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WO2014111611A1 - Procédé d'analyse d'un gaz et nez artificiel - Google Patents

Procédé d'analyse d'un gaz et nez artificiel Download PDF

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Publication number
WO2014111611A1
WO2014111611A1 PCT/ES2014/070025 ES2014070025W WO2014111611A1 WO 2014111611 A1 WO2014111611 A1 WO 2014111611A1 ES 2014070025 W ES2014070025 W ES 2014070025W WO 2014111611 A1 WO2014111611 A1 WO 2014111611A1
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WIPO (PCT)
Prior art keywords
sensor
parameter
artificial nose
nose
modulation
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Ceased
Application number
PCT/ES2014/070025
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English (en)
Spanish (es)
Inventor
David Jesús YAÑEZ VILLARREAL
Francisco DE BORJA RODRÍGUEZ ORTIZ
Eduardo SERRANO JEREZ
Pablo VARONA MARTÍNEZ
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SGENIA SOLUCIONES SL
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SGENIA SOLUCIONES SL
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Application filed by SGENIA SOLUCIONES SL filed Critical SGENIA SOLUCIONES SL
Publication of WO2014111611A1 publication Critical patent/WO2014111611A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0004—Gaseous mixtures, e.g. polluted air
    • G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
    • G01N33/0027—General constructional details of gas analysers, e.g. portable test equipment concerning the detector
    • G01N33/0031—General constructional details of gas analysers, e.g. portable test equipment concerning the detector comprising two or more sensors, e.g. a sensor array
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00

Definitions

  • the present invention relates to a method of analyzing a gas by means of an artificial nose and a bio-inspired artificial nose of general application, which uses adaptive modulation strategies of the sensor parameters directed by the objective given to the nose.
  • the incorporation of said strategies gives the artificial nose of the invention reduced dimensions, therefore, high portability, a wide range of applicability and a reduced production cost.
  • Electronic noses are machines designed to accurately detect and discriminate odors.
  • a generally accepted definition of an artificial olfactory system was given by Gardner and Bartlett in 1994 (Oxford Press): "instrument comprising a grouping of chemical sensors with partially overlapping sensitivities together with a pattern recognition system, capable of analyzing and recognizing aromas simple or complex. "
  • the detection module includes the sensors responsible for directly or indirectly translating the presence of a smell into signals electric. When they come into contact with volatile components present in the gas, the sensors react, experiencing a physical change in their properties. The sensor response is received in the electronic module, which transforms the signal into a digital value. The values are analyzed below in the processing module, which is responsible for recognizing and / or classifying the recorded signals.
  • the method of operation of an artificial nose comprises a learning or training stage, in which the artificial nose is subjected to the analysis of a series of recognized samples to construct reference models. At a later stage of odor acquisition, the artificial nose is able to recognize new samples from the reference models.
  • olfactory sensors There are many types of olfactory sensors based on different physical principles: chemoresistive, chemocapacitive, potentiometric, gravimetric, optical, acoustic, thermal, polymeric, ammeter, chromatographic, spectrometric, field effect, etc.
  • Chemosensitive sensors are the most widespread due to their small size and easy integration into an electrical circuit.
  • matrices are used that combine sensors of this type, which offer certain advantageous characteristics, based on the design of a commercial electronic nose.
  • sensor arrays or multisensor components also have clear economic disadvantages, reliability, stability over time and miniaturization. DESCRIPTION OF THE INVENTION
  • a method of analyzing a gas by means of an artificial nose comprising at least one sensor comprising: (a) detecting by means of at least one sensor a sample of the gas to be analyzed, and
  • the adaptive modulation of at least one parameter is performed by a feedback function that modifies at least one parameter that affects the operating mode of the sensor.
  • the efficiency measure is determined from the comparison of the signal obtained from the detection with at least a second signal.
  • the second signal may be a theoretical or reference signal, or it may be a second signal obtained by detection.
  • the efficiency measure is determined from the comparison of the signal obtained from the detection with at least one threshold value.
  • the modulation of at least one parameter can be performed based on measures of efficiency of recognition of odors and / or discrimination of odors and / or classification of odors and / or in a learning stage.
  • the adaptive modulation of the parameters can be discrete (responding to specific events detected in the acquisition of the signal), or continuous (during the entire acquisition process).
  • the activation of the modulation starts automatically depending on the task assigned to the nose.
  • the modulation of the parameters is preferably activated when it is determined that a smell is not identified with the current sensor parameters.
  • the modulation of the parameters is preferably activated when it is determined that the signal of an odorant does not provide sufficient discriminant characteristics with the current parameters of the sensor.
  • Typical events that define the need to start a new modulation are the saturation of the signal or the arrival at a steady state of the same when the objective of the task assigned to the nose has not yet been achieved.
  • the timing of these events in general is not known a priori, and is determined by the comparison with the efficiency measure.
  • Adaptive modulation of at least one parameter can be performed during one stage of training the artificial nose or during the stage of acquisition of the smell by the artificial nose.
  • the parameter to be modulated is the gas flow rate that affects the sensor and / or the heating temperature.
  • the parameters to be modulated are selected according to the type of sensor, which can be any olfactory sensor.
  • two parameters that can be adaptively modulated are the heating temperature of the sensor and the gas flow that affects the sensor (sniffing).
  • the flow rate, the incident wavelength on the sensitive surface and the optical path length can be adaptively modulated.
  • the flow rate and amplitude (in voltage and intensity) of the frequency signal used are susceptible to adaptively modulating to determine the electrical capacity of the sensor.
  • QCM gravimetric sensors quartz crystal micro balance
  • the flow and base resonance frequency of the assembly can be varied by adaptively modulating Young's module with a piezoelectric prestressing.
  • SAW gravimetric sensors Surface acoustic wave
  • the flow rate and the type of pulse that propagates square, sine wave, ramp Certainly can be adaptively modulated.
  • Potentiometric sensors can adaptively modulate the flow and working pressure in order to vary in a controlled way the partial pressure of the gas in the solution.
  • an artificial nose comprising:
  • the artificial nose according to the second inventive aspect is adapted to perform the method according to the first inventive aspect and its different embodiments.
  • the artificial nose of the invention can be based on a single sensor, adapted to work in different regimes obtained from the application of strategies consisting of the adaptive modulation of at least one parameter that affects the operation and, consequently, the sensitivity of the sensor.
  • the artificial nose of the invention has dimensions and weight much lower than the olfactory devices considered portable in the market, so it can be considered ultraportable.
  • the senor consists of a single sensitive surface.
  • the processing means comprise a microcontroller, a PC or a PLC (programmable logic controller).
  • the introduction of adaptive modulation strategies in the learning or training stage and / or during the acquisition of the smell results in a more versatile artificial nose than the state of the art, by expanding the range of sensitivities with respect to artificial noses based on non-matrix sensors.
  • its use is allowed in electronic noses of general application, obtaining capacities for detecting and separating aromas analogous and even higher than those obtained in systems based on a matrix of sensors of greater cost and size.
  • the artificial nose and the method of the invention have clear competitive advantages, related both to its low production cost and its robustness, in addition to a substantial simplification of the electronics responsible for amplifying, filtering and conditioning the measured signal, with which substantially reduces the size and weight of the artificial nose and increases its portability.
  • the sensor is chemo-resistive and the adaptive modulation is carried out on the incoming air flow and / or on the heating temperature, which is the temperature at which the sensor works.
  • the adaptive modulation of the flow or air flow in a manner analogous to what occurs in nature, information from the odorous particles found in the gas under analysis is enriched by introducing into it fluid dynamic complexity that affects at pressure, temperature, average free path of particles, diffusivity, etc.
  • Adaptive air flow modulation can be performed both during the learning stage and during the acquisition of the smell.
  • the range of temperature values to which the sensor's sensitive surface is subjected is regulated.
  • the variation of the heating temperature affects the concentration of odorants on the sensitive surface, its diffusivity, etc.
  • Adaptive modulation of the heating temperature of the sensor can be performed both during the learning stage and during the acquisition of the smell.
  • the present method of analysis is intended to be preferably performed on an artificial nose with a single sensor, it is also applicable in artificial noses with more than one sensor.
  • the invention allows the theoretical and operational establishment of the best adaptive modulation functions based on the objective, which can be for example the detection of a smell, the discrimination between two or more odors, the classification of one or more odors in a series of categories, the identification of an odorant in a mixture, the maintenance of the effective stability of the sensor, etc.
  • the efficiency measure determines the instants and the way of performing adaptive modulation, which takes place by relevant events that are detected in the signal in relation to the objective given to the nose. The occurrence of these events is not known a priori and, in general, they do not have to be periodic.
  • the present invention is applicable in a number of areas, including:
  • Health field infection detection, study of anosmias and early prediction of associated neurodegenerative pathologies, detection of oncological conditions, blood or biogenic fluid analysis, pathologies of the endocrine system, characterization of clinical olfactory tests, etc.
  • Robotics mobile and industrial.
  • Figure 1. Shows a schematic elevation of an artificial nose according to the invention.
  • Figure 2. Shows a schematic representation in perspective of the path made by a gas subjected to analysis in an artificial nose according to the invention.
  • Figure 3. Shows a schematic representation of the signals and control elements of an artificial nose according to the invention.
  • Figure 4. It shows a representation of (A) an array of six standard chemoresistant sensors and (B) a virtual array of sensors obtained thanks to the variation of different heating and flow temperature values.
  • Figure 5. Shows (A) a schematic representation of the flow of information between the Sensory, electronic and processing modules of an artificial nose according to the state of the art and (B) according to the present invention.
  • Figure 6. It shows two sets of signals of two different odors made by a matrix of four sensitive surfaces.
  • Figure 7. Sample (A) two readings obtained from two different odors made in different instants by the same surface without modulation and (B) the reading of these two same odors subjected to different modulation regimes at times t 2 , t 3 and t 4 . These moments are defined by the efficiency measure and in general cannot be predetermined.
  • Figure 8. Shows an example of adaptive modulation according to the invention for the task of discriminating two very similar concentrations of ethanol.
  • the artificial nose comprises a sensor (10), an electronic board (3) and a microcontroller (12) housed inside an envelope (2).
  • the envelope has a series of accesses through which the entry and / or exit of the gas to be analyzed in the artificial nose is allowed.
  • the gas is penetrated (7) into the artificial nose through a first access (4).
  • the gas inlet is forced through a fan (9), so that the gas directly affects the sensor (10).
  • the sensor (10) selected to illustrate the invention is of the chemoresistant type and has four pins, two for the supply of the heating temperature and another two for its signal output.
  • the fan responsible for pumping gas is an axial fan of small dimensions capable of generating a flow of up to 2.7m 3 / h.
  • the fan (9) is fixed to an inner wall of the enclosure (2), so that it forces the gas inlet directly on the sensor.
  • the artificial nose of the example has a second access (5), made as a set of holes (5), for the exit (8) of the gas to the outside of the nose. Additional accesses can be provided, for example a third access (6) for the output of a multi-wire cable (11) responsible for carrying the communications and electrically feeding the artificial nose.
  • the electronics have been placed inside a 50 x 35 x 17mm commercial ABS envelope (2) on whose side the passage of the power and communications cable has been facilitated with a hole.
  • the cover (1) of the envelope (2) two sets of holes have been machined for the access and exit of the gas to be analyzed.
  • the size of the gas inlet holes (4) is preferably about 0.4mm.
  • the size of the gas outlet orifices (5) is preferably about I mm.
  • the size of the hole for the communication cable (6) is preferably about 5mm in diameter.
  • the artificial nose there is a microcontrolled electronic device capable of regulating both the heating temperature and the gas flow.
  • the adaptive modulation of the heating temperature and the flow rate is carried out in this embodiment by means of two PWM type FET gate power control systems with low pass filter.
  • the device has two communication modes: a USB protocol communication module and an RS-485 module for systems Long distance multipoint
  • the processing means must be adapted for the acquisition of the signal readings and their analysis
  • the adaptive modulation of the gas flow and the heating temperature of the sensor can be controlled by the microcontroller embedded in the artificial nose or by an external PC or PLC
  • the possibility of adaptively modulating, depending on events defined by the objective given to the nose, both the gas flow and the temperature is integrated as an additional functionality in the learning algorithm and / or classification, increasing the discrimination capacity of the equipment During the analysis process both parameters can be adjusted din ically and in real time based on the state procurement in the that is the artificial nose.
  • the microcontroller (12) housed in the electronic board (3) adaptively modulates the respective activity of the heating temperature power control systems (13) of the chemoresistant sensor (10) and of the flow rate (14) of the fan (9) by means of two signals (18) regulated by pulse width (classical method of regulation and energy management typically known as PWM). It also has two communication modules (15, 16) dedicated to the transfer of information to external processing means (17).
  • PWM pulse width
  • Figure 4 shows by comparison a matrix of six real chemo-resistive sensors (af) of a state-of-the-art artificial nose (A) and the virtual sensor matrix (represented in lighter color) with different sensitivities of a artificial nose according to the invention (B), obtained from a single sensor (adaptive temperature modulation function sensor T1, flow darker represented F1), subjected to different adaptive modulation functions (Tx) of heating temperatures and to different functions of adaptive modulation (Fy) of flow or gas flow values with odorant that is passed through its surface.
  • af real chemo-resistive sensors
  • A state-of-the-art artificial nose
  • B virtual sensor matrix
  • the artificial nose of the invention is able to obtain different and partially overlapped effective sensitivities from a single sensitive surface, equivalent to the sensitivities that would be obtained using a high number of virtual sensors operating from consecutive way.
  • adaptive modulation is performed by means of a feedback function m (f) that modifies the parameters of acquisition (and / or learning and / or recognition) based on an objective efficiency function given to the nose (for example a function that measures the distance between signals).
  • the times t where modulation is effective are determined by events observed in the sensor signal and are automatically defined in relation to to the objective given to the nose.
  • the module responsible for managing the adaptive modulation of the parameter (s) is the processing module, which is able to vary these parameters in real time in an adaptive manner to optimize the detection and discrimination of the odor depending on the objective given to the nose.
  • FIG. 5A shows the sensory (21), electronic (22) and processing (23) modules together with the flow of information that occurs between them in a traditional artificial nose.
  • the sensory (24), electronic (25) and processing (26) modules are represented respectively together with the information flow and the modulation that occurs between them in the artificial nose according to the present invention.
  • Figure 6 is an example of the classic method for odor discrimination. It shows, as a function of time (t), two sets of signals (S a 1 , S b 1 , S c 1 , S d 1 ; S a 2 , S b 2 , Sc 2 , S d 2 ) for two different odors (1 and 2) made by a matrix of four sensitive surfaces (a, b, c, d).
  • the figure shows that although the signals (S C 1 , S C 2 ) obtained by the same surface are hardly distinguishable for the two odors, the other signals (S a 1 , S b 1 , S d 1 ; S a 2 , S b 2 , S d 2 ) are clearly different for the two odors, that is, three of the four sensitive surfaces provide additional information on the smell with which discrimination is possible.
  • Figure 7 A shows a graph representing two signal readings (S to 1 ; S to 2 ) obtained for two different odors as a function of time, made at different times by the same sensitive surface to keep the modulation parameters constant .
  • the two odors produce signals that are difficult to distinguish in a certain operating mode of the sensor.
  • Figure 7B shows the effect produced in the reading of signals for these two same odors, which at first (ti) are indistinguishable but subject to different regimes at instants (t 2 , t 3 , t 4 ) in those that a modulation parameter has been adaptively modified are easily distinguishable.
  • these parameters may be the heating temperature and / or the flow rate.
  • FIG. 8 An example of gas flow modulation to discriminate two very similar concentrations of ethanol is shown in Figure 8. Without modulation the nose is not able to discriminate these two concentrations.
  • S to 1 corresponds to the signal recorded by the artificial nose of the invention for 0.5% ethanol and S to 2 corresponds to the signal recorded for 0.45% ethanol.
  • Modulation m F (in this example, gas flow F) is performed until the distance d between the two signals reaches an appropriate threshold.
  • the moments in which a flow modulation is performed are indicated by arrows.
  • the panel on the left shows the signals obtained as a function of time and the panel on the right shows the instantaneous distance (d) between the signals, together with the threshold considered appropriate for discrimination (0.04V in this example).
  • the measure of process efficiency would be the distance between the two recorded signals, made as the difference between one and the other.
  • the distance between signals can be calculated in another way, so that it is not necessarily the difference between one and the other. While the distance is less than the set threshold value, modulation is performed adaptive of the gas flow incident on the sensor.
  • the lower panel shows the modulation function (m F ) used in this example, which corresponds to a function that modifies the gas flow in the appropriate direction if the discrimination threshold has not been reached in a time interval. Once the distance between the two signals has reached the established threshold, the discrimination between the two signals is considered satisfactory and the process ends.
  • modulation function m F
  • more complex functions can be used in which the modification of the parameter to be modulated is dependent on the measure of efficiency employed defined in relation to the objective given to the nose.
  • the adaptive modulation of the parameters is discrete, but in other cases it could be continuous.
  • the gas flow rate and the heating temperature have been mentioned as modulable parameters in relation to a chemoresistant sensor, it will be understood that the above explanations are equally applicable to other modulable parameters in relation to other types of olfactory sensors .

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  • Food Science & Technology (AREA)
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  • Investigating Or Analyzing Materials By The Use Of Fluid Adsorption Or Reactions (AREA)
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  • Electrochemistry (AREA)

Abstract

Le procédé d'analyse est réalisé au moyen d'un nez artificiel comprenant au moins un capteur, et consiste à détecter un échantillon du gaz à analyser et à moduler, de façon adaptative, au moins un paramètre qui affecte le régime de fonctionnement du capteur en fonction d'un signal résultant de la détection du capteur et d'une mesure d'efficacité. Le nez artificiel comprend au moins un capteur d'odeur et des moyens de traitement conçus pour moduler, de façon adaptative, au moins un paramètre qui affecte le régime de fonctionnement du capteur en fonction d'un signal résultant de la détection du capteur et d'une mesure d'efficacité. L'incorporation de stratégies de modulation adaptative confère au nez artificiel de l'invention des dimensions réduites, et par conséquent une portabilité élevée, un large champ d'application et un coût de production réduit.
PCT/ES2014/070025 2013-01-17 2014-01-17 Procédé d'analyse d'un gaz et nez artificiel Ceased WO2014111611A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
ES201330048A ES2486891B1 (es) 2013-01-17 2013-01-17 Método de análisis de un gas y nariz artificial
ESP201330048 2013-01-17

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11009494B2 (en) 2018-09-04 2021-05-18 International Business Machines Corporation Predicting human discriminability of odor mixtures
US11592427B2 (en) * 2018-10-01 2023-02-28 Brown University Multi-parametric machine olfaction

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20230349875A1 (en) * 2020-09-22 2023-11-02 Uhoo Pte Ltd Apparatus and method for measuring air quality

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO1987001204A1 (fr) * 1985-08-15 1987-02-26 Global Geochemistry Corporation Analyse chimique par modulation controlee de l'echantillon et correlation de la detection
ES8707613A1 (es) * 1985-05-30 1987-08-01 Siemens Ag Procedimiento y sensor para el analisis de gases
US20050229675A1 (en) * 2004-04-20 2005-10-20 Stephan Haupt Gas sensor with increased measurig sensitivity
WO2006111727A1 (fr) * 2005-04-19 2006-10-26 City Technology Limited Ensemble de capteur de gaz comprenant un element catalytique
WO2008061214A2 (fr) * 2006-11-16 2008-05-22 Honeywell International Inc. Capteur avec modulateur d'analyte

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
ES8707613A1 (es) * 1985-05-30 1987-08-01 Siemens Ag Procedimiento y sensor para el analisis de gases
WO1987001204A1 (fr) * 1985-08-15 1987-02-26 Global Geochemistry Corporation Analyse chimique par modulation controlee de l'echantillon et correlation de la detection
US20050229675A1 (en) * 2004-04-20 2005-10-20 Stephan Haupt Gas sensor with increased measurig sensitivity
WO2006111727A1 (fr) * 2005-04-19 2006-10-26 City Technology Limited Ensemble de capteur de gaz comprenant un element catalytique
WO2008061214A2 (fr) * 2006-11-16 2008-05-22 Honeywell International Inc. Capteur avec modulateur d'analyte

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11009494B2 (en) 2018-09-04 2021-05-18 International Business Machines Corporation Predicting human discriminability of odor mixtures
US11592427B2 (en) * 2018-10-01 2023-02-28 Brown University Multi-parametric machine olfaction
US11828742B2 (en) 2018-10-01 2023-11-28 Brown University Multi-parametric machine olfaction

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ES2486891B1 (es) 2015-10-27

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