CN103513013A - Intelligent electronic nose system based device and method for analyzing quality of ice black tea beverage - Google Patents
Intelligent electronic nose system based device and method for analyzing quality of ice black tea beverage Download PDFInfo
- Publication number
- CN103513013A CN103513013A CN201310333110.5A CN201310333110A CN103513013A CN 103513013 A CN103513013 A CN 103513013A CN 201310333110 A CN201310333110 A CN 201310333110A CN 103513013 A CN103513013 A CN 103513013A
- Authority
- CN
- China
- Prior art keywords
- gas
- solenoid valve
- sensor
- sample
- air
- 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.)
- Pending
Links
Images
Landscapes
- Sampling And Sample Adjustment (AREA)
Abstract
The invention relates to an intelligent electronic nose system based device and method for analyzing quality of an ice black tea beverage, and solves the technical problems of subjective differences and harm to human body in the existing detection on volatile gas of a beverage sample by human organs. The device comprises a gas gathering unit, a gas recovery unit, a processing unit and a control unit. The gas gathering unit comprises a gas chamber, a sample room, a first communicating pipe and a second communicating pipe, which constitute a return type circulation path. The gas recovery unit is connected to the gas chamber; the processing unit is connected with the gas recovery unit; and an air inlet mechanism, an air outlet solenoid valve and a collection unit are respectively connected with the control unit. The invention has the advantages that the electronic nose system realizes more comprehensive and objective test results and also avoids harm of the sample gas to human health; and the gas is circulating during gas recovery, so that the gas is more uniformly mixed and the detection data is more accurate.
Description
Technical field
The present invention relates to a kind of technology to beverage Quality Detection, especially relate to a kind of icy bleak tea beverage attributional analysis device based on smart electronics nasus system, and the icy bleak tea beverage Quality Analysis Methods based on smart electronics nasus system.
Background technology
Beverage is people's current consumption product, consumer choose and drinking process in, the fragrance of beverage and taste have larger impact to it.If beverage taste is not suitable for consumer or unstable, in fact can directly affect the market sale of product, relate to manufacturer's benefit.Therefore, manufacturer, in beverage research and development and production run, can carry out sensory evaluation evaluation to it.
For a long time, people judge the quality of beverage etc. by the sense organ of self, and this judgement is usually with very strong subjectivity, and evaluation analysis result tends to along with differences such as age, experiences, has sizable individual difference.Even if same person also can be because health, emotional change draw Different Results.Moreover sense of smell differentiates it is a volatile substance suction process, and long-term experiment can work the mischief to the health of human body, and some bad smell can make the personnel of judging responsive especially and make result wrong; In addition, in sensory evaluation process, often needing has the composition of personnel of the experience of judging to judge group in a large number, and process is comparatively loaded down with trivial details, and evaluation result does not often have repeatability, therefore day by day urgent for novel analytical technology demand.
Publication No. is the Chinese patent application of CN101769889A, the electric nasus system that a kind of quality of agricultural product detects is disclosed, its structure comprises that one mainly completes the gas enrichment module that low concentration smell is collected, one is mainly converted into olfactory signal casing gas path module and the sensor array of electric signal, the one Conditioning Circuits of Sensor numeric field data pretreatment module of mainly sensor array output signal being carried out to filtering, analog to digital conversion, feature extraction, the embedded system that a pair of signal is identified and judged and store with data, one shows and result output module; Described gas enrichment module consists of the adsorption tube, heating wire and the attemperating unit that are filled with adsorbent.This invention also can be collected gas and be identified, but Shortcomings part is gone back in this invention: the one, and function is more single, can not identify agricultural product other samples in addition; But sensor exists randomness to sample collection method, affect test result; The 3rd, the system that do not propose is processed the data of sensor collection, to obtain the method for precise results.
Summary of the invention
The present invention solves existing human body self organ that leans on drink sample volatilization gas is detected, there is subjective differences, and harmful technical matters, a kind of icy bleak tea beverage attributional analysis device and method based on smart electronics nasus system is provided.
Above-mentioned technical matters of the present invention is mainly solved by following technical proposals: a kind of icy bleak tea beverage attributional analysis device based on smart electronics nasus system, comprise gas collection unit, gas production unit, processing unit and control module, described gas collection unit comprises air chamber, sample chamber, the first communicating pipe and the second communicating pipe, air chamber and sample chamber all have import and outlet, be connected to described the first communicating pipe between air chamber outlet and sample chamber entrance, be connected to described the second communicating pipe between air chamber entrance and sample chamber outlet, make air chamber and sample chamber form the circulation path of a hollow, in described gas compartment, be provided with admission gear, on the second communicating pipe, be provided with gas outlet, on gas outlet, be provided with the solenoid valve of giving vent to anger, described collecting unit is connected to air chamber, by gathering gas in air chamber, processing unit is connected with gas production unit, described admission gear, the solenoid valve of giving vent to anger, collecting unit is connected with control module respectively, by control module, control them and carry out work.In the present invention, gas collection unit carries out pre-service to the gas gathering, and gas is circulated and makes gas mixing more even, and according to detecting data, other are diluted, and the data of the gas detection gathering after processing are like this more accurate.This sample is arranged in sample chamber, and carrier gas has air chamber to pass into, and by the first communicating pipe and the second communicating pipe, carrier gas is circulated between air chamber and sample chamber, and the gas that drives sample to give out circulates together.Set out gas port emission gases, for gas collection unit is cleaned to use.Sample to sample gas in gas production unit, output signal is to processing unit, and processing unit carries out analyzing and processing to signal, analyzes the quality of sample.Control module is controlled the work of the executive components such as admission gear, the solenoid valve of giving vent to anger, collecting unit, has made the step of gas collection, gas production.
As a kind of preferred version, described sample chamber comprises drawing and pulling type pedestal, is provided with the cell body of placing sample on pedestal, on the top of pedestal, leaves cavity, and sample chamber outlet and entrance are arranged on the outlet of ,Qie sample chamber, top, sample chamber and are positioned at cell body top position.In this programme, sample chamber adopts drawer type, and this pedestal can pull, and sample is placed on pedestal, facilitates sample is put into sample chamber like this.On pedestal top, leave cavity, for gas communication use, gas is entered by entrance, in cavity, flows, and takes away the gas that sample distributes, and there is any discrepancy again flows out for gas.
As a kind of preferred version, on the second communicating pipe between described air chamber and gas outlet, be provided with the 4th solenoid valve, on the second communicating pipe, be also provided with the first air pump, described the 4th solenoid valve and the first air pump are connected on control module.The 4th solenoid valve is set and facilitates emission gases, when the 4th closed electromagnetic valve, formed the independent route to the first communicating pipe, sample chamber, the second communicating pipe, gas outlet by air chamber, easy to exhaust.Air pump is for driving gas.
As a kind of preferred version, described admission gear has multiple carrier gas air intake opening, these air intake openings comprise air inlet, filtered air air intake opening and inert gas air intake opening, on air inlet, air filtration air intake opening, inert gas air intake opening, be respectively arranged with the first solenoid valve, the second solenoid valve and the 3rd solenoid valve, the first solenoid valve, the second solenoid valve and the 3rd solenoid valve are connected with control module respectively.Admission gear can arrange three kinds of carrier gas air intake openings, and air inlet is used for passing into air, on air filtration air intake opening, is provided with active carbon filtering device, and what pass into is the air after filtering, and what inert gas air intake opening passed into is nitrogen, helium or argon gas.Solenoid control break-make on three air intake openings, and control module is controlled these electromagnetic valve works.Gas production unit gathers the gas in each carrier gas situation, the data that gather is processed, and get the mean value that detects data in three kinds of situations, makes like this result of detection more accurate.
As a kind of preferred version, described gas production unit comprises gas production suction pipe and the sensor array consisting of some sensors, each sensor setting is one independently in chamber, described gas production suction pipe one end is connected on air chamber, on gas production suction pipe port, be provided with the 5th solenoid valve, on gas production suction pipe, be provided with the second air pump, the gas production suction pipe other end is connected respectively on the chamber of each sensor, each sensor is connected on processing unit, on the chamber of each sensor, be also connected with detergent line, in detergent line, be provided with the 6th solenoid valve and the 3rd air pump.
Gas production unit is connected on air chamber, in air chamber, gathers gas, and control module, by controlling the 5th solenoid valve, can be controlled gas production unit and start or stop gas production.The gas gathering is entered into respectively in the chamber of each sensor by suction pipe, and sensor detects gas, and detection data are sent to processing unit.Detergent line is used for passing into pure air, has the 3rd air pump that pneumatic pump is as indoor in each sensor cavity, and sensor is cleaned.Described sensor has 8, is respectively sulfide gas sensor, hydrogen gas sensor, ammonia gas sensor, NOx sensor, charcoal hydrogen component gas sensor, ethanol sensor, benzene class sensor and alkanes sensor.
As a kind of preferred version, in described sample chamber, be provided with stirring air-out mechanism, stir air-out mechanism and comprise rotating shaft, rotating shaft is hollow, rotating shaft is communicated with sample chamber import, in rotating shaft, be connected with stirring pipe, the centre position of stirring pipe is provided with shaft seat, stirring pipe is arranged in rotating shaft by shaft seat, form a T-shaped structure, stirring pipe is hollow seal pipe, and stirring pipe is communicated with rotating shaft, in a side of the termination of stirring pipe, be provided with some the first pores, in another termination of stirring pipe and the opposing side of the first pore, be provided with some the second pores.This stirs air-out mechanism not in sample solution, the in the situation that of ventilation, can be rotated, and solution example is stirred, make sample mix even, and carrier gas is discharged by stirring in air-out mechanism, can evenly mix with sample volatilization gas, it is more accurate to make to detect.In this stirring pipe, the first pore of two ends and the second pore respectively in the opposite direction, can automatic traction stirring pipe be rotated around the shaft like this after gas passes into.
An icy bleak tea beverage Quality Analysis Methods for smart electronics nasus system, comprises the following steps:
Step 1: 20~30 ℃ of experimental situation temperature are set, and humidity is 56%-65%, and the sensor array of gas production unit is cleaned, is passed into pure air in the chamber of each sensor, and operation 8-12min, makes each sensor in original state;
Step 2: gas is carried out to pre-service, icy bleak tea sample to be measured is got to 20ml, pour in sample chamber, first gas collection unit is cleaned, after cleaning, by air intake opening, pass into carrier gas, the escaping gas that drives sample to produce by the air pump 20-30min that circulates with carrier gas in gas collection unit;
Step 3: by gas production suction pipe collected specimens gas, gas is drained in the chamber of each sensor, by control module, control each sensor the gas in chamber is detected, be 40-60s detection time, and each sensor sends to processing unit by the information detecting;
Step 4: processing unit is processed the response curve that obtains each sensor to information, and at 30 points of each response curve up-sampling, the data that each curve sampling is obtained are as input data I nput(t), utilize non-linear stochastic resonance model to calculate signal to noise ratio snr, this non-linear stochastic resonance model algorithm is as follows:
Stochastic resonance system comprises three factors: bistable system, and descriptive system feature carried out by power-actuated overdamping Brownian movement of cycle particle with one in input signal and external noise source in bistable state potential well,
V (x) is non-linear symmetric potential function, and ξ (t) is white Gaussian noise, and its auto-correlation connection function is: E[ξ (t) ξ (0)]=2D δ (t), a is input signal strength, f
0be frequency modulating signal, D is noise intensity, and a, b are all real parameters,
Therefore above formula can change into:
Obtaining signal to noise ratio (S/N ratio) is:
S (ω) is signal spectral density, S
n(Ω) be the noise intensity in signal frequency range;
Get this signal to noise ratio (S/N ratio) peak of curve as signal to noise ratio (S/N ratio) eigenwert;
Step 5: bring input variable into a kind of Nonlinear state space model
In formula:
σ is input variable, signal to noise ratio (S/N ratio) eigenwert, ε be intermediate transfer parameter, τ be initial phase,
for output variable, κ are that real parameter, η are that real parameter, Γ are the real parameter of correcting,
Then define residual error variable:
Defining classification master pattern again:
In formula, L is data length, and just Δ is compared with each threshold value Thr in predefined threshold library, if had
can judge that sample is type under this threshold value, obtain this sample quality information, if
need to re-start type judgement.
As a kind of preferred version, each threshold value of described threshold library is for obtaining in advance, its process is: obtain in advance every class sample, then use analytical equipment to detect every class sample, detecting data input accidental resonance model, analyze, obtain signal to noise ratio (S/N ratio) eigenwert, more every class sample is taken multiple measurements, get the mean value of the signal to noise ratio (S/N ratio) eigenwert that such sample repeatedly obtains as the threshold value Thr of such sample of judgement, the threshold value of all kinds of samples has formed threshold library jointly.
As a kind of preferred version, in step 2, pass into carrier gas and comprise three kinds, its operating process is:
Pass into air: open the first solenoid valve, the 4th solenoid valve, close the second solenoid valve, the 3rd solenoid valve, the 5th solenoid valve and the solenoid valve of giving vent to anger, gas circulates, and then by gas production unit, is gathered;
Pass into filtered air: open the second solenoid valve, the solenoid valve of giving vent to anger, close the first solenoid valve, the 3rd solenoid valve, the 4th solenoid valve and the 5th solenoid valve, remove the carrier gas passing into last time, after completing, removing closes the solenoid valve of giving vent to anger, open the 4th solenoid valve, gas circulates, and then by gas production unit, is gathered;
Pass into inert gas: open the 3rd solenoid valve, the solenoid valve of giving vent to anger, close the first solenoid valve, the second solenoid valve, the 4th solenoid valve and the 5th solenoid valve, remove the carrier gas passing into last time, after completing, removing closes the solenoid valve of giving vent to anger, open the 4th solenoid valve, gas circulates, and then by gas production unit, is gathered;
Processing unit is averaged the data that obtain in three kinds of carrier gas situations, then obtains the response curve of each sensor.In order further to improve, detect degree of accuracy, can be in three kinds of situations collected specimens gas, and will the data that detect in three kinds of situations be averaged.
As a kind of preferred version, step 4 kind is stochastic sampling to each response curve up-sampling or samples in each response curve equal intervals.
Therefore, advantage of the present invention is: 1. built electric nasus system, by system, sample gas detected, make testing result more comprehensively, also more objective, simultaneously also avoided sample gas to work the mischief to health; 2. the Electronic Nose that adopts polytype sensor to form, each sensor is all located at independently and in chamber, sample is detected, and has avoided a plurality of sensors to coexist one case and has formed phase mutual interference, has improved accuracy of detection, quick, reproducible; 3. while gathering gas, gas circulates, and gas is mixed more even, makes the data of detection more accurate.
Accompanying drawing explanation
Accompanying drawing 1 is a kind of structural representation of gas collection unit in the present invention;
Accompanying drawing 2 is another kind of structural representations of gas collection unit in the present invention;
Accompanying drawing 3 is a kind of structural representations that are provided with three kinds of carrier gas air intake openings in the present invention;
Accompanying drawing 4 is a kind of structural representations of gas production unit in the present invention;
Accompanying drawing 5 is a kind of framework schematic diagram that control module of the present invention is connected with sensor, air pump;
Accompanying drawing 6 is a kind of structural representations that stir air-out mechanism in the present invention.
1-gas collection unit 2-air chamber 3-sample chamber 4-the first communicating pipe 5-the second communicating pipe 6-gas outlet 7-solenoid valve 8-air inlet 9-filtered air air intake opening 10-inert gas air intake opening 11-gas production suction pipe 12-first solenoid valve 13-second solenoid valve 14-the 3rd solenoid valve 15-the 4th solenoid valve 16-the 5th solenoid valve 17-the 6th solenoid valve 18-first air pump 19-second air pump 20-pedestal 21-cell body 22-cavity 23-sensor 24-chamber 25-the 3rd air pump 26-processing unit 27-control module 28-gas production unit 29-rotating shaft 30-shaft seat 31-stirring pipe 32-first pore 33-the second pore of giving vent to anger
Embodiment
Below by embodiment, and by reference to the accompanying drawings, technical scheme of the present invention is described in further detail.
Embodiment:
A kind of icy bleak tea beverage attributional analysis device based on smart electronics nasus system of the present embodiment, as shown in Figure 1 and Figure 2, includes gas collection unit 1, gas production unit 28, processes the processing unit 26 that detects data and the control module 27 of controlling executable operations.
In sample chamber 3, be provided with stirring air-out mechanism, stirring air-out mechanism is submerged in sample, as shown in Figure 6, stir air-out mechanism and comprise rotating shaft 29, rotating shaft is hollow, rotating shaft is communicated with sample chamber import, in rotating shaft, be connected with stirring pipe 31, the centre position of stirring pipe is provided with shaft seat, stirring pipe is arranged in rotating shaft by shaft seat, form a T-shaped structure, stirring pipe is hollow seal pipe, stirring pipe is communicated with rotating shaft, in a side of the termination of stirring pipe, be provided with some the first pores 32, in another termination of stirring pipe and the opposing side of the first pore, be provided with some the second pores 33.When passing into carrier gas, carrier gas has sample chamber entrance to enter rotating shaft, has rotating shaft to enter stirring pipe, then has respectively the first opposing pore of two ends and the second pore to discharge, and stirring pipe is rotated around the shaft.
On gas production unit, be also provided with wiper mechanism, for sensor is cleaned.This wiper mechanism comprises detergent line, and this detergent line is connected in each sensor separate chamber, is provided with and controls the 6th solenoid valve 17 of switching and the 3rd air pump 25 of driving gas in detergent line.
As shown in Figure 5, each sensor of gas production unit is controlled being connected on control module also, and control module is controlled working sensor.In addition, the first solenoid valve, the 4th solenoid valve, the 5th solenoid valve, the 6th solenoid valve, the first air pump, the second air pump, the 3rd air pump and all controlled being connected on control module of solenoid valve of giving vent to anger, control module is controlled their work, to complete gas production process.
As shown in Figure 2, give the another kind of structure in gas collection unit, gas collection unit adopts drawer-type structure here, this sample chamber comprise one can pull pedestal 20, on pedestal, be provided with the cell body 21 of placing sample, operating personnel can extract pedestal out, push pedestal after putting into sample again.At pedestal and top, sample chamber, leave and as the outlet of the cavity 22,Gai sample chamber of other circulations and entrance, be all arranged on the outlet of Shang,Qie sample chamber, top and be positioned at cell body top position.
In addition, in order to improve the accuracy that detects data, can also design in three kinds of different carrier gas situations sample gas is detected, finally detection data be averaged.This admission gear will be designed to pass into respectively the mechanism of three kinds of carrier gas like this.,Gai admission gear also comprises filtered air air intake opening 9 and inert gas air intake opening 10 as shown in Figure 3, and the carrier gas that filtered air air intake opening passes into is the air through activated carbon filtration, and the gas that inert gas air intake opening passes into is nitrogen, can be also argon gas or helium.On filtered air air intake opening, be provided with and on the second solenoid valve 13 inert gas air intake openings, be provided with the 3rd solenoid valve 14, the second solenoid valves and the 3rd solenoid valve controlled being connected on control module respectively.
The analytical approach of the icy bleak tea beverage attributional analysis device of the present embodiment based on smart electronics nasus system is as follows: comprises the following steps,
Step 1:
25 ℃ of experimental situation temperature are set, humidity is 60%, sensor array to gas production unit cleans, at first, second, third solenoid valve, all close and in situation, open the 6th battery valve exactly, by the 3rd air pump, clean air is passed in the chamber of each sensor, operation 10min, cleans each sensor and makes each sensor in original state.
Step 2:
At sampler chamber, put into icy bleak tea sample 20ml, , then gas collection unit is also cleaned, only adopt a kind of carrier gas as air situation under, open the first solenoid valve of air inlet, the solenoid valve of giving vent to anger, close the 4th solenoid valve simultaneously, so just make gas collection unit form a gas exhaust piping, pass into air, until gas is all discharged to be full of and is passed into carrier gas in original gas collection unit, then close the battery valve of giving vent to anger, open the 4th solenoid valve, make gas collection unit form back-shaped circulation path, the escaping gas that drives sample to produce by the first air pump 20min that circulates in gas collection unit with carrier gas.
Step 3:
Gas production unit starts gas production, now open the 5th solenoid valve of gas production suction pipe, sample gas is sucked to gas production suction pipe and be passed in the separate chamber of each sensor, control module is controlled each working sensor, gas in chamber is detected, be 50s detection time, and each sensor sends to processing unit by the data that detect.
Step 4:
Each sensor detects the value of meeting with a response, using time and response intensity as coordinate axis, obtain the response curve of each sensor, 8 sensors obtain 8 bar response curves, then equidistantly at 30 points of each response curve up-sampling, obtain 240 each point data as one group of input data I nput(t), then utilize non-linear stochastic resonance model to calculate signal to noise ratio snr, this non-linear stochastic resonance model algorithm is:
Stochastic resonance system comprises three factors: bistable system, and descriptive system feature carried out by power-actuated overdamping Brownian movement of cycle particle with one in input signal and external noise source in bistable state potential well,
V (x) is non-linear symmetric potential function, and ξ (t) is white Gaussian noise, and its auto-correlation connection function is: E[ξ (t) ξ (0)]=2D δ (t), a is input signal strength, f
0be frequency modulating signal, D is noise intensity, and a, b are all real parameters,
Therefore above formula can change into:
Obtaining signal to noise ratio (S/N ratio) is:
S (ω) is signal spectral density, S
n(Ω) be the noise intensity in signal frequency range;
Input data I nput(t) be updated to
in formulacalculate signal to noise ratio snr, this signal to noise ratio snr is curve, gets this signal to noise ratio (S/N ratio) peak of curve as signal to noise ratio (S/N ratio) eigenwert.
Step 5:
By signal to noise ratio (S/N ratio) eigenwert, be that input variable is brought a kind of Nonlinear state space model into
In formula:
σ is input variable, signal to noise ratio (S/N ratio) eigenwert, ε be intermediate transfer parameter, τ be initial phase,
for output variable, κ are that real parameter, η are that real parameter, Γ are the real parameter of correcting,
Then define residual error variable:
Defining classification master pattern again:
In formula, L is data length, and just Δ is compared with each threshold value Thr in predefined threshold library, if had
can judge that sample is type under this threshold value, obtain this sample quality information, if
need to re-start type judgement.
Wherein above-mentioned each threshold value of the threshold library of mentioning Thr is for obtaining in advance, its process is: obtain in advance every class sample, as first day to the icy bleak tea sample of eight days, then use analytical equipment to detect every class sample, detecting data input accidental resonance model, analyze, obtain signal to noise ratio (S/N ratio) eigenwert, every class sample is taken multiple measurements, for example the icy bleak tea sample of first day is carried out 10 times, obtain 10 signal to noise ratio (S/N ratio) eigenwerts, then measurement is got to the mean value of the signal to noise ratio (S/N ratio) eigenwert that such sample repeatedly obtains as the threshold value Thr of such sample of judgement, obtain the threshold value of all kinds of samples, the threshold value of all kinds of samples has formed threshold library jointly.
,Ruo admission gear adopts three kinds of carrier gas air intake structures in addition, in step 2, increases the step that passes into other carrier gas, and whole operating process is:
If by pass into forward for air, filtered air, inert gas forward.
Pass into air: open the first solenoid valve, the 4th solenoid valve, close the second solenoid valve, the 3rd solenoid valve, the 5th solenoid valve and the solenoid valve of giving vent to anger, gas circulates, and then by gas producing device, is gathered;
Pass into filtered air: open the second solenoid valve, the solenoid valve of giving vent to anger, close the first solenoid valve, the 3rd solenoid valve, the 4th solenoid valve and the 5th solenoid valve, remove the carrier gas passing into last time, after completing, removing closes the solenoid valve of giving vent to anger, open the 4th solenoid valve, gas circulates, and then by gas producing device, is gathered;
Pass into inert gas: open the 3rd solenoid valve, the solenoid valve of giving vent to anger, close the first solenoid valve, the second solenoid valve, the 4th solenoid valve and the 5th solenoid valve, remove the carrier gas passing into last time, after completing, removing closes the solenoid valve of giving vent to anger, open the 4th solenoid valve, gas circulates, and then by gas producing device, is gathered;
And processing unit is to the data that obtain are averaged, then obtain the response curve of each sensor in three kinds of carrier gas situations.
Specific embodiment described herein is only to the explanation for example of the present invention's spirit.Those skilled in the art can make various modifications or supplement or adopt similar mode to substitute described specific embodiment, but can't depart from spirit of the present invention or surmount the defined scope of appended claims.
Although more used the terms such as gas collection unit, air chamber, sample chamber, the first communicating pipe, the second communicating pipe herein, do not got rid of the possibility of using other term.Use these terms to be only used to describe more easily and explain essence of the present invention; They are construed to any additional restriction is all contrary with spirit of the present invention.
Claims (10)
1. the icy bleak tea beverage attributional analysis device based on smart electronics nasus system, it is characterized in that: comprise gas collection unit (1), gas production unit (28), processing unit (26) and control module (27), described gas collection unit comprises air chamber (2), sample chamber (3), the first communicating pipe (4) and the second communicating pipe (5), air chamber and sample chamber all have import and outlet, be connected to described the first communicating pipe between air chamber outlet and sample chamber entrance, be connected to described the second communicating pipe between air chamber entrance and sample chamber outlet, make air chamber and sample chamber form the circulation path of a hollow, in described gas compartment, be provided with admission gear, on the second communicating pipe, be provided with gas outlet (6), on gas outlet, be provided with the solenoid valve of giving vent to anger (7), described gas production unit is connected to air chamber, by gathering gas in air chamber, processing unit is connected with gas production unit, described admission gear, the solenoid valve of giving vent to anger, collecting unit is connected with control module respectively, by control module, control them and carry out work.
2. a kind of icy bleak tea beverage attributional analysis device based on smart electronics nasus system according to claim 1, it is characterized in that described sample chamber (3) comprises drawing and pulling type pedestal (20), on pedestal, be provided with the cell body (21) of placing sample, on the top of pedestal, leave cavity (22), sample chamber outlet and entrance are arranged on the outlet of ,Qie sample chamber, top, sample chamber and are positioned at cell body top position.
3. a kind of icy bleak tea beverage attributional analysis device based on smart electronics nasus system according to claim 1 and 2, it is characterized in that being provided with the 4th solenoid valve (15) on the second communicating pipe (5) between described air chamber (2) and gas outlet, on the second communicating pipe, be also provided with the first air pump (18), described the 4th solenoid valve and the first air pump are connected on control module (27).
4. a kind of icy bleak tea beverage attributional analysis device based on smart electronics nasus system according to claim 3, it is characterized in that described admission gear has multiple carrier gas air intake opening, these air intake openings comprise air inlet (8), filtered air air intake opening (9) and inert gas air intake opening (10), air inlet, filtered air air intake opening, on inert gas air intake opening, be respectively arranged with the first solenoid valve (12), the second solenoid valve (13) and the 3rd solenoid valve (14), the first solenoid valve (12), the second solenoid valve (13) is connected with control module (27) respectively with the 3rd solenoid valve.
5. a kind of icy bleak tea beverage attributional analysis device based on smart electronics nasus system according to claim 4, it is characterized in that described gas production unit (28) comprises gas production suction pipe (11) and the sensor array consisting of some sensors (23), each sensor setting is one independently in chamber (24), described gas production suction pipe one end is connected on air chamber, on gas production suction pipe port, be provided with the 5th solenoid valve, on gas production suction pipe, be provided with the second air pump (19), the gas production suction pipe other end is connected respectively on the chamber of each sensor, each sensor is connected on processing unit (26), on the chamber of each sensor, be also connected with detergent line, in detergent line, be provided with the 6th solenoid valve (17) and the 3rd air pump (25), described sensor (23) has 8, be respectively sulfide gas sensor, hydrogen gas sensor, ammonia gas sensor, NOx sensor, charcoal hydrogen component gas sensor, ethanol sensor, benzene class sensor and alkanes sensor.
6. a kind of icy bleak tea beverage attributional analysis device based on smart electronics nasus system according to claim 1, it is characterized in that being provided with stirring air-out mechanism in described sample chamber (3), stir air-out mechanism and comprise rotating shaft (29), rotating shaft is hollow, rotating shaft is communicated with sample chamber import, in rotating shaft, be connected with stirring pipe (31), the centre position of stirring pipe is provided with shaft seat, stirring pipe is arranged in rotating shaft by shaft seat, form a T-shaped structure, stirring pipe is hollow seal pipe, stirring pipe is communicated with rotating shaft, in a side of the termination of stirring pipe, be provided with some the first pores (32), in another termination of stirring pipe and the opposing side of the first pore, be provided with some the second pores (33).
7. the icy bleak tea beverage Quality Analysis Methods based on smart electronics nasus system, the device that adopts claim 1-6 any one to describe, is characterized in that: comprise the following steps:
Step 1: 20~30 ℃ of experimental situation temperature are set, and humidity is 56%-65%, and the sensor array of gas production unit is cleaned, is passed into pure air in the chamber of each sensor, and operation 8-12min, makes each sensor in original state;
Step 2: gas is carried out to pre-service, icy bleak tea sample to be measured is got to 20ml, pour in sample chamber, first gas collection unit is cleaned, after cleaning, by air intake opening, pass into carrier gas, the escaping gas that drives sample to produce by the air pump 20-30min that circulates with carrier gas in gas collection unit;
Step 3: by gas production unit collected specimens gas, gas is drained in the chamber of each sensor in gas production unit, by control module, control each sensor the gas in chamber is detected, be 40-60s detection time, and each sensor sends to processing unit by the information detecting;
Step 4: processing unit is processed the response curve that obtains each sensor to information, and at 30 points of each response curve up-sampling, the data that each curve sampling is obtained are as input data I nput(t), substitution non-linear stochastic resonance model calculates signal to noise ratio snr, and this non-linear stochastic resonance model algorithm is as follows:
Stochastic resonance system comprises three factors: bistable system, and descriptive system feature carried out by power-actuated overdamping Brownian movement of cycle particle with one in input signal and external noise source in bistable state potential well,
V (x) is non-linear symmetric potential function, and ξ (t) is white Gaussian noise, and its auto-correlation connection function is: E[ξ (t) ξ (0)]=2D δ (t), a is input signal strength, f
0be frequency modulating signal, D is noise intensity, and a, b are all real parameters,
Therefore above formula can change into:
Obtaining signal to noise ratio (S/N ratio) is:
S (ω) is signal spectral density, S
n(Ω) be the noise intensity in signal frequency range;
Get this signal to noise ratio (S/N ratio) peak of curve as signal to noise ratio (S/N ratio) eigenwert;
Step 5: bring input variable into a kind of Nonlinear state space model
In formula:
σ is input variable, signal to noise ratio (S/N ratio) eigenwert, ε be intermediate transfer parameter, τ be initial phase,
for output variable, κ are that real parameter, η are that real parameter, Γ are the real parameter of correcting,
Then define residual error variable:
Defining classification master pattern again:
In formula, L is data length, and just Δ is compared with each threshold value Thr in predefined threshold library, if had
can judge that sample is type under this threshold value, obtain this sample quality information, if
need to re-start type judgement.
8. a kind of icy bleak tea beverage Quality Analysis Methods based on smart electronics nasus system according to claim 7, it is characterized in that each threshold value of described threshold library is for obtaining in advance, its process is: obtain in advance every class sample, then use analytical equipment to detect every class sample, detecting data input accidental resonance model, analyze, obtain signal to noise ratio (S/N ratio) eigenwert, again every class sample is taken multiple measurements, get the mean value of the signal to noise ratio (S/N ratio) eigenwert that such sample repeatedly obtains as the threshold value Thr of such sample of judgement, the threshold value of all kinds of samples has formed threshold library jointly.
9. according to a kind of icy bleak tea beverage Quality Analysis Methods based on smart electronics nasus system described in claim 7 or 8, it is characterized in that in step 2, passing into carrier gas comprises three kinds, its operating process is:
Pass into air: open the first solenoid valve, the 4th solenoid valve, close the second solenoid valve, the 3rd solenoid valve, the 5th solenoid valve and the solenoid valve of giving vent to anger, gas circulates, and then by gas production unit, is gathered;
Pass into filtered air: open the second solenoid valve, the solenoid valve of giving vent to anger, close the first solenoid valve, the 3rd solenoid valve, the 4th solenoid valve and the 5th solenoid valve, remove the carrier gas passing into last time, after completing, removing closes the solenoid valve of giving vent to anger, open the 4th solenoid valve, gas circulates, and then by gas production unit, is gathered;
Pass into inert gas: open the 3rd solenoid valve, the solenoid valve of giving vent to anger, close the first solenoid valve, the second solenoid valve, the 4th solenoid valve and the 5th solenoid valve, remove the carrier gas passing into last time, after completing, removing closes the solenoid valve of giving vent to anger, open the 4th solenoid valve, gas circulates, and then by gas production unit, is gathered;
Processing unit is averaged the data that obtain in three kinds of carrier gas situations, then obtains the response curve of each sensor.
10. according to a kind of icy bleak tea beverage Quality Analysis Methods based on smart electronics nasus system described in claim 7 or 8, it is characterized in that in step 4 that to each response curve up-sampling be stochastic sampling or in each response curve equal intervals sampling.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201310333110.5A CN103513013A (en) | 2013-08-01 | 2013-08-01 | Intelligent electronic nose system based device and method for analyzing quality of ice black tea beverage |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201310333110.5A CN103513013A (en) | 2013-08-01 | 2013-08-01 | Intelligent electronic nose system based device and method for analyzing quality of ice black tea beverage |
Publications (1)
Publication Number | Publication Date |
---|---|
CN103513013A true CN103513013A (en) | 2014-01-15 |
Family
ID=49896063
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201310333110.5A Pending CN103513013A (en) | 2013-08-01 | 2013-08-01 | Intelligent electronic nose system based device and method for analyzing quality of ice black tea beverage |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN103513013A (en) |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106289887A (en) * | 2016-08-10 | 2017-01-04 | 天津大学 | A kind of bionical method of sampling respiration of Electronic Nose |
CN107064238A (en) * | 2017-03-31 | 2017-08-18 | 浙江大学 | A kind of portability tea perfume detection electric nasus system and its detection method |
CN108362531A (en) * | 2018-04-20 | 2018-08-03 | 吉林省圣宜达科技有限公司 | A kind of gas monitoring system suitable for underground coal mine |
CN109738585A (en) * | 2018-12-30 | 2019-05-10 | 盐城工学院 | A kind of electronic nose |
CN114002306A (en) * | 2021-11-12 | 2022-02-01 | 暨南大学 | Membrane sample injection structure for extracting volatile organic compounds in water through bubble enrichment |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN202181215U (en) * | 2011-06-30 | 2012-04-04 | 湖北省宏源药业有限公司 | Device for synthesizing lithium hexafluorophosphate |
CN102654495A (en) * | 2012-05-21 | 2012-09-05 | 浙江工商大学 | Electronic nose used for detecting maturity of cherimoya and detection method of electronic nose |
CN102879432A (en) * | 2012-10-22 | 2013-01-16 | 浙江工商大学 | Method of using electronic nose for detecting freshness of tilapia |
CN102879436A (en) * | 2012-10-22 | 2013-01-16 | 浙江工商大学 | Method of using electronic nose for detecting freshness of river crucian carp |
US20130061692A1 (en) * | 2011-08-25 | 2013-03-14 | Muresan Enterprize | Electronic nose apparatus |
-
2013
- 2013-08-01 CN CN201310333110.5A patent/CN103513013A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN202181215U (en) * | 2011-06-30 | 2012-04-04 | 湖北省宏源药业有限公司 | Device for synthesizing lithium hexafluorophosphate |
US20130061692A1 (en) * | 2011-08-25 | 2013-03-14 | Muresan Enterprize | Electronic nose apparatus |
CN102654495A (en) * | 2012-05-21 | 2012-09-05 | 浙江工商大学 | Electronic nose used for detecting maturity of cherimoya and detection method of electronic nose |
CN102879432A (en) * | 2012-10-22 | 2013-01-16 | 浙江工商大学 | Method of using electronic nose for detecting freshness of tilapia |
CN102879436A (en) * | 2012-10-22 | 2013-01-16 | 浙江工商大学 | Method of using electronic nose for detecting freshness of river crucian carp |
Non-Patent Citations (3)
Title |
---|
惠国华等: "基于电子鼻系统的粮食霉变检测方法研究", 《中国食品学报》 * |
邹小波等: "电子鼻在饮料识别中的应用研究", 《农业工程学报》 * |
郑海霞等: "基于电子鼻的牛奶品质预测方法研究", 《中国食品学报》 * |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106289887A (en) * | 2016-08-10 | 2017-01-04 | 天津大学 | A kind of bionical method of sampling respiration of Electronic Nose |
CN106289887B (en) * | 2016-08-10 | 2018-11-13 | 天津大学 | A kind of bionical method of sampling respiration of electronic nose |
CN107064238A (en) * | 2017-03-31 | 2017-08-18 | 浙江大学 | A kind of portability tea perfume detection electric nasus system and its detection method |
CN107064238B (en) * | 2017-03-31 | 2019-05-24 | 浙江大学 | A kind of portability tea perfume detection electric nasus system and its detection method |
CN108362531A (en) * | 2018-04-20 | 2018-08-03 | 吉林省圣宜达科技有限公司 | A kind of gas monitoring system suitable for underground coal mine |
CN109738585A (en) * | 2018-12-30 | 2019-05-10 | 盐城工学院 | A kind of electronic nose |
CN114002306A (en) * | 2021-11-12 | 2022-02-01 | 暨南大学 | Membrane sample injection structure for extracting volatile organic compounds in water through bubble enrichment |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN103558351A (en) | Green tea beverage quality analysis apparatus based on intelligent electronic nose system, and method | |
CN103513013A (en) | Intelligent electronic nose system based device and method for analyzing quality of ice black tea beverage | |
CN103512921A (en) | Intelligent electronic nose system based device and method for analyzing freshness of pear | |
CN103512795A (en) | Intelligent electronic nose system based device and method for analyzing quality of Tie Guanyin beverage | |
CN103424525B (en) | Milk quality detection equipment and method | |
CN103091121B (en) | A kind of air purifier test device and method of testing thereof | |
CN105223222B (en) | Identification method for porphyra haitanensis in different harvesting periods | |
WO2016090855A1 (en) | Automatic white wine blending system based on odor control | |
CN108896706A (en) | The foul gas multiple spot centralization electronic nose instrument on-line analysis of big data driving | |
CN102879432A (en) | Method of using electronic nose for detecting freshness of tilapia | |
CN102253230A (en) | Automatic analyzer and analysis method of blood platelets | |
CN103512922A (en) | Electrical fire detection system and method based on electronic nose system | |
CN105067252A (en) | Water chilling unit fault detection method based on improved FastICA | |
CN105675745A (en) | Device and method for quantitative measurement of human body emitted volatile organic compounds | |
CN104713989B (en) | A kind of gaseous metabolism based on mixing chamber technology detection device and method | |
CN212301487U (en) | Multi-channel fumigant gas concentration detector | |
CN209400274U (en) | A kind of water body environment DNA intelligent acquisition device | |
CN106053387A (en) | Exhaled air detection method and device | |
CN209727908U (en) | A kind of electronic nose equipment based on food inspection | |
CN103512920A (en) | Intelligent electronic nose system based device and method for analyzing quality of lemon tea beverage | |
CN110664408B (en) | Alveolar gas collection system, cleaning system and alveolar gas collection method | |
CN107532978A (en) | The apparatus and method of detection pollution position, and computer readable recording medium storing program for performing | |
CN105527414A (en) | Method and apparatus for measuring concentrations of various exhaled gases by use of one gas sensor | |
CN108760600A (en) | A kind of detection method for air purifier Removal efficiency of particulate matter | |
CN114136854A (en) | Multi-working-condition oil fume purification device performance evaluation system and method |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
AD01 | Patent right deemed abandoned |
Effective date of abandoning: 20160601 |
|
C20 | Patent right or utility model deemed to be abandoned or is abandoned |