The Space Program and military use large quantities Hydrazine (Hz) and monomethyl hydrazine (MMI-I) as rocket propellant. These substances are very toxic and are suspected human carcinogens. The American Conference of Governmental Industrial Hygienist set the threshold limit value to be 10 parts per billion (ppb). Current off-the-shelf portable instruments require 10 to 20 minutes of exposure to detect 10 ppb concentration. This shortcofriing is not acceptable for many operations. A new prototype instrument using a gas sensor array and pattern recognition software technology (i.e., an electronic nose) has demonstrated the ability to identify either Hz or MM}{ and quantify their concentrations at 10 parts per billion in 90 seconds. This paper describes the design of the portable electronic nose (e-nose) instrument, test equipment setup, test protocol, pattern recognition algorithm, concentration estimation method, and laboratory test results

Brooks, Kathy B.

Griffin, Tim P.

Linnell, Bruce R.

Peterson, Barbara V.

Young, Rebecca C.

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A Portable Electronic Nose.
For Hydrazine and Monomethyl Hydrazine Detection 
Rebecca C. Young, Bruce R. Linnell, Barbara V. Peterson, Kathy B. Brooks, Tim P. Griffin 
Applied Chemistry Laboratory, NASA Kennedy Space Center, Florida 32899 
Abstract 
The Space Program and military use large quantities Hydrazine (Hz) and monomethyl hydrazine (MMI-I) 
as rocket propellant. These substances are very toxic and are suspected human carcinogens. The 
American Conference of Governmental Industrial Hygienist set the threshold limit value to be 10 parts 
per billion (ppb). Current off-the-shelf portable instruments require 10 to 20 minutes of exposure to 
detect 10 ppb concentration. This shortcofriing is not acceptable for many operations. A new prototype 
instrument using a gas sensor array and pattern recognition software technology (i.e., an electronic nose) 
has demonstrated the ability to identify either Hz or MM}{ and quantify their concentrations at 10 parts 
per billion in 90 seconds. This paper describes the design of the portable electronic nose (e-nose) 
instrument, test equipment setup, test protocol, pattern recognition algorithm, concentration estimation 
method, and laboratory test results. 
Keywords: Electronic nose, space program, hypergolic fuel, pattern recognition, classification 
Introduction 
An electronic nose' (e-nose) consists of an array of non-specific vapor sensors. In general, the sensor 
array is designed such that each individual sensor responds to a broad range of chemicals, but'with a 
unique sensitivity relative to the other sensors. Different sensor types also have different analytic 
performances - for example, some sensors are more sensitive to specific vapors, while others are less 
prone to drift due to changes in ambient conditions (e.g., temperature, RI-I, pressure). Chemical 
identification is achieved by comparing the sensor response pattern of an unknown vapor to previously 
established patterns of known vapors: Many commercial e-noses can be trained to provide a level of 
quality for flavors and food products, diagnosis of certain diseases, detection of chemical spills, and other 
applications; however, none can quantify the concentrations. NASA at Kennedy Space Center (KSC) 
has assessed the sensitivity of several commercially available and developing e-noses. One very sensitive 
e-nose has been further developed as a hand-held instrument that is not only capable of identifying Hz or 
IvtN'[H vapors but also quantifying their concentrations at the 10 ppb level in 90 seconds. The hand-held 
instrument uses rechargeable battery that can last for 8 hours of continuous operation. It also uses a Palm 
Pilot instead of a laptop computer for reducing size and faster initial setup. The prototype unit has 
completed the lab test and is being field tested as a personnel safety monitor. 
Approach 
A literature and market search for available e-noses was performed to identify instruments suitable for 
these applications. A number of compact commercial instruments were available in a moderate price 
range. In addition, several intruments that were not yet commercially available but were in an advanced 
Approved for public release, distribution is unlimited. 
This work performed.under contract NASA1003OQ6 with John F. Kennedy Space Center.
stage of development were considered. A short series of tests were conducted to determine whether or 
not a specific instrument could meet the required sensitivities for HzJMIMH detection. One instrument 
that performed most favorably was tested further and pattern recognition and concentration prediction 
software were developed for it to achieve near 100% correctness in identification and 95% accuracy in 
concentration prediction. 
Experimental 
VaDor Generation—Calibrated Standards 
Test vapors were generated using permeation devices (PD) and ovens (Kintek Model 360), as shown in 
Figure 1. The PDs were maintained at a constant temperature and were purged continuously with dry 
nitrogen at 100 cc/mm. This gas stream was blended with l.9L/min of dry clean air to generate 2.0 L/min 
of the vapor. Flows were verified prior to tests using flow meters (SKC Accuflow). In the "Zero" mode, 
the vapor stream through the PDs was not mixed with the I .9L/min air stream, but rather was vented 
through a separate pneumatic line. This provided a source of non-contaminated air. Activation of a 
solenoid valve internal to the permeation oven allowed the purged vapor stream to mix with the clean air, 
thus generating the test vapors. 
HZ and MMH vapor concentrations were verified using an impinger filled with O.1M H2SO4 to scrub a 
known volume of vapor. The HZ or MMH concentration in the resulting solution was determined by 
coulometric titration2'. 
Vapors from the permeation ovens either were used directly or were precisely blended with air from a 
temperature (T), humidity (RH) and flow rate (F) controller (Miller-Nelson Model HCS-40). Dilution 
factors up to 25 were conveniently obtained. Three ranges of RH values were typically used in testing—
low (50%), medium (70%), and high (85%). 
Earlier work has shown that stainless steel and other materials are incompatible with HZ or MMH vapors, 
especially at low concentrations 4 . The use of stainless steel tubing and fittings was kept to a minimum. 
All pneumatic lines were either Teflon or Bev-a-Line IV® tubing, which were shown to have minimal 
effect on these vapors, even in the low-ppb range. 
!TITh1 IL 
Fiur	 ":
KAMINA i- Pen 
B-nose Instrumentation 
The various e-noses that were included in this study are provided in Table 1. MOS stands for metal-oxide 
semiconductor and PC stands for polymer composite. Either commercially available e-noses or pre-
production models were used, and had to be lightweight and portable. The extent of evaluation was based 
first upon the ability to detect Hz and MM}J vapors at the 10 ppb level. Instruments with sufficient 
sensitivity to vapors of interest were then subjected to more rigorous testing. This testing encompassed an 
assessment of the analytic performance of the instrument, an evaluation of the ability of a "trained" 
instrument to identify test vapors using the vender supplied operating system, and the in-house 
development of identification algorithms to assess the information content of the raw data. 
Table 1: E-nose instrumentation used in this study 
Instrument Manufacturer Array 
i-Pen2 Air Sense 10 MOS 
SarnDetect Daimler-Benz Aerospac 5 MOS 
Cyranose Cyrano Sciences 32 PC 
KAMINA Karisruhe Research center 38 MOS
Hvpemolic Fuels Tests 
Sensitivity Screening: In the case of HZ and MMH, the ACGIH TLV standard of 10 ppb was selected. 
KSC has adopted the ACGIH standard for its operations. Several of the technologies showed reasonable 
sensitivity to ppm levels of HZ or MMH. Of the instruments tested, only the KAMINA and i-Pen (Figure 
2) was able to respond to 10 ppb levels of HZ and MM}{ with a signal to noise ratio greater than 3. The 
responses of the KAMINA and i-Pen to 10 ppb HZ and 10 ppb MMI-I are displayed in Figures 3 and 4 
respectively.
Figure 2 Vendor units for screening test. 
IA
1.0 
0.8 
0.6 
0
0.4 
0.2 
0.0
0	 1	 2	 3	 4	 5	 6	 7	 8 
Time (minutes) 
HFIZ_MMH 
Figure 3: Response of the KAM1NA to 10 ppb of HZ and MMH. The average of the 38 sensors are plotted as RJRo 
where R is the sensor response at any point in time and Ro is the response of the sensor in clean air 
	
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-- - ... - . ..
	 .L .	 . -	 ._ -	 C4)	 NC	 INC 
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i11I11III0	 I1w-	 •j1ft...l )VNi.
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JLLJ	 !1 o.Igj1_______ 
Figure 4: Response of the i-Pen to 10 ppb of MMR (left) and Hz (right). The 10-sensor response plot, 
the sensor values, and radial plot are shown. 
Prototype Desi gn and Fabrication 
Although both KAMINA and i-Pen met the 10 ppb detection limit requirement, i-Pen was selected for 
further development. This was because the signal from the i-Pen is less noisy and the vendor was willing 
to provide the communications protocols for the development of an e-nose interface with the Palm Pilot. 
The Lithium-Ion battery was selected after much research to provide at least 8 hours of continuous 
operation for the lowest weight. The filter consists of glass wool soaked in a 50% solution of sulphuric 
acid and water, suctioned to dampness, and dried at 60 degrees C. Figure 5 shows a schematic diagram of 
the prototype unit, and Figure 6 shows some photos of the unit.
Out
In 
Figure 5 Prototype schematic 
t 
Figure 6 Prototype Unit.
Training and Validation Testinn 
The i-Pen was trained using four concentrations of Hz and MMH vapors at three RHs. The nominal 
concentrations were 10, 50, 100, and 500 ppb. The RH values were 50%, 70%, and 85%. A lab 
computer was used to acquire the training data. 
From the training data, a model was created using statistical pattern recognition algorithms developed in-
house to ensure near 100% correctness in identifying the sample as Hz or MMH. Then algorithms were 
applied to quantif' the concentration of the identified vapor. See the next section for details on the 
algorithms. 
Validation data using Hz and MMH vapors at various concentrations and %RH were then gathered using 
the Palm Pilot, as it would be used in the field. 
Vanor Identification and Quantification Algorithms 
Code was written for the Palm Pilot to implement a standard quadratic c1assifier 51 . Given class i with 
mean i, and covariance matrix , an unknown sample x is assigned to that class with the smallest value 
of
(x-p)TL(x-p) + ln(ILI) 
After a class has been selected, the square of the Mahalanobis distance51 (x4u1)T1(xp) from the example 
to the estimated class is calculated, and compared to a predetermined threshold. If the example is too far 
from the class, the example is rejected as an unknown vapor. 
To estimate the concentration, the model data was plotted to show sensor response as a function of 
concentration, as shown in Figure 7. This data was then fitted to the formula A(1 - e), also shown in 
Figure 7, to find the least-squares values for the parameters A and B. This formula was determined to be 
appropriate because the sensor response should go to zero as the concentration goes to zero, and the 
sensor response should saturate at high enough concentrations. Other formulas with similar qualities 
were tested, but this one performed the best. When presented with an unknown sample, the inverse of 
this formula was then used to convert the sensor response for each of the ten sensors into a concentration 
estimation. Many different techniques were explored to convert the ten concentration estimates into a 
single value, including taking the mean, the mean weighted by the quality of the curve fit, and multiple 
linear regression, but it turned out that the estimate of one particular sensor was consistently the best: 
Figure 7 Concentration curve fitting (one sensor)
Results 
The following trials were gathered using the prototype unit exactly as it would be used in the field. All 
tests were done at 70% RH. Note that 250 ppb vapors were not part of the training data. 
Vapor Std. Cone. 
(ppb)
Identified as Cone. Reading 
(ppb)
%error 
_______ 
_______ 
Hz 7.2
____________ 
Hz 7 -2.7 
Hz 7.2 Hz 8 11 
Hz 7.2 IvIlvffI 10 N/A 
Hz 7.2 Hz 7 -2.7 
Hz 7.2 MM}I 9 N/A 
Hz 7.2 MMH 8 N/A 
Hz 95 Hz 95 0 
Hz 95 Hz 101 6.3 
Hz 95 Hz 98 3.2 
Hz 95 Hz 102 7.4 
Hz 95 Hz 102 7.4 
Hz 95 Hz 103 8.4 
Hz 250 Hz 249 -0.4 
Hz 250 Hz 251 0.4 
Hz 250 Hz 251 0.4 
Hz 250 Hz 245 -2.0 
Hz 250 Hz 246 -1.6 
Hz 250 Hz 243 -2.8 
Hz 524 Hz 532 1.5 
Hz 524 Hz 528 0.8 
Hz 524 Hz 510 -2.7 
Hz 524 Hz 514 -1.9 
Hz 524 Hz 488 -6.9 
Hz 524 Hz 507 -3.2 
MMH 11 MIvIIH 9 -18 
MIMB 11 MMH 10 -9 
MMH 11 MMH 8 -27 
MMH 11 MMH 7 -36 
MIv[H 11 Hz 4 N/A 
MMH 11 MMH 8 -27 
MIvfH 95 MMH 84 -12 
MMH 95 MMH 84 -12 
IVIMH 95 MMH 85 -10 
MIvIH 95 MMH 87 -8.4 
MIIvIH 95 MMH 85 -10 
MIME 95 Ml\'[I-I 88 -7.4 
MIvfH 250 MIvIH 227 -9.2 
MMH 250 MMIH 228 -8.8 
MIv[H 250 MIME 229 -8.4 
IvIMH 250 MIME 225	 1 -10 
MIVEH 250 MIvIIH	 J 226	 [ -9.6
MIvIH 250 MIvIH 230	 1 -8 
MMH 461 MMH 465 0.9 
MMH 461 MIvIH 452 -1.9 
IvlII'vfH 461 MMH 466 1.1 
MMH 461 MMH 472 2.4 
MMB 461 MJvIH 456 -1.1 
MMH 461 MMH 464 0.6 
Table 2 - Validation data results 
Table 3 shows the summary statistics for each concentration. The overall classification success rate is 
92%, and the mean I%errorl is 7% (5% excluding MMII at 11 ppb). Note that errors ofjust a few ppb 
have large %errors at 11 ppb; the average error in estimation at 11 ppb for MIvIH is only 2.6 ppb. 
Vapor Std. Conc. 
(ppb)
% correctly 
identified
Mean %error 
_______________ 
________ 
Hz 7.2 50 5.5 
Hz 95 100 5.5 
Hz 250 100 1.3 
Hz 524 100 2.8 
Mlv[H 11 83 23 
MMII 95 100 10 
MMH 250 100 9 
MMII-I 461 100 1.3
Table 3 - Summary Statistics 
Summary 
A prototype portable e-nose capable of detecting 10 ppm IvfMH and Hz has been developed at KSC 
NASA, capable of detecting, identifying, and quantifying vapors in only 90 seconds, with a 2 to 8 minute 
recovery time (depending on the concentration of the exposure). This unit classifies vapors with better 
than 90% accuracy, and quantifies the concentration with an average of about 5% error, except at 10 ppb 
levels, where the erroris less than 3 ppb. 
References 
[1] H. Nagle, R. Gutierrez-Osuna, S. Schiffman, "The How and Why of Electronic Noses", WEE 
Spectrum, September 1998, pp. 22-34. 
[2] J. Wyatt, S. Rose-Pehrsson, T. Cecil, K. Crossman, N. Mehta, R. Young, "Coulometric Method for the 
Quantification of Low-Level Concentrations of Hydrazine and Monomethylhydrazine", American 
Industrial Hygiene Association Journal, June 1993, pp. 28 5-292 
[3] "Determination of Concentrations of N2H4 or MMII Vapor in Nitrogen or Air by the Columnetric 
Titration Method", Applied Chemistry Laboratory, Kennedy Space Center, internal document. 
[4] P. Taffe, S. Rose-Pehrsson, J. Wyatt, "Material Compatibility with Threshold Limit Value Levels of 
Monomethyl Hydrazine", NRL Memorandum Report 6291, October 1988. 
1973. Duda and P.E. Hart, "Pattern Classification and Scene Analysis", John Wiley&Sons, New York,
A Portable Electronic Nose for 
Hydrazine and Monomethyl 
Hydrazine Detection 
Rebecca Young, Bruce Linnell, 
Barbara Peterson, Kathy Brooks, 
Timothy Griffin 
Presented by Barry Meneghelli 
Overview 
• Background 
• Experimental setup 
• E-nose screening 
• Algorithms 
• Results 
• Conclusions
1
Need for Hypergol detection 
• Hypergolic fuels hydrazine (Hz) and monomethyl 
hydrazine (MMH) are very toxic, and are 
suspected carcinogens 
• Need to detect 10 ppb levels 
• Current technology takes 10-20 minutes to 
respond to 10 ppb 
• Current technology does not confirm that the 
detected vapor is MMH or Hz 
• Need for fast response, specific identification & 
quantification at very low concentrations 
Electronic nose 
• Typically consists of 5-60 non-specific 
vapor sensors 
• Pattern recognition software 
• Most applications are qualitative (food 
quality, medical diagnosis, etc.) 
• E-noses not normally used for quantitative 
analysis (concentration estimation)
I
2
Experimental Setup I 
• Kintek model 360 permeation devices 
provide test vapors 
• Miller-Nelson model HCS-40 controller 
provides dilution air at known temperature, 
flow rate, and humidity
F-noses tested 
• Airsense i-Pen2	 - 10 MOS sensors 
• SamDetect	 - 5 MOS sensors 
• Cyranose	 - 32 PC sensors 
• KAMINA
	
38 MOS sensors 
• MOS = metal-oxide 
semiconductor 
• PC = polymer composite 
Initial Screening 
• Only Airsense and Kamina were able to 
detect vapors at 10 ppb with acceptable 
response times (90 seconds) 
• Airsense selected for further development 
because of S/N ratio, sensor stability, and 
willingness of vendor to provide 
communications protocols to e-nose
4
4
E-noses tested

Airsense	 Kamina 
________ 
Y'jII 
_.JL-.	 ridk
5
lIT 
Out
Prototype Unit (schematic)
Prototype Unit 
IiIi.
Classification Algorithm 
• Quadratic classifier: given class iwith 
mean p, and covariance matrix L an 
unknown sample x is assigned to the class 
with the smallest value of 
(x-p1)T,(x-p1) + ln(Jl) 
• Once classified, the example may be 
rejected as an unknown vapor if it is too 
far from the assumed class. 
Concentration Estimation I 
3.5 ___________
—MMH 
--Hz 
3 
2.5	 -, - 
10	 50	 100	 150	 200	 250	 300	 350	 400	 450	 500	 550
Concentration (ppb)
'I-
7
Concentration Estimation II 
• Data fitted to A(1e) 
• Inverse formula converts each sensor 
response to a concentration estimation 
• Combine 10 estimates into one : tried 
mean, mean weighted by quality of curve 
fit, multiple linear regression, etc. 
• Best results came from using the estimate 
of one specific sensor 
Training and Validation 
• Training data: 10, 50, 100, 500 ppb at 
50%, 70%, and 85% relative humidity 
• Data acquired by lab computer, processed 
in Matlab, downloaded to Palm Pilot 
• Validation data: 10, 100, 250, 500 ppb at 
70% RH 
• Gathered by Palm Pilot
- r
8
.*	 4	 -
Results 
Vapor Std. Conc. 
(ppb)
% correctly 
identified
Mean 
%error I __________ 
Hz 7.2 50 5.5 
Hz 95 100 5.5 
Hz 250 100 1.3 
Hz 524 100 2.8 
MMH 11 83 23 
MMH 95 100 10 
MMH 250 100 9 
MMH 461 100 1.3
Conclusions 
• A portable e-nose has been developed at 
KSC NASA which can detect, identify, and 
quantify hypergolic fuels 
• lOppbthreshold 
• 90 second sample time 
• >= 90% identification success 
• <= 5% quantification %error (for >10 ppb) 
• 2-8 minute recovery time 


A Portable Electronic Nose For Hydrazine and Monomethyl Hydrazine Detection

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