CN117901409B - Preparation method and system of intelligent coating sensor based on 3D printing technology - Google Patents
Preparation method and system of intelligent coating sensor based on 3D printing technology Download PDFInfo
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- CN117901409B CN117901409B CN202410074235.9A CN202410074235A CN117901409B CN 117901409 B CN117901409 B CN 117901409B CN 202410074235 A CN202410074235 A CN 202410074235A CN 117901409 B CN117901409 B CN 117901409B
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- 239000011248 coating agent Substances 0.000 title claims abstract description 199
- 238000000576 coating method Methods 0.000 title claims abstract description 199
- 238000010146 3D printing Methods 0.000 title claims abstract description 29
- 238000005516 engineering process Methods 0.000 title claims abstract description 24
- 238000002360 preparation method Methods 0.000 title claims abstract description 18
- 238000000547 structure data Methods 0.000 claims abstract description 44
- 238000010276 construction Methods 0.000 claims abstract description 40
- 229910000831 Steel Inorganic materials 0.000 claims abstract description 38
- 239000010959 steel Substances 0.000 claims abstract description 38
- 238000007639 printing Methods 0.000 claims abstract description 32
- 238000000034 method Methods 0.000 claims abstract description 20
- 238000012544 monitoring process Methods 0.000 claims abstract description 15
- 239000010410 layer Substances 0.000 claims description 177
- 230000006870 function Effects 0.000 claims description 51
- 239000011241 protective layer Substances 0.000 claims description 40
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 claims description 21
- 239000007921 spray Substances 0.000 claims description 21
- 238000004458 analytical method Methods 0.000 claims description 18
- 239000003973 paint Substances 0.000 claims description 15
- 238000003756 stirring Methods 0.000 claims description 14
- 239000011259 mixed solution Substances 0.000 claims description 12
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 10
- 239000007822 coupling agent Substances 0.000 claims description 9
- 230000001419 dependent effect Effects 0.000 claims description 8
- 238000004519 manufacturing process Methods 0.000 claims description 8
- 238000005507 spraying Methods 0.000 claims description 8
- 230000007062 hydrolysis Effects 0.000 claims description 7
- 238000006460 hydrolysis reaction Methods 0.000 claims description 7
- NIXOWILDQLNWCW-UHFFFAOYSA-N acrylic acid group Chemical group C(C=C)(=O)O NIXOWILDQLNWCW-UHFFFAOYSA-N 0.000 claims description 6
- 238000006243 chemical reaction Methods 0.000 claims description 6
- 239000003795 chemical substances by application Substances 0.000 claims description 6
- 230000003301 hydrolyzing effect Effects 0.000 claims description 6
- 238000013507 mapping Methods 0.000 claims description 6
- 239000012153 distilled water Substances 0.000 claims description 5
- 239000006087 Silane Coupling Agent Substances 0.000 claims description 4
- BQCADISMDOOEFD-UHFFFAOYSA-N Silver Chemical compound [Ag] BQCADISMDOOEFD-UHFFFAOYSA-N 0.000 claims description 4
- 230000007797 corrosion Effects 0.000 claims description 4
- 238000005260 corrosion Methods 0.000 claims description 4
- 239000002270 dispersing agent Substances 0.000 claims description 4
- 239000000839 emulsion Substances 0.000 claims description 4
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- 229910052709 silver Inorganic materials 0.000 claims description 4
- 239000004332 silver Substances 0.000 claims description 4
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- BLRPTPMANUNPDV-UHFFFAOYSA-N Silane Chemical compound [SiH4] BLRPTPMANUNPDV-UHFFFAOYSA-N 0.000 description 3
- 239000000463 material Substances 0.000 description 3
- 239000011159 matrix material Substances 0.000 description 3
- 229910000077 silane Inorganic materials 0.000 description 3
- 238000003860 storage Methods 0.000 description 3
- SMZOUWXMTYCWNB-UHFFFAOYSA-N 2-(2-methoxy-5-methylphenyl)ethanamine Chemical compound COC1=CC=C(C)C=C1CCN SMZOUWXMTYCWNB-UHFFFAOYSA-N 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 239000011521 glass Substances 0.000 description 2
- 238000009413 insulation Methods 0.000 description 2
- 239000012212 insulator Substances 0.000 description 2
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- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
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- 239000013530 defoamer Substances 0.000 description 1
- 238000007598 dipping method Methods 0.000 description 1
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Abstract
The invention discloses a preparation method and a system of an intelligent coating sensor based on a 3D printing technology, wherein the method comprises the following steps: scanning to obtain three-dimensional scanning data and specific application; inputting specific application and three-dimensional scanning data into a coating construction model, and receiving basic structure data; converting the basic structure data into a file format corresponding to the 3D printer; printing is performed on a target area of a target steel bridge member to form a coating sensor. According to the intelligent coating sensor preparation method and system based on the 3D printing technology, the coating sensor with complex and various structural forms, high precision, uniform coating distribution and controllable thickness can be conveniently and rapidly prepared on the surface of the steel bridge member through scanning of the target area and automatic generation of relevant data of the coating sensor, the sensor preparation process is simple and convenient, the coating style can be customized according to the application target of the sensor, and the high precision and standardized development of a coating sensor crack monitoring system are facilitated.
Description
Technical Field
The invention relates to the field of nondestructive monitoring of bridge structures, in particular to a preparation method and a system of an intelligent coating sensor based on a 3D printing technology.
Background
The current intelligent coating sensor is manufactured by adopting an air pressure spraying process, the manufactured sensor is single in structural form, the sensor manufacture with complex pattern and high precision requirements is difficult to realize, and the high-precision development of a crack monitoring system of the coating sensor is not facilitated.
The coating sensors manufactured by the pneumatic spraying process have the problems of uneven coating distribution and difficult control of coating thickness, the actual condition of the coating is different from the overall design, the quality difference among the coating sensors is large, the stability is poor, and the standardization of a crack monitoring system of the coating sensors is not facilitated.
The traditional intelligent coating sensor manufacturing process is intelligent, low in degree of mechanization, complex in operation and low in efficiency.
Disclosure of Invention
In order to at least overcome the defects in the prior art, the application aims to provide a preparation method and a system of an intelligent coating sensor based on a 3D printing technology.
In a first aspect, an embodiment of the present application provides a method for preparing an intelligent coating sensor based on a 3D printing technology, including:
Scanning the surface profile of a target area of a target steel bridge member to obtain three-dimensional scanning data, and obtaining the specific application of a sensor required by the target steel bridge member in bridge nondestructive monitoring;
Inputting the specific application and the three-dimensional scanning data into a coating construction model, and receiving an insulating layer structure, a sensing layer structure and a protective layer structure which are output by the coating construction model as basic structure data;
converting the basic structure data into a file format corresponding to a 3D printer, and inputting the basic structure data into the 3D printer;
And printing on a target area of a target steel bridge member according to the basic structure data by the 3D printer to form a coating sensor.
When the embodiment of the application is implemented, the surface profile of the target area of the target steel bridge member needs to be scanned firstly to obtain specific three-dimensional scanning data for constructing the coating sensor; meanwhile, the matched structures and sizes of the coating sensors with different purposes are different, for example, the corresponding structure sizes of the sensors receiving and transmitting signals with different frequencies are different, so that the corresponding purposes are required to be acquired as reference data.
In the embodiment of the application, a coating construction model is constructed in advance, specific application and three-dimensional scanning data are input into the coating construction model as input data, and basic structure data output by the coating construction model can be obtained, and it is understood that the basic structure data comprise structural shapes of an insulating layer structure, a sensing layer structure and a protective layer structure and corresponding sizes, so that a subsequent 3D printer can conveniently print to generate a sensor. Based on the basic structure data, the basic structure data is converted into a file format corresponding to the 3D printer, the file format can be identified by the 3D printer, and finally printing is completed on the target area. According to the embodiment of the application, the coating sensor with complex and various structural forms, high precision, uniform coating distribution and controllable thickness can be conveniently and rapidly prepared on the surface of the steel bridge member through scanning the target area and automatically generating the related data of the coating sensor, the manufacturing process of the sensor is simple and convenient, the coating pattern can be customized according to the application target of the sensor, and the high-precision and standardized development of a coating sensor crack monitoring system is facilitated.
In one possible implementation, the generating of the coating build model includes:
acquiring sensing layer parameters corresponding to different specific purposes, and generating a plurality of sensing layer structures according to the sensing layer parameters; the sensing layer parameter of each specific application corresponds to at least one sensing layer structure;
Selecting a sensing layer structure which is most matched with the surface profile data from sensing layer structures corresponding to each specific application according to the surface profile data of the steel bridge component;
establishing a mapping relation between the surface profile data and the sensing layer structure to form an analysis array; the elements in the same analysis array are surface profile data and a sensing layer structure;
Constructing a parameter generating function for each analysis array, wherein independent variables of the parameter generating function are surface profile data, and the dependent variable of the parameter generating function is the size parameter of the sensing layer structure, the size parameter of the insulating layer structure and the size parameter of the protective layer structure;
And constructing a model by taking all the parameter generating functions as the coating.
In one possible implementation, the acquisition of the infrastructure data includes:
inputting the specific application and the three-dimensional scan data into the coating build model;
The coating construction model selects a parameter generating function matched with the coating construction model according to the specific application, and inputs the three-dimensional scanning data serving as surface profile data of the parameter generating function into the parameter generating function;
receiving model selection data of a sensing layer structure corresponding to the coating construction model as a basic structure, and taking size parameters of the sensing layer structure, the insulating layer structure and the protective layer structure generated by the coating construction model as size parameters of the basic structure;
and taking the model selection data of the base structure and the dimension parameters of the base structure as the base structure data.
In one possible implementation, printing, by the 3D printer, on a target area of a target steel bridge member according to the infrastructure data to form a coating sensor includes:
injecting an insulating layer coating into the 3D printer charging barrel, wherein the 3D printer generates an insulating layer coating on a target area of a target steel bridge component through controlling the deposition thickness of the coating by a repeated pattern according to the basic structure data;
after the insulating layer coating is sprayed and dried, replacing the coating with a sensing layer coating and replacing a spray head, and spraying the sensing layer coating on the insulating layer coating;
and after the coating of the sensing layer is sprayed and dried, replacing the coating with the coating of the protective layer and replacing the spray head, and spraying the coating of the protective layer on the coating of the insulating layer.
In one possible implementation, the insulating layer coating employs a circuit board moisture-proof insulator; the protective layer paint adopts three-proofing paint of a circuit board with corrosion resistance, high temperature resistance and water resistance.
In one possible implementation, the preparation of the sensing layer coating includes:
The silane coupling agent is prepared by the following steps of (by mass ratio) 30:1, hydrolyzing to generate a hydrolysis coupling agent;
mixing silver-plated copper powder with silver content of 5% with the hydrolytic coupling agent, and uniformly stirring to form a first mixed solution; the mass ratio of the silver-plated copper powder to the hydrolysis coupling agent is 2:1;
Adding distilled water into the 2/3 aqueous acrylic emulsion of the silver-plated copper powder and fully stirring to form a second mixed solution;
And after the first mixed solution and the second mixed solution are mixed, adding a dispersing agent accounting for 4% of the mass of the silver-plated copper powder, a defoaming agent accounting for 1.33% of the mass of the silver-plated copper powder, and a leveling agent accounting for 2% of the mass of the silver-plated copper powder, and fully stirring to form the sensing layer coating.
In one possible implementation, the thickness of the insulating layer coating is 20-40 μm, the thickness of the sensing layer coating is 8-18 μm, and the thickness of the protective layer coating is 10-20 μm.
In a second aspect, an embodiment of the present application provides an intelligent coating sensor preparation system based on a 3D printing technology, including:
the acquisition unit is configured to scan the surface profile of a target area of a target steel bridge member to acquire three-dimensional scanning data and acquire the specific application of a sensor required by the target steel bridge member in bridge nondestructive monitoring;
a build unit configured to input the specific use and the three-dimensional scan data into a coating build model, and to receive an insulating layer structure, a sensing layer structure, and a protective layer structure output from the coating build model as basic structure data;
The conversion unit is configured to convert the basic structure data into a file format corresponding to the 3D printer and input the basic structure data into the 3D printer;
And printing on a target area of a target steel bridge member according to the basic structure data by the 3D printer to form a coating sensor.
In one possible implementation, the generating of the coating build model includes:
acquiring sensing layer parameters corresponding to different specific purposes, and generating a plurality of sensing layer structures according to the sensing layer parameters; the sensing layer parameter of each specific application corresponds to at least one sensing layer structure;
Selecting a sensing layer structure which is most matched with the surface profile data from sensing layer structures corresponding to each specific application according to the surface profile data of the steel bridge component;
establishing a mapping relation between the surface profile data and the sensing layer structure to form an analysis array; the elements in the same analysis array are surface profile data and a sensing layer structure;
Constructing a parameter generating function for each analysis array, wherein independent variables of the parameter generating function are surface profile data, and the dependent variable of the parameter generating function is the size parameter of the sensing layer structure, the size parameter of the insulating layer structure and the size parameter of the protective layer structure;
And constructing a model by taking all the parameter generating functions as the coating.
In one possible implementation, the building unit is further configured to:
inputting the specific application and the three-dimensional scan data into the coating build model;
The coating construction model selects a parameter generating function matched with the coating construction model according to the specific application, and inputs the three-dimensional scanning data serving as surface profile data of the parameter generating function into the parameter generating function;
receiving model selection data of a sensing layer structure corresponding to the coating construction model as a basic structure, and taking size parameters of the sensing layer structure, the insulating layer structure and the protective layer structure generated by the coating construction model as size parameters of the basic structure;
and taking the model selection data of the base structure and the dimension parameters of the base structure as the base structure data.
Compared with the prior art, the invention has the following advantages and beneficial effects:
According to the intelligent coating sensor preparation method and system based on the 3D printing technology, the coating sensor with complex and various structural forms, high precision, uniform coating distribution and controllable thickness can be conveniently and rapidly prepared on the surface of the steel bridge member through scanning of the target area and automatic generation of relevant data of the coating sensor, the sensor preparation process is simple and convenient, the coating style can be customized according to the application target of the sensor, and the high precision and standardized development of a coating sensor crack monitoring system are facilitated.
Drawings
The accompanying drawings, which are included to provide a further understanding of embodiments of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the principles of the application. In the drawings:
FIG. 1 is a schematic diagram of a 3D printing apparatus according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a 3D printing apparatus according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a 3D printed grid-type coated sensor according to an embodiment of the present application;
FIG. 4 shows a grid pattern of coating sensors printed on a component in accordance with an embodiment of the present application;
FIG. 5 is a cross-sectional structural view of a coating sensor according to an embodiment of the present application;
FIG. 6 is a sample of a coating sensor pattern according to an embodiment of the application;
FIG. 7 is a schematic diagram showing steps of a method according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for the purpose of illustration and description only and are not intended to limit the scope of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. A flowchart, as used in this disclosure, illustrates operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be implemented out of order and that steps without logical context may be performed in reverse order or concurrently. Furthermore, one or more other operations may be added to or removed from the flow diagrams by those skilled in the art under the direction of the present disclosure.
In addition, the described embodiments are only some, but not all, embodiments of the application. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
Referring to fig. 7 in combination, a flow chart of a method for preparing an intelligent coating sensor based on a 3D printing technology according to an embodiment of the present invention is provided, and further, the method for preparing an intelligent coating sensor based on a 3D printing technology specifically may include the following descriptions of step S1 to step S4.
S1: scanning the surface profile of a target area of a target steel bridge member to obtain three-dimensional scanning data, and obtaining the specific application of a sensor required by the target steel bridge member in bridge nondestructive monitoring;
S2: inputting the specific application and the three-dimensional scanning data into a coating construction model, and receiving an insulating layer structure, a sensing layer structure and a protective layer structure which are output by the coating construction model as basic structure data;
s3: converting the basic structure data into a file format corresponding to a 3D printer, and inputting the basic structure data into the 3D printer;
S4: and printing on a target area of a target steel bridge member according to the basic structure data by the 3D printer to form a coating sensor.
When the embodiment of the application is implemented, the surface profile of the target area of the target steel bridge member needs to be scanned firstly to obtain specific three-dimensional scanning data for constructing the coating sensor; meanwhile, the matched structures and sizes of the coating sensors with different purposes are different, for example, the corresponding structure sizes of the sensors receiving and transmitting signals with different frequencies are different, so that the corresponding purposes are required to be acquired as reference data.
In the embodiment of the application, a coating construction model is constructed in advance, specific application and three-dimensional scanning data are input into the coating construction model as input data, and basic structure data output by the coating construction model can be obtained, and it is understood that the basic structure data comprise structural shapes of an insulating layer structure, a sensing layer structure and a protective layer structure and corresponding sizes, so that a subsequent 3D printer can conveniently print to generate a sensor. Based on the basic structure data, the basic structure data is converted into a file format corresponding to the 3D printer, the file format can be identified by the 3D printer, and finally printing is completed on the target area. According to the embodiment of the application, the coating sensor with complex and various structural forms, high precision, uniform coating distribution and controllable thickness can be conveniently and rapidly prepared on the surface of the steel bridge member through scanning the target area and automatically generating the related data of the coating sensor, the manufacturing process of the sensor is simple and convenient, the coating pattern can be customized according to the application target of the sensor, and the high-precision and standardized development of a coating sensor crack monitoring system is facilitated.
In one possible implementation, the generating of the coating build model includes:
acquiring sensing layer parameters corresponding to different specific purposes, and generating a plurality of sensing layer structures according to the sensing layer parameters; the sensing layer parameter of each specific application corresponds to at least one sensing layer structure;
Selecting a sensing layer structure which is most matched with the surface profile data from sensing layer structures corresponding to each specific application according to the surface profile data of the steel bridge component;
establishing a mapping relation between the surface profile data and the sensing layer structure to form an analysis array; the elements in the same analysis array are surface profile data and a sensing layer structure;
Constructing a parameter generating function for each analysis array, wherein independent variables of the parameter generating function are surface profile data, and the dependent variable of the parameter generating function is the size parameter of the sensing layer structure, the size parameter of the insulating layer structure and the size parameter of the protective layer structure;
And constructing a model by taking all the parameter generating functions as the coating.
When the embodiment of the application is implemented, in the process of constructing a coating construction model, the parameters of the sensing layers of the sensors with different purposes are required to be acquired, and the type of the sensing layer structure can be selected based on the parameters, such as a net structure, a lattice structure, a tree structure and the like. And analyzing the sensing layer structure based on the surface profile data of different steel bridge members, selecting the sensing layer structure suitable for different surface profile data, and constructing a parameter generating function. The parameter generating function is essentially a pairing function, the independent variable of the parameter generating function is surface profile data, the dependent variable is the dimension parameter of the sensing layer structure, and meanwhile, the related parameters of the insulating layer and the protecting layer are required to be generated by referring to the dimension parameter of the sensing layer structure, so that the parameter generating function also has the dimension parameter of the insulating layer structure and the dimension parameter of the protecting layer structure as dependent variable.
In one possible implementation, the acquisition of the infrastructure data includes:
inputting the specific application and the three-dimensional scan data into the coating build model;
The coating construction model selects a parameter generating function matched with the coating construction model according to the specific application, and inputs the three-dimensional scanning data serving as surface profile data of the parameter generating function into the parameter generating function;
receiving model selection data of a sensing layer structure corresponding to the coating construction model as a basic structure, and taking size parameters of the sensing layer structure, the insulating layer structure and the protective layer structure generated by the coating construction model as size parameters of the basic structure;
and taking the model selection data of the base structure and the dimension parameters of the base structure as the base structure data.
When the embodiment of the application is implemented, based on the generated coating construction model, a parameter generation function matched with a specific application can be selected through the coating construction model, and three-dimensional scanning data is input into the function to obtain the model selection and the size parameter of the sensing layer, the size parameter of the insulating layer structure and the size parameter of the protective layer structure, so that the purpose of rapidly designing the coating sensor is achieved.
In one possible implementation, printing, by the 3D printer, on a target area of a target steel bridge member according to the infrastructure data to form a coating sensor includes:
injecting an insulating layer coating into the 3D printer charging barrel, wherein the 3D printer generates an insulating layer coating on a target area of a target steel bridge component through controlling the deposition thickness of the coating by a repeated pattern according to the basic structure data;
after the insulating layer coating is sprayed and dried, replacing the coating with a sensing layer coating and replacing a spray head, and spraying the sensing layer coating on the insulating layer coating;
and after the coating of the sensing layer is sprayed and dried, replacing the coating with the coating of the protective layer and replacing the spray head, and spraying the coating of the protective layer on the coating of the insulating layer.
In one possible implementation, the insulating layer coating employs a circuit board moisture-proof insulator; the protective layer paint adopts three-proofing paint of a circuit board with corrosion resistance, high temperature resistance and water resistance.
When the embodiment of the application is implemented, the sensing layer and the matrix can be separated by adopting the circuit board dampproof insulating agent as the insulating layer coating, so that the electric signals of the sensing layer and the matrix are mutually separated, and the interference is avoided; and the coverage of the sensing layer is smooth, so that the coating quality is improved. The insulating layer and the matrix have good adhesion and excellent damage synchronism. The protective layer paint has good cohesiveness and damage synchronism when the circuit board three-proofing paint is adopted, the sensing layer is protected from being interfered by external environments such as wind, rain, atmospheric corrosion and the like, and the durability and the accuracy of the sensor are improved.
In one possible implementation, the preparation of the sensing layer coating includes:
The silane coupling agent is prepared by the following steps of (by mass ratio) 30:1, hydrolyzing to generate a hydrolysis coupling agent;
mixing silver-plated copper powder with silver content of 5% with the hydrolytic coupling agent, and uniformly stirring to form a first mixed solution; the mass ratio of the silver-plated copper powder to the hydrolysis coupling agent is 2:1;
Adding distilled water into the 2/3 aqueous acrylic emulsion of the silver-plated copper powder and fully stirring to form a second mixed solution;
And after the first mixed solution and the second mixed solution are mixed, adding a dispersing agent accounting for 4% of the mass of the silver-plated copper powder, a defoaming agent accounting for 1.33% of the mass of the silver-plated copper powder, and a leveling agent accounting for 2% of the mass of the silver-plated copper powder, and fully stirring to form the sensing layer coating.
In the practice of the embodiments of the present application, copper powder is combined with water-based acrylic acid through hydrolyzed silane coupling solution, the aqueous acrylic acid has certain cementing capacity after being dried, so that copper powder with conductive property is uniformly attached to the surface of the insulating layer, and the sensing layer is prepared. The sensing layer has good damage synchronism and resistance characteristics, the resistance value of the sensing layer is less influenced by external factors such as temperature, and the accuracy of the whole crack monitoring system is not influenced.
In one possible implementation, the thickness of the insulating layer coating is 20-40 μm, the thickness of the sensing layer coating is 8-18 μm, and the thickness of the protective layer coating is 10-20 μm.
Based on the same inventive concept, the embodiment of the application also provides an intelligent coating sensor preparation system based on a 3D printing technology, which comprises the following steps:
the acquisition unit is configured to scan the surface profile of a target area of a target steel bridge member to acquire three-dimensional scanning data and acquire the specific application of a sensor required by the target steel bridge member in bridge nondestructive monitoring;
a build unit configured to input the specific use and the three-dimensional scan data into a coating build model, and to receive an insulating layer structure, a sensing layer structure, and a protective layer structure output from the coating build model as basic structure data;
The conversion unit is configured to convert the basic structure data into a file format corresponding to the 3D printer and input the basic structure data into the 3D printer;
And printing on a target area of a target steel bridge member according to the basic structure data by the 3D printer to form a coating sensor.
In one possible implementation, the generating of the coating build model includes:
acquiring sensing layer parameters corresponding to different specific purposes, and generating a plurality of sensing layer structures according to the sensing layer parameters; the sensing layer parameter of each specific application corresponds to at least one sensing layer structure;
Selecting a sensing layer structure which is most matched with the surface profile data from sensing layer structures corresponding to each specific application according to the surface profile data of the steel bridge component;
establishing a mapping relation between the surface profile data and the sensing layer structure to form an analysis array; the elements in the same analysis array are surface profile data and a sensing layer structure;
Constructing a parameter generating function for each analysis array, wherein independent variables of the parameter generating function are surface profile data, and the dependent variable of the parameter generating function is the size parameter of the sensing layer structure, the size parameter of the insulating layer structure and the size parameter of the protective layer structure;
And constructing a model by taking all the parameter generating functions as the coating.
In one possible implementation, the building unit is further configured to:
inputting the specific application and the three-dimensional scan data into the coating build model;
The coating construction model selects a parameter generating function matched with the coating construction model according to the specific application, and inputs the three-dimensional scanning data serving as surface profile data of the parameter generating function into the parameter generating function;
receiving model selection data of a sensing layer structure corresponding to the coating construction model as a basic structure, and taking size parameters of the sensing layer structure, the insulating layer structure and the protective layer structure generated by the coating construction model as size parameters of the basic structure;
and taking the model selection data of the base structure and the dimension parameters of the base structure as the base structure data.
In the embodiment of the present application, a specific preparation scheme is shown, wherein fig. 1 and 2 are schematic diagrams of a 3D printing system in the present application, and the printing system mainly comprises a component transportation platform 1, a printing component 2, a scanning/printing area 3, a component fixing device 4, a first height adjuster 5, a three-dimensional scanner 6, a second height adjuster 7, a lateral displacement controller 8, a longitudinal displacement controller 9, a vertical displacement and horizontal rotation controller 10, a first cylinder 11, a second cylinder 12, a third cylinder 13, a first spray head 14, a second spray head 15, a third spray head 16, a spray head conversion device 17, an intelligent coating sensor 18, and a vertical rotation controller 19. Wherein 1, 2, 3 constitute a component transportation system; 4.5, forming a three-dimensional scanning system; 6 to 17 and 19 constitute a 3D printing system.
The process of manufacturing the intelligent coating sensor by using the 3D printing technology is as follows:
Preparation of a sensing layer coating (the content of each component is calculated by mass): (1) hydrolysis of the silane coupling agent. 30g of distilled water, 1gKH model 550 silane coupling solution, was added to the beaker, and the mixture was left to stand for 2 hours after stirring with a glass rod for 1min. (2) 30g of silver-plated copper powder with the silver content of 5% is selected, 15g of hydrolyzed silane coupling solution is added, and the mixture is fully mixed to be in a plastic state. (3) 20g of the aqueous acrylic emulsion was weighed out in a beaker, 15g of distilled water was added, and stirring was carried out for 1min. (4) Mixing the materials obtained in step (2) and (3), stirring for 5min, adding dispersant, defoamer and leveling agent to 1.2g, 0.4g and 0.6g in batches, and stirring for 10min after each batch. (5) And dipping a proper amount of sensing layer paint by using a glass rod, observing the surface condition of the obtained paint, and completing the paint preparation without obvious particle aggregation and good fluidity.
Feeding: an insulation layer material (commercial circuit board pcb moisture-proof insulation) is added to the first cartridge 11, a formulated sensor layer coating is added to the second cartridge 12, and a protective layer material is added to the third cartridge 13.
Component classification: each component is classified according to the printing scheme in advance, the scheme is consistent or similar as a group, and the printing efficiency is improved.
Scanning a component: the component 2 is placed on the transport platform, the first height adjuster 5 is adjusted, and the three-dimensional scanner 6 is placed at a suitable height. The part to be printed is moved to the range of the scanning/printing region 3, the fixing device 4 is started, and the influence of movement of the component in the transportation printing process on the printing precision is prevented. Starting a transportation platform, moving the area to be scanned/printed 3 into the working area of the three-dimensional scanner 6, receiving a signal by the scanner, and starting scanning; the area to be scanned/printed 3 is moved out of the working area of the three-dimensional scanner 6, the signal is turned off, and the scanning is stopped.
Design of each layer of patterns of the sensor: on the basis of the scanning result, according to the monitoring requirement, the design of the insulating layer, the design of the sensing layer and the design of the protective layer are shown in fig. 3, the thickness of the insulating layer is 20um, the thickness of the sensing layer is 10um, and the thickest part of the protective layer (the part of the insulating layer, which is not sprayed with the sensing layer) is 20um, and the rest parts are 10um so as to ensure the smoothness of the surface of the protective layer. Setting a printing path and pattern repetition times according to the patterns and the thickness, outputting the patterns and the pattern repetition times into a file format acceptable by a 3D printer, and storing the set file in the format as a template, so that the next call or fine adjustment is facilitated.
And (3) coating printing: the insulating layer is first printed. Starting an internal stirring system of the first charging barrel 11 to uniformly disperse the coating; starting a second height adjuster 7 to adjust the whole printing system to a proper height; starting the spray head conversion device 17 to convert the working spray head into the first spray head 14; and starting the printer, outputting the 3D printing file, and starting the printing work. The longitudinal and transverse movement of the printing spray head is controlled by the transverse displacement controller 8 and the longitudinal displacement controller 9, the vertical rotation of the printing spray head is controlled by the vertical rotation controller 19, and the vertical displacement and horizontal rotation controller 10 can control the horizontal rotation of the spray head. The full-directional path movement of the spray head can be realized through 8, 9, 10 and 19, and then high-precision coating printing of complex patterns and complex components is realized. After the printing and drying of the insulating layer are completed, the working spray heads are converted into the second spray head 15 and the third spray head 16 by utilizing the spray head conversion device 17 to respectively print the sensing layer and the protective layer, and the printing process is the same as that of the insulating layer. The arrangement of the wiring terminals is completed in the printing gap between the sensing layer and the protective layer. After the printing work of all the components is finished, clean water is added into each charging barrel to finish the printing work for 3-4 times so as to remove residual paint, and the printer is prevented from being blocked after the paint is dried and solidified. Through the above steps, the coated sensor printed on the component in this embodiment is shown in fig. 4. Fig. 5 shows a cross-sectional structure of a coated sensor fabricated based on 3D printing technology. In a more specific embodiment, FIG. 6 shows a coating build model that is an alternative to the coating build model.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps described in connection with the embodiments disclosed herein may be embodied in electronic hardware, in computer software, or in a combination of the two, and that the elements and steps of the examples have been generally described in terms of function in the foregoing description to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the several embodiments provided by the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices, or elements, or may be an electrical, mechanical, or other form of connection.
The elements described as separate components may or may not be physically separate, and it will be apparent to those skilled in the art that elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the elements and steps of the examples have been generally described functionally in the foregoing description so as to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention is essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a grid device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing description of the embodiments has been provided for the purpose of illustrating the general principles of the invention, and is not meant to limit the scope of the invention, but to limit the invention to the particular embodiments, and any modifications, equivalents, improvements, etc. that fall within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. The preparation method of the intelligent coating sensor based on the 3D printing technology is characterized by comprising the following steps of:
Scanning the surface profile of a target area of a target steel bridge member to obtain three-dimensional scanning data, and obtaining the specific application of a sensor required by the target steel bridge member in bridge nondestructive monitoring;
Inputting the specific application and the three-dimensional scanning data into a coating construction model, and receiving an insulating layer structure, a sensing layer structure and a protective layer structure which are output by the coating construction model as basic structure data;
converting the basic structure data into a file format corresponding to a 3D printer, and inputting the basic structure data into the 3D printer;
And printing on a target area of a target steel bridge member according to the basic structure data by the 3D printer to form a coating sensor.
2. The method for preparing an intelligent coating sensor based on a 3D printing technology according to claim 1, wherein the generating of the coating build model comprises:
acquiring sensing layer parameters corresponding to different specific purposes, and generating a plurality of sensing layer structures according to the sensing layer parameters; the sensing layer parameter of each specific application corresponds to at least one sensing layer structure;
Selecting a sensing layer structure which is most matched with the surface profile data from sensing layer structures corresponding to each specific application according to the surface profile data of the steel bridge component;
establishing a mapping relation between the surface profile data and the sensing layer structure to form an analysis array; the elements in the same analysis array are surface profile data and a sensing layer structure;
Constructing a parameter generating function for each analysis array, wherein independent variables of the parameter generating function are surface profile data, and the dependent variable of the parameter generating function is the size parameter of the sensing layer structure, the size parameter of the insulating layer structure and the size parameter of the protective layer structure;
And constructing a model by taking all the parameter generating functions as the coating.
3. The method for preparing an intelligent coating sensor based on a 3D printing technology according to claim 2, wherein the obtaining of the infrastructure data comprises:
inputting the specific application and the three-dimensional scan data into the coating build model;
The coating construction model selects a parameter generating function matched with the coating construction model according to the specific application, and inputs the three-dimensional scanning data serving as surface profile data of the parameter generating function into the parameter generating function;
receiving model selection data of a sensing layer structure corresponding to the coating construction model as a basic structure, and taking size parameters of the sensing layer structure, the insulating layer structure and the protective layer structure generated by the coating construction model as size parameters of the basic structure;
and taking the model selection data of the base structure and the dimension parameters of the base structure as the base structure data.
4. The method for preparing an intelligent coating sensor based on 3D printing technology according to claim 1, wherein printing on a target area of a target steel bridge member by the 3D printer according to the basic structure data to form the coating sensor comprises:
injecting an insulating layer coating into the 3D printer charging barrel, wherein the 3D printer generates an insulating layer coating on a target area of a target steel bridge component through controlling the deposition thickness of the coating by a repeated pattern according to the basic structure data;
after the insulating layer coating is sprayed and dried, replacing the coating with a sensing layer coating and replacing a spray head, and spraying the sensing layer coating on the insulating layer coating;
and after the coating of the sensing layer is sprayed and dried, replacing the coating with the coating of the protective layer and replacing the spray head, and spraying the coating of the protective layer on the coating of the insulating layer.
5. The method for preparing the intelligent coating sensor based on the 3D printing technology, which is characterized in that the insulating layer paint adopts a circuit board moisture-proof insulating agent; the protective layer paint adopts three-proofing paint of a circuit board with corrosion resistance, high temperature resistance and water resistance.
6. The method for preparing the intelligent coating sensor based on the 3D printing technology according to claim 4, wherein the preparation of the sensing layer paint comprises the following steps:
The silane coupling agent is prepared by the following steps of (by mass ratio) 30:1, hydrolyzing to generate a hydrolysis coupling agent;
mixing silver-plated copper powder with silver content of 5% with the hydrolytic coupling agent, and uniformly stirring to form a first mixed solution; the mass ratio of the silver-plated copper powder to the hydrolysis coupling agent is 2:1;
Adding distilled water into the 2/3 aqueous acrylic emulsion of the silver-plated copper powder and fully stirring to form a second mixed solution;
And after the first mixed solution and the second mixed solution are mixed, adding a dispersing agent accounting for 4% of the mass of the silver-plated copper powder, a defoaming agent accounting for 1.33% of the mass of the silver-plated copper powder, and a leveling agent accounting for 2% of the mass of the silver-plated copper powder, and fully stirring to form the sensing layer coating.
7. The method for preparing the intelligent coating sensor based on the 3D printing technology according to claim 4, wherein the thickness of the insulating layer coating is 20-40 μm, the thickness of the sensing layer coating is 8-18 μm, and the thickness of the protective layer coating is 10-20 μm.
8. A smart coating sensor manufacturing system based on 3D printing technology using the method of any one of claims 1 to 7, characterized in that it comprises:
the acquisition unit is configured to scan the surface profile of a target area of a target steel bridge member to acquire three-dimensional scanning data and acquire the specific application of a sensor required by the target steel bridge member in bridge nondestructive monitoring;
a build unit configured to input the specific use and the three-dimensional scan data into a coating build model, and to receive an insulating layer structure, a sensing layer structure, and a protective layer structure output from the coating build model as basic structure data;
The conversion unit is configured to convert the basic structure data into a file format corresponding to the 3D printer and input the basic structure data into the 3D printer;
And printing on a target area of a target steel bridge member according to the basic structure data by the 3D printer to form a coating sensor.
9. The intelligent coating sensor manufacturing system based on 3D printing technology of claim 8, wherein the generation of the coating build model comprises:
acquiring sensing layer parameters corresponding to different specific purposes, and generating a plurality of sensing layer structures according to the sensing layer parameters; the sensing layer parameter of each specific application corresponds to at least one sensing layer structure;
Selecting a sensing layer structure which is most matched with the surface profile data from sensing layer structures corresponding to each specific application according to the surface profile data of the steel bridge component;
establishing a mapping relation between the surface profile data and the sensing layer structure to form an analysis array; the elements in the same analysis array are surface profile data and a sensing layer structure;
Constructing a parameter generating function for each analysis array, wherein independent variables of the parameter generating function are surface profile data, and the dependent variable of the parameter generating function is the size parameter of the sensing layer structure, the size parameter of the insulating layer structure and the size parameter of the protective layer structure;
And constructing a model by taking all the parameter generating functions as the coating.
10. The smart coating sensor manufacturing system based on 3D printing technology of claim 9, wherein the build unit is further configured to:
inputting the specific application and the three-dimensional scan data into the coating build model;
The coating construction model selects a parameter generating function matched with the coating construction model according to the specific application, and inputs the three-dimensional scanning data serving as surface profile data of the parameter generating function into the parameter generating function;
receiving model selection data of a sensing layer structure corresponding to the coating construction model as a basic structure, and taking size parameters of the sensing layer structure, the insulating layer structure and the protective layer structure generated by the coating construction model as size parameters of the basic structure;
and taking the model selection data of the base structure and the dimension parameters of the base structure as the base structure data.
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| WO2018067626A1 (en) * | 2016-10-04 | 2018-04-12 | Arizona Board Of Regents On Behalf Of Arizona State University | Flexible sensors incorporating piezoresistive composite materials and fabrication methods |
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