CN111398531B - Efficient graphene film identification system and method - Google Patents
Efficient graphene film identification system and method Download PDFInfo
- Publication number
- CN111398531B CN111398531B CN202010266730.1A CN202010266730A CN111398531B CN 111398531 B CN111398531 B CN 111398531B CN 202010266730 A CN202010266730 A CN 202010266730A CN 111398531 B CN111398531 B CN 111398531B
- Authority
- CN
- China
- Prior art keywords
- graphene film
- parameters
- firing
- unqualified
- module
- 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.)
- Active
Links
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 title claims abstract description 245
- 229910021389 graphene Inorganic materials 0.000 title claims abstract description 205
- 238000000034 method Methods 0.000 title claims abstract description 114
- 238000012545 processing Methods 0.000 claims abstract description 39
- 238000012797 qualification Methods 0.000 claims abstract description 14
- 238000010304 firing Methods 0.000 claims description 107
- 238000012544 monitoring process Methods 0.000 claims description 26
- 229910052799 carbon Inorganic materials 0.000 claims description 20
- 229910002804 graphite Inorganic materials 0.000 claims description 20
- 239000010439 graphite Substances 0.000 claims description 20
- 238000005259 measurement Methods 0.000 claims description 14
- 239000012528 membrane Substances 0.000 claims description 14
- 239000002344 surface layer Substances 0.000 claims description 14
- 238000012937 correction Methods 0.000 claims description 11
- 239000000523 sample Substances 0.000 claims description 10
- 238000007621 cluster analysis Methods 0.000 claims description 8
- 238000012549 training Methods 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000003763 carbonization Methods 0.000 claims description 4
- 238000005087 graphitization Methods 0.000 claims description 4
- 238000005245 sintering Methods 0.000 claims description 4
- 238000003490 calendering Methods 0.000 claims description 3
- 238000000465 moulding Methods 0.000 claims description 3
- 239000000463 material Substances 0.000 abstract description 9
- 239000010421 standard material Substances 0.000 abstract description 7
- 238000003672 processing method Methods 0.000 abstract description 4
- 238000010835 comparative analysis Methods 0.000 abstract description 2
- 230000009286 beneficial effect Effects 0.000 description 9
- 238000010586 diagram Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- XKRFYHLGVUSROY-UHFFFAOYSA-N Argon Chemical compound [Ar] XKRFYHLGVUSROY-UHFFFAOYSA-N 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000009792 diffusion process Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 229920001721 polyimide Polymers 0.000 description 2
- 238000002360 preparation method Methods 0.000 description 2
- 238000003908 quality control method Methods 0.000 description 2
- 238000005096 rolling process Methods 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 229910052786 argon Inorganic materials 0.000 description 1
- 238000010000 carbonizing Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000007789 gas Substances 0.000 description 1
- 238000011112 process operation Methods 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0096—Testing material properties on thin layers or coatings
Landscapes
- Chemical & Material Sciences (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Pathology (AREA)
- Physics & Mathematics (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- Immunology (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Engineering & Computer Science (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Electrochemistry (AREA)
- Carbon And Carbon Compounds (AREA)
Abstract
The invention provides a high-efficiency graphene film identification system and a method, wherein the system comprises: the establishing module is used for establishing standard unit area mass of the standard graphene film of each specification and forming a standard mass set; the identification module is used for identifying the target graphene film and determining index parameters of the target graphene film; and the processing module is used for determining the target unit area mass of the target graphene film according to the index parameters determined by the identification module, and determining the qualification of the target graphene film by comparing and analyzing the target unit area mass with the standard mass set. The method is used for determining the quality of the graphene film in unit area through identification and determining the qualification of the graphene film through a comparative analysis processing method, and further effectively distinguishing the graphene film produced by poor-quality materials or non-standard materials.
Description
Technical Field
The invention relates to the technical field of heat-conducting graphite films, in particular to a system and a method for identifying a high-efficiency graphene film.
Background
The artificial heat conduction graphene film is formed by carbonizing, graphitizing and rolling a polyimide film (PI film for short) at high temperature, is of a laminated structure, has various polyimide film types and manufacturers and uneven quality, and can be fired into a high-grade graphene film by using a PI film with low cost by some manufacturers, and can not be effectively identified by conventional detection;
at present, main performance indexes of the artificial heat conduction graphene film are thermal diffusion, density and thickness, wherein the density is generally tested by adopting a true density instrument, and the testing principle is that a quantitative sample is selected, a graphite gap is filled with argon gas, the true sample volume and the sample mass are converted, and then the true density is obtained through conversion.
For example: usually, standard graphite of 25um is strictly sintered by PI of 50um, if manufacturers select PI of 38um for sintering, thermal diffusion and thickness of the standard graphite can meet requirements according to an industrial detection mode, density can also meet requirements if the density is tested by the true density instrument, and if the thickness of a graphene film of 25um sintered by 38PI is taken as a standard lower limit, the density obtained by measurement can also easily meet requirements through a drainage method or a thickness method, so that the graphene film product sintered by PI of 38um is easy to flow into a terminal market, but the performance of the standard product can be reduced by 30% in the using process of the standard product in the terminal market.
Therefore, the invention mainly solves the technical problem that the existing graphite firing raw materials are various in variety, and the graphene film produced by inferior materials or non-standard materials cannot be effectively distinguished.
Disclosure of Invention
The invention provides a high-efficiency graphene film identification system which is used for determining the quality of a graphene film in unit area through identification and determining the qualification of the graphene film through a contrast analysis processing method, so that the graphene film produced by inferior materials or non-standard materials can be effectively distinguished.
The invention provides a high-efficiency graphene film identification system, which comprises:
the establishing module is used for establishing standard unit area mass of the standard graphene film of each specification and forming a standard mass set;
the identification module is used for identifying a target graphene film and determining index parameters of the target graphene film, wherein the index parameters comprise: the carbon content, firing process, and shrinkage of the target graphene film;
and the processing module is used for determining the target unit area mass of the target graphene film according to the index parameters determined by the identification module, and determining the qualification of the target graphene film by comparing, analyzing and processing the target unit area mass and the standard mass set.
In one possible implementation, the authentication module includes:
the intercepting unit is used for intercepting a preset area in the target graphene film to obtain the graphene film to be identified;
the carbon content measuring unit is used for measuring the carbon content of the graphene film to be identified to obtain the carbon content of the graphene film to be identified;
the firing process determination unit is used for determining the firing process of the graphene film to be identified to obtain the firing process of the graphene film to be identified;
and the shrinkage rate measuring unit is used for measuring the shrinkage rate of the graphene film to be identified to obtain the shrinkage rate of the graphene film to be identified.
In one possible implementation of the method according to the invention,
the preset area in the target graphene film intercepted by the intercepting unit is a block area in different directions and at different positions, which is intercepted by the intercepting unit with the center point of the target graphene film as the center of a circle and different lengths as the radius;
and a preset area is formed by all the block areas.
In one possible way of realisation,
the authentication module further comprises:
a calculating unit, configured to calculate, according to a measurement result of the shrinkage measuring unit, a percentage of a difference between a size C1 of the graphene film to be identified at a molding temperature and a size C2 of the graphene film after being taken out of the mold and cooled to room temperature, so as to obtain a first shrinkage P1;
a correction unit, configured to perform correction processing on the first shrinkage rate P1 to obtain a second shrinkage rate P2;
wherein n represents the number of indexes affecting the shrinkage rate of the graphene film to be identified; f (delta)iχi) An index correction function representing an ith index affecting shrinkage of the graphene film to be identified; deltaiRepresenting effects ofThe influence factor of the ith index of the shrinkage rate of the graphene film to be identified; chi shapeiAn influence ratio of an influence factor representing an ith index influencing the shrinkage of the graphene film to be identified;
wherein the obtained second shrinkage rate is the shrinkage rate of the graphene film to be identified, which is obtained by the shrinkage rate determination unit.
In one possible implementation manner, the method further includes:
the monitoring module is used for monitoring each sub-process in the firing process flow of the target graphene film;
the processing module is also used for determining whether the operation process of each sub-process is qualified or not based on the standard firing process and the sub-process monitoring result of the monitoring module;
if the quality is qualified, continuing to perform subsequent operations;
otherwise, based on the alarm module, executing corresponding alarm operation on the unqualified sub-process;
wherein the sub-process comprises: high-temperature carbonization, graphitization and calendering.
In one possible way of realisation,
the monitoring module is further used for monitoring the adopted fired graphite before the new target graphene film is fired;
the processing module is used for determining whether the fired graphite meets the standard for firing the target graphene film or not according to the monitoring result of the monitoring module, and if so, performing a firing process;
otherwise, corresponding alarm operation is carried out based on the alarm module.
In one possible implementation manner, the method further includes:
the statistical module is used for carrying out statistics on the firing parameters of each sub-process in the firing process flow;
the processing module is used for identifying the firing parameters based on the firing process model and determining whether the firing parameters meet the firing standard or not according to the identification result;
if so, training the firing process model based on the firing parameters;
if the firing parameters do not meet the requirements, carrying out cluster analysis on the firing parameters, and determining unqualified class parameters according to a cluster analysis result;
meanwhile, determining the proportion B of the unqualified class parameters in all class parameters;
wherein, betajnRepresenting firing values for each of different classes of parameters that are acceptable and unacceptable, and n being 1,2. And when n is 1,2.. p, corresponding to unqualified class parameters; when n is p +1.. q, corresponding to qualified class parameters; beta is aj1Represents the firing value of the j1 th parameter in the unqualified first-class parameters, and the value range of the j1 is [1, m1]；βj2Represents the firing value of the j2 th parameter in the unqualified second type of parameters, and the value range of the j2 is [1, m2]；βjpRepresents the firing value of the jth parameter in the unqualified pth parameters, and the value range of the jp is [1, mp](ii) a When n is equal to q, corresponding jn has a value range of [1, mq [ ]]；
The processing module is further used for executing corresponding operation based on the statistical module and the processing model again when the proportion B of the unqualified class parameters is larger than the preset proportion B' of the unqualified class parameters, and obtaining a new proportion B1 of the unqualified class parameters;
if the proportion B of the unqualified class parameters is consistent with the proportion B1 of the new unqualified class parameters, performing corresponding alarm operation based on an alarm module;
wherein, in the process of obtaining the proportion B1 of the new unqualified class parameters, the method further comprises the following steps:
the determining module is used for determining whether the data type of the corresponding new unqualified parameter is consistent with the data type of the unqualified parameter corresponding to the percentage B;
if so, judging whether the occupation ratio B of the unqualified class parameters is consistent with the occupation ratio B1 of the new unqualified class parameters, and continuing to execute subsequent operations;
otherwise, based on the time axis, acquiring a plurality of groups of class parameters according to the statistical module and the processing module, and further acquiring the new unqualified class parameter ratio B2;
and judging the consistency of the percentage of occupation B of the unqualified class parameters and the percentage of occupation B2 of the new unqualified class parameters.
In one possible way of realisation,
the first measurement module is used for measuring a first friction force of a nanoprobe and measuring a second friction force of the nanoprobe on the target graphene film;
the first scanning module is used for scanning the surface area of the target graphene film passed by the nano probe and determining the sub-friction force of the target graphene film in different sub-areas of the surface area based on the first friction force and the second friction force measured by the measuring module;
the second scanning module is used for scanning the target graphene film and acquiring a surface layer structure of the target graphene film;
a second measurement module, configured to measure the surface voltage values of the target graphene film in different sub-regions of the surface region determined by the first scanning module;
a third measurement module, configured to obtain, by the second scanning module, a structure voltage value of the target graphene film of the surface layer structure of the target graphene film and of a sub-structure corresponding to the sub-region;
the processing module is configured to correct the sub-friction forces of the different sub-regions determined by the first scanning module based on the surface voltage value obtained by the second measuring module and the structural voltage value obtained by the third measuring module, and perform superposition display processing on the corrected sub-friction force of each sub-region and the surface layer structure obtained by the second scanning module;
meanwhile, determining whether the firing process based on the aspect of friction force identification is qualified or not according to the corrected sub-friction force of each sub-area;
when the mean square friction value of the sub-friction of all the sub-areas is within the standard friction range, the firing process based on the friction discrimination aspect is qualified;
otherwise, the sintering process based on the friction force identification aspect is unqualified, and corresponding alarm operation is executed based on an alarm module.
The invention provides a high-efficiency graphene film identification method, which comprises the following steps:
step 1: establishing standard unit area mass of the standard graphene film of each specification, and forming a standard mass set;
step 2: identifying a target graphene film, and determining index parameters of the target graphene film;
wherein the index parameters include: the carbon content, firing process, and shrinkage of the target graphene film;
and step 3: and determining the target unit area mass of the target graphene film according to the determined index parameters, and determining the qualification of the target graphene film by comparing, analyzing and processing the target unit area mass and the standard mass set.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic structural diagram of an efficient graphene membrane identification system according to an embodiment of the present invention;
FIG. 2 is a schematic structural diagram of an authentication module in an embodiment of the present invention;
FIG. 3 is a block diagram of a preset block according to an embodiment of the present invention;
FIG. 4 is a block diagram of a firing process based on a friction discriminating aspect of an embodiment of the present invention;
fig. 5 is a flowchart of a method for identifying a graphene film according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The invention provides a high-efficiency graphene membrane identification system, as shown in fig. 1, comprising:
the establishing module is used for establishing standard unit area mass of the standard graphene film of each specification and forming a standard mass set;
the identification module is used for identifying a target graphene film and determining index parameters of the target graphene film, wherein the index parameters comprise: the carbon content, firing process, and shrinkage of the target graphene film;
and the processing module is used for determining the target unit area mass of the target graphene film according to the index parameters determined by the identification module, and determining the qualification of the target graphene film by comparing, analyzing and processing the target unit area mass and the standard mass set.
In this embodiment, the target graphene film may include one or more graphene film samples that have been fired, and the efficiency of the identification may be improved by identifying the one or more graphene film samples.
In the embodiment, standard control of quality in a standard area is established for heat-conducting graphene films of various specifications, the quality in the standard area of graphene to be measured is measured, the theoretical carbon content of a PI film in a unit area, a firing process and the shrinkage rate jointly determine the quality in the unit area of a graphite film, and the theoretical carbon content and the shrinkage rate of the PI films of different manufacturers and different specifications have large difference, so that the corresponding graphite film has large difference in quality in the unit area, and the PI films of the same specification have the possibility of changing the quality in the unit area of the graphite film due to excessive carbon loss caused by the fluctuation of the firing process, so that three index parameters of the carbon content, the firing process and the shrinkage rate need to be identified.
Therefore, whether large changes or runaway of PI manufacturers, specifications and processes occur can be effectively identified by monitoring the unit area mass of the graphite film. And its benefits include: the change of a graphite film preparation main material manufacturer can be effectively monitored, the mixed batch or the counterfeit of the graphite film preparation main material specification can be effectively monitored, the abnormal process or the process change of the key process of the graphite film manufacturer can be effectively monitored, and the like.
In this example, and by performing a comparative analysis process on the target mass per unit area to a set of standard masses, the qualification of the target graphene film is determined, for example:
by sampling a plurality of graphene film samples, wherein the samples are respectively No. 1, No. 2 and No. 3, the quality of the samples No. 1, No. 2 and No. 3 is subjected to averaging calculation, the average value is m, m is (m1+ m2+ m3)/3, and whether the average value m meets the standard quality control range of the corresponding graphene in the standard quality set is compared as follows: (LCL, UCL), and is further used to determine the qualification of the target graphene film, wherein LCL is the lower specification control limit and UCL is the upper specification control limit.
If the standard quality is in the standard quality control range, the standard quality is qualified, otherwise, the standard quality is unqualified.
The beneficial effects of the above technical scheme are: the qualification of the graphene film is determined by identifying and determining the mass of the graphene film in unit area and by a contrast analysis processing method, so that the graphene film produced by poor-quality materials or non-standard materials can be effectively distinguished.
The invention provides a high-efficiency graphene membrane identification system, as shown in fig. 2, the identification module comprises:
the intercepting unit is used for intercepting a preset area in the target graphene film to obtain the graphene film to be identified;
the carbon content measuring unit is used for measuring the carbon content of the graphene film to be identified to obtain the carbon content of the graphene film to be identified;
the firing process determination unit is used for determining the firing process of the graphene film to be identified to obtain the firing process of the graphene film to be identified;
and the shrinkage rate measuring unit is used for measuring the shrinkage rate of the graphene film to be identified to obtain the shrinkage rate of the graphene film to be identified.
The beneficial effects of the above technical scheme are: the carbon content, the firing process and the shrinkage rate of the graphene film to be identified are respectively obtained through the identification module, and an identification data basis is provided for determining the graphene film to be identified.
The invention provides a high-efficiency graphene film identification system.A preset area in a target graphene film intercepted by an intercepting unit is a block area in different directions and different positions respectively intercepted by taking a central point of the target graphene film as a circle center and different lengths as radiuses;
and a preset area is formed by all the block areas.
In this embodiment, the target graphene film refers to a film including one or more graphene film samples in the content, for example, the preset region in the intercepted target graphene film is a block region in different directions and at different positions, which is obtained by respectively intercepting the block region in different directions and at different positions with the center point of a single graphene film sample as the center of a circle and different lengths as radii, and is the preset region of the single graphene film sample;
as shown in fig. 3, for example, a represents a single graphene film sample, and o point represents a central point, and b1 and b2 represent different radii, respectively, and correspond to a1 and a2 region blocks, respectively, and the a1 and a2 region blocks constitute a predetermined region.
The beneficial effects of the above technical scheme are: by obtaining the region blocks in different directions, different radiuses and different positions, the identified unit area quality is more accurate, the high efficiency of the graphene film is improved, a data base is provided for determining the qualification of the graphene film, and the graphene film produced by inferior materials or non-standard materials is effectively distinguished.
The invention provides a high-efficiency graphene membrane identification system, as shown in fig. 2, the identification module further comprises:
a calculating unit, configured to calculate, according to a measurement result of the shrinkage measuring unit, a percentage of a difference between a size C1 of the graphene film to be identified at a molding temperature and a size C2 of the graphene film after being taken out of the mold and cooled to room temperature, so as to obtain a first shrinkage P1;
a correction unit, configured to perform correction processing on the first shrinkage rate P1 to obtain a second shrinkage rate P2;
wherein n represents the number of indexes affecting the shrinkage rate of the graphene film to be identified; f (delta)iχi) An index correction function representing an ith index affecting shrinkage of the graphene film to be identified; deltaiAn influence factor representing an ith index that influences the shrinkage of the graphene film to be identified; chi shapeiAn influence ratio of an influence factor representing an ith index influencing the shrinkage of the graphene film to be identified;
wherein the obtained second shrinkage rate is the shrinkage rate of the graphene film to be identified, which is obtained by the shrinkage rate determination unit.
The beneficial effects of the above technical scheme are: the first shrinkage rate of the graphene film to be identified is calculated primarily according to a basic shrinkage rate formula, the first shrinkage rate is corrected through a correction unit based on parameters such as an influence factor and an influence ratio, the more accurate shrinkage rate of the graphene film to be identified is obtained through calculation by a shrinkage rate measurement unit, and the accuracy of obtaining unit area mass subsequently is improved.
The invention provides a high-efficiency graphene film identification system, which further comprises:
the monitoring module is used for monitoring each sub-process in the firing process flow of the target graphene film;
the processing module is also used for determining whether the operation process of each sub-process is qualified or not based on the standard firing process and the sub-process monitoring result of the monitoring module;
if the quality is qualified, continuing to perform subsequent operations;
otherwise, based on the alarm module, executing corresponding alarm operation on the unqualified sub-process;
wherein the sub-process comprises: high-temperature carbonization, graphitization and calendering.
In this embodiment, for example, if the high-temperature carbonization process in the sub-processes fails, a light warning is performed; if the graphitization process is unqualified, voice warning is carried out; and if the rolling process is unqualified, vibrating a warning lamp.
And in this embodiment, each sub-process is monitored to ensure the firing correctness during the firing process, so as to avoid the unqualified fired graphene film caused by internal process operation.
The beneficial effects of the above technical scheme are: the manufacturing process is monitored, so that misjudgment of the graphene film caused by misoperation of the manufacturing process is avoided in the process of judging the finally obtained graphene film.
The invention provides a high-efficiency graphene membrane identification system, wherein the monitoring module is also used for monitoring the adopted fired graphite before a new target graphene membrane is fired;
the processing module is used for determining whether the fired graphite meets the standard for firing the target graphene film or not according to the monitoring result of the monitoring module, and if so, performing a firing process;
otherwise, corresponding alarm operation is carried out based on the alarm module.
For example: the standard graphite of 25um strictly adopts PI firing of 50um, and at this moment, just select different graphite to carry out PI firing to the producer and carry out the monitoring, stop the emergence of this condition from the root.
The beneficial effects of the above technical scheme are: the graphene film is monitored before firing, so that unqualified graphene films can be effectively avoided fundamentally, and the workload of subsequently identifying the graphene film is further reduced.
The invention provides a high-efficiency graphene film identification system, which further comprises:
the statistical module is used for carrying out statistics on the firing parameters of each sub-process in the firing process flow;
the processing module is used for identifying the firing parameters based on the firing process model and determining whether the firing parameters meet the firing standard or not according to the identification result;
if so, training the firing process model based on the firing parameters;
if the firing parameters do not meet the requirements, carrying out cluster analysis on the firing parameters, and determining unqualified class parameters according to a cluster analysis result;
meanwhile, determining the proportion B of the unqualified class parameters in all class parameters;
wherein, betajnRepresenting firing values for each of different classes of parameters that are acceptable and unacceptable, and n being 1,2. And when n is 1,2.. p, corresponding to unqualified class parameters; when n is p +1.. q, corresponding to qualified class parameters; beta is aj1Represents the firing value of the j1 th parameter in the unqualified first-class parameters, and the value range of the j1 is [1, m1]；βj2Represents the firing value of the j2 th parameter in the unqualified second type of parameters, and the value range of the j2 is [1, m2]；βjpRepresents the firing value of the jth parameter in the unqualified pth parameters, and the value range of the jp is [1, mp](ii) a When n is equal to q, corresponding jn has a value range of [1, mq [ ]]；
The processing module is further used for executing corresponding operation based on the statistical module and the processing model again when the proportion B of the unqualified class parameters is larger than the preset proportion B' of the unqualified class parameters, and obtaining a new proportion B1 of the unqualified class parameters;
if the proportion B of the unqualified class parameters is consistent with the proportion B1 of the new unqualified class parameters, performing corresponding alarm operation based on an alarm module;
wherein, in the process of obtaining the proportion B1 of the new unqualified class parameters, the method further comprises the following steps:
the determining module is used for determining whether the data type of the corresponding new unqualified parameter is consistent with the data type of the unqualified parameter corresponding to the percentage B;
if so, judging whether the occupation ratio B of the unqualified class parameters is consistent with the occupation ratio B1 of the new unqualified class parameters, and continuing to execute subsequent operations;
otherwise, based on the time axis, acquiring a plurality of groups of class parameters according to the statistical module and the processing module, and further acquiring the new unqualified class parameter ratio B2;
and judging the consistency of the percentage of occupation B of the unqualified class parameters and the percentage of occupation B2 of the new unqualified class parameters.
The beneficial effects of the above technical scheme are: the firing process model is trained based on the consistent firing parameters, the training recognition precision of the firing process model is improved, the unqualified class parameter proportion B is calculated for the first time, the unqualified class parameter proportion B1 is verified through the statistical module and the processing module again, errors caused in the calculation process can be effectively reduced through comparison of B with B1, meanwhile, the processing efficiency of unqualified class parameters is improved, and the effectiveness of determining the unqualified class parameters is further improved on the basis of improving a comparison sample through comparison of B with B2.
The invention provides a high-efficiency graphene membrane identification system, as shown in fig. 4, further comprising:
the first measurement module is used for measuring a first friction force of a nanoprobe and measuring a second friction force of the nanoprobe on the target graphene film;
the first scanning module is used for scanning the surface area of the target graphene film passed by the nano probe and determining the sub-friction force of the target graphene film in different sub-areas of the surface area based on the first friction force and the second friction force measured by the measuring module;
the second scanning module is used for scanning the target graphene film and acquiring a surface layer structure of the target graphene film;
a second measurement module, configured to measure the surface voltage values of the target graphene film in different sub-regions of the surface region determined by the first scanning module;
a third measurement module, configured to obtain, by the second scanning module, a structure voltage value of the target graphene film of the surface layer structure of the target graphene film and of a sub-structure corresponding to the sub-region;
the processing module is configured to correct the sub-friction forces of the different sub-regions determined by the first scanning module based on the surface voltage value obtained by the second measuring module and the structural voltage value obtained by the third measuring module, and perform superposition display processing on the corrected sub-friction force of each sub-region and the surface layer structure obtained by the second scanning module;
meanwhile, determining whether the firing process based on the aspect of friction force identification is qualified or not according to the corrected sub-friction force of each sub-area;
when the mean square friction value of the sub-friction of all the sub-areas is within the standard friction range, the firing process based on the friction discrimination aspect is qualified;
otherwise, the sintering process based on the friction force identification aspect is unqualified, and corresponding alarm operation is executed based on an alarm module.
In the embodiment, the friction force can be used as a main parameter in the firing process, and whether the firing process is qualified in the aspect of the friction force is determined by determining the friction force, so that the accuracy of acquiring the mass per unit area is improved.
Determining sub-friction forces of the target graphene film in different sub-areas of the surface area by measuring a first friction force of the nanoprobe and a second friction force of the nanoprobe to the target graphene film, scanning the surface area of the target graphene film through which the nanoprobe passes, and based on the first friction force and the second friction force measured by the measuring module, wherein the sub-friction forces are obtained based on the surface area;
the method comprises the steps of scanning a target graphene film, obtaining a surface layer structure of the target graphene film, and correcting the sub-friction force by measuring surface voltage values of different subregions of a surface region and structure voltage values of the surface layer structure corresponding to the subregions, so that the friction force of each subregion can be effectively and accurately obtained;
the sub-friction force of each sub-area and the obtained surface layer structure are subjected to superposition display processing so as to display the correction friction force of each sub-area, and visual understanding is facilitated.
The beneficial effects of the above technical scheme are: the friction force of the sub-areas and the surface layer structures of the sub-areas are determined, so that the graphene film is finely divided and judged, the friction force is effectively corrected by determining the surface voltage value of each sub-area and the structure voltage value of the surface layer structure, the qualified performance of the firing process based on the friction force identification aspect can be effectively and visually determined by judging whether the mean square friction value of the sub-friction force of all the sub-areas is within the standard friction range, the unqualified firing process can be timely processed conveniently by performing alarm operation, the qualified performance of the graphene film is indirectly determined, and the graphene film produced by inferior materials or non-standard materials is effectively distinguished.
The invention provides a high-efficiency graphene film identification method, as shown in fig. 5, comprising the following steps:
step 1: establishing standard unit area mass of the standard graphene film of each specification, and forming a standard mass set;
step 2: identifying a target graphene film, and determining index parameters of the target graphene film;
wherein the index parameters include: the carbon content, firing process, and shrinkage of the target graphene film;
and step 3: and determining the target unit area mass of the target graphene film according to the determined index parameters, and determining the qualification of the target graphene film by comparing, analyzing and processing the target unit area mass and the standard mass set.
The beneficial effects of the above technical scheme are: the qualification of the graphene film is determined by identifying and determining the mass of the graphene film in unit area and by a contrast analysis processing method, so that the graphene film produced by poor-quality materials or non-standard materials can be effectively distinguished.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (8)
1. A high efficiency graphene membrane discrimination system, comprising:
the establishing module is used for establishing standard unit area mass of the standard graphene film of each specification and forming a standard mass set;
the identification module is used for identifying a target graphene film and determining index parameters of the target graphene film;
wherein the index parameters include: the carbon content, firing process, and shrinkage of the target graphene film;
the processing module is used for determining the target unit area mass of the target graphene film according to the index parameters determined by the identification module, and determining the qualification of the target graphene film by comparing, analyzing and processing the target unit area mass and the standard mass set;
the system, still include:
the statistical module is used for carrying out statistics on the firing parameters of each sub-process in the firing process flow;
the processing module is used for identifying the firing parameters based on the firing process model and determining whether the firing parameters meet the firing standard or not according to the identification result;
if so, training the firing process model based on the firing parameters;
if the firing parameters do not meet the requirements, carrying out cluster analysis on the firing parameters, and determining unqualified class parameters according to a cluster analysis result;
meanwhile, determining the proportion B of the unqualified class parameters in all class parameters;
wherein, betajnRepresenting firing values for each of different classes of parameters that are acceptable and unacceptable, and n being 1,2. And when n is 1,2.. p, corresponding to unqualified class parameters; when n is p +1.. q, corresponding to qualified class parameters; beta is aj1Represents the firing value of the j1 th parameter in the unqualified first-class parameters, and the value range of the j1 is [1, m1]；βj2Represents the firing value of the j2 th parameter in the unqualified second type of parameters, and the value range of the j2 is [1, m2]；βjpRepresents the firing value of the jth parameter in the unqualified pth parameters, and the value range of the jp is [1, mp](ii) a When n is equal to q, corresponding jn has a value range of [1, mq [ ]]；
The processing module is further used for executing corresponding operation based on the statistical module and the processing model again when the proportion B of the unqualified class parameters is larger than the preset proportion B' of the unqualified class parameters, and obtaining a new proportion B1 of the unqualified class parameters;
if the proportion B of the unqualified class parameters is consistent with the proportion B1 of the new unqualified class parameters, performing corresponding alarm operation based on an alarm module;
wherein, in the process of obtaining the proportion B1 of the new unqualified class parameters, the method further comprises the following steps:
the determining module is used for determining whether the data type of the corresponding new unqualified parameter is consistent with the data type of the unqualified parameter corresponding to the percentage B;
if so, judging whether the occupation ratio B of the unqualified class parameters is consistent with the occupation ratio B1 of the new unqualified class parameters, and continuing to execute subsequent operations;
otherwise, based on the time axis, acquiring a plurality of groups of class parameters according to the statistical module and the processing module, and further acquiring the new unqualified class parameter ratio B2;
and judging the consistency of the percentage of occupation B of the unqualified class parameters and the percentage of occupation B2 of the new unqualified class parameters.
2. The efficient graphene membrane discrimination system of claim 1, wherein the discrimination module comprises:
the intercepting unit is used for intercepting a preset area in the target graphene film to obtain the graphene film to be identified;
the carbon content measuring unit is used for measuring the carbon content of the graphene film to be identified to obtain the carbon content of the graphene film to be identified;
the firing process determination unit is used for determining the firing process of the graphene film to be identified to obtain the firing process of the graphene film to be identified;
and the shrinkage rate measuring unit is used for measuring the shrinkage rate of the graphene film to be identified to obtain the shrinkage rate of the graphene film to be identified.
3. The efficient graphene membrane discrimination system of claim 2,
the preset area in the target graphene film intercepted by the intercepting unit is a block area in different directions and at different positions, which is intercepted by the intercepting unit with the center point of the target graphene film as the center of a circle and different lengths as the radius;
and a preset area is formed by all the block areas.
4. The efficient graphene membrane discrimination system of claim 2, wherein the discrimination module further comprises:
a calculating unit, configured to calculate, according to a measurement result of the shrinkage measuring unit, a percentage of a difference between a size C1 of the graphene film to be identified at a molding temperature and a size C2 of the graphene film after being taken out of the mold and cooled to room temperature, so as to obtain a first shrinkage P1;
a correction unit, configured to perform correction processing on the first shrinkage rate P1 to obtain a second shrinkage rate P2;
wherein n represents the number of indexes affecting the shrinkage rate of the graphene film to be identified; f (delta)iχi) An index correction function representing an ith index affecting shrinkage of the graphene film to be identified; deltaiAn influence factor representing an ith index that influences the shrinkage of the graphene film to be identified; chi shapeiAn influence ratio of an influence factor representing an ith index influencing the shrinkage of the graphene film to be identified;
wherein the obtained second shrinkage rate is the shrinkage rate of the graphene film to be identified, which is obtained by the shrinkage rate determination unit.
5. The efficient graphene membrane discrimination system of claim 1, further comprising:
the monitoring module is used for monitoring each sub-process in the firing process flow of the target graphene film;
the processing module is also used for determining whether the operation process of each sub-process is qualified or not based on the standard firing process and the sub-process monitoring result of the monitoring module;
if the quality is qualified, continuing to perform subsequent operations;
otherwise, based on the alarm module, executing corresponding alarm operation on the unqualified sub-process;
wherein the sub-process comprises: high-temperature carbonization, graphitization and calendering.
6. The efficient graphene membrane discrimination system of claim 5,
the monitoring module is further used for monitoring the adopted fired graphite before the new target graphene film is fired;
the processing module is used for determining whether the fired graphite meets the standard for firing the target graphene film or not according to the monitoring result of the monitoring module, and if so, performing a firing process;
otherwise, corresponding alarm operation is carried out based on the alarm module.
7. The efficient graphene membrane discrimination system of claim 1,
the first measurement module is used for measuring a first friction force of a nanoprobe and measuring a second friction force of the nanoprobe on the target graphene film;
the first scanning module is used for scanning the surface area of the target graphene film passed by the nano probe and determining the sub-friction force of the target graphene film in different sub-areas of the surface area based on the first friction force and the second friction force measured by the measuring module;
the second scanning module is used for scanning the target graphene film and acquiring a surface layer structure of the target graphene film;
a second measurement module, configured to measure the surface voltage values of the target graphene film in different sub-regions of the surface region determined by the first scanning module;
a third measurement module, configured to obtain, by the second scanning module, a structure voltage value of the target graphene film of the surface layer structure of the target graphene film and of a sub-structure corresponding to the sub-region;
the processing module is configured to correct the sub-friction forces of the different sub-regions determined by the first scanning module based on the surface voltage value obtained by the second measuring module and the structural voltage value obtained by the third measuring module, and perform superposition display processing on the corrected sub-friction force of each sub-region and the surface layer structure obtained by the second scanning module;
meanwhile, determining whether the firing process based on the aspect of friction force identification is qualified or not according to the corrected sub-friction force of each sub-area;
when the mean square friction value of the sub-friction of all the sub-areas is within the standard friction range, the firing process based on the friction discrimination aspect is qualified;
otherwise, the sintering process based on the friction force identification aspect is unqualified, and corresponding alarm operation is executed based on an alarm module.
8. A method for identifying a high-efficiency graphene film, comprising:
step 1: establishing standard unit area mass of the standard graphene film of each specification, and forming a standard mass set;
step 2: identifying a target graphene film, and determining index parameters of the target graphene film;
wherein the index parameters include: the carbon content, firing process, and shrinkage of the target graphene film;
and step 3: determining the target unit area mass of the target graphene film according to the determined index parameters, and determining the qualification of the target graphene film by comparing the target unit area mass with the standard mass set for analysis;
wherein, the method further comprises:
counting the firing parameters of each sub-flow in the firing process flow;
identifying the firing parameters based on a firing process model, and determining whether the firing parameters meet firing standards according to identification results;
if so, training the firing process model based on the firing parameters;
if the firing parameters do not meet the requirements, carrying out cluster analysis on the firing parameters, and determining unqualified class parameters according to a cluster analysis result;
meanwhile, determining the proportion B of the unqualified class parameters in all class parameters;
wherein, betajnRepresenting firing values for each of different classes of parameters that are acceptable and unacceptable, and n being 1,2. And when n is 1,2.. p, corresponding to unqualified class parameters; when n is p +1.. q, corresponding to qualified class parameters; beta is aj1Represents the firing value of the j1 th parameter in the unqualified first-class parameters, and the value range of the j1 is [1, m1]；βj2Represents the firing value of the j2 th parameter in the unqualified second type of parameters, and the value range of the j2 is [1, m2]；βjpRepresents the firing value of the jth parameter in the unqualified pth parameters, and the value range of the jp is [1, mp](ii) a When n is equal to q, corresponding jn has a value range of [1, mq [ ]]；
When the ratio B of the unqualified class parameters is larger than the preset ratio B' of the unqualified class parameters, re-executing corresponding operation, and obtaining a new ratio B1 of the unqualified class parameters;
if the proportion B of the unqualified class parameters is consistent with the proportion B1 of the new unqualified class parameters, performing corresponding alarm operation;
wherein, in the process of obtaining the proportion B1 of the new unqualified class parameters, the method further comprises the following steps:
determining whether the data type of the corresponding new unqualified class parameter is consistent with the data type of the unqualified class parameter corresponding to the percentage B;
if so, judging whether the occupation ratio B of the unqualified class parameters is consistent with the occupation ratio B1 of the new unqualified class parameters, and continuing to execute subsequent operations;
otherwise, acquiring a plurality of groups of class parameters based on a time axis, and further acquiring the new unqualified class parameter occupation ratio B2;
and judging the consistency of the percentage of occupation B of the unqualified class parameters and the percentage of occupation B2 of the new unqualified class parameters.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010266730.1A CN111398531B (en) | 2020-04-07 | 2020-04-07 | Efficient graphene film identification system and method |
| CN202011431545.XA CN112697969B (en) | 2020-04-07 | 2020-04-07 | High-efficiency graphene film identification system based on surface friction force |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010266730.1A CN111398531B (en) | 2020-04-07 | 2020-04-07 | Efficient graphene film identification system and method |
Related Child Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011431545.XA Division CN112697969B (en) | 2020-04-07 | 2020-04-07 | High-efficiency graphene film identification system based on surface friction force |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111398531A CN111398531A (en) | 2020-07-10 |
| CN111398531B true CN111398531B (en) | 2021-01-08 |
Family
ID=71435091
Family Applications (2)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010266730.1A Active CN111398531B (en) | 2020-04-07 | 2020-04-07 | Efficient graphene film identification system and method |
| CN202011431545.XA Active CN112697969B (en) | 2020-04-07 | 2020-04-07 | High-efficiency graphene film identification system based on surface friction force |
Family Applications After (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011431545.XA Active CN112697969B (en) | 2020-04-07 | 2020-04-07 | High-efficiency graphene film identification system based on surface friction force |
Country Status (1)
| Country | Link |
|---|---|
| CN (2) | CN111398531B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113533415B (en) * | 2021-07-19 | 2022-07-22 | 苏州鸿凌达电子科技有限公司 | Heat conduction performance detection method applied to graphene/graphite heat conduction module |
| CN113933238A (en) * | 2021-10-19 | 2022-01-14 | 海瑞膜科技南通有限公司 | High-efficiency graphene film identification system based on surface friction force |
Family Cites Families (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003028802A (en) * | 2001-07-12 | 2003-01-29 | Sony Corp | Method for evaluating carbon film and method for manufacturing magnetic recording medium |
| KR101366114B1 (en) * | 2012-09-10 | 2014-02-24 | 전자부품연구원 | Method for monitoring of surface of graphene |
| TWI478868B (en) * | 2012-09-19 | 2015-04-01 | 鐘化股份有限公司 | Method for producing carbonaceous film, and method for producing graphite film |
| CN203894592U (en) * | 2013-12-27 | 2014-10-22 | 无锡格菲电子薄膜科技有限公司 | CVD monitoring system for preparation of grapheme film |
| JP6337825B2 (en) * | 2015-04-21 | 2018-06-06 | 住友金属鉱山株式会社 | Method for judging quality of polyimide film, and method for producing copper-clad laminate and flexible wiring board using the polyimide film |
| CN105092473B (en) * | 2015-07-13 | 2018-11-02 | 武汉华星光电技术有限公司 | A kind of quality determining method and system of polysilicon membrane |
| CN108445166B (en) * | 2016-10-27 | 2021-02-09 | 苏州大学 | Three-dimensional porous graphene ultrathin film and preparation method thereof |
| CN109425633A (en) * | 2017-09-04 | 2019-03-05 | 深圳正峰印刷有限公司 | A kind of heat shrinkage film shrinking percentage test method and test device |
| CN108159887A (en) * | 2018-01-11 | 2018-06-15 | 天津工业大学 | A kind of method for evaluating graphene oxide membrane nanochannel structural stability |
| CN108896708A (en) * | 2018-05-31 | 2018-11-27 | 武汉华星光电技术有限公司 | Film detecting device and film detection method |
| CN109580650B (en) * | 2018-12-14 | 2021-06-25 | 清华大学 | Method for detecting surface cleanliness of graphene |
| CN109781769A (en) * | 2019-01-03 | 2019-05-21 | 新冶高科技集团有限公司 | A kind of device and measurement method measuring graphene film thermo electric material Electrothermal Properties |
| CN109540726A (en) * | 2019-01-09 | 2019-03-29 | 江苏鸿凌达科技有限公司 | A kind of high-efficiency artificial graphene film discrimination method |
| CN110887864B (en) * | 2019-11-18 | 2020-07-24 | 江苏鸿凌达科技有限公司 | Testing method of graphene heat-conducting film |
-
2020
- 2020-04-07 CN CN202010266730.1A patent/CN111398531B/en active Active
- 2020-04-07 CN CN202011431545.XA patent/CN112697969B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN112697969A (en) | 2021-04-23 |
| CN112697969B (en) | 2022-03-25 |
| CN111398531A (en) | 2020-07-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111398531B (en) | Efficient graphene film identification system and method | |
| CN116167640B (en) | LCP film production quality detection data analysis method and system | |
| CN102925602B (en) | Furnace profile maintenance method for blast furnace operation | |
| CN116298225A (en) | Online monitoring and analyzing system for ceramsite production process | |
| CN113341087A (en) | Intelligent monitoring and analyzing method and system for river water pollution source and computer storage medium | |
| CN109540726A (en) | A kind of high-efficiency artificial graphene film discrimination method | |
| CN113900035B (en) | Battery detection method, device, equipment and storage medium | |
| CN115169745A (en) | Production quality prediction method, system and computer readable medium | |
| CN113299351B (en) | Creep data screening method based on statistical test and state inspection | |
| CN115582522A (en) | High-precision chromium alloy continuous casting molding monitoring method and system | |
| CN109063218A (en) | A kind of control method and system of statistic processes | |
| CN114280371A (en) | Lithium battery coating pole piece quality consistency detection method | |
| CN114034335A (en) | Temperature and humidity parameter stable state identification method for environmental test equipment | |
| CN109033031B (en) | Bearing state detection method based on high-dimensional random matrix | |
| CN110398514B (en) | Method for rapidly judging content of metal impurities in cellulose gum | |
| CN117075018B (en) | BMS control panel capability test intelligent analysis management system | |
| CN115655382B (en) | Chemical fiber production line process on-line monitoring analysis system | |
| CN117787928B (en) | Automatic assembly equipment assembly efficiency analysis management system based on big data | |
| CN113837671B (en) | New product quality management method and system | |
| CN116954174A (en) | Quality early warning method and system based on key parameters of lithium battery coating equipment | |
| CN117571490B (en) | Pressure test analysis method in closed space | |
| CN113467434B (en) | CCA fermentation process KPI related fault monitoring method based on double-layer k nearest neighbor standardization | |
| CN108957296B (en) | Circuit health detection method based on entanglement relation discrimination | |
| CN117597638A (en) | Method for operating a press, computer program and electronically readable data carrier | |
| CN117870507A (en) | Membrane electrode uniformity test and evaluation method for hydrogen production by water electrolysis of proton exchange membrane |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP03 | Change of name, title or address | ||
| CP03 | Change of name, title or address |
Address after: No. 98 Wangting Street, Wangting Town, Xiangcheng District, Suzhou City, Jiangsu Province, 215100 Patentee after: Suzhou honglingda Electronic Technology Co.,Ltd. Country or region after: China Patentee after: SHENZHEN HANHUA THERMAL MANAGEMENT TECHNOLOGY Co.,Ltd. Address before: 215000 No.11 Chengpu Road, Suzhou Industrial Park, Wuzhong District, Suzhou City, Jiangsu Province Patentee before: SUZHOU KANRONICS ELECTRONIC TECHNOLOGY Co.,Ltd. Country or region before: China Patentee before: SHENZHEN HANHUA THERMAL MANAGEMENT TECHNOLOGY Co.,Ltd. |