CN117434908B - Intelligent stirring monitoring method and system for precise ABC glue - Google Patents
Intelligent stirring monitoring method and system for precise ABC glue Download PDFInfo
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- CN117434908B CN117434908B CN202311736175.4A CN202311736175A CN117434908B CN 117434908 B CN117434908 B CN 117434908B CN 202311736175 A CN202311736175 A CN 202311736175A CN 117434908 B CN117434908 B CN 117434908B
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- 239000003292 glue Substances 0.000 title claims abstract description 188
- 238000003756 stirring Methods 0.000 title claims abstract description 73
- 238000012544 monitoring process Methods 0.000 title claims abstract description 49
- 238000000034 method Methods 0.000 title claims abstract description 44
- 238000013507 mapping Methods 0.000 claims abstract description 38
- 238000002360 preparation method Methods 0.000 claims abstract description 25
- 238000004519 manufacturing process Methods 0.000 claims abstract description 21
- 239000002245 particle Substances 0.000 claims description 138
- 238000009826 distribution Methods 0.000 claims description 107
- 239000004615 ingredient Substances 0.000 claims description 68
- 239000000463 material Substances 0.000 claims description 48
- 238000012360 testing method Methods 0.000 claims description 17
- 238000007418 data mining Methods 0.000 claims description 16
- 238000010606 normalization Methods 0.000 claims description 15
- 238000012545 processing Methods 0.000 claims description 15
- 238000004458 analytical method Methods 0.000 claims description 7
- 238000005457 optimization Methods 0.000 claims description 7
- 238000012216 screening Methods 0.000 claims description 5
- 230000000007 visual effect Effects 0.000 claims description 4
- 238000013019 agitation Methods 0.000 claims description 2
- 238000003860 storage Methods 0.000 claims description 2
- 230000000694 effects Effects 0.000 abstract description 6
- 238000005065 mining Methods 0.000 abstract 1
- 239000000853 adhesive Substances 0.000 description 16
- 230000001070 adhesive effect Effects 0.000 description 16
- 239000012790 adhesive layer Substances 0.000 description 11
- 238000002156 mixing Methods 0.000 description 5
- 238000007405 data analysis Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 239000013543 active substance Substances 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 3
- 239000003795 chemical substances by application Substances 0.000 description 3
- 238000005315 distribution function Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012549 training Methods 0.000 description 3
- 239000004925 Acrylic resin Substances 0.000 description 2
- 229920000178 Acrylic resin Polymers 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 239000003822 epoxy resin Substances 0.000 description 2
- 238000009472 formulation Methods 0.000 description 2
- 239000000314 lubricant Substances 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 229920000647 polyepoxide Polymers 0.000 description 2
- -1 polysiloxane Polymers 0.000 description 2
- 229920001296 polysiloxane Polymers 0.000 description 2
- 239000000758 substrate Substances 0.000 description 2
- 239000000919 ceramic Substances 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000000354 decomposition reaction Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 239000004033 plastic Substances 0.000 description 1
- 229920000642 polymer Polymers 0.000 description 1
- 238000007781 pre-processing Methods 0.000 description 1
- 238000007142 ring opening reaction Methods 0.000 description 1
- 239000005060 rubber Substances 0.000 description 1
- 230000035939 shock Effects 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
Classifications
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
- G05B19/41875—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by quality surveillance of production
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32252—Scheduling production, machining, job shop
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
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- Engineering & Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Quality & Reliability (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Application Of Or Painting With Fluid Materials (AREA)
Abstract
The invention relates to the technical field of monitoring and alarming, and provides an intelligent stirring monitoring method and system of precise ABC glue, wherein the method comprises the following steps: acquiring ABC glue basic information, preparing pretreatment, mining ABC glue preset application scene index data, and acquiring scene expected indexes; obtaining glue production records, constructing a function mapping channel, optimizing glue production characteristics according to scene expected indexes, obtaining a glue configuration flow optimizing result, controlling feeding configuration and intelligent monitoring, solving the problem that an ABC glue monitoring scheme cannot be practically applied to glue configuration, the ABC glue obtained by monitoring configuration does not support the use of the technical problem in a special limited use environment, determining relevant indexes of target glue according to the requirements of the special limited use environment, and globally optimizing to determine an optimal target glue preparation scheme, so that dynamic monitoring of real-time preparation and stirring states is realized, and the configuration of the ABC glue is optimized and practically applied to glue configuration technical effects.
Description
Technical Field
The invention relates to the technical field of monitoring and alarming, in particular to an intelligent stirring monitoring method and system for precise ABC glue.
Background
ABC glue is an organosilicon structure ring-opening polymer, has excellent adhesion and flexibility, and can be used for bonding various materials, such as metal, ceramic, rubber, plastic and the like; ABC glue has the characteristics of water resistance, shock resistance, temperature resistance, peelability and the like, and is widely applied to the fields of aerospace, electronic and electric appliances, automobile manufacturing and the like.
Generally, the application scenes of the ABC glue have diversity, but correspondingly, if the temperature difference of the application scenes is large, the temperature resistance of the ABC glue needs to be paid special attention to; if the application scene is a furniture panel, the requirements on the aesthetic property are high, and the strippability of the ABC glue is required to be paid special attention to, but the preparation configuration intelligent optimization of the ABC glue preparation process cannot be performed by contrast with the application scene of the ABC glue.
In summary, in the prior art, the ABC glue monitoring scheme cannot be practically applied to glue configuration, and the ABC glue obtained by monitoring configuration does not support the technical problem of use in a specially defined use environment.
Disclosure of Invention
The application provides an intelligent stirring monitoring method and system for precise ABC glue, and aims to solve the technical problem that a monitoring scheme for ABC glue in the prior art cannot be practically applied to glue configuration, and ABC glue obtained by monitoring configuration does not support use in a special limited use environment.
In view of the above problems, embodiments of the present application provide an intelligent stirring monitoring method and system for precise ABC glue.
In a first aspect of the disclosure, an intelligent stirring monitoring method for precise ABC glue is provided, wherein the method comprises: obtaining ABC glue formula basic information, wherein the ABC glue formula basic information comprises ingredient basic information, feeding sequence information, configuration environment information and stirring basic information; carrying out preparation pretreatment on a plurality of material conveying containers according to the basic information of the ingredients; acquiring ABC glue preset application scene information for data mining to acquire expected temperature resistance, expected adhesion characteristics and expected strippability; acquiring glue production record data, and constructing a functional mapping channel from the feeding sequence information, the configuration environment information and the stirring basic information to temperature resistance, adhesion characteristics and strippability; according to the expected temperature resistance, the expected adhesion characteristic and the expected strippability, optimizing the feeding sequence information and/or the configuration environment information and/or the stirring basic information based on the function mapping channel to obtain a glue configuration flow optimizing result; and controlling the plurality of material conveying containers to carry out feeding configuration in the glue configuration container according to the optimizing result of the glue configuration flow, and carrying out intelligent monitoring.
In another aspect of the present disclosure, an intelligent agitation monitoring system for precision ABC glue is provided, wherein the system comprises: the basic information acquisition module is used for acquiring ABC glue formula basic information, wherein the ABC glue formula basic information comprises ingredient basic information, feeding sequence information, configuration environment information and stirring basic information; the preparation pretreatment module is used for carrying out preparation pretreatment on a plurality of material conveying containers according to the batching basic information; the data mining module is used for acquiring ABC glue preset application scene information to perform data mining and acquiring expected temperature resistance, expected adhesion characteristics and expected strippability; the index configuration module is used for acquiring glue production record data and constructing a functional mapping channel from the feeding sequence information, the configuration environment information and the stirring basic information to temperature resistance, adhesion characteristics and peelability; the process optimizing module is used for optimizing the feeding sequence information and/or the configuration environment information and/or the stirring basic information according to the expected temperature resistance, the expected adhesion characteristic and the expected peelability, and acquiring a glue configuration process optimizing result based on the function mapping channel; and the feeding configuration module is used for controlling the plurality of feeding containers to carry out feeding configuration in the glue configuration container according to the optimizing result of the glue configuration flow and carrying out intelligent monitoring.
One or more technical solutions provided in the present application have at least the following technical effects or advantages:
due to the adoption of the method for acquiring ABC glue basic information and carrying out preparation pretreatment, the preset application scene index data of the ABC glue is mined, and the expected indexes of the scene are acquired; acquiring a glue production record and constructing a function mapping channel; according to the expected indexes of the scene, optimizing the glue production characteristics by utilizing the functional mapping channel, acquiring the optimizing result of the glue configuration flow, controlling a plurality of material conveying containers to carry out feeding configuration in the glue configuration containers and monitoring, determining the related indexes of the target glue according to the requirements of the special limited use environment, carrying out data global optimizing to determine the optimal preparation scheme of the target glue, realizing dynamic monitoring of real-time preparation and stirring states, carrying out monitoring data analysis by utilizing a data mining technology to generate stirring decisions, optimizing the configuration of ABC glue and being practically applied to the technical effect of glue configuration.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
Fig. 1 is a schematic diagram of a possible flow chart of an intelligent stirring monitoring method for precise ABC glue according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of determining the possibility of expected peelability in an intelligent stirring monitoring method of precise ABC glue according to an embodiment of the present application;
fig. 3 is a schematic flow chart of a possible process for obtaining a glue configuration flow optimizing result in the intelligent stirring monitoring method of precise ABC glue according to an embodiment of the present application;
fig. 4 is a schematic diagram of a possible structure of an intelligent stirring monitoring system for precise ABC glue according to an embodiment of the present application.
Reference numerals illustrate: the system comprises a basic information acquisition module 100, a preparation preprocessing module 200, a data mining module 300, an index configuration module 400, a flow optimizing module 500 and a feeding configuration module 600.
Detailed Description
The embodiment of the application provides an intelligent stirring monitoring method and system for precise ABC glue, which solve the technical problem that a monitoring scheme of ABC glue cannot be practically applied to glue configuration, ABC glue obtained by monitoring configuration does not support the use in a special limited use environment, and the technical effects of determining relevant indexes of target glue according to the requirements of the special limited use environment, performing data global optimization to determine an optimal preparation scheme of the target glue, dynamically monitoring real-time preparation and stirring states, performing monitoring data analysis by utilizing a data mining technology to generate stirring decisions, optimizing the configuration of ABC glue and being practically applied to glue configuration are achieved.
Having described the basic principles of the present application, various non-limiting embodiments of the present application will now be described in detail with reference to the accompanying drawings.
Example 1
As shown in fig. 1, an embodiment of the present application provides an intelligent stirring monitoring method for precise ABC glue, where the method includes:
s10: obtaining ABC glue formula basic information, wherein the ABC glue formula basic information comprises ingredient basic information, feeding sequence information, configuration environment information and stirring basic information;
s20: carrying out preparation pretreatment on a plurality of material conveying containers according to the basic information of the ingredients;
step S20 includes the steps of:
s21: acquiring a plurality of ingredient types, a plurality of ingredient proportions and ingredient total amount information according to the ingredient basic information;
s22: determining a plurality of ingredient feeds of the plurality of ingredient types according to the ingredient total amount information, the plurality of ingredient types and the plurality of ingredient proportions;
s23: and matching the plurality of material conveying containers according to the plurality of material proportioning types and the plurality of material proportioning feeding amounts for material proportioning pre-storage, wherein the plurality of material conveying containers are in one-to-one correspondence with the plurality of material proportioning types.
Specifically, the ABC glue consists of three components A, B, C, wherein the component A is epoxy resin and curing agent, the component B is acrylic resin and active agent, and the component C is polysiloxane-based lubricant; obtaining ABC glue formula basic information, wherein the ABC glue formula basic information comprises ingredient basic information, feeding sequence information, configuration environment information and stirring basic information, and the ingredient basic information is used for representing ingredient types, ingredient proportions and ingredient total amounts;
The feeding sequence information is used for representing that the component A and the component B are mixed uniformly and stirred, then the component C is added, three components are fully mixed, the component B and the component C are mixed uniformly and stirred, then the component A is added, three components are fully mixed, the component A and the component C are mixed uniformly and stirred, then the component B is added, and then three components are fully mixed, and the component A, the component B and the component C are directly fully mixed;
the stirring basic information comprises stirring control characteristics of each node, wherein the first node stirring control characteristic of each node stirring control characteristic comprises the stirring speed and the stirring time of the first node, the first node stirring control characteristic is any node of the stirring control characteristics of each node, and any node refers to how long to start stirring after an active agent or a curing agent or any ingredient is fed, and also can refer to starting stirring at a certain temperature after any ingredient is fed;
the preparation pretreatment is carried out on a plurality of material conveying containers according to the material mixing basic information, and comprises a plurality of interfaces, namely an A port, a B port and a C port, wherein the preparation pretreatment is used for representing the material mixing of corresponding quantity pre-stored respectively through the interfaces, the material mixing types comprise epoxy resin, curing agent, acrylic resin, active agent, polysiloxane-based lubricant and other material mixing types, and the material mixing proportion is that of the A component: the dosage of the component B is as follows: the consumption of the component C, according to the basic information of the ingredients, a plurality of ingredient types, a plurality of ingredient proportions and total ingredient amount information are obtained;
According to the total amount information of ingredients, the plurality of ingredient types and the plurality of ingredient proportions, carrying out product operation according to the plurality of ingredient proportions and the total amount information of ingredients, calculating to obtain the component A consumption, the component B consumption and the component C consumption, carrying out characteristic combination on the component A consumption, the component B consumption and the component C consumption and the plurality of ingredient types, and determining a plurality of ingredient feeding amounts of the plurality of ingredient types;
selecting a material conveying container according to the plurality of ingredient types, preferably, carrying out material conveying container volume selection according to the plurality of ingredient feeding amounts without any chemical reaction, preferably, matching the plurality of material conveying containers according to the plurality of ingredient types and the plurality of ingredient feeding amounts, and carrying out ingredient pre-storing, wherein the plurality of material conveying containers are in one-to-one correspondence with the plurality of ingredient types, and provide a data support basis for subsequent analysis.
S30: acquiring ABC glue preset application scene information for data mining to acquire expected temperature resistance, expected adhesion characteristics and expected strippability;
step S30 includes the steps of:
S31: the ABC glue preset application scene information is traversed to select a temperature maximum value, the temperature maximum value is obtained, the expected temperature resistance is set, including,
s32: when the maximum temperature value is smaller than or equal to an ABC glue rated temperature resistant threshold value, setting the ABC glue rated temperature resistant threshold value as the expected temperature resistant performance;
s33: when the maximum temperature value is larger than the ABC glue rated temperature resistance threshold, setting the maximum temperature value as the expected temperature resistance;
s34: traversing the ABC glue preset application scene information to select the maximum value of the adhesion characteristic index, obtaining the maximum value of the adhesion characteristic index, and setting the maximum value of the adhesion characteristic index as the expected adhesion characteristic;
s35: and traversing the ABC glue preset application scene information to carry out adhesion characteristic index balance analysis, obtaining an adhesion characteristic index balance state, and setting the adhesion characteristic index balance state as the expected strippability.
Specifically, data mining is carried out by acquiring ABC glue preset application scene information to obtain expected temperature resistance, expected adhesion characteristics and expected strippability, wherein the steps include that temperature maximum selection is carried out by traversing the ABC glue preset application scene information to obtain a temperature maximum value, the expected temperature resistance is set, further, the ABC glue rated temperature resistance threshold is the most appropriate temperature which does not affect the stability of the glue, the temperature maximum value is compared with the ABC glue rated temperature resistance threshold, when the temperature maximum value is smaller than or equal to the ABC glue rated temperature resistance threshold, the temperature difference corresponding to the ABC glue preset application scene information is indicated to be within the limit of the ABC glue rated temperature resistance threshold, the stability of the glue is not affected, and the ABC glue rated temperature resistance threshold is set to be the expected temperature resistance; when the maximum temperature value is larger than the ABC glue rated temperature-resistant threshold, namely, the temperature difference corresponding to ABC glue preset application scene information is indicated to exceed the ABC glue rated temperature-resistant threshold limit, the stability of the glue is possibly affected, and preferably, the maximum temperature value is set to be the expected temperature-resistant performance;
Judging whether the initial adhesion, the adhesive force, the cohesive force and the adhesive base force meet respective thresholds or not by referring to the determining step of the expected temperature resistance, selecting the maximum value of the adhesion characteristic index by traversing the ABC glue preset application scene information, obtaining the maximum value of the adhesion characteristic index, and setting the maximum value as the expected adhesion characteristic;
and referring to the step of determining the expected temperature resistance, judging whether all the forces are balanced according to the initial adhesion force < cohesion force less than or equal to the adhesion base force, traversing the ABC glue preset application scene information to perform adhesion characteristic index balance analysis, obtaining an adhesion characteristic index balance state, setting the expected peelability, and determining the related index of the target glue according to the requirement of a special limited use environment from the ABC glue preset application scene, so as to provide support for ensuring that the ABC glue obtained by configuration is supported to be used in the special limited use environment.
As shown in fig. 2, step S35 includes the steps of:
s351: the adhesion characteristic index comprises an initial adhesion index, an adhesion index, a cohesive force index and a cohesive base force index;
s352: constructing an initial balance state of the adhesion characteristic index, wherein the initial balance state is as follows: the initial adhesion index is less than the adhesion index, the cohesion index is less than or equal to the adhesion index;
S353: acquiring adhesion test record data based on the initial equilibrium state, wherein the adhesion test record data comprises adhesion characteristic index deviation record data and adhesion state record data;
s354: setting the adhesion characteristic index deviation record data of which the adhesion state record data accords with a preset adhesion state as the expected peelability.
Specifically, the ABC glue preset application scene information is traversed to carry out adhesion characteristic index balance analysis, an adhesion characteristic index balance state is obtained, and the expected peelability is set, wherein the adhesion characteristic index comprises an initial adhesion index, an adhesion index, a cohesive force index and an adhesive base force index; whether peeling would cause damage to the substrate: the initial adhesion index is less than the adhesion index; whether the adhesive layer can fall off the base material: adhesive force index < cohesive force index; whether peeling can cause damage to the glue line: the cohesive force index is less than or equal to the adhesive base force index, and the initial equilibrium state of the adhesive characteristic index is obtained by combining: the initial adhesion index is less than the adhesion index, the cohesion index is less than or equal to the adhesion index;
the adhesion test record data comprises adhesion characteristic index deviation record data and adhesion state record data, adhesion test is carried out, after the adhesion of the base material A and the base material B is finished by using ABC glue, the adhesion test record data is obtained based on the initial balance state, the adhesion test record data comprises the adhesion characteristic index deviation record data and the adhesion state record data, and whether the base material is damaged by peeling is judged; judging whether the adhesive layer can fall off the base material; judging whether the stripping can cause damage to the adhesive layer; the bonding state record data corresponds to that the peeling is damaged or not damaged to the substrate, the adhesive layer is peeled off or not peeled off, the adhesive layer is damaged or not damaged;
The preset bonding state corresponds to the allowable damage degree of the base material, the allowable damage degree of the adhesive layer, the allowable time length of the adhesive layer falling off the base material and the like, the deviation between the initial adhesion index and the adhesive force index in the bonding test process is calculated, whether the deviation between the initial adhesion index and the adhesive force index in the bonding test process is in the allowable damage degree of the base material corresponding to the preset bonding state or not is judged according to the allowable damage degree of the base material corresponding to the preset bonding state, and the judgment result is taken as the first expected peelability;
calculating the deviation between the adhesive force index and the cohesive force index in the adhesive test process, judging whether the deviation between the adhesive force index and the cohesive force index in the adhesive test process is in the allowable time length of the adhesive layer shedding base material corresponding to the preset adhesive state according to the allowable time length of the adhesive layer shedding base material corresponding to the preset adhesive state, and taking the judging result as a second expected strippable property;
calculating the deviation between cohesive force indexes and adhesive base force indexes in the adhesion test process, judging whether the deviation between the cohesive force indexes and the adhesive base force indexes in the adhesion test process is in the allowable damage degree of the adhesive layer corresponding to the preset adhesion state according to the allowable damage degree of the adhesive layer corresponding to the preset adhesion state, and taking the judgment result as a third expected peelability;
If the first expected detachability, the second expected detachability and the third expected detachability are all passed, the adhesion state record data are indicated to be in accordance with the adhesion characteristic index deviation record data of a preset adhesion state, and if any one of the first expected detachability, the second expected detachability and the third expected detachability is not passed, the adhesion state record data are indicated to be not in accordance with the adhesion characteristic index deviation record data of a preset adhesion state; setting the adhesion characteristic index deviation record data of which the adhesion state record data accords with a preset adhesion state as the expected strippability, setting the adhesion characteristic index deviation record data of which the adhesion state record data accords with the preset adhesion state as the expected strippability, carrying out specific quantitative calculation according to an initial balance state, judging whether all forces are balanced or not, and determining specific deviation so as to ensure the effectiveness of the expected strippability.
S40: acquiring glue production record data, and constructing a functional mapping channel from the feeding sequence information, the configuration environment information and the stirring basic information to temperature resistance, adhesion characteristics and strippability;
S50: according to the expected temperature resistance, the expected adhesion characteristic and the expected strippability, optimizing the feeding sequence information and/or the configuration environment information and/or the stirring basic information based on the function mapping channel to obtain a glue configuration flow optimizing result;
s60: and controlling the plurality of material conveying containers to carry out feeding configuration in the glue configuration container according to the optimizing result of the glue configuration flow, and carrying out intelligent monitoring.
Specifically, the glue production record data, namely different feeding orders or configuration environments, such as environmental parameters of temperature, pH value and the like, or stirring speed and duration, the different feeding orders in the glue production record data are recorded as the feeding order information, the configuration environments in the glue production record data are recorded as the configuration environment information, the stirring speed and duration in the glue production record data are recorded as the stirring base information, and a functional mapping channel from the feeding order information, the configuration environment information and the stirring base information to the temperature resistance, the adhesion characteristic and the strippability is constructed according to the time sequence information in the glue production record data;
Training a temperature resistance prediction sub-channel according to the glue production record data; training an adhesion characteristic prediction sub-channel according to the glue production record data; training a peelability prediction sub-channel according to the glue production record data; combining the temperature resistance prediction sub-channel, the adhesion characteristic prediction sub-channel and the strippable prediction sub-channel as parallel nodes to generate a functional mapping channel;
based on the function mapping channel, optimizing the feeding sequence information and/or the configuration environment information and/or the stirring basic information according to the expected temperature resistance, the expected adhesion characteristic and the expected strippability, obtaining a glue configuration flow optimizing result, controlling the plurality of material conveying containers to feed and configure in the glue configuration container according to the glue configuration flow optimizing result, performing intelligent monitoring, dynamically monitoring real-time configuration and stirring states, giving an alarm when deviating from the glue configuration flow optimizing result, and guaranteeing stable production of glue.
As shown in fig. 3, step S50 includes the steps of:
s51: acquiring a configuration flow control index set according to the feeding sequence information, the configuration environment information and the stirring basic information;
S52: taking the addition result of the temperature resistance, the adhesion property and the peelability as a control particle fitness;
s53: setting control particles for the feeding sequence information and/or the configuration environment information and/or the stirring basic information through a visual interface of a user side to obtain M initial control particles, wherein M is more than or equal to 20, and M is an integer;
s54: and optimizing the control particle fitness and the function mapping channel based on the M initial control particles to obtain the optimizing result of the glue configuration flow.
Specifically, the feeding sequence information, the configuration environment information and/or the stirring basic information are optimized according to the expected temperature resistance, the expected adhesion property and the expected strippability, and a glue configuration flow optimizing result is obtained based on the function mapping channel, wherein the configuration flow control index set corresponds to a plurality of dimension indexes, and the feeding sequence value, the feeding quantity, the temperature of the environment, the pH and the speed and the duration of any node of stirring of each material are independent dimensions, and a configuration flow control index set is obtained according to the feeding sequence information, the configuration environment information and the stirring basic information;
Calculating a control particle fitness=f (temperature resistance performance index value, adhesion property index value, peelability index value) as a result of addition of the temperature resistance performance, the adhesion property, and the peelability as a control particle fitness; on the visual interface of the user side, randomly setting control particles for the feeding sequence information and/or the configuration environment information and/or the stirring basic information to obtain M initial control particles; based on the M initial control particles, performing global optimization on the control particle fitness and the function mapping channel, updating the M initial control particles, and obtaining the glue configuration flow optimizing result; according to the control particle fitness of the M initial control particles, the optimal solution of the problem is continuously and iteratively found by utilizing a group competition strategy among the control particles, and the optimal preparation scheme of the target glue is determined by carrying out data global optimization.
Step S54 includes the steps of:
s541: constructing a control particle distribution space according to the configuration flow control index set;
s542: inputting the M initial control particles into the control particle distribution space for distribution, and obtaining an initial distribution result;
S543: performing multistage expansion distribution on the initial distribution result in the control particle distribution space based on the control particle fitness and the function mapping channel to obtain a control particle expansion distribution result;
s544: and screening i control particles with large-to-small adaptability in the control particle expansion distribution result, and setting the i control particles as the glue configuration flow optimizing result, wherein i is more than or equal to 1 and less than or equal to 10.
Specifically, based on the M initial control particles, optimizing the fitness of the control particles and the functional mapping channel, and obtaining the optimizing result of the glue configuration flow, including constructing a D-dimensional control particle distribution space according to a plurality of dimension indexes corresponding to the configuration flow control index set, recording the D-dimensional control particle distribution space as a control particle distribution space, where the position of the mth control particle in the M initial control particles is X m =(x m1 ,x m2 ,...,x Dm ) Wherein m is E (0, 20]And m is an integer;
inputting the M initial control particles in the control particle distribution space by referring to the position of the mth control particle, acquiring the distribution of the M initial control particles in the control particle distribution space, and recording the distribution of the M initial control particles in the control particle distribution space as an initial distribution result; performing multistage expansion distribution on the initial distribution result in the control particle distribution space based on the control particle fitness and the function mapping channel to obtain a control particle expansion distribution result; sorting the adaptability of the control particle expansion distribution results from big to small, screening i control particles with the adaptability of the control particle expansion distribution results from big to small, adding the i control particles obtained by screening to the glue configuration flow optimizing result, specifically expanding the data global optimizing step, and searching the optimal solution of the problem by continuous iteration.
Step S543 includes the steps of:
s543-1: obtaining the maximum fitness and the minimum fitness of M initial control particle fitness of the M initial control particles;
s543-2: performing max-min normalization processing according to the maximum fitness and the minimum fitness traversing the M initial control particle fitness, and obtaining M normalization processing results;
s543-3: setting the maximum expansion number and the minimum expansion number, and calculating the maximum deviation of the expansion number;
s543-4: calculating the product of the maximum deviation of the expansion quantity and the M normalization processing results to obtain M expansion quantity constraint factors;
s543-5: adding the M expansion quantity constraint factors with the minimum expansion quantity respectively and rounding up to generate M expansion quantity constraint values;
s543-6: performing primary expansion distribution on the initial distribution result in the control particle distribution space according to normal distribution based on a standard deviation value interval and the M expansion quantity constraint values to obtain a control particle primary expansion distribution result;
s543-7: and carrying out secondary expansion distribution on the primary expansion distribution result of the control particles in the control particle distribution space according to normal distribution until N-level expansion distribution based on the control particle fitness and the function mapping channel to obtain the control particle expansion distribution result, wherein N is the maximum expansion series number, N is more than or equal to 1, and N is an integer.
Specifically, the control particle fitness and the function mapping channel are used for carrying out multistage expansion distribution on the initial distribution result in the control particle distribution space to obtain a control particle expansion distribution result, wherein the control particle expansion distribution result comprises the steps of calculating control particle fitness=f (temperature resistance performance index value, adhesion characteristic index value and peelability index value), substituting the M initial control particles into a formula for calculating the control particle fitness, respectively carrying out fitness calculation to obtain M initial control particle fitness of the M initial control particles, comparing the M initial control particle fitness, and determining the maximum fitness and the minimum fitness of the M initial control particle fitness;
performing max-min normalization processing according to the maximum fitness and the minimum fitness traversing the M initial control particle fitness, respectively calculating the distances between other fitness except the maximum fitness and the minimum fitness and the maximum fitness among the M initial control particle fitness, and obtaining the relative proximity degree between the other fitness except the maximum fitness and the minimum fitness and the optimal matching characteristic among the M initial control particle fitness, and taking the relative proximity degree as the basis of normalization processing to obtain M normalization processing results;
Setting maximum expansion quantity and minimum expansion quantity by comparing the maximum adaptation degree and the minimum adaptation degree, calculating maximum expansion quantity deviation, wherein the maximum expansion quantity deviation=maximum expansion quantity-minimum expansion quantity, calculating the product of the maximum expansion quantity deviation and the M normalization processing results, and taking the product of the maximum expansion quantity deviation and the M normalization processing results as M expansion quantity constraint factors; adding the M expansion quantity constraint factors with the minimum expansion quantity respectively, and recording the addition result as M expansion quantity addition constraint factors; using a ceil function, adding the M expansion numbers and rounding up the constraint factors, and rounding up to obtain M expansion number constraint values;
controlling a particle expansion distribution function:wherein, the method comprises the steps of, wherein,δ g is the standard deviation when the g-th level is expanded, g is the number of expansion levels, g is less than or equal to N, N is the maximum number of expansion levels, wherein N is more than or equal to 1 and N is an integer,δ sta as a result of the initial standard deviation,δ fin as a result of the final standard deviation,g max the maximum expansion series is customized, w is a nonlinear adjusting factor, and specific data are set according to actual conditions;
according to the control particle expansion distribution function, carrying out primary expansion distribution on the initial distribution result in the control particle distribution space based on a standard deviation value interval and the M expansion quantity constraint values according to a distribution mode of normal distribution, and obtaining a primary expansion distribution result of the control particles; and according to the control particle expansion distribution function, carrying out secondary expansion distribution to N-level expansion distribution according to normal distribution based on the control particle fitness and the control particle first-level expansion distribution result of the function mapping channel in the control particle distribution space, obtaining the control particle expansion distribution result, carrying out monitoring data analysis by utilizing a data mining technology to generate a stirring decision, and optimizing the configuration of ABC glue.
In summary, the intelligent stirring monitoring method and system for precise ABC glue provided by the embodiment of the application have the following technical effects:
1. due to the adoption of the method for acquiring ABC glue basic information and carrying out preparation pretreatment, the preset application scene index data of the ABC glue is mined, and the expected indexes of the scene are acquired; acquiring a glue production record and constructing a function mapping channel; according to the intelligent stirring monitoring method and system for the precise ABC glue, related indexes of the target glue are determined according to the requirements of a special limited use environment, the optimal preparation scheme of the target glue is determined through data global optimization, dynamic monitoring of real-time preparation and stirring states are realized, monitoring data analysis is carried out by utilizing a data mining technology to generate stirring decisions, and the configuration of the ABC glue is optimized and the technical effects of being practically applied to glue configuration are achieved.
2. The particle distribution space is constructed and controlled by adopting a control index set according to the configuration flow; inputting M initial control particles for distribution, and obtaining initial distribution results; in the control particle distribution space, multilevel expansion distribution is carried out based on the control particle fitness and the function mapping channel, a control particle expansion distribution result is obtained, a glue configuration flow optimizing result is set, a data global optimizing step is specifically expanded, and the optimal solution of the problem is found through continuous iteration.
Example two
Based on the same inventive concept as the intelligent stirring monitoring method of the precise ABC glue in the foregoing embodiments, as shown in fig. 4, an embodiment of the present application provides an intelligent stirring monitoring system of the precise ABC glue, where the system includes:
the basic information acquisition module 100 is configured to acquire ABC glue formulation basic information, where the ABC glue formulation basic information includes ingredient basic information, feeding sequence information, configuration environment information, and stirring basic information;
a preparation pretreatment module 200, configured to perform preparation pretreatment on a plurality of material conveying containers according to the ingredient basic information;
the data mining module 300 is used for acquiring ABC glue preset application scene information to perform data mining and acquiring expected temperature resistance, expected adhesion characteristics and expected strippability;
the index configuration module 400 is used for obtaining glue production record data and constructing a functional mapping channel from the feeding sequence information, the configuration environment information and the stirring basic information to temperature resistance, adhesion characteristics and peelability;
the process optimizing module 500 is configured to optimize the feeding sequence information and/or the configuration environment information and/or the stirring base information according to the expected temperature resistance, the expected adhesion characteristic and the expected peelability, and obtain a glue configuration process optimizing result based on the function mapping channel;
And the feeding configuration module 600 is configured to control the plurality of feeding containers to perform feeding configuration in the glue configuration container according to the optimizing result of the glue configuration flow, and perform intelligent monitoring.
Further, the system includes:
the ingredient information acquisition module is used for acquiring information of a plurality of ingredient types, a plurality of ingredient proportions and an ingredient total amount according to the ingredient basic information;
the feeding amount determining module is used for determining a plurality of ingredient feeding amounts of the plurality of ingredient types according to the ingredient total amount information, the plurality of ingredient types and the plurality of ingredient proportions;
the ingredient pre-storing module is used for matching the plurality of material conveying containers to carry out ingredient pre-storing according to the plurality of ingredient types and the plurality of ingredient feeding amounts, wherein the plurality of material conveying containers are in one-to-one correspondence with the plurality of ingredient types.
Further, the system includes:
the expected temperature resistance setting module is used for traversing the ABC glue preset application scene information to select the maximum temperature value, obtaining the maximum temperature value, setting the expected temperature resistance, comprising,
the expected temperature resistance setting module is used for setting the ABC glue rated temperature resistance threshold as the expected temperature resistance when the maximum temperature value is smaller than or equal to the ABC glue rated temperature resistance threshold;
The expected temperature resistance setting module is used for setting the maximum temperature value as the expected temperature resistance when the maximum temperature value is larger than the rated temperature resistance threshold of the ABC glue;
the expected adhesion characteristic setting module is used for traversing the ABC glue preset application scene information to select the maximum value of the adhesion characteristic index, acquiring the maximum value of the adhesion characteristic index and setting the maximum value as the expected adhesion characteristic;
the expected strippability setting module is used for traversing the ABC glue preset application scene information to carry out adhesion characteristic index balance analysis, obtaining an adhesion characteristic index balance state and setting the expected strippability.
Further, the system includes:
the adhesion characteristic index decomposition module is used for the adhesion characteristic indexes including an initial adhesion index, an adhesion index, a cohesive force index and an adhesion base index;
the initial balance state determining module is used for constructing an initial balance state of the adhesion characteristic index, and the initial balance state is as follows: the initial adhesion index is less than the adhesion index, the cohesion index is less than or equal to the adhesion index;
the adhesion test record data acquisition module is used for acquiring adhesion test record data based on the initial balance state, wherein the adhesion test record data comprises adhesion characteristic index deviation record data and adhesion state record data;
And the expected peelability determining module is used for setting the adhesion characteristic index deviation record data, which is consistent with a preset adhesion state, of the adhesion state record data as the expected peelability.
Further, the system includes:
the configuration flow control index set acquisition module is used for acquiring a configuration flow control index set according to the feeding sequence information, the configuration environment information and the stirring basic information;
a control particle fitness determination module for controlling particle fitness as a result of addition of the temperature resistance, the adhesion property, and the peelability;
the control particle setting module is used for setting control particles for the feeding sequence information and/or the configuration environment information and/or the stirring basic information through a visual interface of a user side to obtain M initial control particles, wherein M is more than or equal to 20, and M is an integer;
the glue configuration flow optimizing result obtaining module is used for obtaining the glue configuration flow optimizing result based on the M initial control particles, the control particle fitness and the function mapping channel.
Further, the system includes:
the control particle distribution space construction module is used for constructing a control particle distribution space according to the configuration flow control index set;
The initial distribution result acquisition module is used for inputting the M initial control particles into the control particle distribution space for distribution, and acquiring initial distribution results;
the multistage expansion distribution module is used for carrying out multistage expansion distribution on the initial distribution result in the control particle distribution space based on the control particle fitness and the function mapping channel, and obtaining a control particle expansion distribution result;
the glue configuration flow optimizing result determining module is used for screening i control particles with large-to-small adaptability in the control particle expansion distribution result, and setting the i control particles as the glue configuration flow optimizing result, wherein i is more than or equal to 1 and less than or equal to 10.
Further, the system includes:
the maximum fitness and minimum fitness acquisition module is used for acquiring the maximum fitness and the minimum fitness of M initial control particle fitness of the M initial control particles;
the normalization processing module is used for performing max-min normalization processing according to the maximum fitness and the minimum fitness and traversing the M initial control particle fitness to obtain M normalization processing results;
the maximum deviation calculation module of the expansion quantity is used for setting the maximum expansion quantity and the minimum expansion quantity and calculating the maximum deviation of the expansion quantity;
The expansion quantity constraint factor acquisition module is used for calculating the product of the maximum deviation of the expansion quantity and the M normalization processing results to acquire M expansion quantity constraint factors;
the expansion quantity constraint value generation module is used for respectively summing the M expansion quantity constraint factors with the minimum expansion quantity and rounding up to generate M expansion quantity constraint values;
the control particle first-stage expansion distribution result acquisition module is used for carrying out first-stage expansion distribution on the initial distribution result in the control particle distribution space according to normal distribution based on a standard deviation value interval and the M expansion quantity constraint values to acquire a control particle first-stage expansion distribution result;
the control particle expansion distribution result acquisition module is used for carrying out secondary expansion distribution on the control particle primary expansion distribution result in the control particle distribution space according to normal distribution until N-level expansion distribution based on the control particle fitness and the function mapping channel to acquire the control particle expansion distribution result, wherein N is the maximum expansion series, N is more than or equal to 1, and N is an integer.
Any of the steps of the methods described above may be stored as computer instructions or programs in a non-limiting computer memory and may be called by a non-limiting computer processor to identify any of the methods to implement embodiments of the present application, without unnecessary limitations.
Further, the foregoing and/or the foregoing may refer to a plurality of elements being individually or collectively selected. It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the present application and the equivalents thereof, the present application is intended to cover such modifications and variations.
Claims (8)
1. An intelligent stirring monitoring method of precise ABC glue is characterized by comprising the following steps:
obtaining ABC glue formula basic information, wherein the ABC glue formula basic information comprises ingredient basic information, feeding sequence information, configuration environment information and stirring basic information;
carrying out preparation pretreatment on a plurality of material conveying containers according to the basic information of the ingredients; and
acquiring ABC glue preset application scene information for data mining to acquire expected temperature resistance, expected adhesion characteristics and expected strippability;
acquiring glue production record data, and constructing a functional mapping channel from the feeding sequence information, the configuration environment information and the stirring basic information to temperature resistance, adhesion characteristics and strippability;
according to the expected temperature resistance, the expected adhesion characteristic and the expected strippability, optimizing the feeding sequence information and/or the configuration environment information and/or the stirring basic information based on the function mapping channel to obtain a glue configuration flow optimizing result;
And controlling the plurality of material conveying containers to carry out feeding configuration in the glue configuration container according to the optimizing result of the glue configuration flow, and carrying out intelligent monitoring.
2. The method of claim 1, wherein the dispensing preconditioning is performed in a plurality of delivery vessels based on the dispensing base information, comprising:
acquiring a plurality of ingredient types, a plurality of ingredient proportions and ingredient total amount information according to the ingredient basic information;
determining a plurality of ingredient feeds of the plurality of ingredient types according to the ingredient total amount information, the plurality of ingredient types and the plurality of ingredient proportions;
and matching the plurality of material conveying containers according to the plurality of material proportioning types and the plurality of material proportioning feeding amounts for material proportioning pre-storage, wherein the plurality of material conveying containers are in one-to-one correspondence with the plurality of material proportioning types.
3. The method of claim 1, wherein collecting ABC glue preset application scenario information for data mining to obtain desired temperature resistance, desired adhesion characteristics, and desired strippability, comprises:
the ABC glue preset application scene information is traversed to select a temperature maximum value, the temperature maximum value is obtained, the expected temperature resistance is set, including,
When the maximum temperature value is smaller than or equal to an ABC glue rated temperature resistant threshold value, setting the ABC glue rated temperature resistant threshold value as the expected temperature resistant performance;
when the maximum temperature value is larger than the ABC glue rated temperature resistance threshold, setting the maximum temperature value as the expected temperature resistance;
traversing the ABC glue preset application scene information to select the maximum value of the adhesion characteristic index, obtaining the maximum value of the adhesion characteristic index, and setting the maximum value of the adhesion characteristic index as the expected adhesion characteristic;
and traversing the ABC glue preset application scene information to carry out adhesion characteristic index balance analysis, obtaining an adhesion characteristic index balance state, and setting the adhesion characteristic index balance state as the expected strippability.
4. The method of claim 3, wherein traversing the ABC glue preset application scenario information for adhesion property index balance analysis to obtain an adhesion property index balance state, setting to the desired peelability, comprises:
the adhesion characteristic index comprises an initial adhesion index, an adhesion index, a cohesive force index and a cohesive base force index;
constructing an initial balance state of the adhesion characteristic index, wherein the initial balance state is as follows: the initial adhesion index is less than the adhesion index, the cohesion index is less than or equal to the adhesion index;
Acquiring adhesion test record data based on the initial equilibrium state, wherein the adhesion test record data comprises adhesion characteristic index deviation record data and adhesion state record data;
setting the adhesion characteristic index deviation record data of which the adhesion state record data accords with a preset adhesion state as the expected peelability.
5. The method of claim 1, wherein optimizing the feed order information and/or the configuration environment information and/or the agitation basis information based on the function mapping channel according to the desired temperature resistance, the desired adhesion property, and the desired peelability, obtaining a glue configuration flow optimization result comprises:
acquiring a configuration flow control index set according to the feeding sequence information, the configuration environment information and the stirring basic information;
taking the addition result of the temperature resistance, the adhesion property and the peelability as a control particle fitness;
setting control particles for the feeding sequence information and/or the configuration environment information and/or the stirring basic information through a visual interface of a user side to obtain M initial control particles, wherein M is more than or equal to 20, and M is an integer;
And optimizing the control particle fitness and the function mapping channel based on the M initial control particles to obtain the optimizing result of the glue configuration flow.
6. The method of claim 5, wherein optimizing the control particle fitness and the function mapping channel based on the M initial control particles, obtaining the glue configuration flow optimization result comprises:
constructing a control particle distribution space according to the configuration flow control index set;
inputting the M initial control particles into the control particle distribution space for distribution, and obtaining an initial distribution result;
performing multistage expansion distribution on the initial distribution result in the control particle distribution space based on the control particle fitness and the function mapping channel to obtain a control particle expansion distribution result;
and screening i control particles with large-to-small adaptability in the control particle expansion distribution result, and setting the i control particles as the glue configuration flow optimizing result, wherein i is more than or equal to 1 and less than or equal to 10.
7. The method of claim 6, wherein performing multistage expansion distribution on the initial distribution result in the control particle distribution space based on the control particle fitness and the function mapping channel, obtaining a control particle expansion distribution result, comprises:
Obtaining the maximum fitness and the minimum fitness of M initial control particle fitness of the M initial control particles;
performing max-min normalization processing according to the maximum fitness and the minimum fitness traversing the M initial control particle fitness, and obtaining M normalization processing results;
setting the maximum expansion number and the minimum expansion number, and calculating the maximum deviation of the expansion number;
calculating the product of the maximum deviation of the expansion quantity and the M normalization processing results to obtain M expansion quantity constraint factors;
adding the M expansion quantity constraint factors with the minimum expansion quantity respectively and rounding up to generate M expansion quantity constraint values;
performing primary expansion distribution on the initial distribution result in the control particle distribution space according to normal distribution based on a standard deviation value interval and the M expansion quantity constraint values to obtain a control particle primary expansion distribution result;
and carrying out secondary expansion distribution on the primary expansion distribution result of the control particles in the control particle distribution space according to normal distribution until N-level expansion distribution based on the control particle fitness and the function mapping channel to obtain the control particle expansion distribution result, wherein N is the maximum expansion series number, N is more than or equal to 1, and N is an integer.
8. An intelligent stirring monitoring system for precise ABC glue, which is used for implementing the intelligent stirring monitoring method for precise ABC glue according to any one of claims 1 to 7, and comprises the following steps:
the basic information acquisition module is used for acquiring ABC glue formula basic information, wherein the ABC glue formula basic information comprises ingredient basic information, feeding sequence information, configuration environment information and stirring basic information;
the preparation pretreatment module is used for carrying out preparation pretreatment on a plurality of material conveying containers according to the batching basic information; and
the data mining module is used for acquiring ABC glue preset application scene information to perform data mining and acquiring expected temperature resistance, expected adhesion characteristics and expected strippability;
the index configuration module is used for acquiring glue production record data and constructing a functional mapping channel from the feeding sequence information, the configuration environment information and the stirring basic information to temperature resistance, adhesion characteristics and peelability;
the process optimizing module is used for optimizing the feeding sequence information and/or the configuration environment information and/or the stirring basic information according to the expected temperature resistance, the expected adhesion characteristic and the expected peelability, and acquiring a glue configuration process optimizing result based on the function mapping channel;
And the feeding configuration module is used for controlling the plurality of feeding containers to carry out feeding configuration in the glue configuration container according to the optimizing result of the glue configuration flow and carrying out intelligent monitoring.
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