CN1453584A - Fast non-destructive detection method and device of food smell based on gas sensor array technology - Google Patents
Fast non-destructive detection method and device of food smell based on gas sensor array technology Download PDFInfo
- Publication number
- CN1453584A CN1453584A CN 03131660 CN03131660A CN1453584A CN 1453584 A CN1453584 A CN 1453584A CN 03131660 CN03131660 CN 03131660 CN 03131660 A CN03131660 A CN 03131660A CN 1453584 A CN1453584 A CN 1453584A
- Authority
- CN
- China
- Prior art keywords
- gas
- sensor array
- food
- sample
- gas sensor
- Prior art date
- Legal status (The legal status 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 status listed.)
- Granted
Links
Images
Abstract
Some sample of relevant food is estimated by some professionals with their sensory organ or tested through conventional physical and chemical analysis to establish correlative data base. Some other sample is determined with sensor array through carrying the smell of the food to the sensor array reaction chamber via carrier gas, amplifying and filtering the signal from the sensor array, A/D conversion in A/D converter and data processing in computer. The result of computer processing is related with those in the established data base and one knowledge library is obtained through learning for the determination of truth and quality of tested sample. The said method is fast and simple, needs no pre-treatment of the sample and organic solvent extraction, and has the artificial intelligent identification to unknown sample. The present invention facilitates the physical and chemical analysis of food products.
Description
Affiliated technical field
The present invention relates to a kind of detection method and device, refer in particular to fast non-destructive detection method and device based on gas sensor array and pattern-recognition at food aroma and local flavor at food smell.
Background technology
The quality of numerous food product uniqueness and characteristic can be traced back to the chemical substance that generates its smell.Up to now, the way of smell evaluation is finished by trained professional, and individual's assessment is widely different, has very big subjectivity, and also relates to the problem of health and safety in some cases.With the most use in the measurement of odor method of food in recent years is vapor-phase chromatography, and its mensuration need prepare and handle sample, selects suitable extraction solvent, and suitable chromatographic separation condition.Usually want dozens of minutes to 1 hour analysis time.Because volatile matter concentration is generally all lower, can not meet the demands sometimes with gas chromatographic detection, and to unknown material if no standard specimen, usually can't be qualitative.Promptly enable qualitatively, also can only obtain the discriminating of certain or certain several composition, rather than the information of sense of smell integral body; And this detection all needs to destroy sample usually, therefore unlikelyly carries out online Non-Destructive Testing.
By retrieval, relevant Chinese patent is arranged, application number 02111043.8 " a kind of olfactory analog device and olfactory analog method of testing ", application number 02111963.5 " portable intelligent electronic nose and preparation method thereof ", application number 0127299.3 " alarm controller of electronic nose ".Because the odorousness that food distributed is generally all lower, more than several described inventions smell of being used for discerning the food volatilization following problem is arranged: the environment of being tested is not controlled when 1) detecting, in the test environment that opens wide, carry out, and we know that gas sensor is to the composition of test environment on every side, temperature, humidity, partial pressure of oxygen is responsive especially, sensor is a value to the morning that is reflected at of the smell that same food distributed like this, and be a value noon, said nothing of the difference in winter and summer, and different place, partial pressure of oxygen difference in the air ambient, the composition difference, the noise of Chan Shenging can be bigger than required signal like this.(2) feature extraction is simple, only rests in the time domain scope and gets eigenwert, and what have only gets stationary value, can waste a large amount of useful informations like this.(3) used analytical approach is too simple, use error anti-pass BP neural network mostly, and the convergence capabilities of this network and recognition capability is all limited, can only discern the big simple gas of several othernesses, is unsuitable for detecting the smell of food volatilization.
On device, above several patents mostly adopt vacuum pump batch (-type) getter device, this proving installation seems to resemble very much the work of animal nose, but can produce following problem, (1) vacuum pump air-breathing, actual is to be carrier gas with the ambient air, and begin when air-breathing, harvester can produce certain vacuum, and the partial pressure of oxygen around the gas sensor can fluctuate like this, can produce very big interference to the sensor acquisition signal.(2) after the survey food smell is sucked sensor reaction chamber along with air by vacuum pump, can be more and more rarer, cause all the sensors under same odorousness, to work.(3) the sensor acquisition signal is not nursed one's health, and directly the A/D conversion enters computing machine, is to be difficult to realize when middle light concentration gas sample collecting.(4) with oxygen gas sensor being restored back test at once, though can save the test duration, used sensor over oxidation is restored, is exactly not add the smell of being surveyed, and directly sucks air, and the value of sensor also can change.
Other has related U.S. patent, the patent No. is: 6,496,813, patent name is: " Classifying apparatus usinga combination of statistical methods and neuronal networks; designed in particular for odourrecognition (being exclusively used in the statistical method of smell identification and the sorter that neural network combines) ", this patent is mainly paid attention on the sensing data analytical approach, and used statistical method and Neural Network Data result are not fine.The patent No. is: 6,450,008, patent name is: " Food applications ofartificial olfactometry (be used for food manually smell the flavor detection method) ", this invention also is the device that food smell is detected, but in the used detection method, the inventor has used several groups of gas sensors to detect the smell that food distributes, and need pre-service before detection, processing procedure is more loaded down with trivial details.
Summary of the invention
In view of above-mentioned prior art development, purpose of the present invention is exactly that a kind of method of utilizing the food smell Non-Destructive Testing that gas sensor array and pattern-recognition combine will be provided, can carry out quick, easy, objective detection to food quality, food quality is guaranteed thereby accurately, in real time, effectively food production is monitored.
The objective of the invention is to realize by the following method:
A part of sample of getting relevant food please the professional carry out subjective appreciation to it, or it is done conventional physico-chemical analysis, sets up the database relevant with food quality.
Getting another part sample measures with sensor array, by the head space smell in the food being passed to the sensor array reaction chamber with carrier gas, sensor and gas reaction obtain corresponding signal, and this signal carries out the A/D conversion by the A/D capture card and is input to computing machine after modulate circuit amplification and filtering.
With computing machine the data of being gathered are handled, pattern classification system is handled the data of gas sensor array and is connected and learn, train with database in (1) when adopting principal component analysis (PCA), neural network and genetic algorithm to make up high-precision real, obtains a knowledge base.Make it to determine the true and false, quality of sample, the quality of different size such as whether qualified.
In a single day knowledge base forms, just can be since (2) step to the detection of this food.
Realize that device of the present invention is made up of air feed part, part of data acquisition, Computer signal processing section.
Described air feed part is linked in sequence carrier gas generator, carrier gas filtration unit, gas meter to form by gas pipeline;
Described part of data acquisition is a water bath with thermostatic control test casing, be provided with the gas sensor array reaction chamber of bar shaped in the casing, the gas sensor array reaction chamber two ends of this bar shaped are respectively equipped with air intake opening and gas outlet, are respectively equipped with admission line and outlet pipe on this air intake opening and the gas outlet; Admission line is connected the outlet side of the solenoid valve of two-position three way, and the inlet end of solenoid valve is connected with the two-way pipeline, and wherein one road pipeline is directly connected to the air feed part, is sequentially with gas sample generating chamber, solenoid valve on the way in addition, is connected to the air feed part; Outlet pipe reaches the external exhaust usefulness of doing of constant water bath box; The gas sensor array reaction chamber inside surface of described bar shaped is smooth, does not have the gas dead angle, and the even alternative arrangement in the inside a plurality of gas sensors, forms sensor array.
Described gas sample generating chamber is an obturator, and pressure, temperature, humidity sensor are equipped with in the top, and can make institute's test sample like this this produces head space gas under same pressure, temperature, humidity, and the precision of test and repeatability are improved;
Described Computer signal processing section is linked in sequence by signal conditioning circuit plate, A/D capture card and computing machine and forms.Pressure in described modulate circuit plate and the bar shaped gas sensor array reaction chamber in each gas sensor and the gas sample generating chamber, temperature, humidity sensor are exported and are connected, and power supply are provided and solenoid valve is controlled.
The invention has the beneficial effects as follows:
Just constituted gas sensor array owing to the gas sensor of multiple different qualities is combined, evenly alternative arrangement is in the sensor reaction chamber of the smooth bar shaped of inside surface, and structural volume is little, and thermal diffusivity is good, does not have gas residue.Essential surface when the drive of carrier gas simultaneously smell passes through through each sensor, and odorousness does not have diluting effect, sensor easily restores, compare with single gas sensor detection, gas sensor array device not only sensing range is wideer, and its sensitivity, reliability and repeatability all improve a lot;
With constant temperature water bath apparatus the temperature of test environment is controlled under certain condition, with the pressurized air of certain flow after filtering as carrier gas, can control the environment of test like this, guarantee each test condition unanimity, thereby the accuracy of test and repeatability are improved.
Airtight gas sample generating chamber separates with sensor response chamber, behind independent generation head space under certain pressure, humidity, the temperature, brings the head space smell into sensor reaction chamber and sensor response by carrier gas, reduces so as far as possible and disturbs.
Pattern classification system is handled the data of gas sensor array during with high-precision real, has improved sensitivity, selectivity and the repeatability of test, enlarges its identification range.Food the cannot-harm-detection device of the present invention can not only be measured fast and analyze contained trace, trace and even the ultratrace chemical constitution of food smell, especially can rapidly and accurately measurement data be converted to and the corresponding to result of expert's subjective appreciation.It not only can measure different signals according to various smell, and these signals and the signal in the database that study is set up can be compared, and discerns judgement.
The present invention compares with vapor-phase chromatography, and the method technical operation is fast and convenient, and sample does not need pre-treatment, does not also need any organic solvent to extract, and measures a sample less than 5 minutes, and the recognition reaction that unknown sample is had artificial intelligence.Compare with people's sense of smell, measurement result is more objective, reliable.Can be food service industry and product is carried out physicochemical analysis new lossless detection method and device is provided, auxiliary or replace specialty to judge personnel with it.
Description of drawings
Fig. 1: technical scheme synoptic diagram of the present invention.
Fig. 2 a: example of pick-up unit of the present invention.
Fig. 3: gas sensor is arranged synoptic diagram in the embodiment of the invention in the gas sensor array reaction chamber.
Fig. 4: the data processing software interface of the embodiment of the invention.
Fig. 5: the result of the principle component analysis data disposal route of 1 pair of five kinds of cigarette of the embodiment of the invention.
Fig. 6: the result of the principle component analysis data disposal route of 2 pairs of five kinds of different concentration ethanol solution of the embodiment of the invention.
Among the figure: 1. pneumatic accumulator, 2. reduction valve, 3. active carbon filter, 4. gas meter, 5. gas circuit three-way piece, 6. solenoid valve A, 7. water bath with thermostatic control test casing, 8. gaseous sample generating chamber, 9. solenoid valve B, 10. gas sensor array reaction chamber (13 gas sensors are equipped with in the inside), 11. exhausr ports, 12. computing machines, 13.A/D capture card, 14. the sensor array modulate circuit, 15. temperature sensors, 17. humidity sensors, 16. pressure transducer, 18. sample holder, 19. filtered through silica gel devices, s1～s13 are gas sensor.
Embodiment
Consult Fig. 2, food smell the cannot-harm-detection device of the present invention, it is made up of air feed part, part of data acquisition, Computer signal processing section.
The air feed part is linked in sequence carrier gas generator, carrier gas filtration unit, gas meter to form by gas pipeline; Wherein the carrier gas generator is made up of pneumatic accumulator (1) and reduction valve decompression (2); The carrier gas filtration unit is made up of active carbon filter (3) and filtered through silica gel device (19), and gas meter (4) has the function of adjustments of gas flow.
Described part of data acquisition is a water bath with thermostatic control test casing (7), be provided with the gas sensor array reaction chamber (10) of bar shaped in the casing, gas sensor array reaction chamber (10) two ends of this bar shaped are respectively equipped with air intake opening and gas outlet, are respectively equipped with admission line and outlet pipe on this air intake opening and the gas outlet; Admission line is connected the outlet side of the solenoid valve B (9) of two-position three way, the inlet end of solenoid valve is connected with the two-way pipeline, wherein one road pipeline is directly connected to the air feed part, is sequentially with gas sample generating chamber (8), solenoid valve A (6) on the way in addition, is connected to the air feed part; Outlet pipe reaches water bath with thermostatic control test casing
(7) the outer exhaust usefulness of doing; In the gas sensor array reaction chamber (10) of described bar shaped evenly alternative arrangement a plurality of gas sensors (as the s1 among Fig. 3～s13), form sensor array; Described gas sample generating chamber (8) is an obturator, pressure transducer (16), temperature sensor (15), humidity sensor (17) are equipped with in the top, can make institute's test sample like this this produces head space gas under same pressure, temperature, humidity, and the precision of test and repeatability are improved; This another principal feature of water bath with thermostatic control proving installation is that gas sensor array is in the carrier gas of certain flow all the time, has avoided the interference of carrier gas.
The Computer signal processing section comprises sensor array modulate circuit (14), A/D capture card (13) and computing machine (12).Each gas sensor in described sensor array modulate circuit (14) and the bar shaped gas sensor array reaction chamber (10) (s1～s13) and in the gas sample generating chamber pressure transducer (16), temperature sensor (15), the humidity sensor (17) of (8) export and be connected, and power supply is provided and solenoid valve (6), (9) is controlled.Described computing machine (12) not only will be preserved, handle and discern through the multidimensional digital signal of A/D capture card (13) conversion sensor, also will be to the solenoid valve transmitting control commands.
The inorganic, metal oxide N-type semiconductor N sensor that the embodiment of the invention selects for use 13 performances to overlap each other is formed gas sensor array, and its function is that the effect of different scent molecules on its surface is converted into the physical signalling that can survey.The even alternative arrangement of this sensor array makes that carrier gas must be through the surface of all the sensors, as the s1～s13 among Fig. 3 through sensor reaction chamber the time in the gas sensor reaction chamber of strip.
To introduce embodiments of the invention in detail in conjunction with the accompanying drawings now.
As shown in Figure 1, collect the food samples of surveying, sample is demarcated, please cigarette evaluation expert be evaluated by the cigarette that is detected here by professional's subjective appreciation or conventional physico-chemical analysis, obtain the data of expert, set up into database the kinds of cigarettes evaluation; Data in this database will be as the calibration value and the expectation value of later pattern-recognition study, training.
Pick-up unit shown in Figure 2 is as follows at the testing process of cigarette: when a. starts working, open computing machine and start equipment, gas sample generating chamber (8) and gas sensor array reaction chamber (10) have constant temperature water bath apparatus control at a certain temperature.Solenoid valve A (6) closes, solenoid valve B (9) be in make certain flow carrier gas (500ml/min air) after filtering, directly enter sensor reaction chamber, gas sensor reaches stable in the carrier gas of this flow.At the same time the cigarette sample of being surveyed (get 10 gram pipe tobaccos, or inject the flue gas of a 20ml) is contained in the sample holder (18), it is airtight to put into gas sample generating chamber (8) lining, produces head space gas under certain temperature, pressure, humidity.B. after a period of time, keep carrier gas flux constant, open solenoid valve A (6), switching solenoid valve B (9) path makes carrier gas pass through gas sample generating chamber (8), the head space smell of institute's test sample product is taken to gas sensor array reaction chamber (10) and gas sensor array (s1～s13) reaction, produce one group of signal, this group signal is through gas sensor modulate circuit (14), and the electric signal that sensor is produced carries out filtering, amplification; By A/D capture card (15), convert analog electrical signal to digital signal input computing machine (16) again; Computing machine writes down the signal data of all the sensors always in this process.C. stop to gather after writing down the data of a period of time, computer software is to the data of the being gathered data processing through denoising, level and smooth, feature extraction and pattern recognition analysis.Draw the smell kind surveyed, gas componant, concentration estimated value etc.Control electromagnetic valve (6), (9) are got back on the original gas circuit carrier gas simultaneously, i.e. carrier gas directly by sensor reaction chamber, is restored sensor; Generate taking-up institute test sample product in the chamber from gas sample, and it is purged cleaning, so that test next time with carrier gas.
Repeat above a, b, the c step can repeatedly be tested.
In the present embodiment interface of computer data process software embodiment as shown in Figure 4, the numerical value of each sensor directly is reflected on the interface, and can optionally show the response curve of each gas sensor.Can set frequency acquisition and monitor gas sample generating chamber at any time and temperature, humidity and the pressure etc. of gas sensor array reaction chamber, and when gathering, data are saved in the file, and each air valve is controlled.When press stop to gather after, will handle the data of being gathered after pressing the data analysis button again, obtain a result.
Fig. 5 is the result of the principle component analysis data disposal route of five kinds of cigarette of the embodiment of the invention 1 test.
Among the embodiment 1, the present invention has set up the genetic neural network evaluation model of cigarette inherent quality, the gas sensor numerical value that obtains with computing machine is as the input of genetic neural network, the database of front expert evaluation is as the expectation value of network, training set to fragrance, coordination, assorted gas, pungency, pleasant impression and 6 indexs of total points is trained respectively, with the network of training corresponding training set and test set are calculated, can get the result of calculation of training set and test set, shown in table 1 and 2.Table 1 is the accuracy of device of the present invention to training set and test set network calculations result, and table 2 is that device of the present invention is to test set network evaluation value and the contrast of cigarette expert evaluation value.
Table 1 training set and test set genetic neural network network calculations result's accuracy (%)
Index fragrance is coordinated assorted gas excitant pleasant impression total points training set and is returned and declare accuracy 97 94 100 100 100 97 test sets test accuracy 100 100 100 100 100 100 table 2 test set genetic neural network network evaluation values and refer to evaluate sample number into spectrum mark result 123456789 10 fragrant network 27 26 26 26 30 30 31 32 33 32 gas experts 26 26 26 26 30 30 31 31 32 32 association's networks 3.6 3.5 3.6 3.6 4.6 4.4 5.1 5.1 5.1 4.9 with the contrast of cigarette expert evaluation value and transfer experts 3.5 3.5 3.5 3.5 4.5 4.5 5.0 5.0 5.0 5.0 assorted network 11 11 11 11 13 13 13 14 14 14 gas experts 11 11 11 11 13 13 13 13 14 14 to sting
68.4 67.3 70.7 70.7 80.8 79.1 84.7 84.7 87.1 84.1 fens experts 67.0 67.0 70.0 70.0 79.5 79.5 83.5 83.5 86.5 86.5 of expert's 12 12 12 12 13 13 14 14 14 14 property co-net networks, 13 12 13 13 14 15 16 16 16 16 flavor expert's 12 12 13 13 15 15 16 16 16 16 overall networks
2 pairs of 5 kinds of different concentration ethanol solution of embodiment detect, and measure the concentration data of each solution when setting up database with the conventional chemical method, as the calibration value and the expectation value of later on solution being carried out pattern-recognition study, training.The solution of getting 5 milliliters during at every turn with the pick-up unit test sample book is contained in the sample holder (18), and it is airtight to put into gas sample generating chamber (8) lining, and other course of work is identical with embodiment 1.Last computing machine is Fig. 6 to the principal component analysis (PCA) result of five kinds of different concentration ethanol.
In addition, the pick-up unit of realizing above-mentioned functions can both be encapsulated in the chest of ordinary individual's computer cabinet size except that carrier gas storage facility (Air compressing bottle) compactly, and interface and software with personal computer are provided.Therefore this food inspection device maneuverability does not need any pre-service to survey food, as long as quantified sample is put into good seal in the smell generating chamber, operating computer is controlled and detected each valve then.
Claims (4)
1. based on the food smell fast non-destructive detection method of gas sensor array technology, it is characterized in that:
A. a part of sample of getting relevant food please the professional carry out subjective appreciation to it, or it is done conventional physico-chemical analysis, sets up the database relevant with food quality;
B. getting another part sample measures with sensor array, by the head space smell in the food being passed to the sensor array reaction chamber with carrier gas, sensor and gas reaction obtain corresponding signal, this signal carries out the A/D conversion by the A/D capture card and is input to computing machine after modulate circuit amplification and filtering;
C. with computing machine the data of being gathered are handled, pattern classification system is handled the data of gas sensor array and is connected with the database of having set up and learns, trains when adopting principal component analysis (PCA), neural network and genetic algorithm to make up high-precision real, obtain a knowledge base, make it to determine the true and false, quality of sample, the quality of different size such as whether qualified.
Knowledge base is in case form, and just can go on foot since b the detection of this food.
2. implement the food smell quick nondestructive pick-up unit based on the gas sensor array technology of claim 1, form, it is characterized in that by air feed part, part of data acquisition, Computer signal processing section:
Described air feed part is linked in sequence carrier gas generator, carrier gas filtration unit, gas meter to form by gas pipeline;
Described part of data acquisition is a water bath with thermostatic control test casing (7), be provided with the gas sensor array reaction chamber (10) of bar shaped in the casing, gas sensor array reaction chamber (10) two ends of this bar shaped are respectively equipped with air intake opening and gas outlet, are respectively equipped with admission line and outlet pipe on this air intake opening and the gas outlet; Admission line is connected the outlet side of the solenoid valve B (9) of two-position three way, the inlet end of solenoid valve is connected with the two-way pipeline, wherein one road pipeline is connected to the air feed part, is sequentially with gas sample generating chamber (8), solenoid valve A (6) on the way in addition, is connected to the air feed part; Outlet pipe reaches the outer exhaust usefulness of doing of water bath with thermostatic control test casing (7); Arranging a plurality of gas sensors (s1～s13), form sensor array in the gas sensor array reaction chamber (10) of described bar shaped;
3. the food smell quick nondestructive pick-up unit based on the gas sensor array technology according to claim 1, it is characterized in that described gas sample generating chamber (8) is obturator, pressure transducer (16), temperature sensor (15), humidity sensor (17) are equipped with in the top.
4. the food smell quick nondestructive pick-up unit based on the gas sensor array technology according to claim 1, it is characterized in that there is sensor array modulate circuit (14), A/D capture card (13) and computing machine (12) composition that is linked in sequence described Computer signal processing section, the sensor output in described modulate circuit plate (14) and the bar shaped gas sensor array reaction chamber (10) in each gas sensor and the gas sample generating chamber (8) is connected.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNB031316603A CN1194227C (en) | 2003-06-02 | 2003-06-02 | Fast non-destructive detection method and device of food smell based on gas sensor array technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CNB031316603A CN1194227C (en) | 2003-06-02 | 2003-06-02 | Fast non-destructive detection method and device of food smell based on gas sensor array technology |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN1453584A true CN1453584A (en) | 2003-11-05 |
| CN1194227C CN1194227C (en) | 2005-03-23 |
Family
ID=29260458
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CNB031316603A Expired - Fee Related CN1194227C (en) | 2003-06-02 | 2003-06-02 | Fast non-destructive detection method and device of food smell based on gas sensor array technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN1194227C (en) |
Cited By (32)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN100507538C (en) * | 2007-03-28 | 2009-07-01 | 浙江大学 | Method for producing taste sense transducer containing polymer-carbon black |
| CN100507539C (en) * | 2007-03-29 | 2009-07-01 | 浙江大学 | Method for producing taste sense transducer containing electroconductive polymer |
| CN100507537C (en) * | 2007-03-28 | 2009-07-01 | 浙江大学 | Method for producing taste sense transducer containing electroconductive polymer |
| CN100510730C (en) * | 2006-08-04 | 2009-07-08 | 南昌大学 | Polypyrrole-PVC membrane decorative taste sensor array and detecting method |
| CN101881761A (en) * | 2010-03-11 | 2010-11-10 | 大连理工大学 | Humidity adjustable high precision closed loop gas distribution system |
| CN101936912A (en) * | 2010-08-25 | 2011-01-05 | 江苏大学 | Method and device for detecting freshness of fish based on olfaction visualization |
| CN102221571A (en) * | 2010-04-16 | 2011-10-19 | 陕西中烟工业有限责任公司 | Online rapid detector for perfuming uniformity of shredded tobacco |
| CN102507550A (en) * | 2011-10-20 | 2012-06-20 | 江苏大学 | Manufacturing method of food odor visible sensor based on natural pigment |
| CN101419212B (en) * | 2008-12-08 | 2012-10-17 | 浙江大学 | Bird egg freshness detection device and method by utilizing volatile matter |
| CN101419213B (en) * | 2008-12-08 | 2012-11-07 | 浙江大学 | Detection method for bird egg crack by utilizing volatile matter |
| CN103063813A (en) * | 2012-12-26 | 2013-04-24 | 江苏大学 | Rapid nondestructive on-line detection method and apparatus for freshness of fishes |
| CN103308650A (en) * | 2012-03-15 | 2013-09-18 | 森斯瑞股份公司 | Odour and/or gas identification system |
| CN103412099A (en) * | 2013-08-01 | 2013-11-27 | 浙江工商大学 | Device and method for detecting pawpaw storage time |
| CN103412100A (en) * | 2013-08-01 | 2013-11-27 | 浙江工商大学 | Device and method for detecting kiwi fruit storage time |
| CN103575764A (en) * | 2013-07-30 | 2014-02-12 | 中国标准化研究院 | Honey detection method based on support vector machine algorithm optimization |
| CN103630575A (en) * | 2013-12-05 | 2014-03-12 | 大连理工大学 | Multielectrode combined integrated gas sensor |
| CN101368924B (en) * | 2007-03-30 | 2014-03-26 | 索尼德国有限责任公司 | A method of altering the sensitivity and/or selectivity of a chemiresistor sensor array |
| CN101738991B (en) * | 2008-11-26 | 2014-09-10 | 国立成功大学 | Method for detecting out-of-specification quality of product and estimating actually measured value of product |
| CN104483460A (en) * | 2014-09-30 | 2015-04-01 | 山东国家农产品现代物流工程技术研究中心 | Sensor array optimization method for meat detection |
| CN104914225A (en) * | 2015-05-06 | 2015-09-16 | 浙江大学 | Method for forecasting content of clarifying agent in fruit juice based on smell sense fingerprint information |
| CN105866359A (en) * | 2016-04-04 | 2016-08-17 | 浙江理工大学 | Edible oil quality testing system |
| CN105891431A (en) * | 2016-04-04 | 2016-08-24 | 浙江理工大学 | Linseed oil quality detection method |
| US9772317B2 (en) | 2012-07-26 | 2017-09-26 | Sensirion Ag | Method for operating a portable electronic device |
| CN107468210A (en) * | 2017-06-29 | 2017-12-15 | 江苏大学 | A kind of Artificial Olfactory detection method based on terminal detection+internet+big data cloud computing platform |
| CN107688042A (en) * | 2017-08-14 | 2018-02-13 | 中国水产科学研究院渔业机械仪器研究所 | A kind of scallop attributional analysis device based on metal oxide semiconductor sensor |
| TWI622767B (en) * | 2016-09-02 | 2018-05-01 | 國立交通大學 | Meat detection device |
| CN107991396A (en) * | 2017-10-25 | 2018-05-04 | 江苏大学 | A kind of potato full-powder method for quick identification based on flavor analysis |
| CN108535421A (en) * | 2018-05-17 | 2018-09-14 | 长园共创电力安全技术股份有限公司 | Cable insulation defect macromolecular escaping gas detecting system |
| CN109406719A (en) * | 2018-08-31 | 2019-03-01 | 浙江工商大学 | A kind of odor detection system of carrier gas sample introduction |
| CN109724645A (en) * | 2019-01-07 | 2019-05-07 | 江苏大学 | A kind of portable electric nose system of real-time monitoring gold ear fermentation process state |
| CN109932515A (en) * | 2019-03-29 | 2019-06-25 | 廊坊市智恒机器人科技有限公司 | A kind of bionic smell recognition method |
| CN111443161A (en) * | 2020-01-23 | 2020-07-24 | 华东理工大学 | Electronic nose gas-sensitive-chromatographic information fusion and flavor substance on-site detection and analysis method |
-
2003
- 2003-06-02 CN CNB031316603A patent/CN1194227C/en not_active Expired - Fee Related
Cited By (41)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN100510730C (en) * | 2006-08-04 | 2009-07-08 | 南昌大学 | Polypyrrole-PVC membrane decorative taste sensor array and detecting method |
| CN100507537C (en) * | 2007-03-28 | 2009-07-01 | 浙江大学 | Method for producing taste sense transducer containing electroconductive polymer |
| CN100507538C (en) * | 2007-03-28 | 2009-07-01 | 浙江大学 | Method for producing taste sense transducer containing polymer-carbon black |
| CN100507539C (en) * | 2007-03-29 | 2009-07-01 | 浙江大学 | Method for producing taste sense transducer containing electroconductive polymer |
| CN101368924B (en) * | 2007-03-30 | 2014-03-26 | 索尼德国有限责任公司 | A method of altering the sensitivity and/or selectivity of a chemiresistor sensor array |
| CN101738991B (en) * | 2008-11-26 | 2014-09-10 | 国立成功大学 | Method for detecting out-of-specification quality of product and estimating actually measured value of product |
| CN101419212B (en) * | 2008-12-08 | 2012-10-17 | 浙江大学 | Bird egg freshness detection device and method by utilizing volatile matter |
| CN101419213B (en) * | 2008-12-08 | 2012-11-07 | 浙江大学 | Detection method for bird egg crack by utilizing volatile matter |
| CN101881761B (en) * | 2010-03-11 | 2012-11-21 | 大连理工大学 | Humidity adjustable high precision closed loop gas distribution system |
| CN101881761A (en) * | 2010-03-11 | 2010-11-10 | 大连理工大学 | Humidity adjustable high precision closed loop gas distribution system |
| CN102221571A (en) * | 2010-04-16 | 2011-10-19 | 陕西中烟工业有限责任公司 | Online rapid detector for perfuming uniformity of shredded tobacco |
| CN102221571B (en) * | 2010-04-16 | 2013-01-02 | 陕西中烟工业有限责任公司 | Online rapid detector for perfuming uniformity of shredded tobacco |
| CN101936912A (en) * | 2010-08-25 | 2011-01-05 | 江苏大学 | Method and device for detecting freshness of fish based on olfaction visualization |
| CN102507550B (en) * | 2011-10-20 | 2013-11-20 | 江苏大学 | Manufacturing method of food odor visible sensor based on natural pigment |
| CN102507550A (en) * | 2011-10-20 | 2012-06-20 | 江苏大学 | Manufacturing method of food odor visible sensor based on natural pigment |
| CN103308650A (en) * | 2012-03-15 | 2013-09-18 | 森斯瑞股份公司 | Odour and/or gas identification system |
| CN103308650B (en) * | 2012-03-15 | 2017-03-01 | 盛思锐股份公司 | Abnormal smells from the patient and/or gas identifying system |
| US9772317B2 (en) | 2012-07-26 | 2017-09-26 | Sensirion Ag | Method for operating a portable electronic device |
| CN103063813B (en) * | 2012-12-26 | 2014-12-24 | 江苏大学 | Rapid nondestructive on-line detection method and apparatus for freshness of fishes |
| CN103063813A (en) * | 2012-12-26 | 2013-04-24 | 江苏大学 | Rapid nondestructive on-line detection method and apparatus for freshness of fishes |
| CN103575764A (en) * | 2013-07-30 | 2014-02-12 | 中国标准化研究院 | Honey detection method based on support vector machine algorithm optimization |
| CN103575764B (en) * | 2013-07-30 | 2015-12-23 | 中国标准化研究院 | A kind of honey detection method optimized based on algorithm of support vector machine |
| CN103412100A (en) * | 2013-08-01 | 2013-11-27 | 浙江工商大学 | Device and method for detecting kiwi fruit storage time |
| CN103412099A (en) * | 2013-08-01 | 2013-11-27 | 浙江工商大学 | Device and method for detecting pawpaw storage time |
| CN103630575A (en) * | 2013-12-05 | 2014-03-12 | 大连理工大学 | Multielectrode combined integrated gas sensor |
| CN104483460A (en) * | 2014-09-30 | 2015-04-01 | 山东国家农产品现代物流工程技术研究中心 | Sensor array optimization method for meat detection |
| CN104914225A (en) * | 2015-05-06 | 2015-09-16 | 浙江大学 | Method for forecasting content of clarifying agent in fruit juice based on smell sense fingerprint information |
| CN105866359A (en) * | 2016-04-04 | 2016-08-17 | 浙江理工大学 | Edible oil quality testing system |
| CN105891431A (en) * | 2016-04-04 | 2016-08-24 | 浙江理工大学 | Linseed oil quality detection method |
| TWI622767B (en) * | 2016-09-02 | 2018-05-01 | 國立交通大學 | Meat detection device |
| CN107468210A (en) * | 2017-06-29 | 2017-12-15 | 江苏大学 | A kind of Artificial Olfactory detection method based on terminal detection+internet+big data cloud computing platform |
| CN107688042B (en) * | 2017-08-14 | 2019-09-24 | 中国水产科学研究院渔业机械仪器研究所 | A kind of scallop attributional analysis device based on metal oxide semiconductor sensor |
| CN107688042A (en) * | 2017-08-14 | 2018-02-13 | 中国水产科学研究院渔业机械仪器研究所 | A kind of scallop attributional analysis device based on metal oxide semiconductor sensor |
| CN107991396A (en) * | 2017-10-25 | 2018-05-04 | 江苏大学 | A kind of potato full-powder method for quick identification based on flavor analysis |
| CN108535421A (en) * | 2018-05-17 | 2018-09-14 | 长园共创电力安全技术股份有限公司 | Cable insulation defect macromolecular escaping gas detecting system |
| CN109406719A (en) * | 2018-08-31 | 2019-03-01 | 浙江工商大学 | A kind of odor detection system of carrier gas sample introduction |
| CN109724645A (en) * | 2019-01-07 | 2019-05-07 | 江苏大学 | A kind of portable electric nose system of real-time monitoring gold ear fermentation process state |
| CN109932515A (en) * | 2019-03-29 | 2019-06-25 | 廊坊市智恒机器人科技有限公司 | A kind of bionic smell recognition method |
| CN111443161A (en) * | 2020-01-23 | 2020-07-24 | 华东理工大学 | Electronic nose gas-sensitive-chromatographic information fusion and flavor substance on-site detection and analysis method |
| CN111443161B (en) * | 2020-01-23 | 2021-01-05 | 华东理工大学 | Electronic nose gas-sensitive-chromatographic information fusion and flavor substance on-site detection and analysis method |
| WO2021147275A1 (en) * | 2020-01-23 | 2021-07-29 | 高大启 | Gas sensitivity and chromatography multi-information fusion and flavor substance on-site test and analysis method for electronic nose instrument |
Also Published As
| Publication number | Publication date |
|---|---|
| CN1194227C (en) | 2005-03-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN1194227C (en) | Fast non-destructive detection method and device of food smell based on gas sensor array technology | |
| US6839636B1 (en) | Multiple sensing system and device | |
| CN103134850B (en) | A kind of tea leaf quality method for quick based on characteristic perfume | |
| US20020152037A1 (en) | Multiple sensing system and device | |
| CN107085018A (en) | A kind of electric nasus system detected for VOC and stench class gas | |
| JPH11500821A (en) | Method and apparatus for detecting aroma and odor substances and applications | |
| CN1687765A (en) | Portable gas detector | |
| JP2002022692A (en) | Odor measuring apparatus | |
| US11409797B2 (en) | Systems and methods for generating smell data and a database thereof | |
| Nicolas et al. | Establishing the limit of detection and the resolution limits of odorous sources in the environment for an array of metal oxide gas sensors | |
| CN105486812A (en) | Electronic nose stink grade assignment method in continuous environment air quality monitoring process and application | |
| CN1987456A (en) | Predicting method for fruit maturity | |
| CN201955325U (en) | Hand-held device for quickly detecting pesticide residues | |
| JPH07294405A (en) | Apparatus for evaluation of quality of air at inside of blocked-up space | |
| CN109633094A (en) | A kind of odor concentration on-line monitoring method | |
| CN105866190A (en) | Electronic nose device for food detection and detection method | |
| Illahi et al. | Electronic Nose Technology and Application: A Review | |
| Kanade et al. | Development of an E-nose using metal oxide semiconductor sensors for the classification of climacteric fruits | |
| CN100412543C (en) | Gas detecting apparatus and method based on field ionization effect | |
| CN112083047A (en) | Portable gas detection device and detection method | |
| CN1896742A (en) | Space-pollution realtime monitoring indicator | |
| CN1687764A (en) | Device for testing smell of auxiliary material for cigarette | |
| CN209372744U (en) | A kind of multichannel intelligent polluted gas monitoring device | |
| CN109239285B (en) | Detector for measuring meat corruption degree | |
| Sharmilana et al. | Classification and identification of volatile organic solvents based on functional groups using electronic nose |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant | ||
| C19 | Lapse of patent right due to non-payment of the annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |