- Email: [email protected]
Gas measurement systems based on IEEE1451.2 standard
Sensors and Actuators B 116 (2006) 11–16
Gas measurement systems based on IEEE1451.2 standard Antonio Pardo ∗ , Lourdes C´amara, Joan Cabr´e, Alexandre Perera, Xavier Cano, Santiago Marco, Jose Bosch Sistemes d’Instrumentaci´o i Comunicacions, Departament d’Electr`onica, Universitat de Barcelona, C/Mart´ı i Franqu´es 1, 2a. 08028 Barcelona, Spain Received 11 July 2005 Available online 19 April 2006
Abstract The design of electronic noses has a considerable dependence on the selected transducer set. There are many sensor technologies useful for be integrated in electronic noses, but every technology involves a dedicated electronics. In that sense, migration of the instrument to different sensor technologies usually involves a major redesign of the electronics and the software. The standard IEEE1451 can be a helpful tool to design smart electronic noses compatible with the possibility to use different sensors technologies without major redesigning efforts. In this work we present a solution for the development of electronic noses based on this standard and we have analyzed and studied its feasibility in this kind of systems. © 2006 Elsevier B.V. All rights reserved. Keywords: IEEE1451; Gas sensors; STIM; TEDS; Electronic noses
1. Introduction An electronic nose is an instrument basically comprised of an array of gas sensors plus a pattern recognition system. In consequence, the implementation of an electronic nose involves the integration of different chemical transducers that provide a set of basic response signals, and advanced data processing that perform the extraction of the suitable information from the transducers signals. Moreover, some of the sensors used in these devices have different working conditions and the response depends on many different variables (including environmental data) [1,2]. Actual designs are based on gas sensors arrays (plus temperature, humidity, . . . sensors) connected to data acquisitions systems via the corresponding conditioning circuitry, and a processor (Microcontroller, DSP but in most cases a PC) that controls the measurement sequence and process the data measured properly. For good performance of the instrument, the selection of the transducer technology for the gas sensor array is critical [3]. In the current state of the technique, any change in the transducers system implies changes in the design of hardware and software.
∗
Corresponding author. Tel.: +34 93 4039168; fax: +34 93 4021148. E-mail address: [email protected] (A. Pardo).
0925-4005/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.snb.2006.03.012
In order to simplify the instrumentation and to obtain more flexible designs, the IEEE1451 standard could be an interesting option. The use of this standard for electronic noses was first proposed by Distante [4] and it has been under consideration within the standardisation group (WG3) funded by European project NOSE-II. This standard defines the implementation of transducer based instrumentation splitting the system in two modules: • The Smart Transducer Interface Module (STIM) [5] carries out all the functions related with the transducers (signal conditioning, measuring sensors and drive actuators), and also contains the information about the transducers used in a normalized format in the Transducer Electronic Data Sheets (TEDS). • The Network Capable Application Processor (NCAP) [6] is the second module and has different functions: it communicates with the STIM via the Transducer Independent Interface (TII); it process the data measured by the STIM if necessary; it controls the activity of the STIM and communicates via a digital network. Researchers worldwide are working under this standard, developing prototypes of STIM and NCAP. National Institute of Standards and Technology (NIST) has implemented A Live
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A. Pardo et al. / Sensors and Actuators B 116 (2006) 11–16
Internet Demonstration of IEEE 1451 [7], University of Limerick is working in a implementation of 1451.2 with 12 bits ADC Microconverter [8], Institute of Computer information Technologies in Ukraine and NIST are developing a dynamically reprogramable NCAP [9], Southeast University in China are studying distributed measurement systems under 1451 standard [10], University of Siena and CNR of Lecce are working on IEEE1451.5 [11], and University of Barcelona is developing intelligent instruments using IEEE1451 general standard [12]. The evident interest in IEEE1451 standard comes from the interesting features and contributions that the standard can afford to the development of intelligent systems. Features as, for example Plug & Play (due to the use of TEDS), hot connection, the use of the standardized connector TII, the use of physical units in a easy way, migration between different networks types is easy due to the facilities defined by the standard in the NCAP structure. The design of electronic noses can take advantages from these features to simplify and increase its performances. For example, the system can use different gas sensors technologies (tin oxide, electrochemical, . . .) without redesigning the whole system; it is only necessary to implement the proper condition circuitry and load the TEDS information in the STIM. This paper presents and implementation of an STIM for tin oxide sensors following the 1451.2 standard. 2. 1451 based smart gas sensor array The developed STIM consist of two blocks: • A signal conditioning module. • A control module, that drives the actuators, acquires the sensor signals, and implements TEDS and the TII.
Fig. 1. Block diagram of the STIM control module.
3. STIM control module The STIM control module [5] is in charge of carrying out all the tasks defined in the IEEE1451.2 standard, but the sensor signal conditioning. We have developed this module with an ADuC812 microcontroller (that has all the resources to implement the TII, STIM channels, . . .) and two external memories, a 512 MB Flash and a 512 MB SRAM. Despite these memories seem too big, this prototype allows us to evaluate different data sets in TEDS, and study its use for electronic noses. In Fig. 1 we present a block diagram of the STIM control module. 4. STIM transducer module As it is mentioned above, the transducers in this module are:
The prototype includes: 4 Gas sensors (tin oxide). SB Series from FIS (Japan). 1 Temperature sensor (LM335, National Semiconductor). 1 Humidity sensor (HIH3605, Honeywell). 2 Digital actuators, one for an electro valve and other for an electro pump.
• 4 Tin oxide gas sensors (implies 4 analog voltage signals channels and a common actuator to drive the heaters). • 1 Temperature sensor (voltage output signal). • 1 Humidity sensor (voltage output signal). • 1 Digital actuator (to drive an electro valve). • 1 Digital actuator (to drive a pump).
In a first approach, taking into account six sensors and two actuators, we had to develop a STIM with eight channels: six analog sensors and two digital actuators. However, tin oxide gas sensors are comprised of a metal oxide semiconductor sensing element together with an integrated heater resistance to increase sensor operation temperature in order to increment sensor sensitivity. To implement this sensor technology in the STIM, the heater has been considered as another actuator but despite the prototype considers the implementation of four gas sensors, we have decided to excite the four heaters with the same signal. Therefore the system will implement nine channels with a dedicated actuator channel, called specifically heater, for heating the four sensors.
To drive the gas sensor heaters, a Pulsed Width Modulated (PWM) signal has been implemented instead of the usual continuous gas sensor power supply. This solution allows to implement electronics that optimises power consumption. In that sense, heater drivers hardware are designed for working in a exclusive bi-state mode that permits and efficient power transfer from the supply to the heater, with low dissipation in the driver. Basic sensing resistance interface is based in a half-bridge configuration. However, it has to be taken into account that the sensing resistance can take a wide range of values, covering 2–3 orders of magnitude from low operating temperature to high operating temperature. Therefore, it could be interesting to adequate the “load” resistance to the signal response in the
• • • •
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Fig. 2. Gas sensor driving and automatic selection of load resistance circuit schematic.
measurement system. To do this we have included in the design an analog multiplexer and four resistances (from 180 to 1 M) to each sensor. A software algorithm will select automatically the best resistance in each measurement. In Fig. 2 we present the schematic of the gas sensor with the driver, a MOSFET driven by the PWM signal, and the analog multiplexer that changes the load resistance of the sensor. Each multiplexer is a dual 4:1 multiplexer that is used for two sensors. The selection of the load resistance is carried out by the inputs A and B, that are controlled by the microcontroller. All the functions described in this module could be controlled by the STIM control module. But the ADuC resources are used completely by the signals and process described in the control module section. So we have decided to use a small and cheap microcontroller (Z86E08) in order to generate the required signals in this module: • PWM to the heaters. • Switching codes for the analog multiplexers that select the gain resistances. • Signals for actuators. The communication between the control module and this one is carried out via I2C. Only the analog output of sensors are connected directly to the control module. The gain resistance selection algorithm is also implemented in the control module. The interface circuitry of the humidity and the temperature sensors are quite simple because their operational output voltage range. The humidity sensor, a HIH3605 from Honeywell, is
Fig. 3. Block diagram of the STIM transducer module.
powered by constant voltage of 5 V, it generates an output voltage between 0.8 and 4.1 V and it does not need any additional device. The temperature sensor, a LM335 from National Semiconductors, only needs a 2k2 resistance between the device and the power supply. Finally, the driver for the two actuators are simply two MOSFET that act as power switches controlled by two digital outputs of the microcontroller. In Fig. 3 we present a block diagram of the STIM transducer module. 5. Implemented software and functions The STIM working procedure starts with an initialization process of variables and signals states, and the TEDS memory
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dump to the NCAP. After this sequence the program remains in a infinite loop, waiting for to possible interrupts: • NIOE signal, that indicates that the NCAP is starting a frame transfer of a function related with a specific channel. The STIM them analyzes the function sent by the NCAP and executes it. • Trigger signal, that initiates the process related with the channel trigger address defined previously by the NCAP. Both events control all possible process in the STIM, that basically are execution of IEEE1451 functions. When the process related with one event is finished, the execution returns to the waiting loop. We have implemented three types of functions: Physical Layer Communication Protocol Functions (Read byte, Write byte, Trigger detection); Link Layer Communication Protocol Functions (IEEE1451 Frame Transmission and I2 C Communication); Application Layer Functions (IEEE1451 Standard Functions, Memory Management and four specific Manufacturer’s Use Only Functions).
Fig. 4. Output voltage of the humidity sensor and relative humidity and temperature (from Honeywell).
6. TEDS and calibration Mainly we have developed the mandatory TEDS defined by the standard. That is, a Meta TEDS with information needed for the NCAP to gain access to any channel plus common information of the STIM; a Meta-identification TEDS with information to identify the STIM plus information common to all channels, and one Channel TEDS for each channel, that has the specific information of each channel to enable a proper operation. Additionally, we have included two calibration TEDS, one for the humidity sensor and other one for the temperature sensor. In the case of the humidity sensor we have given the sensor response depending on the relative humidity and the temperature. This information is provided by the sensor manufacturer and it is shown in Fig. 4. From this information, we have developed the following relation: H=
1 V − 0.8 −5 488.06 − T 6.7 × 10
(1)
However, the 1451 standard does not support arbitrary input–output relations. The standard proposes the use of multinomial functions. In order to express Eq. (1) in this format, we have to develop the temperature term in a Taylor’s series. The resulting expression in is: H = c10 [x1 − H1 ] + c11 [x1 − H1 ]T + c12 [x1 − H1 ]T 2
(2)
where cij and Hi are the coefficients that we store in the calibration TEDS for this channel, T the measured temperature, x the raw value of the voltage measured at the output of the humidity sensor, and H is the relative humidity. The use of calibration TEDS for humidity and temperature channels, allow to us not only to calibrate the sensors but also to convert raw values into its corresponding physical values.
It is important to mention that before the first use of the STIM, we have to generate the TEDS of our transducer set using a TEDS editor in a PC, and to transfer them to the Flash memory of the STIM via the TII connector. We have carried out this process using the parallel interface of the PC. After that, the system is ready to be connected to a NCAP, and it has not to be reconfigured if we do not change the transducer set. When we connect the STIM to a NCAP, this one stars a boot process (the NSDET signal of the TII is intended for this use) where TEDS are transferred to the NCAP. 7. Measures In order to carry out sensor measurements, the NCAP only has to follow the procedure defined by the IEEE1451 standard. For example, for a gas sensor (channels 1–4) the NCAP carry out the following steps: 1. Sends a Write Channel function to the desired channel in order to configure the measure. 2. Sends a Write Trigger Channel function (1–4). 3. Activate the Trigger signal. 4. Sends a Read Channel function to the channel, to read the measured data. While steps 3 and 4 had to be repeated for each measure, steps 1 and 2 only are necessary if the measure configuration changes or if we want to change channel to be measured. In Fig. 5 we present TII and STIM signals when trigger is activated (step 3). In the example we have configured channel trigger as number 3 in the step 2. We can see that the activity starts with the activation of the signal NTRIG in the TII, after that the STIM starts the measurement sequence: automatic gain of
A. Pardo et al. / Sensors and Actuators B 116 (2006) 11–16
Fig. 5. Evolution of signals in the TII and the STIM when Trigger signal is activated in order to measure a gas sensor.
the gas sensors (I2C activity in lines SDA and SCL, and signals MUXA and MUXB that changes the sensor load resistance); once the gain is fixed the ADC measures the sensor output. We can see also one of the PWM pulse, signal CALEFA. We have tested our STIM with the following measure: • • • •
Measurement: 50 s of air + 30 s of methane + 40 s of air. Methane concentration = 6000 ppm. Carrier gas: synthetic air. Sensor: FIS sensor; series SB11A This measure has been carried out with two systems:
• Data Logger: Heating the gas sensor with constant voltage = 0.9 V (standard procedure in our Lab). • STIM: Heating the gas sensor with pulsed voltage: period = 8.2 ms, pulse width = 310 s (0–4 V amplitude). Since the thermal time constant of the sensor is about 500 ms (according to the manufacturer) the sensor temperature cannot follow the PWM signal, and the thermal dynamics operate as a low pass filter for the heater signal. In Fig. 6 a comparison between both measures are presented. We can see that basically both measures have the same dynamics except and offset probably due to a sensor drift. 8. Conclusions We have developed a STIM based on the IEEE1451.2 standard to be used as a electronic nose. We have included a typical set of transducer to implement an electronic nose, the signal conditioning electronics and the control system of a STIM. We have implemented sensor and actuator channels and the associated TEDS. So the NCAP can send measurement and actuation functions to the STIM and interpret the results properly. Further work requires to study how the TEDS can be used to store information concerning the characteristics of the gas sensor and to propose how the full instrument can be calibrated.
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Fig. 6. Methane measures with a Data Logger system (black dots) and the STIM (red line). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of the article.)
An interesting option is to study the possibilities given by the multinomial calibration considered in the standard. Acknowledgments We want to acknowledge the partial funding of European project NOSE II (IST2001-32494) and Spanish project MCYT TEC2004-07853-C02-01. References [1] R. Menon, C.O. Yoon, D. Moses, A.J. Heeger, in: T. Skotheim, R. Elsenbaumer, J.R. Reynolds (Eds.), Handbook of Conductive Polymers, second ed., Marcel-Dekker, New York, 1997, pp. 27–84. [2] R.S. Hobson, A. Clausi, T. Oh, A.G. Elie, Temperature Correction to Chemoresistive Sensors in an e-NOSE-ANN System, IEEE Sens. J. 3 (4), pp. 484–489. [3] A. Pardo, S. Marco, C. Calaza, A. Ortega, A. Perera, T. Sundic, J. Samitier, Methods for sensor selection in pattern recognition, in: J.W. Gardner, K.C. Persaud (Eds.), Electronic Noses and Olfaction, 2000, IoP Publishing, 2000, pp. 83–88. [4] C. Distante, Smart interfaces for transducers, in: Proc. of the 10th International Symposium on Olfaction and Electronic Noses, Riga, June 25–28, 2003, pp. 90–91. [5] IEEE Standards Board, IEEE Standard for a Smart Transducer Interface for Sensors and Actuators-Transducer to Microprocessor Protocols and Transducer Electronic Data Sheet (TEDS) Formats, 1997. [6] IEEE Standards Board, IEEE Standard for a Smart Transducer Interface for Sensors and Actuators-Nework Capable Application Processor (NCAP) Information Model, 1999. [7] NIST IEEE 1451 Internet Demo (online): http://motion.aptd.nist.gov/ P1451/ISADemo.htm. [8] P. Conway, D. Heffernan, B. O’Mara, P. Burton, T. Miao, IEEE 1451.2: An interpretation and example implementation, in: Instrumentation and Measurement Technology Conference, 2000. Proceedings of the 17th IEEE, vol. 2, May 1–4, 2000, pp. 535–540. [9] R. Kochan, K. Lee, V. Kochan, A. Sachenko, Development of a dynamically reprogrammable NCAP, in: IMCT 2004 Instrumentation and Measurement Technology Conference, Italy, 2004. [10] G. Song, A. Song, W. Huang, Distributed measurement system based on network smart sensors with standardized interfaces, Sens. Actuators A 120 (2005) 147–153.
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[11] N. Ulivieri, C. Distante, T. Luca, S. Rocchi, P. Siciliano, IEEE1451.4: A way to standardize gas sensor, Sens. Actuators B 114 (2006) 141–151. [12] L. Camara, O. Ruiz, A. Herms, J. Samitier, J. Bosch, Automatic generation of intelligent instruments for IEEE1451, Measuremnt 35 (2004) 3–9.
Biographies Antonio Pardo received his diploma in physics 1991 and his PhD in 2000 from the University of Barcelona. During his PhD studies he worked in system identification with applications in gas sensor systems. Now is professor at the Electronics Department of the Physics Faculty in University of Barcelona. His research interest focused on signal processing for gas sensors, pattern recognition and smart sensors. Lourdes C´amara received her diploma in 1990 from the Universitat de Barcelona. Master in Microelectronics in the Centro Nacional de Microelectronica (CNM) in Barcelona in 1993. She get the investigation sufficiency in the micro and optoelectronics physiscs program in the Universitat de Barcelona in 1994. She has been working as a professor in the same university since 1991 and at the same time developing different projects on different subjects: portable alcoholimeters, tactile sensors, intelligent instrumentation for transducers within different communication networks. She is developing her PhD in this last subject focused mainly in the application for ethernet. Actually, she is leading the research department of a private company. Moreover, this scientific motivation in her life, the most important thing are her two wonderful sons and climbing mountains. Joan Cabr´e received his diploma in electronics engineering in 2003. He developed research on IEEE1451 as a final year project. Alexandre Perera was born in Barcelona, Spain, in 1973. He received a degree (1996) and a PhD (2003) in physics from University of Barcelona
and a degree in electrical engineering (2001) from the same university. From 2003 to 2005, he stayed as a postdoctoral research associate at the Texas A&M University. In this period, he worked on intelligent signal processing for power systems within an EPRI sponsored project at PSAL Laboratory. In the same period he also worked at PRISM Laboratory in artificial olfaction related research. His research activity is focused on pattern recognition algorithms with applications ranging from chemical sensors to power systems, embedded systems and intelligent instrumentation. Xavier Cano, born in Vic. (Spain), in 1969. He received a diploma in industrial electronics in 1994 from the Universitat Polit`ecnica de Catalunya, a degree in electronic engineering in 2000 from the Universitat de Barcelona and a master degree from the same university in 2002. Since 2001, he is assistant professor at the UB and joined the ISPlab research group at the UB in 2005. His research work is focused on smart sensors instrumentation and RF ID systems technnolgy. Santiago Marco received his diploma in physics in 1988 and his PhD in physics in 1993 from the University of Barcelona. During his PhD studies he developed a novel micromachined pressure sensor for biomedical applications based in vertically structured silicon membranes. Since 1995, he is associate professor at the University of Barcelona. His research interests focuses on the design, simulation and modelling of micromachined sensors and actuators as well as on the dynamic modelling of chemical sensor arrays. Jose Bosch received his diploma in physics in 1987 and his PhD in physics in 1993 from University of Barcelona and master on materials science from University of Barcelona (1990). During his PhD studies he worked on the optimization of electrical and optical novel techniques for the characterization of heterostructures. Since 1995, he is an associate professor at the University of Barcelona. His research interest focuses on microprocessors and microcontrollers in the field of intelligent instrumentation. He also love to climb big mountains and actually he is organizing an expedition to Himalaya.
Gas measurement systems based on IEEE1451.2 standard Antonio Pardo ∗ , Lourdes C´amara, Joan Cabr´e, Alexandre Perera, Xavier Cano, Santiago Marco, Jose Bosch Sistemes d’Instrumentaci´o i Comunicacions, Departament d’Electr`onica, Universitat de Barcelona, C/Mart´ı i Franqu´es 1, 2a. 08028 Barcelona, Spain Received 11 July 2005 Available online 19 April 2006
Abstract The design of electronic noses has a considerable dependence on the selected transducer set. There are many sensor technologies useful for be integrated in electronic noses, but every technology involves a dedicated electronics. In that sense, migration of the instrument to different sensor technologies usually involves a major redesign of the electronics and the software. The standard IEEE1451 can be a helpful tool to design smart electronic noses compatible with the possibility to use different sensors technologies without major redesigning efforts. In this work we present a solution for the development of electronic noses based on this standard and we have analyzed and studied its feasibility in this kind of systems. © 2006 Elsevier B.V. All rights reserved. Keywords: IEEE1451; Gas sensors; STIM; TEDS; Electronic noses
1. Introduction An electronic nose is an instrument basically comprised of an array of gas sensors plus a pattern recognition system. In consequence, the implementation of an electronic nose involves the integration of different chemical transducers that provide a set of basic response signals, and advanced data processing that perform the extraction of the suitable information from the transducers signals. Moreover, some of the sensors used in these devices have different working conditions and the response depends on many different variables (including environmental data) [1,2]. Actual designs are based on gas sensors arrays (plus temperature, humidity, . . . sensors) connected to data acquisitions systems via the corresponding conditioning circuitry, and a processor (Microcontroller, DSP but in most cases a PC) that controls the measurement sequence and process the data measured properly. For good performance of the instrument, the selection of the transducer technology for the gas sensor array is critical [3]. In the current state of the technique, any change in the transducers system implies changes in the design of hardware and software.
∗
Corresponding author. Tel.: +34 93 4039168; fax: +34 93 4021148. E-mail address: [email protected] (A. Pardo).
0925-4005/$ – see front matter © 2006 Elsevier B.V. All rights reserved. doi:10.1016/j.snb.2006.03.012
In order to simplify the instrumentation and to obtain more flexible designs, the IEEE1451 standard could be an interesting option. The use of this standard for electronic noses was first proposed by Distante [4] and it has been under consideration within the standardisation group (WG3) funded by European project NOSE-II. This standard defines the implementation of transducer based instrumentation splitting the system in two modules: • The Smart Transducer Interface Module (STIM) [5] carries out all the functions related with the transducers (signal conditioning, measuring sensors and drive actuators), and also contains the information about the transducers used in a normalized format in the Transducer Electronic Data Sheets (TEDS). • The Network Capable Application Processor (NCAP) [6] is the second module and has different functions: it communicates with the STIM via the Transducer Independent Interface (TII); it process the data measured by the STIM if necessary; it controls the activity of the STIM and communicates via a digital network. Researchers worldwide are working under this standard, developing prototypes of STIM and NCAP. National Institute of Standards and Technology (NIST) has implemented A Live
12
A. Pardo et al. / Sensors and Actuators B 116 (2006) 11–16
Internet Demonstration of IEEE 1451 [7], University of Limerick is working in a implementation of 1451.2 with 12 bits ADC Microconverter [8], Institute of Computer information Technologies in Ukraine and NIST are developing a dynamically reprogramable NCAP [9], Southeast University in China are studying distributed measurement systems under 1451 standard [10], University of Siena and CNR of Lecce are working on IEEE1451.5 [11], and University of Barcelona is developing intelligent instruments using IEEE1451 general standard [12]. The evident interest in IEEE1451 standard comes from the interesting features and contributions that the standard can afford to the development of intelligent systems. Features as, for example Plug & Play (due to the use of TEDS), hot connection, the use of the standardized connector TII, the use of physical units in a easy way, migration between different networks types is easy due to the facilities defined by the standard in the NCAP structure. The design of electronic noses can take advantages from these features to simplify and increase its performances. For example, the system can use different gas sensors technologies (tin oxide, electrochemical, . . .) without redesigning the whole system; it is only necessary to implement the proper condition circuitry and load the TEDS information in the STIM. This paper presents and implementation of an STIM for tin oxide sensors following the 1451.2 standard. 2. 1451 based smart gas sensor array The developed STIM consist of two blocks: • A signal conditioning module. • A control module, that drives the actuators, acquires the sensor signals, and implements TEDS and the TII.
Fig. 1. Block diagram of the STIM control module.
3. STIM control module The STIM control module [5] is in charge of carrying out all the tasks defined in the IEEE1451.2 standard, but the sensor signal conditioning. We have developed this module with an ADuC812 microcontroller (that has all the resources to implement the TII, STIM channels, . . .) and two external memories, a 512 MB Flash and a 512 MB SRAM. Despite these memories seem too big, this prototype allows us to evaluate different data sets in TEDS, and study its use for electronic noses. In Fig. 1 we present a block diagram of the STIM control module. 4. STIM transducer module As it is mentioned above, the transducers in this module are:
The prototype includes: 4 Gas sensors (tin oxide). SB Series from FIS (Japan). 1 Temperature sensor (LM335, National Semiconductor). 1 Humidity sensor (HIH3605, Honeywell). 2 Digital actuators, one for an electro valve and other for an electro pump.
• 4 Tin oxide gas sensors (implies 4 analog voltage signals channels and a common actuator to drive the heaters). • 1 Temperature sensor (voltage output signal). • 1 Humidity sensor (voltage output signal). • 1 Digital actuator (to drive an electro valve). • 1 Digital actuator (to drive a pump).
In a first approach, taking into account six sensors and two actuators, we had to develop a STIM with eight channels: six analog sensors and two digital actuators. However, tin oxide gas sensors are comprised of a metal oxide semiconductor sensing element together with an integrated heater resistance to increase sensor operation temperature in order to increment sensor sensitivity. To implement this sensor technology in the STIM, the heater has been considered as another actuator but despite the prototype considers the implementation of four gas sensors, we have decided to excite the four heaters with the same signal. Therefore the system will implement nine channels with a dedicated actuator channel, called specifically heater, for heating the four sensors.
To drive the gas sensor heaters, a Pulsed Width Modulated (PWM) signal has been implemented instead of the usual continuous gas sensor power supply. This solution allows to implement electronics that optimises power consumption. In that sense, heater drivers hardware are designed for working in a exclusive bi-state mode that permits and efficient power transfer from the supply to the heater, with low dissipation in the driver. Basic sensing resistance interface is based in a half-bridge configuration. However, it has to be taken into account that the sensing resistance can take a wide range of values, covering 2–3 orders of magnitude from low operating temperature to high operating temperature. Therefore, it could be interesting to adequate the “load” resistance to the signal response in the
• • • •
A. Pardo et al. / Sensors and Actuators B 116 (2006) 11–16
13
Fig. 2. Gas sensor driving and automatic selection of load resistance circuit schematic.
measurement system. To do this we have included in the design an analog multiplexer and four resistances (from 180 to 1 M) to each sensor. A software algorithm will select automatically the best resistance in each measurement. In Fig. 2 we present the schematic of the gas sensor with the driver, a MOSFET driven by the PWM signal, and the analog multiplexer that changes the load resistance of the sensor. Each multiplexer is a dual 4:1 multiplexer that is used for two sensors. The selection of the load resistance is carried out by the inputs A and B, that are controlled by the microcontroller. All the functions described in this module could be controlled by the STIM control module. But the ADuC resources are used completely by the signals and process described in the control module section. So we have decided to use a small and cheap microcontroller (Z86E08) in order to generate the required signals in this module: • PWM to the heaters. • Switching codes for the analog multiplexers that select the gain resistances. • Signals for actuators. The communication between the control module and this one is carried out via I2C. Only the analog output of sensors are connected directly to the control module. The gain resistance selection algorithm is also implemented in the control module. The interface circuitry of the humidity and the temperature sensors are quite simple because their operational output voltage range. The humidity sensor, a HIH3605 from Honeywell, is
Fig. 3. Block diagram of the STIM transducer module.
powered by constant voltage of 5 V, it generates an output voltage between 0.8 and 4.1 V and it does not need any additional device. The temperature sensor, a LM335 from National Semiconductors, only needs a 2k2 resistance between the device and the power supply. Finally, the driver for the two actuators are simply two MOSFET that act as power switches controlled by two digital outputs of the microcontroller. In Fig. 3 we present a block diagram of the STIM transducer module. 5. Implemented software and functions The STIM working procedure starts with an initialization process of variables and signals states, and the TEDS memory
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dump to the NCAP. After this sequence the program remains in a infinite loop, waiting for to possible interrupts: • NIOE signal, that indicates that the NCAP is starting a frame transfer of a function related with a specific channel. The STIM them analyzes the function sent by the NCAP and executes it. • Trigger signal, that initiates the process related with the channel trigger address defined previously by the NCAP. Both events control all possible process in the STIM, that basically are execution of IEEE1451 functions. When the process related with one event is finished, the execution returns to the waiting loop. We have implemented three types of functions: Physical Layer Communication Protocol Functions (Read byte, Write byte, Trigger detection); Link Layer Communication Protocol Functions (IEEE1451 Frame Transmission and I2 C Communication); Application Layer Functions (IEEE1451 Standard Functions, Memory Management and four specific Manufacturer’s Use Only Functions).
Fig. 4. Output voltage of the humidity sensor and relative humidity and temperature (from Honeywell).
6. TEDS and calibration Mainly we have developed the mandatory TEDS defined by the standard. That is, a Meta TEDS with information needed for the NCAP to gain access to any channel plus common information of the STIM; a Meta-identification TEDS with information to identify the STIM plus information common to all channels, and one Channel TEDS for each channel, that has the specific information of each channel to enable a proper operation. Additionally, we have included two calibration TEDS, one for the humidity sensor and other one for the temperature sensor. In the case of the humidity sensor we have given the sensor response depending on the relative humidity and the temperature. This information is provided by the sensor manufacturer and it is shown in Fig. 4. From this information, we have developed the following relation: H=
1 V − 0.8 −5 488.06 − T 6.7 × 10
(1)
However, the 1451 standard does not support arbitrary input–output relations. The standard proposes the use of multinomial functions. In order to express Eq. (1) in this format, we have to develop the temperature term in a Taylor’s series. The resulting expression in is: H = c10 [x1 − H1 ] + c11 [x1 − H1 ]T + c12 [x1 − H1 ]T 2
(2)
where cij and Hi are the coefficients that we store in the calibration TEDS for this channel, T the measured temperature, x the raw value of the voltage measured at the output of the humidity sensor, and H is the relative humidity. The use of calibration TEDS for humidity and temperature channels, allow to us not only to calibrate the sensors but also to convert raw values into its corresponding physical values.
It is important to mention that before the first use of the STIM, we have to generate the TEDS of our transducer set using a TEDS editor in a PC, and to transfer them to the Flash memory of the STIM via the TII connector. We have carried out this process using the parallel interface of the PC. After that, the system is ready to be connected to a NCAP, and it has not to be reconfigured if we do not change the transducer set. When we connect the STIM to a NCAP, this one stars a boot process (the NSDET signal of the TII is intended for this use) where TEDS are transferred to the NCAP. 7. Measures In order to carry out sensor measurements, the NCAP only has to follow the procedure defined by the IEEE1451 standard. For example, for a gas sensor (channels 1–4) the NCAP carry out the following steps: 1. Sends a Write Channel function to the desired channel in order to configure the measure. 2. Sends a Write Trigger Channel function (1–4). 3. Activate the Trigger signal. 4. Sends a Read Channel function to the channel, to read the measured data. While steps 3 and 4 had to be repeated for each measure, steps 1 and 2 only are necessary if the measure configuration changes or if we want to change channel to be measured. In Fig. 5 we present TII and STIM signals when trigger is activated (step 3). In the example we have configured channel trigger as number 3 in the step 2. We can see that the activity starts with the activation of the signal NTRIG in the TII, after that the STIM starts the measurement sequence: automatic gain of
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Fig. 5. Evolution of signals in the TII and the STIM when Trigger signal is activated in order to measure a gas sensor.
the gas sensors (I2C activity in lines SDA and SCL, and signals MUXA and MUXB that changes the sensor load resistance); once the gain is fixed the ADC measures the sensor output. We can see also one of the PWM pulse, signal CALEFA. We have tested our STIM with the following measure: • • • •
Measurement: 50 s of air + 30 s of methane + 40 s of air. Methane concentration = 6000 ppm. Carrier gas: synthetic air. Sensor: FIS sensor; series SB11A This measure has been carried out with two systems:
• Data Logger: Heating the gas sensor with constant voltage = 0.9 V (standard procedure in our Lab). • STIM: Heating the gas sensor with pulsed voltage: period = 8.2 ms, pulse width = 310 s (0–4 V amplitude). Since the thermal time constant of the sensor is about 500 ms (according to the manufacturer) the sensor temperature cannot follow the PWM signal, and the thermal dynamics operate as a low pass filter for the heater signal. In Fig. 6 a comparison between both measures are presented. We can see that basically both measures have the same dynamics except and offset probably due to a sensor drift. 8. Conclusions We have developed a STIM based on the IEEE1451.2 standard to be used as a electronic nose. We have included a typical set of transducer to implement an electronic nose, the signal conditioning electronics and the control system of a STIM. We have implemented sensor and actuator channels and the associated TEDS. So the NCAP can send measurement and actuation functions to the STIM and interpret the results properly. Further work requires to study how the TEDS can be used to store information concerning the characteristics of the gas sensor and to propose how the full instrument can be calibrated.
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Fig. 6. Methane measures with a Data Logger system (black dots) and the STIM (red line). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of the article.)
An interesting option is to study the possibilities given by the multinomial calibration considered in the standard. Acknowledgments We want to acknowledge the partial funding of European project NOSE II (IST2001-32494) and Spanish project MCYT TEC2004-07853-C02-01. References [1] R. Menon, C.O. Yoon, D. Moses, A.J. Heeger, in: T. Skotheim, R. Elsenbaumer, J.R. Reynolds (Eds.), Handbook of Conductive Polymers, second ed., Marcel-Dekker, New York, 1997, pp. 27–84. [2] R.S. Hobson, A. Clausi, T. Oh, A.G. Elie, Temperature Correction to Chemoresistive Sensors in an e-NOSE-ANN System, IEEE Sens. J. 3 (4), pp. 484–489. [3] A. Pardo, S. Marco, C. Calaza, A. Ortega, A. Perera, T. Sundic, J. Samitier, Methods for sensor selection in pattern recognition, in: J.W. Gardner, K.C. Persaud (Eds.), Electronic Noses and Olfaction, 2000, IoP Publishing, 2000, pp. 83–88. [4] C. Distante, Smart interfaces for transducers, in: Proc. of the 10th International Symposium on Olfaction and Electronic Noses, Riga, June 25–28, 2003, pp. 90–91. [5] IEEE Standards Board, IEEE Standard for a Smart Transducer Interface for Sensors and Actuators-Transducer to Microprocessor Protocols and Transducer Electronic Data Sheet (TEDS) Formats, 1997. [6] IEEE Standards Board, IEEE Standard for a Smart Transducer Interface for Sensors and Actuators-Nework Capable Application Processor (NCAP) Information Model, 1999. [7] NIST IEEE 1451 Internet Demo (online): http://motion.aptd.nist.gov/ P1451/ISADemo.htm. [8] P. Conway, D. Heffernan, B. O’Mara, P. Burton, T. Miao, IEEE 1451.2: An interpretation and example implementation, in: Instrumentation and Measurement Technology Conference, 2000. Proceedings of the 17th IEEE, vol. 2, May 1–4, 2000, pp. 535–540. [9] R. Kochan, K. Lee, V. Kochan, A. Sachenko, Development of a dynamically reprogrammable NCAP, in: IMCT 2004 Instrumentation and Measurement Technology Conference, Italy, 2004. [10] G. Song, A. Song, W. Huang, Distributed measurement system based on network smart sensors with standardized interfaces, Sens. Actuators A 120 (2005) 147–153.
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[11] N. Ulivieri, C. Distante, T. Luca, S. Rocchi, P. Siciliano, IEEE1451.4: A way to standardize gas sensor, Sens. Actuators B 114 (2006) 141–151. [12] L. Camara, O. Ruiz, A. Herms, J. Samitier, J. Bosch, Automatic generation of intelligent instruments for IEEE1451, Measuremnt 35 (2004) 3–9.
Biographies Antonio Pardo received his diploma in physics 1991 and his PhD in 2000 from the University of Barcelona. During his PhD studies he worked in system identification with applications in gas sensor systems. Now is professor at the Electronics Department of the Physics Faculty in University of Barcelona. His research interest focused on signal processing for gas sensors, pattern recognition and smart sensors. Lourdes C´amara received her diploma in 1990 from the Universitat de Barcelona. Master in Microelectronics in the Centro Nacional de Microelectronica (CNM) in Barcelona in 1993. She get the investigation sufficiency in the micro and optoelectronics physiscs program in the Universitat de Barcelona in 1994. She has been working as a professor in the same university since 1991 and at the same time developing different projects on different subjects: portable alcoholimeters, tactile sensors, intelligent instrumentation for transducers within different communication networks. She is developing her PhD in this last subject focused mainly in the application for ethernet. Actually, she is leading the research department of a private company. Moreover, this scientific motivation in her life, the most important thing are her two wonderful sons and climbing mountains. Joan Cabr´e received his diploma in electronics engineering in 2003. He developed research on IEEE1451 as a final year project. Alexandre Perera was born in Barcelona, Spain, in 1973. He received a degree (1996) and a PhD (2003) in physics from University of Barcelona
and a degree in electrical engineering (2001) from the same university. From 2003 to 2005, he stayed as a postdoctoral research associate at the Texas A&M University. In this period, he worked on intelligent signal processing for power systems within an EPRI sponsored project at PSAL Laboratory. In the same period he also worked at PRISM Laboratory in artificial olfaction related research. His research activity is focused on pattern recognition algorithms with applications ranging from chemical sensors to power systems, embedded systems and intelligent instrumentation. Xavier Cano, born in Vic. (Spain), in 1969. He received a diploma in industrial electronics in 1994 from the Universitat Polit`ecnica de Catalunya, a degree in electronic engineering in 2000 from the Universitat de Barcelona and a master degree from the same university in 2002. Since 2001, he is assistant professor at the UB and joined the ISPlab research group at the UB in 2005. His research work is focused on smart sensors instrumentation and RF ID systems technnolgy. Santiago Marco received his diploma in physics in 1988 and his PhD in physics in 1993 from the University of Barcelona. During his PhD studies he developed a novel micromachined pressure sensor for biomedical applications based in vertically structured silicon membranes. Since 1995, he is associate professor at the University of Barcelona. His research interests focuses on the design, simulation and modelling of micromachined sensors and actuators as well as on the dynamic modelling of chemical sensor arrays. Jose Bosch received his diploma in physics in 1987 and his PhD in physics in 1993 from University of Barcelona and master on materials science from University of Barcelona (1990). During his PhD studies he worked on the optimization of electrical and optical novel techniques for the characterization of heterostructures. Since 1995, he is an associate professor at the University of Barcelona. His research interest focuses on microprocessors and microcontrollers in the field of intelligent instrumentation. He also love to climb big mountains and actually he is organizing an expedition to Himalaya.