wavelengths sufficient to capture the overlapping
absorption lines for carbon monoxide and methane enabled the
simultaneous measurement of carbon monoxide.
The digital signal processing methods that were employed in
this system were successful in implementing a multivariate
calibration that enabled the analyser to accurately measure
carbon with accuracy of 2 ppm over a concentration range of
0 - 100 ppm range in the gas stream of 1000 ppmv of methane
balanced hydrogen.