CN109060892A - SF based on graphene composite material sensor array6Decompose object detecting method - Google Patents
SF based on graphene composite material sensor array6Decompose object detecting method Download PDFInfo
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Abstract
The present invention relates to a kind of SF based on graphene composite material sensor array6Decompose object detecting method, comprising: processing prepares sensor array；Preparation gained sensor array is arranged in sealed gas chamber and carries out signal acquisition, and bootloader；Air-sensitive test is carried out to sensor array and is stored test result as sample；Building gas identification network model simultaneously identifies atmosphere.Energy consumption can be effectively reduced by the way that graphene-metal oxide nano gas sensitive is added in sensor array in the present invention；Network model is identified by building gas and combines sensor array, it can be to SF6Gas decomposition product is effectively identified.
Description
Technical field
The invention belongs to gas decomposition product detection fields, and in particular to one kind is based on graphene composite material sensor array
The SF of column6Decompose object detecting method.
Background technique
Sulfur hexafluoride (SF6) in gas insulated combined electrical equipment, breaker, quilt in the high-tension electricities equipment such as gas insulated bus
It is widely applied.The study found that SF6Gas can decompose generation fluorination thionyl (SOF under high temperature discharge effect2), fluorination sulfonyl
(SO2F2), sulfur dioxide (SO2) and hydrogen sulfide (H2A series of decomposition products such as S), and electric discharge in decomposition product constituent content and equipment
Degree of strength is related, can be used for equipment fault diagnosis.Traditional gas chromatography mass spectrometry, infrared absorption spectroscopy precision are high, but
It cannot achieve SF6The on-line monitoring of decomposition product.
Based on the gas sensor of nano material because its small in size, at low cost, good portability, on-line monitoring potentiality are big etc. excellent
Point, in SF6It is gradually applied in gas decomposition product detection.But sensors with auxiliary electrode is there are the higher problem of operating temperature, and right
SF6The cross sensitivity problem of the multiple gases generated after decomposition does not have very good solution.
Graphene has the characteristics that high-specific surface area, good electron mobility and low noise, by aoxidizing it with metal
Object is compound, available to have highly sensitive gas sensitive at low temperature, and it is high can be effectively improved traditional devices operating temperature
The problem of.
Summary of the invention
For presently, there are SF6Decomposition product constituent content test problems, the invention proposes one kind to be received based on graphene
The solution of nano composite material sensor array.It is high for operating temperature existing for traditional gas sensor (to be generally greater than 200
DEG C) the problem of, the present invention constructs composite material by way of introducing graphene, to reduce biosensor power consumption.Meanwhile for
The problem of single-sensor output information deficiency, the present invention can increase information by way of designing novel sensor array
Output quantity.In addition, for single-sensor cross sensitivity the problem of, the present invention utilizes constructed sensor array, and ties
Syntype recognizer solves.
A kind of SF based on graphene composite material sensor array6Decompose object detecting method, comprising:
Step S100: processing prepares sensor array；
Step S200: preparation gained sensor array is arranged in sealed gas chamber and carries out signal acquisition, and is powered on initial
Change；
Step S300: air-sensitive test is carried out to sensor array and is stored test result as sample；
Step S400: building gas identification network model simultaneously identifies atmosphere.
Further, the step S100 includes:
Step S101: sensor base processing: by electron beam evaporation deposition technique and photoetching process in sensor substrate
On process designed electrode pattern, and draw corresponding contact conductor, each electrode in brush and sac like to intersecting and non-intersecting；
Step S102: nano air-sensitive thin film preparation: use hydrothermal chemistry synthetic method, by graphene respectively with tin oxide
(SnO2), indium oxide (In2O3), cerium oxide (CeO2), tungsten oxide (WO3) are compounded to form different gas-sensitive nano materials, by gained
Gas-sensitive nano material and ethyl alcohol phase mixing, drop coating form nano air-sensitive thin film on each interdigital electrode group surface；
Step S103: different gas-sensitive nano materials sensor assembling: are attached to different interdigital electrode groups surface, same fork
Refer to that identical gas-sensitive nano material is adhered on the interdigital electrode surface in electrode group.
Further, the sensor array includes sensor base, nano air-sensitive thin film；The sensor base includes
Sensor substrate and interdigital electrode group；The interdigital electrode group includes interdigital electrode；The nano air-sensitive thin film is attached to described
Interdigital electrode group surface.
Further, the sensor substrate prepare material include monocrystalline silicon, glass, ceramics in any one；
Further, the material for preparing of the interdigital electrode includes gold, platinum, any one in silver-palladium, with a thickness of 50~
300nm。
Further, the width of the interdigital electrode is 20~200um, and the spacing of the interdigital electrode is 20~200um.
Further, the nano air-sensitive thin film prepare material include redox graphene, tin oxide, indium oxide,
Cerium oxide and tungsten oxide.
Further, the nano air-sensitive thin film with a thickness of 100nm~1um.
Further, the step S400 includes:
Step S401: acquisition sensor array is listed in the characteristic parameter under different atmosphere environment；
Step S402: it establishes the gas identification network model based on Back Propagation Algorithm and is trained；
Step S403: the gas identification network model completed using training identifies practical atmosphere.
Further, the characteristic parameter is that sensor array is listed in the response signal under every kind of atmosphere.
Compared with prior art, bring of the present invention has the beneficial effect that
1, sensor of the invention array structure is simple, small in size, at low cost, procedure of processing is simple；
2, sensor of the invention is array-supported graphene-metal oxide nano gas sensitive, can be at low temperature
Work, can be effectively reduced energy consumption, and high sensitivity, response recovery time are short, reproducible；
3, sensor of the invention array is made of multiple interdigital electrode groups, and interdigital electrode group can not increase sensor
Under the premise of quantity, multiple outputs of same gas sensitive are obtained as a result, providing more inputs for algorithm for pattern recognition
Amount, and possibility is brought to improve sensor accuracy；
4, the quasi- gas propagated of sensor of the invention array combination error identifies network algorithm, can be realized to multicomponent
SF6The identification of gas decomposition product type and content efficiently solves single-sensor to the defect of multiple gases cross sensitivity.
Detailed description of the invention
Fig. 1 is a kind of SF based on graphene composite material sensor array shown in the embodiment of the present invention6Decompose quality testing
Survey method flow diagram；
Fig. 2 is a kind of processing preparation flow based on graphene composite material sensor array shown in the embodiment of the present invention
Figure；
Fig. 3 is a kind of structural schematic diagram based on graphene composite material sensor array shown in the embodiment of the present invention；
Fig. 4 is the sensor array signal acquisition schematic diagram shown in the embodiment of the present invention；
Fig. 5 is shown in the embodiment of the present invention based on redox graphene/stannic oxide nanometer gas sensitive sensing
The different SF that device is 20ppm to concentration6The dynamic response curve schematic diagram of gas decomposition product；
Fig. 6 is the different SF that the sensor array shown in the embodiment of the present invention is 20ppm to concentration6The response of decomposition product
Result schematic diagram；
Fig. 7 is the gas identification network training flow chart based on Back Propagation Algorithm shown in the embodiment of the present invention；
Fig. 8 is the gas identification network model schematic diagram based on Back Propagation Algorithm shown in the embodiment of the present invention.
Specific embodiment
1 to 8 embodiments of the present invention is described in detail with reference to the accompanying drawing, and described embodiment is the present invention
A part of the embodiment, can not be used to limit the present invention.
A kind of SF based on graphene composite material sensor array6Object detecting method is decomposed, as shown in Figure 1, comprising:
Step S100: processing prepares sensor array；
Step S200: preparation gained sensor array is arranged in sealed gas chamber, and carries out bootloader；
Step S300: air-sensitive test is carried out to sensor array and is stored test result as sample；
Step S400: building gas identification network model simultaneously identifies atmosphere, wherein the atmosphere refers to by a variety of
The mixed gas that gas is mixed to get by different proportion.
In the specific embodiment of step S100, the specific processing preparation process of sensor array is as shown in Fig. 2, specific
Include:
Step S101: sensor base processing: by electron beam evaporation deposition technique and photoetching process in sensor substrate
On process designed electrode pattern, and draw corresponding contact conductor, each electrode is non-intersecting to intersecting in brush and sac like；
Step S102: nano air-sensitive thin film preparation: use hydrothermal chemistry synthetic method, by graphene respectively with tin oxide
(SnO2), indium oxide (In2O3), cerium oxide (CeO2), tungsten oxide (WO3) different gas-sensitive nano materials are compounded to form, gained is received
Rice gas sensitive and ethyl alcohol phase mixing, drop coating form nano air-sensitive thin film on each interdigital electrode group surface；
Step S103: different gas-sensitive nano materials sensor assembling: are attached to different interdigital electrode groups surface, same fork
Refer to that identical gas-sensitive nano material is adhered on the interdigital electrode surface in electrode group.
Resulting sensor array is prepared by present embodiment, as shown in Figure 3, comprising: sensor base, nanometer air-sensitive
Film.The sensor base includes sensor substrate and 4 interdigital electrode groups, and each interdigital electrode group includes 4 interdigital electricity
Pole, wherein sensor substrate can be used monocrystalline silicon, glass or ceramic be used as and prepare material, it is preferred to use monocrystalline silicon；Interdigital electrode
Gold, platinum or silver-palladium can be used as material is prepared, with a thickness of 50~300nm, preferably 100nm；The width of interdigital electrode is
20~200um, preferably 100um, the spacing of interdigital electrode are 20~200um, preferably 100um, the electricity between interdigital electrode
Resistance is 1k Ω~1G Ω；The nano air-sensitive thin film by redox graphene (rGO) respectively with tin oxide (SnO2), indium oxide
(In2O3), cerium oxide (CeO2) and tungsten oxide (WO3) be prepared, be attached to interdigital electrode group surface, with a thickness of 100nm~
1um, preferably 300nm, for realizing the electrical connection between the interdigital electrode；
4 kinds of nano air-sensitive thin films of above-mentioned preparation are respectively attached to the surface of 4 interdigital electrode groups, each interdigital electrode
Group can disposably obtain 4 similar outputs as a result, while reducing sensor array scale again for certain single atmosphere
It ensure that measuring accuracy.4 interdigital electrode groups in the present embodiment can produce the output of 16 groups of signals, can be realized to multicomponent
The identification of gas concentration.
In the specific embodiment of step S200, sensor array is arranged in the sealed gas chamber that volume is 800mL,
Switch atmosphere in gas chamber by way of dynamic air-distributing.Sensor array response signal Acquisition Circuit is as shown in figure 4, from gas
Corresponding connecting terminal is drawn in room, so that sensor gas sensing resistance RciRespectively with measuring resistance RbiSeries connection, by being applied at both ends
Add 5V voltage, tests sensor response signal Vi, can calculate to obtain gas sensing resistance RciSituation of change.Sensor response S
It is defined as the relative variation of nano air-sensitive thin film resistance:
In formula, RaIndicate resistance value of the sensor in background gas, RgIndicate resistance value of the sensor in target atmosphere.
After the completion of sensor array arrangement, it is powered up initialization, whether test NI-USB-6218 data collecting card can be with
By signal ViIt is transmitted to host computer.
In the case that sensor array requires on-line monitoring in the specific implementation process of step S300, by test
Background gas (SF is passed through in gas chamber6) and Standard Gases (Balance Air SF6SOF2、SO2F2、SO2、H2S mode), and pass through change
Mass flow controller velocity ratio controls target gas concentration, to resistance variations situation of the sensor under target gas levels into
Row record.
In the present embodiment, with SOF2And H2Two kinds of typical SF of S6For decomposition product gaseous mixture, type classification is realized to it
And concentration identification.Wherein, gas concentration point takes 0,10,20ppm respectively, shares 9 kinds of atmosphere combinations, as shown in table 1:
Table 1
9 kinds of atmospheres according to shown in table 1 test the output situation of sensor array respectively, array are exported result
It is uploaded to host computer and is stored as sample set.Wherein, Fig. 5 gives redox graphene/stannic oxide nanometer air-sensitive material
Material is to different SF6Dynamic response curve when gas decomposition product, Fig. 6 give the response results of sensor array, wherein ring
Should result be that 4 interdigital electrodes are to the mean value of response in each interdigital electrode group, error is by calculating the standard deviation of response
It obtains.
In the specific implementation process of step S400, a kind of gas identification network based on Back Propagation Algorithm is constructed
Model, for SF6Decomposition product identified, as shown in fig. 7, specific construction step is as follows:
Step S401: acquisition sensor array is listed in the characteristic parameter under different atmosphere environment；
The characteristic parameter is that sensor array is listed in the response signal under every kind of atmosphere, extracts the S conduct of sensor response
Characteristic parameter meets:
S=SI, j (2)
Step S402: establishing and gas of the training based on Back Propagation Algorithm identifies network model, and specific steps include；
(a) normalized of characteristic parameter:
I. the input feature vector parameter of each sample is extracted:
In formula,It is i-th of sensor array of k-th of sample output as a result, d indicates the dimension of input feature vector parameter.
Ii. output characteristic parameter is established according to sample type (different atmospheres):
In formula,Indicate k-th of sample, j-th of atmosphere, m indicates the dimension of output characteristic parameter.0 or 1 is taken, and 1 is
It is that 0 is non-, each sample type is distinguished according to output characteristic parameter.
To sum up, training set D can be obtained:
In formula, l indicates total sample number.
Iii. it inputs, output characteristic parameter is normalized:
In formula,Characteristic parameter before normalization,For characteristic parameter after normalization.For in k-th of sample
Characteristic parameter minimum value,For the characteristic parameter maximum value in k-th of sample.For normalization before output parameter,
For output parameter after normalization.
Training set D after being normalized:
(b) it establishes the gas based on Back Propagation Algorithm and identifies network model, as shown in figure 8, including input layer nerve
16, member, hidden neuron 20, output layer neuron 9, specific training process is as follows:
I. learning rate η ∈ (0,1), all connection weights and threshold value in random initializtion neural network are defined.
Ii. neural network output is calculated
In formula, αhFor the input of hidden layer the neuron, bhFor the output of h-th of neuron of hidden layer.βjIt is exported for j-th
The input of neuron；γhFor the threshold value of h-th of neuron of hidden layer, θjFor the threshold value of j-th of neuron of output layer；vihInput layer
Connection weight between h-th of neuron of i-th of neuron and hidden layer, ωhjFor j-th of nerve of h-th of neuron of hidden layer and output layer
Connection weight between member；D indicates input layer quantity, and q indicates hidden neuron quantity.
Iii. the gradient terms g of output layer neuron is calculatedj:
Iv. the gradient terms e of hidden neuron is calculatedh:
In formula, m indicates output layer neuron quantity.
V. output layer calculated, hidden neuron gradient terms, training neural network are combined.
The connection weight update of output layer, hidden neuron:
ω′hj=ωhj+Δωhj=ωhj+ηgjbh (15)
The threshold value update of output layer, hidden neuron:
θ′j=θj+Δθj=θj-ηgj (17)
γ′h=γh+Δγh=γh-ηeh (18)
Vi. the accumulated error in training set D is calculated:
The final goal of the algorithm is so that the accumulated error E on training set D reaches minimum.It is defeated by comparing network query function
OutAnd reality outputAfter accumulated error reaches required precision, then stops the training to neural network and enter test rank
Section (step (3)) otherwise continues to repeat step (b).
Step S403: the gas identification network model completed using training identifies practical atmosphere, specific to walk
It is rapid as follows:
(a) according to different sample types, multiple groups sample is acquired using the sensor array, constructs test set T:
In formula, n indicates test set sample size.
In the present embodiment, in order to identify 9 kinds of possible atmospheres, 16 groups of response letters are acquired by 4 interdigital electrode groups
Number be used as a sample, 20 groups of response results totally 180 groups of samples are acquired under every kind of atmosphere, to training gas know
Other network model, if error reaches 10-4, that is, think to train completion.
(b) the gas identification network model obtained using training classifies to test set sample, and that examines the model can
By property.
In the present embodiment, the gas identification network model obtained using above-mentioned training classifies to test set T, identifies
It the results are shown in Table 2:
Table 2
By recognition result it is found that sensor array of the present invention can relatively accurately identify SOF2And H2S gaseous mixture
The constituent content of body.
In the following, the embodiment of the present invention provides existing method to SF6The test result of decomposition product, as shown in table 3:
Table 3
By comparing with existing method, graphene of the present invention-metal oxide nano composite material sensor array
Column combine the gas based on error Back-Propagation network algorithm to identify network model, both may be implemented to mixing gas component content
Identification, and there are on-line monitoring potentiality, to realize that the fault diagnosis of high-tension electricity equipment has laid solid foundation.
Specific embodiment is applied in the present invention, and principle and implementation of the present invention are described, implements to above
The explanation of example, is merely used to help understand application method and its core concept of the invention.The present invention in specific embodiment and
There will be changes according to the actual situation in application range, and above-described embodiment does not limit application range of the invention.Not
In the case where being detached from technical characteristic given by technical solution of the present invention, to increase made by technical characteristic, deform or with ability
The replacement of the same content in domain, should all belong to protection scope of the present invention.
Claims (10)
1. a kind of SF based on graphene composite material sensor array6Decompose object detecting method, comprising:
Step S100: processing prepares sensor array；
Step S200: preparation gained sensor array is arranged in sealed gas chamber and carries out signal acquisition, and bootloader；
Step S300: air-sensitive test is carried out to sensor array and is stored test result as sample；
Step S400: building gas identification network model simultaneously identifies atmosphere.
2. the step S100 includes: the method according to claim 1, wherein preferred
Step S101: sensor base processing: added in sensor substrate by electron beam evaporation deposition technique and photoetching process
Work goes out designed electrode pattern, and draws corresponding contact conductor, and each electrode in brush and sac like to intersecting and non-intersecting；
Step S102: nano air-sensitive thin film preparation: use hydrothermal chemistry synthetic method, by graphene respectively with tin oxide (SnO2),
Indium oxide (In2O3), cerium oxide (CeO2), tungsten oxide (WO3) are compounded to form different gas-sensitive nano materials, by gained nanometer air-sensitive
Material and ethyl alcohol phase mixing, drop coating form nano air-sensitive thin film on each interdigital electrode group surface；
Step S103: different gas-sensitive nano materials sensor assembling: are attached to different interdigital electrode groups surface, same interdigital electricity
Identical gas-sensitive nano material is adhered on interdigital electrode surface in the group of pole.
3. the method according to claim 1, wherein the sensor array includes sensor base, nanometer gas
Sensitive film；The sensor base includes sensor substrate and interdigital electrode group；The interdigital electrode group includes interdigital electrode；Institute
It states nano air-sensitive thin film and is attached to interdigital electrode group surface.
4. according to the method described in claim 3, it is characterized in that, the sensor substrate prepare material include monocrystalline silicon,
Any one in glass, ceramics.
5. according to the method described in claim 3, it is characterized in that, the material for preparing of the interdigital electrode includes gold, platinum, silver-
Any one in palladium, with a thickness of 50~300nm.
6. according to the method described in claim 3, it is characterized in that, the width of the interdigital electrode is 20~200um, the fork
The spacing for referring to electrode is 20~200um.
7. according to the method described in claim 3, it is characterized in that, the material for preparing of the nano air-sensitive thin film includes oxygen reduction
Graphite alkene, tin oxide, indium oxide, cerium oxide and tungsten oxide.
8. according to the method described in claim 3, it is characterized in that, the nano air-sensitive thin film with a thickness of 100nm~1um.
9. the method according to claim 1, wherein the step S400 includes:
Step S401: acquisition sensor array is listed in the characteristic parameter under different atmosphere environment；
Step S402: it establishes the gas identification network model based on Back Propagation Algorithm and is trained；
Step S403: the gas identification network model completed using training identifies practical atmosphere.
10. according to the method described in claim 9, it is characterized in that, the characteristic parameter is that sensor array is listed in every kind of atmosphere
Under response signal, the atmosphere refers to the mixed gas being mixed to get by multiple gases by different proportion.
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