A microprocessor and electronics package employing predictive methodology was developed to accelerate the response time of slowly responding hydrogen sensors. The system developed improved sensor response time from approximately 90 seconds to 8.5 seconds. The microprocessor works in real-time providing accurate hydrogen concentration corrected for fluctuations in sensor output resulting from changes in atmospheric pressure and temperature. Following the successful development of the hydrogen sensor system, the system and predictive methodology was adapted to a commercial medical thermometer probe. Results of the experiment indicate that, with some customization of hardware and software, response time improvements are possible for medical thermometers as well as other slowly responding sensors

Cambridge, Vivien J.

Koger, Thomas L.

English

NASA Technical Reports Server

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PREDICTIVE SENSOR METHOD AND APPARATUS
Dr. Vivien J. Cambridge, Sr. Engineer
Sverdrup Technology, Inc.
NASA John C. Stennis Space Center
Stennis Space Center, MS
Thomas L. Koger, Engineer III
Sverdrup Technology, Inc.
NASA John C. Stennis Space Center
Stennis Space Center, MS
N99- - 2 _
ABSTRACT
A microprocessor and electronics package employing predictive methodology was developed to
accelerate the response time of slowly responding hydrogen sensors. The system developed improved
sensor response time from approximately 90 seconds to 8.5 seconds. The microprocessor works in
real-time providing accurate hydrogen concentration corrected for fluctuations in sensor output resulting
from changes in atmospheric pressure and temperature. Following the successful development of the
hydrogen sensor system, the system and predictive methodology was adapted to a commercial medical
thermometer probe. Results of the experiment indicate that, with some customization of hardware and
software, response time improvements are possible for medical thermometers as well as other slowly
responding sensors.
INTRODUCTION
John C. Stennis Space Center (SSC) is NASA's "Center of Excellence" for large rocket engine
ground testing. In the course of certifying the Space Shuttle Main Engine (SSME) for flight readiness and
conducting engine improvement research and development, SSC consumes 10 million pounds of hydrogen
each year. To transport, store, and supply hydrogen for testing, SSC utilizes an extensive system of tank
trucks, barges, storage tanks, pumps, and transfer lines. While most of the hydrogen is handled in liquid
form through cryogenic storage vessels and vacuum jacketed piping, some hydrogen is also converted to
the gaseous state prior to use.
Compounding the variety of hydrogen storage and handling problems found at SSC are a wide
range of environmental conditions which make monitoring for leaks particularly difficult. Temperature
can vary from rather high, due to the near tropical summers of south Mississippi, to very low, due to
leakage of liquid hydrogen. Pressure can vary fairly dramatically in areas near the rocket engines due to
overpressure or drawdown effects during engine tests. In some facility areas, inert "purge" gases are used
to minimize the possibility of hydrogen ignition in the event of leakage. In the dynamic environment of
test operations, dramatic changes in these variable conditions can occur at any time.
The potential for severe damage or injury resulting from the ignition of leaking hydrogen
prompted NASA to pursue development of a fast, rugged and reliable hydrogen leak sensor capable of
providing accurate results through a wide range of rapidly changing environmental conditions. Although
a commercial sensor was available with good ruggedness and immunity to interferences, the sensor
responded slowly and exhibited non-linearities with fluctuations in temperature and pressure. A predictive
sensor method and apparatus was developed to obtain the fastest possible response time while taking
advantage of the slow sensor's more desireable characteristics. The concept was implemented using a
commercially available microcontroller to: 1) acquire data from hydrogen, temperature, and pressure
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sensors, 2) process the predictive algorithm, and 3) linearize the output for the measured fluctuations in
temperature and pressure. The success of this method stimulated further investigations of other
applications involving slow sensors to determine the suitability of the predictive sensor method and
apparatus for commercial development.
PREDICTIVE SENSOR METHODOLOGY AND SYSTEM DEVELOPMENT
To varying degrees, most sensors exhibit responses which lag behind the input eliciting the
response. In conventional measurement systems, this lag is carried through and registered in the systems
output device. A diagram of the conventional measurement process is shown in Figure 1. In many
applications a lagging response is tolerable. In some cases however, a very rapid or near-real time
response may be critical. In such cases, the measurer may be tempted to trade-offother desireable sensor
features such as linearity, repeatability, ruggedness, or cost in order to achieve the desired speed of
response. With the predictive sensor method and apparatus, the desirable characteristics inherent to the
slow sensor are maintained while response time is dramatically improved. An illustration of the predictive
sensor method and apparatus is provided in Fig. 2.
! !icctrical
Response j L
Step Input Lagging Response Lagging Outpul
J Mea£ul.emell 4 _ _ll.'_, r .I
"l S,en,_.,r J [ (_atput,signal ±:_- >" ('--_Read°ut "lj
:k( Amilog )
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Conditions
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A slop change in Ihe concelltration occurs,
l'hc measurement sensor reacts to the step change
The analog outpu! of the sen,vet lags behind the measured conditions
rhe lagging response is earned through to the measurement syslern's output.
Figure !. Illustration of Lagging Response in Conventional Measurement Systems
, (2) ,r4 
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Step [riptll I.agging Response
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2 lhe I/It.'a_;urclllCllt Sellsor rcacls h_ file slop change
_, Ihc alial_,_2 t,ulpul <>I lhe ,;Clls_,r lags behind lh¢ nlcasurt_'d COllttillOl;S
4 lhc laggiilg rc,,p_llSC is carried lhr_,ugh Io lhe lilCasurelllelil syr41Clll'S otllplll.
5) lhe iI/i(,;rl processor...... ctlcul tles 'tnd out puts ....lhe iclu'tl sicp (.;karlg, e occurririg durirlig, the Stlll., picot
Interval. i\ n_m-lagglng oulput is then relayed to all alarm, digit;d, or analog display device.
Figure 2. Illustration of Predictive Sensor Method and Apparatus
....
495
The slow responding hydrogen sensor, for which this method was developed, is an
electrochemical sensor originally designed for service in nuclear power plant containment vessels. With
the exception of response speed the sensor's construction for extreme ruggedness, high reliability, and
good accuracy, make the sensor ideally suited for NASA service. The sensor is comprised of a semi-solid
electrolyte with a platinum black sensing electrode and platinum reference electrode. The sensing
electrode sits behind a polymer membrane which is selectively permeable to hydrogen. The selective
permeability of the membrane is the reason for the sensor's good rejection of gases which typically
interfere with the accuracy of electrochemical sensors. However, the selective permeability of the
membrane is also the primary cause for the sensor's lagging response. Specifically, the hydrogen
molecules diffuse through the membrane at a temperature dependent rate thus limiting_the rate which the
hydrogen enters the electrochemical cell and causes a change in potential between the sensing and
reference electrodes.
Hardware and Software Implementation
An analysis of the lagging process led to the development of a mathematical model. After some
refinement using spreadsheet analysis, the model was implemented for near-real time estimation of
hydrogen concentration and linearization for fluctuations in temperature and pressure. The model was
initially coded and tested in the C language. The code was later converted to BASIC and implemented in
microcontroller firmware. Ultimately, a compact system, known as the Smart Hydrogen Sensor (SHS) was
developed to acquire and process data from the hydrogen sensor, temperature sensor, and pressure sensor.
The system configuration is shown in Fig. 3.
Sigalal Conditioning
And Analog to Digital
Conversion Board
_
RS-485
Digital Output
0-20mA
Analog ¢)utpul
Figure 3. Smart Hydrogen Sensor Hardware Configuration
The approach chosen for the development of the SHS hardware was to use proven, off-the-shelf
components. This approach eliminated the need to design new hardware and minimized testing
requirements.
The SHS is comprised of three pieces of integrated electronics components. The hardware components
;,Ire-
(1)
{2)
(3)
Microcontroller Board
Signal Conditioning Board (designed at Stennis Space Center)
RS232C/O-20mA Converter.
496
Microcontroller Board
The Microcontroller Board is built around an eight-bit microprocessor. It provides three 8-bit
parallel I/O ports (24 bits), two asynchronous serial ports (one full-duplex RS-232, one half-duplex
RS-485), eight-channel analog-to-digital converter (10-bit resolution at five volts), 96 kb of total on-board
memory (EPROM and RAM), and 1024 bits (64 bytes x I6 bits) of EPROM.
As implemented with the SHS, the Microcontroller Board uses a ROM monitor and a multitasking
BASIC compiler. Software development was carried out directly on the Microcontroller Board. The
board interfaces directly to the Signal Conditioning Board.
Signal Conditioning Board
The Signal Conditioning Board, designed at Stennis Space Center, rides piggy back on the
Microcontroller Board. The primary purpose of this board is to (1) convert input power to appropriate
levels needed by the SHS unit and (2) condition the signals from the hydrogen, pressure, and temperature
sensors prior to the digital conversion by the microcontroller.
The signal conditioning board also features a Computer Operating Properly (COP) Watchdog
timer and an eight pole switch (dual-in-line package). The eight pole switch is used to (1) configure the
SHS unit for the RS485 network and (2) place the sensor in either NORMAL or CALIBRATION operating
mode.
RS-232/0-20mA Converter
The RS232/0-20mA Converter provides a direct means for outputting an analog signal from the
SHS unit. The converter uses simple ASCII commands to control a 12-bit digital-to-analog converter. An
on board microprocessor provides the communications interface. The RS232/0-20mA Converter receives
the ASCII commands from the Microcontroller Board's RS232 serial port.
Software Description
The SHS software, written in a special version of BASIC which is unique to the Microcontroller
Board, resides as firmware in EPROM. Although this microcontroiler BASIC utilizes commands not
standard to BASIC, modifications to the software are relatively simple with an understanding of standard
BASIC commands and programming practices.
The main purpose of the firmware is to acquire temperature, pressure, and hydrogen data and use
this data to estimate the concentration of hydrogen in the environment. This estimate is updated every
second and is sent out to a 0-20mA analog channel. Furthermore, the firmware is responsible for
monitoring communications over the RS485 network. If the SHS receives a valid command or request, it
is responsible for responding with an appropriate reply.
Testing and Performance
Several iterations of prototype development and tests were completed before arriving at a software
_uad hardware configuration deemed ready for operations in the NASA environment. The prototypes were
tested in Stennis' laboratories over a wide range of temperatures and were exposed to a variety of
background gases and hydrogen concentrations. Sensors were placed in some of the most severe
operational enviromnents imaginable, including the rigors of actual rocket engine firings, and were
exposed to cryogenic fluids, saturated oxygen vapors, and heavy water deluge sprays.
497
Final testing results showed the sensor response to environmental changes was more linear with
actual response time increased by a factor of 10. For comparison, sensor response time at 68*F to a 90%
step change in H 2 concentration without use of the predictive algorithm was 1.5 minutes. Response time
with the predictive method was significantly shortened to 8.5 seconds.
Additional software added to the system enables menu-driven operation, calibration and
maintenance of the system's computer which reduces maintenance cost and ensures uniformity in system
operations. Benefits of the Smart Hydrogen Sensor are: 1) speed of response, 2) accuracy, 3) reliability, 4)
ruggedness, 5) ease of operation, and 6) flexibility.
APPLICATION STUDY - SMART THERMOMETER FEASIBILITY
With the successful application of the predictive hydrogen detection system, it followed that slow
responding commercial measurement systems might benefit from this development. Further
investigations were thus initiated to determine if the Smart Hydrogen Sensor technology could be readily
applied to similar technological difficulties within the commercial sector. To determine viability, a test
was developed using a leading brand medical-type electronic thermometer mated with the SHS signal
processing hardware and software.
Hardware and Software Design and A_sembly
Testing of the commercial thermometer system showed the normal response time to be between 25
and 30 seconds. Since the analog signal oftbe probe was different from the hydrogen sensor, a custom
analog signal conversion circuit was designed and fabricated. The probe and custom circuit were then
interfaced with an SHS programmable microcontroller and digital to analog converter. The
microcontroller's BASIC software used for the SHS predictive algorithm was modified to process the
temperature data from the thermometer probe.
Upon successful test of the software, the analog and digital electronics were assembled and
calibrated using a precision calibration water bath. The method is similar to the ASTM standard for
calibration of electronic medical thermometers.
Preliminary_ Test and Evaluation
Since medical practice requires the use of plastic sleeves on the thermometer probe for sanitary
purposes, a problem was foreseen with the predictive method in that the individual probe covers could
randomly alter the time constant of the temperature measurement assembly. To test the breadboard system
and the variable time constant hypothesis, a series of temperature measurements were taken in a controlled
temperature bath using different probe covers. Final temperature results obtained with different probe
covers were found to be invariable, but, the time of response to reach the final temperature was tbund to
vary by several seconds. The variation in response time necessitated the entry of a new time constant ira
the software to obtain an accurate prediction of the final temperature. The predictive method would be
_ro_Jcn_at_c in a medical application where acctH acy is critical without an accurate value for the
probe/temperature probe assembly time constzmt.
498
Modification.of Predictive Method
A concept was therefore developed for solving for a unique time constant of the assembly
"on-the-fly" by analyzing the first few seconds of measurement data. The method was developed using the
data available from controlled temperature bath experiments. While these predictions from controlled
experiments yielded promising results, viability under "clinical" conditions remained in question• Further
investigations were then conducted using temperature data from volunteers in the laboratory. Three to
four measurements were obtained from each volunteer using a different probe cover for each measurement.
Selected data representative of the testing is discussed below.
_Rc,s_uM
The data provided in Fig. 4 below shows the raw output of the temperature probe, the standard
predictive method (as employed by the SHS), and the modified predictive method. For Fig. 4, the probe
was inserted approximately 3 to 4 seconds after starting data acquisition. As can be seen, the standard
prediction reaches the final temperature value within approximately 1 second. However, the standard
prediction increases above the actual measured condition as a result of an error in the time constant
assumed for the probe cover / temperature probe assembly used. This effect may be the result of minor
differences in the probe cover or in the way the probe cover is attached to the probe.
Predictive Medical Thermometpy Test
I
7 " . ?/: • !
,, ," ,
7
5 11) 15 2O 25
Time
Temperature Probe Output
"On-the-Fly" Predictive Output
_ _ Standard Predictive Output
3O
Figure 4. Test of Predictive Method in Medical Thermometry Application
499
The "on-the-fly" prediction uses temperature data from the first few seconds to calculate a time
constant value unique to the probe in use. As seen in Fig. 4, this procedure produces a initial lag until the
microcontroller has accumulated sufficient data to compute the time constant and final value, based on the
"on-the-fly" time constant.
While a technique was implemented to solve the unique time constant problem associated with the
probe covers, the data indicate that the technique does not improve the predictive results as it is highly
sensitive to small nuances in the raw data. The use of thinner, more uniform, or more conductive probe
covers might reduce the effect of differences in the manufactured probe covers on the time constant. This
remains an area for further investigation.
More positively, the predictive method could prove beneficial for less critical applications such as
household thermometers which require no sleeve covers. In such applications it is likely that the
relationship between cost considerations and accuracy issues would shift, and more emphasis be placed on
the design of a low cost chip and software.
PREDICTIVE SENSOR TECHNOLOGY APPLICATIONS
The Smart Hydrogen Sensor was developed to enhance the detection of hydrogen in a variety of
gaseous atmospheres. The advanced electronics of the SHS system provide for reliable and rapid
estimation of hydrogen concentration along with enough flexibility to function in a variety of
environments. No commercial technology has been identified that can out perform the SHS in the areas of
speed, accuracy, and reliability. The greatest attr_bute of this newly developed predictive sensor
technology, however, is that it can significantly enhance the speed of response of existing sensor
technology. Faster responses can be obtained without developing a faster sensor. Application of the
predictive methodology may provide cost effective alternatives for existing sensors that are limited by
slow response times. The signal processing algorithm employed can determine in near real time the steady
state response of a normally slow sensor.
While a few shortcomings in its use in temperature measurement for critical medical applications
remain to be resolved, the technology is readily applicable and adaptable to other types of temperature
measurement systems.
500


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