| CPC G01N 30/88 (2013.01) [G01N 33/0032 (2013.01); G01N 33/0034 (2013.01); G01N 33/0062 (2013.01); G06N 3/045 (2023.01); G01N 2030/8804 (2013.01); G01N 2030/8809 (2013.01)] | 10 Claims |
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1. A method for multi-information fusion of gas sensitivity and chromatography and on-site detection and analysis of flavor substances using an electronic nose instrument, wherein the electronic nose instrument comprises a gas sensor array module I, a capillary gas chromatographic column module II, an automatic headspace sampling module III, a computer control and data analysis module IV, an automatic lifter V for headspace sampling, a large-volume headspace vapor generation device VI and two auxiliary gas sources VII-1 and VII-2, which are configured to implement an on-site real-time detection and intelligent analysis of such flavor substances as foods, condiments, fragrances and flavors, and petroleum waxes; wherein,
the gas sensor array module I comprises a gas sensor array I-1, an annular working chamber I-2 for installing the gas sensor array I-1, a thermal insulation layer I-3, a partition plate I-4, a fan I-5 and a resistance heating element I-6, and is located in a middle right part of the electronic nose instrument;
the capillary gas chromatographic column module II comprises a capillary gas chromatographic column II-1, a detector II-2, an amplifier II-3, a recorder II-4, a thermal insulation layer II-5, a fan II-6, a resistance heating wire II-7 and an inlet port II-8, and is located in a right upper part of the electronic nose instrument;
the automatic headspace sampling module III comprises a first micro vacuum pump III-1, a first flowmeter III-2, a first throttle valve III-3, a first two-position two-port electromagnetic valve III-4, a second two-position two-port electromagnetic valve III-5, a two-position three-port electromagnetic valve III-6, a second micro vacuum pump III-7, a third two-position two-port electromagnetic valve III-8, a fourth two-position two-port electromagnetic valve III-9, a side-hole sampling needle III-10, a first pressure relief valve III-11, a first purifier III-12, a second throttle valve III-13, a second pressure relief valve III-14, a second purifier III-15, a third throttle valve III-16, a second flowmeter III-17, a fourth throttle valve III-18 and a fifth throttle valve III-19, and is located in a right lower part of the electronic nose instrument;
main constructional units of the computer control and data analysis module IV comprise an A/D data acquisition card IV-1, a driving and control circuit board IV-2, a computer mainboard IV-3, a 4-path precision DC stabilized power supply IV-4, a WIFI board card IV-5 and a display IV-6, and is located in a left side of the electronic nose instrument;
main constructional units of the automatic lifter V for headspace sampling comprise a support disc V-1, a step motor V-2, a screw mechanism V-3 and a gear transmission mechanism V-4, and is located in a right front lower part of the electronic nose instrument;
main constructional units of the large-volume headspace vapor generation device VI comprise a thermal insulation layer VI-1, a resistance heating wire VI-2, a heat conduction sleeve VI-3, a temperature sensor VI-4, a tested sample VI-5, a 250 ml glass sample bottle VI-6, a silicone rubber sealing sheet VI-7 and a cup cover VI-8; one electronic nose instrument is provided with 4-6 large-volume headspace vapor generation devices VI, and the role of the large-volume headspace vapor generation device VI is to make 10 ml-30 ml tested sample within the 250 ml glass sample bottle VI-6 at a constant temperature of 40-80±0.1° C. for about 30 min in a test site, and generate 220 ml-240 ml headspace vapor; the automatic lifter V is employed to make the large-volume headspace vapor generation device VI up 20 mm within 3 s, so that the side-hole sampling needle III-10 fixed under a gas inlet port of the annular working chamber I-2 penetrates through a silicone rubber sealing sheet VI-7 and contacts with headspace vapor in the 250 ml glass sample bottle VI-6; and
a gas sampling period of a headspace vapor for the tested sample VI-5 by the electronic nose instrument is T-300-600 s, and T=480 s by default; in a gas sampling period T, setting the sampling time of a tested headspace vapor of the capillary gas chromatographic column module II to be earlier than that of the gas sensor array module I; in a case of T=480 s, setting the default headspace vapor sampling time of the capillary gas chromatographic column module II to be 1 s earlier than that of the module I; setting the default ratios of a flow rate, a sampling duration and an accumulated sampling volume of the gas sensor array module I to the capillary gas chromatographic column module II for a tested odor sample to be 1,000:6 ml/min, 60:1 s and 1,000:0.1 ml (theoretical value) in order; and performing, by the computer control and data analysis module IV, a sensitive information selection and analysis operation on the gas sensor array module I and the capillary gas chromatographic column module II simultaneously;
in the gas sampling period T, pumping, by the first micro vacuum pump III-1 and the second micro vacuum pump III-7, the headspace vapor into the gas sensor array module I and the capillary gas chromatographic column module II, respectively, so that the gas sensor array I-1 and the capillary gas chromatographic column II-1 generate a sensitive response, respectively; obtaining, by the electronic nose instrument, 1 group of gas sensor response curves and 1 gas chromatogram to serve as an analog signal of gas sensitivity and gas chromatography obtained by perceiving an odorous sample by the electronic nose instrument;
in the gas sampling period T, extracting, by the computer control and data analysis module IV, 48 response information variables from a plurality of response curves of the gas sensor array module I, selecting 21 feature information variables from a finite-duration semi-separated chromatogram of the capillary gas chromatographic column module II, and therefore obtaining, by the electronic nose instrument, a 69-dimensional response vector x(τ)∈R69, which is referred to as a pattern hereinafter; saving the response vector in a corresponding data file of a hard disk in the computer mainboard IV-3; and sending the pattern data to a cloud terminal and many specified fixed/mobile terminals through a WIFI routing module;
on-site detecting, by the electronic nose instrument, various flavor substances such as foods, condiments, fragrances and flavors, and petroleum waxes for a long time over many months and years to form an big odor data X, and establishing, by a part of data of the big odor data X, a corresponding relation between a gas sensitivity/gas chromatography response and an odor type, an intensity grade and main component concentrations of the flavor substances; and
in a learning stage, learning, by a cascade machine learning model of the computer control and data analysis module IV, a normalized pre-processing big odor data X offline to determine the structure and parameters of the cascade machine learning model, and learning a gas sensitivity/gas chromatography recent response online to finely tune the parameters of the cascade machine learning model; in a decision-making stage, online determining, by the cascade machine learning model, types of various foods, condiments, fragrances and flavors, and petroleum waxes according to a gas sensitivity/gas chromatography current response vector x(τ), and quantitatively predicting an intensity grade and main component concentration values of odors.
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