CN117445405A - Powder material 3D prints many substrate fusion control system - Google Patents
Powder material 3D prints many substrate fusion control system Download PDFInfo
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Abstract
The invention relates to the technical field of 3D printing, in particular to a powder material 3D printing multi-substrate fusion control system, which comprises the following components: the data acquisition module is used for acquiring N groups of substrate external parameters and substrate internal parameters, wherein the substrate external parameters comprise the temperature DWD of a printing head, the temperature CWD of a material bed and the fusion time RS between substrates, and the substrate internal parameters comprise the density MD of a powder bed and the particle size KL of the powder bed; and the preprocessing module is used for processing the collected temperature DWD of the N groups of printing heads, the temperature CWD of the material bed and the fusion time RS between the substrates. The invention can not only improve the judgment precision of the fusion degree of multiple base materials by utilizing the combination of the temperature DWD of the printing head, the temperature CWD of the material bed, the fusion time RS between the base materials, the density MD of the powder bed and the particle size KL of the powder bed, but also evaluate the fusion degree of the multiple base materials in real time and quantitatively, and timely adjust parameters in the printing process, thereby ensuring the quality of 3D printing.
Description
Technical Field
The invention relates to the technical field of 3D printing, in particular to a powder material 3D printing multi-substrate fusion control system.
Background
3D printing technology has been widely used in various fields, especially in the manufacturing industry. 3D printing on a powder basis, in particular powder bed melting techniques (such as laser melting or electron beam melting) have become an important additive manufacturing technique.
There is a printhead assembly, 3D printer and printing method of application publication No. CN104385603B in the prior art, the printhead assembly of the assembly comprising a printhead body and a heating device; the heating device is arranged on the thermal head of the printing head body and is used for heating the base material formed by the previous printing, the printing head component heats the uppermost layer of the printed model through the heating device and heats the base material to a surface micro-melting state, so that the material printed later is better fused with the base material, the problem that the shrinkage ratio of the plastic material in the 3D printing process is larger in 3D printing edge warping is effectively solved, the raw material printing problem with higher cooling speed is also solved, the quality of 3D printing forming is obviously improved, filaments of PP, PE and other types of raw materials and modified materials added with other substances are formed, and the forming quality is better; the printhead assembly of the present invention can also be applied to 3D printing of similar materials.
But there are also the following disadvantages: from the above statement, the prior art only monitors the temperature of the printing head, but the fusion degree of the multi-substrate in 3D printing is closely related to the fusion time between the substrates, the density of the powder bed and the particle size of the powder bed, the temperature of the single collecting printing head and the temperature of the material bed are ignored, the influence of the fusion time between the substrates, the density of the powder bed and the particle size of the powder bed on the fusion of the multi-substrate in 3D printing is ignored, the judgment precision of the fusion degree of the multi-substrate is reduced, the fusion degree of the multi-substrate cannot be evaluated quantitatively in real time, and the printing parameters are adjusted according to the fusion degree.
Disclosure of Invention
In view of the above, the present invention is directed to a powder material 3D printing multi-substrate fusion control system to solve the drawbacks of the prior art.
Based on the above object, the present invention provides a powder material 3D printing multi-substrate fusion control system, comprising:
the data acquisition module is used for acquiring N groups of substrate external parameters and substrate internal parameters, wherein the substrate external parameters comprise the temperature DWD of a printing head, the temperature CWD of a material bed and the fusion time RS between substrates, and the substrate internal parameters comprise the density MD of a powder bed and the particle size KL of the powder bed;
the pretreatment module is used for treating the collected temperatures DWD of the N groups of printing heads, the temperatures CWD of the material beds and the fusion time RS between the base materials to generate an average number of the temperatures DWD of the printing heads, an average number of the temperatures CWD of the material beds and an average number of the fusion time RS between the base materials, and treating the collected densities MD of the N groups of powder beds and the particle sizes KL of the powder beds to generate an average number of the densities MD of the powder beds and an average number of the particle sizes KL of the powder beds;
the data processing module is used for processing the average of the printing head temperature DWD, the average of the temperature CWD of the material bed and the average of the fusion time RS between the substrates to generate an influence coefficient WXS outside the substrates, and processing the average of the density MD of the powder bed and the average of the particle size KL of the powder bed to generate an influence coefficient NXS inside the substrates;
the data analysis module is used for carrying out non-dimensionalization on the influence coefficient WXS outside the substrate and the influence coefficient NXS inside the substrate, generating a multi-substrate fusion index ZS by the influence coefficient WXS outside the substrate and the influence coefficient NXS inside the substrate, and comparing the multi-substrate fusion index ZS with a preset multi-substrate fusion threshold YZ to generate different evaluation signals;
and the execution module is used for executing different strategies according to different evaluation signals.
Further, the collection of the temperature DWD of the print head, the temperature CWD of the material bed, the fusion time RS data between the substrates, the density MD of the powder bed, and the particle size KL of the powder bed, which are collected by the data collection module, is as follows, N is an integer greater than 1:
DWD＝[DWD 1 、DWD 2 …DWD i …DWD N ]
CWD＝[CWD 1 、CWD 2 …CWD i …CWD N ]
RS＝[RS 1 、RS 2 …RS i …RS N ]
MD＝[MD 1 、MD 2 …MD i …MD N ]
KL＝[KL 1 、KL 2 …KL i …KL N ]
wherein, DWD i For the temperature value of the ith set of printheads, CWD i For the temperature value of the material bed of group i, RS i For fusion time between group i substrates, MD i KL for the density of the i-th powder bed i Is the particle size of the powder bed of group i.
Further, the calculation formula of the average of the temperature DWD of the print head and the average of the temperature CWD of the material bed and the average of the fusion time RS between the substrates is as follows:
further, the data processing module processes the average of the printhead temperature DWD and the average of the temperature CWD of the material bed and the average of the fusion time RS between the substrates to generate the influence coefficient WXS outside the substrates as follows:
wherein α is a weight factor of an average of the temperatures of the print head, α is 0.2.ltoreq.α.ltoreq.0.4, β is a weight factor of an average of the temperatures of the material beds, 0.2.ltoreq.β.ltoreq.0.4, γ is a weight factor of an average of the fusion times RS between the substrates, 0.2.ltoreq.γ.ltoreq.0.4, μ is an index factor of an average of the temperatures of the print head, 2.ltoreq.μ.ltoreq.4, θ is an index factor of an average of the temperatures CWD of the material beds, 2.ltoreq.θ.ltoreq.4, τ is an index factor of an average of the fusion times between the substrates, 2.ltoreq.τ.ltoreq.4, and a C1 constant correction coefficient.
Further, the data processing module processes the average of the density MD of the powder bed and the average of the particle size KL of the powder bed to generate the influence coefficient NXS inside the substrate as follows:
wherein ρ is a weight factor coefficient of the average number of densities of the powder bed, ρ is 0.2.ltoreq.ρ.ltoreq.0.4,weight factor coefficient being the average number of particle sizes of the powder bed, +.>Omega is an exponential factor of the average number of densities of the powder bed, 2.ltoreq.ω.ltoreq.4, epsilon is an exponential factor of the average number of particle sizes of the powder bed, 2.ltoreq.ε.ltoreq.4, and a C2 constant correction coefficient.
Further, the data analysis module performs a dimensionless treatment on the influence coefficient WXS outside the substrate and the influence coefficient NXS inside the substrate, performs a correlation analysis on the influence coefficient WXS outside the substrate and the influence coefficient NXS inside the substrate, and generates a formula of a multi-substrate fusion index ZS as follows:
ZS＝δ1*WXS+δ2*NXS+C3
wherein δ1 is a weight factor coefficient of an influence coefficient outside the substrate, δ1 is more than or equal to 0.2 and less than or equal to 0.4, δ2 is a weight factor coefficient of an influence coefficient inside the substrate, δ2 is more than or equal to 0.2 and less than or equal to 0.4, and a C3 constant correction coefficient.
Further, the data analysis module compares the multi-substrate fusion index ZS with a preset multi-substrate fusion threshold YZ, and generates different evaluation signals as follows:
when ZS is more than or equal to YZ, generating a first evaluation signal;
when ZS < YZ, a second evaluation signal is generated.
Further, the execution module executes different strategies according to different evaluation signals, and the specific process is as follows:
when a first evaluation signal is sent out, the fusion degree of the multiple base materials is indicated to meet a preset threshold value, and printing can be continued;
when a second evaluation signal is sent, the fusion degree of the multiple substrates does not reach the preset threshold value, and the printing parameters need to be adjusted.
The invention has the beneficial effects that:
the method comprises the steps of collecting and processing the temperature DWD of a printing head, the temperature CWD of a material bed, the fusion time RS between substrates, the density MD of a powder bed and the particle size KL of the powder bed, generating the average of the temperature DWD of the printing head, the average of the temperature CWD of the material bed, the average of the fusion time RS between substrates, the average of the density MD of the powder bed and the average of the particle size KL of the powder bed, processing the average of the temperature DWD of the printing head, the average of the temperature CWD of the material bed and the average of the fusion time RS between substrates, generating an influence coefficient WXS outside the substrates, processing the average of the density MD of the powder bed and the average of the particle size KL of the powder bed, generating an influence coefficient NXS inside the substrates, performing dimensionless processing on the influence coefficient WXS outside the substrates and the influence coefficient NXS inside the substrates, performing correlation analysis, generating a multi-substrate fusion index ZS, and comparing the multi-substrate fusion index ZS with a preset multi-substrate fusion threshold YZ, and generating different evaluation signals. Therefore, the combination of the temperature DWD of the printing head, the temperature CWD of the material bed, the fusion time RS between the substrates, the density MD of the powder bed and the particle size KL of the powder bed can be utilized, the judgment precision of the fusion degree of multiple substrates is improved, the fusion degree of the multiple substrates can be evaluated in real time and quantitatively, and the parameters can be adjusted in time in the printing process, so that the quality of 3D printing is ensured.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only of the invention and that other drawings can be obtained from them without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of the operation of a modular unit according to the present invention.
Detailed Description
The present invention will be further described in detail with reference to specific embodiments in order to make the objects, technical solutions and advantages of the present invention more apparent.
It is to be noted that unless otherwise defined, technical or scientific terms used herein should be taken in a general sense as understood by one of ordinary skill in the art to which the present invention belongs. The terms "first," "second," and the like, as used herein, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items. The terms "connected" or "connected," and the like, are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "upper", "lower", "left", "right", etc. are used merely to indicate relative positional relationships, which may also be changed when the absolute position of the object to be described is changed.
Example 1
As shown in fig. 1, the present invention provides a powder material 3D printing multi-substrate fusion control system, comprising:
the data acquisition module is used for acquiring N groups of substrate external parameters and substrate internal parameters, wherein the substrate external parameters comprise the temperature DWD of a printing head, the temperature CWD of a material bed and the fusion time RS between substrates, and the substrate internal parameters comprise the density MD of a powder bed and the particle size KL of the powder bed;
when the printhead temperature DWD data changes, a change in the degree of multi-substrate fusion is caused, for specific reasons:
melting point difference of the substrates: different substrates typically have different melting points. If the temperature DWD of the 3D printhead is improperly set, some of the substrates may overheat or overcooled, thereby affecting their degree of melting. Too high a temperature may result in excessive melting, while too low a temperature may result in the substrate not melting.
Variation of mixing ratio: multi-substrate 3D printing typically involves the use of a mix of different substrates. Changing the temperature DWD of the 3D printhead may result in a variation in the mixing ratio of the different substrates. If the temperature increases, some substrates may melt faster, resulting in an increase in their proportion in the mixture.
Viscosity and fluidity changes: the viscosity and flowability of the material may change at different printhead temperatures DWD. This may result in a change in flowability and adhesion of the molten substrate upon stacking and bonding, thereby affecting the degree of fusion.
Therefore, it is important to set the thermal infrared imager to monitor the temperature DWD of the printhead, for example, the following effects can be achieved:
real-time temperature monitoring: thermal infrared imagers can provide real-time temperature monitoring to ensure that the temperature DWD of the printhead remains within a desired range. This helps to avoid problems with overheating or insufficient temperature, thereby reducing quality problems that may occur during printing.
Avoid overheating: thermal infrared imagers may be used to monitor the overheat condition of the printheads. Overheating may lead to material denaturation or printhead damage, so early detection and intervention can protect equipment and improve reliability.
Optimizing printing quality: ensuring uniform and accurate heating of the printhead can improve print quality, avoiding interlayer adhesion and structural problems. By monitoring the temperature profile you can optimize the performance of the printhead.
The production efficiency is improved: thermal infrared imagers may be used to adjust the temperature DWD of the printheads to ensure optimal printing conditions. This helps to improve production efficiency, reduce reject rate, and save time and material costs.
When the temperature CWD data of the material bed is changed, the degree of multi-substrate fusion is changed, for the following specific reasons:
melting point difference of the substrates: different substrates typically have different melting points. If the temperature CWD of the material bed is improperly set, some of the substrates may overheat or overcooled, thereby affecting their degree of melting. Too high a temperature may result in excessive melting, while too low a temperature may result in insufficient melting of the substrate.
Variation of mixing ratio: multi-substrate 3D printing typically involves the use of a mix of different substrates. Changing the temperature CWD of the material bed may result in a change in the mixing ratio of the different substrates. If the temperature increases, some substrates may melt faster, resulting in an increase in their proportion in the mixture.
Viscosity and fluidity changes: at the temperature CWD of the different material beds, the viscosity and flowability of the material change. This may result in a change in flowability and adhesion of the molten substrate upon stacking and bonding, thereby affecting the degree of fusion.
Overheating or overcooling phenomena: the temperature CWD of the material bed being set outside the proper temperature range for certain substrates may cause overheating or overcooling. This directly affects the extent of melting and mixing properties of the multiple substrates.
Therefore, it is important to provide a temperature sensor to monitor the temperature CWD of the material bed, for example, the following effects can be achieved:
improvement of print quality: monitoring the temperature CWD of the material bed can help ensure that the bed surface temperature is evenly distributed throughout the printing process. This helps to avoid temperature inconsistencies in printing, thereby improving print quality.
Reducing curl and warpage: the non-uniformity of the temperature CWD of the material bed is a common cause of curl and warp problems. By monitoring the temperature CWD of the material bed you can detect temperature non-uniformities early and take measures to reduce the deformation of the printed object.
Optimization of bed adhesion: different printing materials may require different bed temperatures to ensure that they adhere well to the bed. By monitoring the temperature CWD of the material bed, you can adjust the temperature to meet the adhesion requirements of different materials, thus improving the reliability of the printing.
When the fusion time RS data between substrates is changed, the degree of fusion of multiple substrates is changed, and the following is a specific reason:
melting point difference of multiple substrates: different substrates typically have different melting points. If the fusion time RS is insufficient, some substrates may not have enough time to completely melt, thereby affecting their degree of fusion. Conversely, if the fusion time is too long, some substrates may excessively melt.
Depth of fusion: the fusion time RS can affect the depth of fusion of the substrate. If the fusion time RS is insufficient, only the surface may be melted and the deep layer may not be melted. This affects the degree of fusion of the multiple substrates.
Phase change heat: the phase change heat (latent heat of fusion) of the different substrates is different and is the heat required to change the substance from a solid state to a liquid state. Adjusting the fusion time RS can affect the phase change process of different substrates and thus their degree of fusion.
Multi-substrate interactions: the fusion time RS may also affect interactions between different substrates, including adhesion and miscibility. Longer fusion times RS may help the different substrates to better intermix and bond.
Melting time profile: the fusion time RS is not necessarily evenly distributed over all substrates. Some substrates may require longer time to melt, while others may require shorter time. This affects the degree of fusion of the multiple substrates.
Therefore, it is important to set the thermal infrared imager to monitor the fusion time RS between the substrates, for example, the following effects can be achieved:
and (3) monitoring a fusion process in real time: thermal infrared imagers can provide real-time temperature distribution images, allowing an operator or control system to monitor the fusion process between substrates.
Reducing print failure: by monitoring the fusion time RS between substrates, the condition of insufficient fusion or non-uniformity can be found early.
When the density MD data of the powder bed is changed, the degree of multi-substrate fusion is changed, for the following specific reasons:
heat conduction: the density MD of the powder bed affects the heat transfer properties. Denser beds generally have higher heat transfer and can transfer heat more efficiently to the substrate. Thus, variations in bed density may affect the heating rate and degree of melting of different substrates.
Air flow: variations in bed density can also affect air flow, which is critical to uniform heat transfer within the bed. If the bed density is uneven or varies, it may result in uneven temperature distribution in different areas, thereby affecting the degree of fusion of the multiple substrates.
Powder distribution: the density MD of different powder beds may affect the uniformity of the distribution of the powder. If the bed density in certain areas is low, it may result in uneven distribution of powder, thereby affecting the degree of fusion of the multiple substrates.
Fluidity: the density MD of different powder beds affects the flowability of different substrates on the bed. Variations in bed density may result in some substrates flowing more readily during printing, while other substrates may be more difficult to flow, thereby affecting their degree of fusion.
Temperature uniformity: variations in bed density may affect the temperature uniformity of the bed. The non-uniform density MD of the powder bed may result in a non-uniform temperature distribution within the bed, thereby affecting the degree of melting of the different substrates.
Multi-substrate interactions: variations in bed density may also affect interactions between different substrates, including adhesion and miscibility. Denser beds may provide better support and mixing conditions, affecting the degree of fusion of multiple substrates.
Therefore, it is particularly important to provide a powder densitometer to monitor the density MD of the powder bed, as may be done with the following effects:
fusion uniformity: different substrates may require different temperatures and heat transfer conditions during the fusion process. By monitoring the density MD of the powder bed, the density uniformity of each zone can be ensured, thereby improving the fusion uniformity of different substrates. The uniform powder bed density MD helps to ensure uniform heat transfer between different substrates and avoids overheating or excessive melting problems.
Mixing: in multi-substrate fusion, the density MD of the powder bed can affect the miscibility of the different substrates. A uniform and properly dense powder bed ensures better mixing of the different substrates together, thereby improving the quality and consistency of the multi-substrate fusion.
Optimizing printing parameters: by monitoring the density MD of the powder bed, you can adjust the printing parameters to better accommodate the need for multi-substrate fusion. For example, you can optimize the printhead temperature, printing speed, and flow control according to the variation of bed density MD to ensure that different substrates achieve optimal results during the fusion process.
Reducing non-uniformity: uneven powder bed density MD may result in some areas of the substrate being insufficiently melted, while other areas may be excessively melted. By monitoring and adjusting the bed density, this non-uniformity can be reduced, ensuring consistency and quality of the different substrates.
When the particle size KL data of the powder bed is changed, the degree of multi-substrate fusion is changed, for the following specific reasons:
fluidity: variations in particle size KL directly affect the flowability of the powder. Larger particles may result in reduced flowability of the powder, making the distribution on the bed uneven, thereby affecting the degree of fusion between the different substrates.
Particle distribution: variations in particle size KL may lead to non-uniform powder distribution, thereby affecting the distribution and contact area of the different substrates during fusion. This may affect the adhesion and degree of fusion between the different substrates.
Melting point change: powders of different particle sizes KL may have different melting point characteristics. This may lead to temperature differences during the melting process, affecting the melting point and degree of fusion of the different substrates.
Uniformity of heat conduction: variations in the particle size KL of the powder bed may affect the uniformity of heat transfer, thereby resulting in non-uniformity of temperature distribution in different regions during the fusion process, affecting the degree of fusion of the multiple substrates.
Therefore, it is particularly important to set up a particle analyzer to monitor the particle size KL of the powder bed, as the following effects can be achieved:
fusion uniformity: multi-substrate fusion typically involves the use of a mixture of powders of different particle sizes. By monitoring and controlling the content of different particle sizes, the mixing uniformity of the powder can be better controlled, so that the fusion uniformity of different base materials is improved. The particle analyzer may help ensure that the particle size distribution of the different powders used meets the requirements to achieve a more uniform fusion.
Adhesion: variations in particle size may affect the adhesion between different substrates. Larger particles may provide more contact area, possibly resulting in better bonding. By monitoring the particle size, powders with the proper cohesiveness can be selected to achieve the desired fusion properties.
Bulk density: the variation in particle size may also affect the bulk density of the powder. Different substrates may require different bulk densities to achieve optimal fusion. Particle analyzers can be used to determine the bulk density of different powders to optimize the density of the bed to meet the requirements of multi-substrate fusion.
In summary, the collection of the temperature DWD of the print head, the temperature CWD of the material bed, the fusion time RS data between the substrates, the density MD of the powder bed, and the particle size KL of the powder bed plays an extremely important role in monitoring the degree of fusion of the multiple substrates, and the following are specific embodiments of the collection of the temperature DWD of the print head, the temperature CWD of the material bed, the fusion time RS data between the substrates, the density MD of the powder bed, and the particle size KL data of the powder bed in this embodiment.
The pretreatment module is used for treating the collected temperatures DWD of the N groups of printing heads, the temperatures CWD of the material beds and the fusion time RS between the base materials to generate an average number of the temperatures DWD of the printing heads, an average number of the temperatures CWD of the material beds and an average number of the fusion time RS between the base materials, and treating the collected densities MD of the N groups of powder beds and the particle sizes KL of the powder beds to generate an average number of the densities MD of the powder beds and an average number of the particle sizes KL of the powder beds, wherein the process is as follows:
wherein the collection of the temperature DWD of the N sets of printheads, the temperature CWD of the material bed, the fusion time RS data between substrates, the density MD of the powder bed, and the particle size KL of the powder bed is as follows, N is an integer greater than 1:
DWD＝[DWD 1 、DWD 2 …DWD i …DWD N ]
CWD＝[CWD 1 、CWD 2 …CWD i …CWD N ]
RS＝[RS 1 、RS 2 …RS i …RS N ]
MD＝[MD 1 、MD 2 …MD i …MD N ]
KL＝[KL 1 、KL 2 …KL i …KL N ]
wherein, DWD i For the temperature value of the ith set of printheads, CWD i For the temperature value of the material bed of group i, RS i For fusion time between group i substrates, MD i KL for the density of the i-th powder bed i Is the particle size of the powder bed of group i.
The average of the temperature DWD of the printhead and the average of the temperature CWD of the material bed and the average of the fusion time RS between substrates are calculated as follows:
the data processing module is used for processing the average of the temperature DWD of the printing head, the average of the temperature CWD of the material bed and the average of the fusion time RS between the substrates, and the process of generating the influence coefficient WXS outside the substrates is as follows:
wherein α is a weight factor of an average of the temperatures of the print head, α is 0.2.ltoreq.α.ltoreq.0.4, β is a weight factor of an average of the temperatures of the material beds, 0.2.ltoreq.β.ltoreq.0.4, γ is a weight factor of an average of the fusion times RS between the substrates, 0.2.ltoreq.γ.ltoreq.0.4, μ is an index factor of an average of the temperatures of the print head, 2.ltoreq.μ.ltoreq.4, θ is an index factor of an average of the temperatures CWD of the material beds, 2.ltoreq.θ.ltoreq.4, τ is an index factor of an average of the fusion times between the substrates, 2.ltoreq.τ.ltoreq.4, and a C1 constant correction coefficient.
From the above formula, it can be seen that: within a certain range, the higher the average of the printhead temperature DWD and the average of the temperature CWD of the material bed, the higher the influence coefficient WXS outside the substrate, and vice versa; the higher the average number of fusion times RS between substrates, the lower the influence coefficient WXS outside the substrate, and vice versa. The average of the printhead temperature DWD, the average of the temperature CWD of the material bed, and the influence coefficient WXS outside the substrate are thus all in positive correlation, and the average of the fusion time RS between substrates and the influence coefficient WXS outside the substrate are in negative correlation.
The data processing module is used for processing the average number of the density MD of the powder bed and the average number of the particle size KL of the powder bed, and generating an influence coefficient NXS of the inside of the substrate, wherein the process is as follows:
wherein ρ is a weight factor coefficient of the average number of densities of the powder bed, ρ is 0.2.ltoreq.ρ.ltoreq.0.4,weight factor coefficient being the average number of particle sizes of the powder bed, +.>Omega is an exponential factor of the average number of densities of the powder bed, 2.ltoreq.ω.ltoreq.4, epsilon is an exponential factor of the average number of particle sizes of the powder bed, 2.ltoreq.ε.ltoreq.4, and a C2 constant correction coefficient.
From the above formula, it can be seen that: within a certain range, the higher the average of the density MD of the powder bed and the average of the particle size KL of the powder bed, the lower the influence coefficient NXS inside the substrate, and vice versa; when the average of the density MD of the powder bed and the average of the particle size KL of the powder bed are lower, the influence coefficient NXS of the inside of the substrate is higher, and vice versa. The average number of the density MD of the powder bed, the average number of the particle size KL of the powder bed and the influence coefficient NXS of the inside of the substrate are thus all in negative correlation.
The data analysis module is used for carrying out non-dimensionalization on the influence coefficient WXS outside the substrate and the influence coefficient NXS inside the substrate, carrying out correlation analysis on the influence coefficient WXS outside the substrate and the influence coefficient NXS inside the substrate, and generating a formula of a multi-substrate fusion index ZS as follows:
ZS＝δ1*WXS+δ2*NXS+C3
wherein δ1 is a weight factor coefficient of an influence coefficient outside the substrate, δ1 is more than or equal to 0.2 and less than or equal to 0.4, δ2 is a weight factor coefficient of an influence coefficient inside the substrate, δ2 is more than or equal to 0.2 and less than or equal to 0.4, and a C3 constant correction coefficient.
The data analysis module is used for comparing the multi-substrate fusion index ZS with a preset multi-substrate fusion threshold YZ, and the process of generating different evaluation signals is as follows:
when ZS is more than or equal to YZ, generating a first evaluation signal;
when ZS < YZ, a second evaluation signal is generated.
The execution module is used for executing different strategies according to different evaluation signals, and the specific process is as follows:
when a first evaluation signal is sent out, the fusion degree of the multiple base materials is indicated to meet a preset threshold value, and printing can be continued;
when a second evaluation signal is sent, the fusion degree of the multiple substrates does not reach the preset threshold value, and the printing parameters need to be adjusted. Such as adjusting the printing speed, adjusting the temperature, and adjusting the layer height or nozzle spacing.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents. The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the processes or functions described in accordance with the embodiments of the present application are all or partially produced. The computer may be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wired (e.g., infrared, wireless, microwave, etc.). The computer readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that contains one or more sets of available media. The usable medium may be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. The semiconductor medium may be a solid state disk.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. 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 application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is merely a channel underwater topography change analysis system and method logic function division, and other divisions may be implemented in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, 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 units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application 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 functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention, but to enable any modification, equivalent or improvement to be made without departing from the spirit and principles of the invention.
Claims (8)
1. A powder material 3D printing multi-substrate fusion control system, comprising:
the data acquisition module is used for acquiring N groups of substrate external parameters and substrate internal parameters, wherein the substrate external parameters comprise the temperature DWD of a printing head, the temperature CWD of a material bed and the fusion time RS between substrates, and the substrate internal parameters comprise the density MD of a powder bed and the particle size KL of the powder bed;
the pretreatment module is used for treating the collected temperatures DWD of the N groups of printing heads, the temperatures CWD of the material beds and the fusion time RS between the base materials to generate an average number of the temperatures DWD of the printing heads, an average number of the temperatures CWD of the material beds and an average number of the fusion time RS between the base materials, and treating the collected densities MD of the N groups of powder beds and the particle sizes KL of the powder beds to generate an average number of the densities MD of the powder beds and an average number of the particle sizes KL of the powder beds;
the data processing module is used for processing the average of the printing head temperature DWD, the average of the temperature CWD of the material bed and the average of the fusion time RS between the substrates to generate an influence coefficient WXS outside the substrates, and processing the average of the density MD of the powder bed and the average of the particle size KL of the powder bed to generate an influence coefficient NXS inside the substrates;
the data analysis module is used for carrying out non-dimensionalization on the influence coefficient WXS outside the substrate and the influence coefficient NXS inside the substrate, carrying out correlation analysis on the influence coefficient WXS outside the substrate and the influence coefficient NXS inside the substrate to generate a multi-substrate fusion index ZS, and comparing the multi-substrate fusion index ZS with a preset multi-substrate fusion threshold YZ to generate different evaluation signals;
and the execution module is used for executing different strategies according to different evaluation signals.
2. The powder material 3D printing multi-substrate fusion control system of claim 1, wherein a set of N sets of temperatures DWD of the printheads, CWD of the material bed, fusion time RS data between the substrates, density MD of the powder bed, and particle size KL of the powder bed collected by the data collection module is as follows, N being an integer greater than 1:
DWD＝[DWD 1 、DWD 2 ...DWD i ...DWD N ]
CWD＝[CWD 1 、CWD 2 ...CWD i ...CWD N ]
RS＝[RS 1 、RS 2 ...RS i ...RS N ]
MD＝[MD 1 、MD 2 ...MD i ...MD N ]
KL＝[KL 1 、KL 2 ...KL i ...KL N ]
wherein, DWD i For the temperature value of the ith set of printheads, CWD i For the temperature value of the material bed of group i, RS i For fusion time between group i substrates, MD i KL for the density of the i-th powder bed i Is the particle size of the powder bed of group i.
3. A powder material 3D printing multi-substrate fusion control system according to claim 2, characterized in that the mean of the temperature DWD of the print head and the mean of the temperature CWD of the material bed and the mean of the fusion time RS between the substrates are calculated as follows:
4. a powder material 3D printing multi-substrate fusion control system according to claim 3, wherein the data processing module processes the average of the printhead temperature DWD and the average of the material bed temperature CWD and the average of the fusion time RS between substrates to generate the external influence coefficient WXS of the substrates as follows:
wherein α is a weight factor of an average of the temperatures of the print head, α is 0.2.ltoreq.α.ltoreq.0.4, β is a weight factor of an average of the temperatures of the material beds, 0.2.ltoreq.β.ltoreq.0.4, γ is a weight factor of an average of the fusion times RS between the substrates, 0.2.ltoreq.γ.ltoreq.0.4, μ is an index factor of an average of the temperatures of the print head, 2.ltoreq.μ.ltoreq.4, θ is an index factor of an average of the temperatures CWD of the material beds, 2.ltoreq.θ.ltoreq.4, τ is an index factor of an average of the fusion times between the substrates, 2.ltoreq.τ.ltoreq.4, and a C1 constant correction coefficient.
5. The powder material 3D printing multi-substrate fusion control system of claim 4, wherein the data processing module processes the average of the density MD of the powder bed and the average of the particle size KL of the powder bed to generate the influence coefficient NXS of the substrate interior as follows:
wherein ρ is a weight factor coefficient of the average number of densities of the powder bed, ρ is 0.2.ltoreq.ρ.ltoreq.0.4,weight factor coefficient being the average number of particle sizes of the powder bed, +.>Omega is an exponential factor of the average number of densities of the powder bed, 2.ltoreq.ω.ltoreq.4, epsilon is an exponential factor of the average number of particle sizes of the powder bed, 2.ltoreq.ε.ltoreq.4, and a C2 constant correction coefficient.
6. The powder material 3D printing multi-substrate fusion control system of claim 5, wherein the data analysis module subjects the influence coefficient WXS outside the substrate and the influence coefficient NXS inside the substrate to a non-dimensionalization process, and subjects the influence coefficient WXS outside the substrate and the influence coefficient NXS inside the substrate to a correlation analysis, and generates a multi-substrate fusion index ZS according to the formula:
ZS01 x WXS ten 02 x nxs ten C3
Wherein δ1 is a weight factor coefficient of an influence coefficient outside the substrate, δ1 is more than or equal to 0.2 and less than or equal to 0.4, δ2 is a weight factor coefficient of an influence coefficient inside the substrate, δ2 is more than or equal to 0.2 and less than or equal to 0.4, and a C3 constant correction coefficient.
7. The powder material 3D printing multi-substrate fusion control system of claim 6, wherein the data analysis module compares the multi-substrate fusion index ZS to a preset multi-substrate fusion threshold YZ to generate different evaluation signals as follows:
when ZS is more than or equal to YZ, generating a first evaluation signal;
when ZS < YZ, a second evaluation signal is generated.
8. The powder material 3D printing multi-substrate fusion control system of claim 7, wherein the execution module executes different strategies according to different evaluation signals, specifically as follows:
when a first evaluation signal is sent out, the fusion degree of the multiple base materials is indicated to meet a preset threshold value, and printing can be continued;
when a second evaluation signal is sent, the fusion degree of the multiple substrates does not reach the preset threshold value, and the printing parameters need to be adjusted.
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