WO1995023335A1 - Monitor and method for detecting volatile materials - Google Patents

Monitor and method for detecting volatile materials Download PDF

Info

Publication number
WO1995023335A1
WO1995023335A1 PCT/GB1995/000401 GB9500401W WO9523335A1 WO 1995023335 A1 WO1995023335 A1 WO 1995023335A1 GB 9500401 W GB9500401 W GB 9500401W WO 9523335 A1 WO9523335 A1 WO 9523335A1
Authority
WO
WIPO (PCT)
Prior art keywords
die
sensors
sensor
sample
responses
Prior art date
Application number
PCT/GB1995/000401
Other languages
French (fr)
Inventor
Diana Margaret Hodgins
Original Assignee
Neotronics Limited
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Neotronics Limited filed Critical Neotronics Limited
Priority to AU17157/95A priority Critical patent/AU1715795A/en
Publication of WO1995023335A1 publication Critical patent/WO1995023335A1/en

Links

Classifications

    • 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
    • G01N33/0006—Calibrating gas analysers
    • 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

Definitions

  • the present invention relates to the detection of volatile materials, such as smells, odours and aromas.
  • the present invention provides a method of testing volatile material in a gaseous sample by means of a plurality of sensors that each responds to volatile materials, to ascertain whether the sample conforms to a reference sample, which method comprises
  • test sample (f) (i) accepting the test sample as being substantially the same as the reference sample if, for each sensor, the test response differs from the said average reference response of the same sensor by less than the spread of that sensor (or a predetermined multiplier of the spread) and/or by less than a predetermined proportion of the average reference response of that sensor or
  • test sample could be rejected as not being the same as the reference sample if the test response from at least one sensor to the test sample differs from me said average reference response of that sensor by more than, say, 3 standard deviations or if the test responses of two or more sensors differ from the respective average reference responses of those sensors by more than, say, 2 standard deviations and/or if the test responses of 3 or more sensors differ from the respective average reference responses of those sensors by more than, say, l '/ ⁇ standard deviations etc.
  • the test sample can be exposed to the sensors on more that one occasion.
  • the spread used in step (f) may include factors not directly derived from the exposures to the reference sample; for example it can be calculated, for each sensor, by adding together (1) the standard deviation (or- a multiple thereof) of the reference responses of that sensor and (2) the standard deviation (or a multiple thereof) of the test responses of that sensor during multiple exposures to the test samples.
  • the spread that is acceptable before any test sample is rejected as not being substantially the same as the reference sample depends on the nature of the material being tested, e.g. in monitoring the quality of animal food, a wider deviation from the average reference values of the sensors is acceptable than is the case, for example, when monitoring the quality of food for human consumption.
  • each sensor output When exposed to an unknown sample tested once, twelve different sensor outputs are obtained.
  • the test response of each sensor is compared to the reference response of each sensor; this can readily be achieved using appropriate computer software.
  • the user can define how far away from the average reference response each sensor output may deviate. This may be in terms of a multiple of the standard deviations obtained from the reference sample and would typically be between 1 and 4 a. It could also be set at a different level for each sensor type, e.g. one sensor could have a limit of 1 ⁇ . a second sensor a limit of 3 ⁇ , etc. Alternatively, the user could define the limits as a percentage difference from the average reference response of each sensor e.g. if the difference exceeds 20% of the average reference response.
  • the type of problem with the sample may also be determined. For example, for a twelve sensor array if one or two sensors exceeds the limits set by a marginal amount then there is probably a taint present in the sample. If however, a different one or two sensor combination exceed the limits on a different sample then that also probably has a taint present, but this taint is of a different formulation. And if all twelve sensors exceed the limits by a significant amount then the sample varies noticeably from reference.
  • a monitor for testing the volatile materials in a gaseous sample which monitor comprises
  • the monitor also includes means for displaying the data, preferably in a digital format, e.g. the average reference response of each sensor, the spread of the reference responses of each sensors, the response of each sensor to a test sample, the test responses of only those sensors whose test response differs from the average reference response for the sensor in question by more than the respective spread (or a predetermined multiplier of the spread) of the sensor in question and/or by more man a predetermined proportion of said average reference response of the sensor in question.
  • a digital format e.g. the average reference response of each sensor, the spread of the reference responses of each sensors, the response of each sensor to a test sample, the test responses of only those sensors whose test response differs from the average reference response for the sensor in question by more than the respective spread (or a predetermined multiplier of the spread) of the sensor in question and/or by more man a predetermined proportion of said average reference response of the sensor in question.
  • Figure 1 is a polar display of the average response produced by each of twelve sensors on exposure to the same sample of cocoa (Cocoa I) on five separate occasions;
  • Figure 2 is a polar plot of the standard deviation of the reference responses each of the twelve sensors derived from the five exposures to Cocoa I referred to in the preceding paragraph;
  • Figure 3 is a polar plot of the difference between the responses of the twelve sensors shown in Figure 1 (the Cocoa I responses) and the average responses produced by the same twelve sensors on exposure to a different sample of the cocoa (Cocoa III) on five separate occasions (the Cocoa IN responses). The difference is expressed as a percentage of the Cocoa III responses;
  • Figure 4 is a polar plot showing the difference between the average Cocoa I responses and the average Cocoa III responses of each sensor of the twelve sensors for which the average Cocoa III response differs from the average Cocoa I response by more than the sum of (1) the st-andard deviation of the Cocoa I responses and (2) the standard deviation of the Cocoa III responses;
  • Figure 5 is a polar plot showing the difference between the average Cocoa I responses and die average Cocoa III responses of each sensor of the twelve sensors for which the average Cocoa III response differs from the average Cocoa I response by more than twice the sum of (1) the standard deviation of the Cocoa I responses and (2) die standard deviation of the Cocoa III responses.
  • each sensor comprises a pair of spaced-apart contacts: the gap between the contacts of each sensor is spanned by a semi-conductive polymer whose resistance can change on exposure to a volatile material; sensors of this type are described in WO93/03355.
  • the polymer of each of the twelve sensors is different; examples of acceptable sensor polymers and methods of producing them are set out in WO93/003355, the content of which is incorporated herein by reference.
  • the arrangement of the sensors is such that the response (i.e. the resistance of the semi-conductive polymer) of each sensor can be measured by the monitor, which also contains a computer to analyse the responses of the sensors and means for displaying the responses and various analyses of the responses.
  • the cocoa In order to evaluate a sample, for example of cocoa, the cocoa is placed in a closed vessel; volatile materials from the cocoa sample will enter into the head space above the sample. The sample is left for a sufficient time to allow the volatile material in the gas space to reach an equilibrium state. The gas sensor array is then placed into the head space of the closed vessel and the resistance of each of the twelve sensors is taken after a predetermined time, for example one to five minutes.
  • the sensor array is exposed to the same sample of cocoa (Cocoa I) on five occasions or is exposed to five different samples, each of which is known to be of an acceptable composition.
  • cocoa I cocoa
  • Figure 1 shows a polar plot of die average response of each sensor taken over the five exposures (each spike representing the response of one of the sensors).
  • Figure 2 is a polar plot showing the standard deviation of die responses of each sensor over the five exposures. The procedure described above for obtaining the reference data is repeated with a different cocoa sample (Cocoa III).
  • the average response from each sensor over the five exposures to Cocoa III is calculated (the average Cocoa III responses) and subtracted from the average response from the Cocoa I reference data of Figure 1 for die same sensor.
  • the difference, expressed as a percentage of die average Cocoa III responses, is shown in Figure 3.
  • the standard deviation of the Cocoa I responses of each sensor was added to die standard deviation of die Cocoa III responses for the same sensor to obtain a spread for each sensor.
  • the difference between the average Cocoa I response and die average Cocoa III response of a sensor exceeds die spread, as calculated above, of diat sensor, the difference between the average Cocoa I response and die average Cocoa III response of the sensor is highlighted or signalled and is included in die polar plot shown in Figure 4.
  • die responses of some of the sensors may be more important than the responses of odiers.
  • a sample may be rejected if the responses of die significant sensors to the sample differs from die respective reference responses by more man, say, two standard deviations whereas a difference of four or six standard deviations can be tolerated in a less relevant sensor before the response for that sensor is highlighted and rejected as being unacceptable.

Abstract

A method is disclosed of testing volatile material in a gaseous sample by means of a plurality of sensors that each responds to volatile materials, to ascertain whether the sample conforms to a reference sample, which method comprises (a) exposing the plurality of sensors to a reference sample of volatile material of known composition or origin, (b) repeating the exposure of the plurality of sensors to the same or a different reference sample on at least three further occasions (and preferably at least five e.g. at least seven and most preferably at least eleven further occasions), (c) recording the response of each of the plurality of sensors to the reference sample on each exposure to obtain for each sensor a plurality of reference responses, (d) for each sensor, calculating (i) the average of the reference responses and (ii) the spread of the reference responses, (e) exposing the said sensors to a test sample and recording the response of each of the plurality of sensors to the test sample to obtain for each sensor a test response, (f) (i) accepting the test sample as being substantially the same as the reference sample if, for each sensor, the test response differs from the said average reference response of the same sensor by less than the spread of that sensor (or a predetermined multiplier of the spread) and/or by less than a predetermined proportion of the average reference response of that sensor or (ii) rejecting the test sample as being not the same as the reference sample if the test response of each of a predetermined number of sensors differs from the respective average reference responses of those sensors by more than the respective spread of those sensors (or a predetermined multiple of the spread) and/or by more than a predetermined proportion of the respective average reference responses of those sensors.

Description

MONITOR AND METHOD FOR DETECTING VOLATILE MATERIALS
TECHNICAL FIELD
The present invention relates to the detection of volatile materials, such as smells, odours and aromas.
BACKGROUND ART
It is known, for example, from WO93/03355 and WO86/01599 that it is possible to detect volatile materials by directly or indirectly measuring the resistance across each of an array of sensors, each sensor including a semi-conductive polymer that interacts with the volatile material to change its resistance. By providing different polymers in the sensors of the array, it is possible to characterise different volatile materials according to the response of the array to that material.
It is known to analyse the data from an array of sensor of this type using a neural network (GB-2 239 094) and using pattern recognition techniques ( O93/03355) that recognise certain patterns in the signals from different sensors to identify common characteristics. It is also known to apply multivariate statistical methods such as principal component analysis, factor analysis and cluster analysis to analyse the data obtained from testing the quality of foodstuffs (see article by Anna V A Ressureccion in Food Technology, November 1988, page 128). However, such multivariate techniques simplify the data before performing the statistical analysis and some significant data can thus be lost in the process.
DISCLOSURE OF THE INVENTION The present invention provides a method of testing volatile material in a gaseous sample by means of a plurality of sensors that each responds to volatile materials, to ascertain whether the sample conforms to a reference sample, which method comprises
(a) exposing the plurality of sensors to a reference sample of volatile material of known composition or origin,
(b) repeating the exposure of the plurality of sensors to the same or a different reference sample on at least three further occasions (and preferably at least five e.g. at least seven and most preferably at least eleven further occasions),
(c) recording the response of each of the plurality of senors to the reference sample on each exposure to obtain for each sensor a plurality of reference responses,
(d) for each sensor, calculating (i) the average of the reference responses and (ii) the spread of the reference responses,
(e) exposing the said sensors to a test sample and recording the response of each of the plurality of senors to the test sample to obtain for each sensor a test response,
(f) (i) accepting the test sample as being substantially the same as the reference sample if, for each sensor, the test response differs from the said average reference response of the same sensor by less than the spread of that sensor (or a predetermined multiplier of the spread) and/or by less than a predetermined proportion of the average reference response of that sensor or
(ii) rejecting the test sample as being not the same as the reference sample if the test response of each of a predetermined number of sensors differs from the respective average reference responses of those sensors by more than the respective spread of those sensors
(or a predetermined multiple of the spread) and/or by more than a predetermined proportion 1385fiόof"espective average reference responses of those sensors. For example, a test sample could be rejected as not being the same as the reference sample if the test response from at least one sensor to the test sample differs from me said average reference response of that sensor by more than, say, 3 standard deviations or if the test responses of two or more sensors differ from the respective average reference responses of those sensors by more than, say, 2 standard deviations and/or if the test responses of 3 or more sensors differ from the respective average reference responses of those sensors by more than, say, l '/∑ standard deviations etc. The test sample can be exposed to the sensors on more that one occasion. The spread used in step (f) may include factors not directly derived from the exposures to the reference sample; for example it can be calculated, for each sensor, by adding together (1) the standard deviation (or- a multiple thereof) of the reference responses of that sensor and (2) the standard deviation (or a multiple thereof) of the test responses of that sensor during multiple exposures to the test samples.
The spread that is acceptable before any test sample is rejected as not being substantially the same as the reference sample depends on the nature of the material being tested, e.g. in monitoring the quality of animal food, a wider deviation from the average reference values of the sensors is acceptable than is the case, for example, when monitoring the quality of food for human consumption.
By way of an example, for a twelve sensor array an average reference response and standard deviation is obtained for each sensor when exposed to a reference sample on five occasions.
When exposed to an unknown sample tested once, twelve different sensor outputs are obtained. The test response of each sensor is compared to the reference response of each sensor; this can readily be achieved using appropriate computer software. The user can define how far away from the average reference response each sensor output may deviate. This may be in terms of a multiple of the standard deviations obtained from the reference sample and would typically be between 1 and 4 a. It could also be set at a different level for each sensor type, e.g. one sensor could have a limit of 1 σ. a second sensor a limit of 3 σ, etc. Alternatively, the user could define the limits as a percentage difference from the average reference response of each sensor e.g. if the difference exceeds 20% of the average reference response.
By using the technique the user can discriminate between sample types whilst maintaining the data from all of the sensors. Conventional pattern recognition techniques take the data from all of the sensors and then reduce this down to two principle components before performing clustering. These techniques may lose information from an array of sensors and therefore is not preferred for this type of application.
By highlighting sensor responses on exposure to test samples which exceed the limits set by the user, the type of problem with the sample may also be determined. For example, for a twelve sensor array if one or two sensors exceeds the limits set by a marginal amount then there is probably a taint present in the sample. If however, a different one or two sensor combination exceed the limits on a different sample then that also probably has a taint present, but this taint is of a different formulation. And if all twelve sensors exceed the limits by a significant amount then the sample varies noticeably from reference.
According to a further aspect of the present invention, there is provided a monitor for testing the volatile materials in a gaseous sample, which monitor comprises
1. a plurality of sensors that are each sensitive to the volatile material,
2. means for storing the responses of each sensor to a plurality of exposures to a reference sample of volatile materials of known composition or origin
(hereafter called the "reference responses"),
3. means for calculating an average of the reference responses for each sensor (e.g. a median or mean value) and the spread (e.g. the standard deviation) of the reference responses for each sensor, 4. means for comparing the response of each sensor on exposure to a test sample with the average reference response and the spread recorded for that sensor and
5. means for indicating if the response of each of a predetermined number of sensors on exposure to the test sample differs from the respective average reference responses for those sensors by more than the said spread for the respective sensors (or a predetermined multiple of the said spread) and/or by more man a predetermined proportion of the said average reference responses of those sensors.
Preferably the monitor also includes means for displaying the data, preferably in a digital format, e.g. the average reference response of each sensor, the spread of the reference responses of each sensors, the response of each sensor to a test sample, the test responses of only those sensors whose test response differs from the average reference response for the sensor in question by more than the respective spread (or a predetermined multiplier of the spread) of the sensor in question and/or by more man a predetermined proportion of said average reference response of the sensor in question. BRIEF DESCRIPTION OF THE DRAWINGS
Figure 1 is a polar display of the average response produced by each of twelve sensors on exposure to the same sample of cocoa (Cocoa I) on five separate occasions;
Figure 2 is a polar plot of the standard deviation of the reference responses each of the twelve sensors derived from the five exposures to Cocoa I referred to in the preceding paragraph;
Figure 3 is a polar plot of the difference between the responses of the twelve sensors shown in Figure 1 (the Cocoa I responses) and the average responses produced by the same twelve sensors on exposure to a different sample of the cocoa (Cocoa III) on five separate occasions (the Cocoa IN responses). The difference is expressed as a percentage of the Cocoa III responses;
Figure 4 is a polar plot showing the difference between the average Cocoa I responses and the average Cocoa III responses of each sensor of the twelve sensors for which the average Cocoa III response differs from the average Cocoa I response by more than the sum of (1) the st-andard deviation of the Cocoa I responses and (2) the standard deviation of the Cocoa III responses; and
Figure 5 is a polar plot showing the difference between the average Cocoa I responses and die average Cocoa III responses of each sensor of the twelve sensors for which the average Cocoa III response differs from the average Cocoa I response by more than twice the sum of (1) the standard deviation of the Cocoa I responses and (2) die standard deviation of the Cocoa III responses.
BEST MODE FOR CARRYING OUT THE INVENTION
An array of twelve sensors are incorporated in a monitor; each sensor comprises a pair of spaced-apart contacts: the gap between the contacts of each sensor is spanned by a semi-conductive polymer whose resistance can change on exposure to a volatile material; sensors of this type are described in WO93/03355. The polymer of each of the twelve sensors is different; examples of acceptable sensor polymers and methods of producing them are set out in WO93/003355, the content of which is incorporated herein by reference. The arrangement of the sensors is such that the response (i.e. the resistance of the semi-conductive polymer) of each sensor can be measured by the monitor, which also contains a computer to analyse the responses of the sensors and means for displaying the responses and various analyses of the responses. In order to evaluate a sample, for example of cocoa, the cocoa is placed in a closed vessel; volatile materials from the cocoa sample will enter into the head space above the sample. The sample is left for a sufficient time to allow the volatile material in the gas space to reach an equilibrium state. The gas sensor array is then placed into the head space of the closed vessel and the resistance of each of the twelve sensors is taken after a predetermined time, for example one to five minutes.
In order to provide reference data, the sensor array is exposed to the same sample of cocoa (Cocoa I) on five occasions or is exposed to five different samples, each of which is known to be of an acceptable composition. Naturally, it is possible to use more man five readings taken in this way in order to establish the reference and of course the greater the number of readings taken, the more accurate the reference data will be. Figure 1 shows a polar plot of die average response of each sensor taken over the five exposures (each spike representing the response of one of the sensors). Figure 2 is a polar plot showing the standard deviation of die responses of each sensor over the five exposures. The procedure described above for obtaining the reference data is repeated with a different cocoa sample (Cocoa III). The average response from each sensor over the five exposures to Cocoa III is calculated (the average Cocoa III responses) and subtracted from the average response from the Cocoa I reference data of Figure 1 for die same sensor. The difference, expressed as a percentage of die average Cocoa III responses, is shown in Figure 3. The standard deviation of the Cocoa I responses of each sensor was added to die standard deviation of die Cocoa III responses for the same sensor to obtain a spread for each sensor. Where me difference between the average Cocoa I response and die average Cocoa III response of a sensor exceeds die spread, as calculated above, of diat sensor, the difference between the average Cocoa I response and die average Cocoa III response of the sensor is highlighted or signalled and is included in die polar plot shown in Figure 4. In fact, in this instance, the difference between the average Cocoa I response and the average Cocoa III response exceeds die spread for all but one of the sensors and accordingly the difference responses for all eleven sensors are included in die Figure 4 plot. This is because Cocoa I and Cocoa III were different types of cocoa. Figure 5 is a plot similar to that of Figure 4 but only includes a difference between the average Cocoa I response and the average Cocoa III response of a sensor if the difference for that sensor exceeds twice the sum of die spread.
From Figures 4 and 5, it can be seen that some sensors are detecting large differences between the Cocoa I and Cocoa III samples while o er sensors are detecting lower but still significant differences. One advantage of die present procedure is diat the user can decide on the level of discrimination between the sample and the reference responses before the sample is rejected as not being die same as die reference. For example, the user may be able to tolerate differences between the test sample and die reference of any sensor of four or even six standard deviations before die response for that sensor is highlighted as being unacceptable. Furthermore, the user may accept differences in excess of ie predetermined acceptable spread if die acceptable spread is not exceeded by more man a predetermined number of sensors widiin die array e.g. by more than two.
Because the sensors of the array respond in a different manner to different constituents of die sample, die responses of some of the sensors may be more important than the responses of odiers. A sample may be rejected if the responses of die significant sensors to the sample differs from die respective reference responses by more man, say, two standard deviations whereas a difference of four or six standard deviations can be tolerated in a less relevant sensor before the response for that sensor is highlighted and rejected as being unacceptable.
From consideration of Figures 4 and 5 it is apparent mat Cocoa I and Cocoa III are essentially different; whether the difference is sufficient to reject the Cocoa III sample depends on d e tolerance the user is willing to put up widi.

Claims

Claims
1. A method of testing volatile material in a gaseous sample by means of a plurality of sensors that each responds to volatile materials, to ascertain whether the sample conforms to a reference sample, which method comprises (a) exposing me plurality of sensors to a reference sample of volatile material of known composition or origin,
(b) repeating the exposure of the plurality of sensors to the same or a different reference sample on at least three further occasions (and preferably at least five e.g. at least seven and most preferably at least eleven further occasions),
(c) recording the response of each of the plurality of senors to the reference sample on each exposure to obtain for each sensor a plurality of reference responses,
(d) for each sensor, calculating (i) die average of die reference responses and (ii) die spread of die reference responses,
(e) exposing die said sensors to a test sample and recording die response of each of die plurality of senors to the test sample to obtain for each sensor a test response.
(f) (i) accepting the test sample as being substantially the same as the reference sample if, for each sensor, the test response differs from e said average reference response of die same sensor by less man the spread of diat sensor (or a predetermined multiplier of die spread) and/or by less dian a predetermined proportion of the average reference response of that sensor or (ϋ) rejecting the test sample as being not the same as the reference sample if the test response of each of a predetermined number of sensors differs from the respective average reference responses of those sensors by more than the respective spread of those sensors (or a predetermined multiple of die spread) and/or by more dian a predetermined proportion of die respective average reference responses of ose sensors.
2. A method as claimed in claim 1 , wherein die test sample is rejected if die response of each of a predetermined number of sensors on exposure to die test sample is not the same as the said average reference response of that sensor plus or minus the spread (or a predetermined multiple of the spread). i
3. A method as claimed in claim 1, wherein the sensors are exposed to the test sample on more than one occasion and it is the average of the response of each sensor to the exposures to the test sample mat is compared with the respective average reference responses. 0
4. A method as claimed in claim 3, wherein, for each sensor, the said spread used in step (0 is calculated by adding togedier (1) the standard deviation (or a multiple thereof) of the reference responses of that sensor and (2) die standard deviation (or a multiple thereof) of the test responses of that sensor.
15
5. A method of claim 1. wherein a test sample is rejected as not being die same as the reference sample if
(a) the test response from at least one sensor to the test sample differs from die said average reference response of that sensor by more than a 0 predetermined number, e.g. 3. standard deviations or
(b) if the test responses of two or more sensors to the test sample differ from the respective average reference responses of those sensors by more than a predetermined number, e.g. 2, standard deviations or
(c) if die test responses of 3 or more sensors to die test sample differ from 25 e respective average reference responses of those sensors by more than a predetermined number, e.g. Vή, standard deviations.
6. A monitor for testing the volatile materials in a gaseous sample, which monitor comprises
1. a plurality of sensors that are each sensitive to the volatile material, 2. means for storing the responses of each sensor to a plurality of exposures to a reference sample of volatile materials of known composition or origin (hereafter called the "reference responses"),
3. means for calculating an average of the reference responses for each sensor (e.g. a median or mean value) and e spread (e.g. die standard deviation) of die reference responses for each sensor,
4. means for comparing the response of each sensor on exposure to a test sample with the average reference response and die spread recorded for that sensor and 5. means for indicating if the response of each of a predetermined number of sensors on exposure to the test sample differs from the respective average reference responses for diose sensors by more than the said spread for die respective sensors (or a predetermined multiple of the said spread) and/or by more man a predetermined proportion of the said average reference responses of diose sensors.
7. A monitor as claimed in claim 6, which includes means for displaying the responses of die sensors.
8. A monitor as claimed in claim 6, which includes means allowing a user to input die multiple of the spread of each or selected sensors into die said comparing means at is used in die comparison performed by die said comparing means.
9. A monitor as claimed in claim 6. which includes means allowing a user to input die predetermined number into die indicating means.
PCT/GB1995/000401 1994-02-25 1995-02-27 Monitor and method for detecting volatile materials WO1995023335A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
AU17157/95A AU1715795A (en) 1994-02-25 1995-02-27 Monitor and method for detecting volatile materials

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
GB9403680A GB9403680D0 (en) 1994-02-25 1994-02-25 Gas sensor
GB9403680.3 1994-02-25

Publications (1)

Publication Number Publication Date
WO1995023335A1 true WO1995023335A1 (en) 1995-08-31

Family

ID=10750944

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/GB1995/000401 WO1995023335A1 (en) 1994-02-25 1995-02-27 Monitor and method for detecting volatile materials

Country Status (3)

Country Link
AU (1) AU1715795A (en)
GB (1) GB9403680D0 (en)
WO (1) WO1995023335A1 (en)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4638443A (en) * 1983-02-21 1987-01-20 Hitachi, Ltd. Gas detecting apparatus
DE4113583A1 (en) * 1990-04-27 1991-10-31 Europ Composants Electron Measuring control for capacitor testing and sorting - using standard reference component to provide mean measurement value and standard deviation
WO1993003355A1 (en) * 1991-07-29 1993-02-18 Neotronics Limited Device for sensing volatile materials
DE4227727A1 (en) * 1992-08-21 1994-02-24 Buna Ag Determining process conditions in gaseous or liq. media - by multiple sensor system using pattern recognition in an adaptive learning phase

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4638443A (en) * 1983-02-21 1987-01-20 Hitachi, Ltd. Gas detecting apparatus
DE4113583A1 (en) * 1990-04-27 1991-10-31 Europ Composants Electron Measuring control for capacitor testing and sorting - using standard reference component to provide mean measurement value and standard deviation
WO1993003355A1 (en) * 1991-07-29 1993-02-18 Neotronics Limited Device for sensing volatile materials
DE4227727A1 (en) * 1992-08-21 1994-02-24 Buna Ag Determining process conditions in gaseous or liq. media - by multiple sensor system using pattern recognition in an adaptive learning phase

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
A. IKEGAMI, ET AL.: "OLFACTORY DETECTION USING INTEGRATED SENSOR", TRANSDUCERS '85. 1985 INTERNATIONAL CONFERENCE ON SOLID-STATE SENSORS AND ACTUATORS; DIGEST OF TECHNICAL PAPERS; PHILADELPHIA, PA, USA, 11 June 1985 (1985-06-11) - 14 June 1985 (1985-06-14), NEW YORK, US, pages 136 - 139 *
T.C. PEARCE, ET AL.: "MACHINE OLFACTION: INTELLIGENT SENSING OF ODOURS", PROCEEDINGS OF THE 1993 INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, LE TOUQUET, FR, 17 October 1993 (1993-10-17), NEW YORK US, pages 165 - 170, XP000462862 *

Also Published As

Publication number Publication date
AU1715795A (en) 1995-09-11
GB9403680D0 (en) 1994-04-13

Similar Documents

Publication Publication Date Title
US5592402A (en) Method for interpreting complex data and detecting abnormal instrumentor process behavior
US5033015A (en) Automated system for testing an imaging sensor
EP0590077A1 (en) A method for providing general calibration for near infrared instruments for measurement of blood glucose
Srivastava et al. Probabilistic artificial neural network and E-nose based classification of Rhyzopertha dominica infestation in stored rice grains
EP3699582A1 (en) Gas sensing device and method for operating a gas sensing device
EP0172969A2 (en) Discriminant analysis of gas constituents
US5237512A (en) Signal recognition and classification for identifying a fire
WO1995023335A1 (en) Monitor and method for detecting volatile materials
JP3703438B2 (en) Differentiation of hair condition
JP3174188B2 (en) Gas identification device
US4314346A (en) Auxiliary apparatus for a particle analyser
JPH0225134B2 (en)
CN112782233B (en) Gas identification method based on array gas sensor
CN111474293B (en) Method and system for determining bacterial wilt solution
CN114169903A (en) Traditional Chinese medicine digital quality control tracing method capable of fusing nondestructive testing technology
EP1588164B1 (en) Performance improvement for hematology analysis
CN111414752A (en) Method and apparatus, computer readable storage medium and program module framework relating to dish flavour and preparation thereof
JPH11503832A (en) Spectroscopic analysis method for heterogeneous samples
JP3174186B2 (en) Gas identification device
JP6346991B2 (en) Method for extracting information contained in NMR measurement results as a signal
CN111855930B (en) Grain nutrient detection device and method
JP2002243682A (en) Gas detection method and gas detector
CN112798865B (en) Impedance test analysis method and device
US7574328B2 (en) Peak pattern evaluation using spring model
Leardi Data Handling

Legal Events

Date Code Title Description
AK Designated states

Kind code of ref document: A1

Designated state(s): AM AT AU BB BG BR BY CA CH CN CZ DE DK ES FI GB GE HU JP KE KG KP KR KZ LK LT LU LV MD MG MN MW NL NO NZ PL PT RO RU SD SE SI SK TJ TT UA US UZ VN

AL Designated countries for regional patents

Kind code of ref document: A1

Designated state(s): KE MW SD SZ UG AT BE CH DE DK ES FR GB GR IE IT LU MC NL PT SE BF BJ CF CG CI CM GA GN ML MR NE SN TD TG

121 Ep: the epo has been informed by wipo that ep was designated in this application
122 Ep: pct application non-entry in european phase
REG Reference to national code

Ref country code: DE

Ref legal event code: 8642

NENP Non-entry into the national phase

Ref country code: CA