CN118003638A - Inkjet printing droplet control method, device and adhesive inkjet printing equipment - Google Patents
Inkjet printing droplet control method, device and adhesive inkjet printing equipment Download PDFInfo
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- CN118003638A CN118003638A CN202410112663.6A CN202410112663A CN118003638A CN 118003638 A CN118003638 A CN 118003638A CN 202410112663 A CN202410112663 A CN 202410112663A CN 118003638 A CN118003638 A CN 118003638A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
- B29C64/30—Auxiliary operations or equipment
- B29C64/386—Data acquisition or data processing for additive manufacturing
- B29C64/393—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
- B29C64/10—Processes of additive manufacturing
- B29C64/106—Processes of additive manufacturing using only liquids or viscous materials, e.g. depositing a continuous bead of viscous material
- B29C64/112—Processes of additive manufacturing using only liquids or viscous materials, e.g. depositing a continuous bead of viscous material using individual droplets, e.g. from jetting heads
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
- B29C64/20—Apparatus for additive manufacturing; Details thereof or accessories therefor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
- B29C—SHAPING OR JOINING OF PLASTICS; SHAPING OF MATERIAL IN A PLASTIC STATE, NOT OTHERWISE PROVIDED FOR; AFTER-TREATMENT OF THE SHAPED PRODUCTS, e.g. REPAIRING
- B29C64/00—Additive manufacturing, i.e. manufacturing of three-dimensional [3D] objects by additive deposition, additive agglomeration or additive layering, e.g. by 3D printing, stereolithography or selective laser sintering
- B29C64/20—Apparatus for additive manufacturing; Details thereof or accessories therefor
- B29C64/205—Means for applying layers
- B29C64/209—Heads; Nozzles
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y10/00—Processes of additive manufacturing
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y30/00—Apparatus for additive manufacturing; Details thereof or accessories therefor
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B33—ADDITIVE MANUFACTURING TECHNOLOGY
- B33Y—ADDITIVE MANUFACTURING, i.e. MANUFACTURING OF THREE-DIMENSIONAL [3-D] OBJECTS BY ADDITIVE DEPOSITION, ADDITIVE AGGLOMERATION OR ADDITIVE LAYERING, e.g. BY 3-D PRINTING, STEREOLITHOGRAPHY OR SELECTIVE LASER SINTERING
- B33Y50/00—Data acquisition or data processing for additive manufacturing
- B33Y50/02—Data acquisition or data processing for additive manufacturing for controlling or regulating additive manufacturing processes
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- Materials Engineering (AREA)
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Abstract
本发明属于快速成型相关技术领域，其公开了一种喷墨打印液滴控制方法、装置及粘结剂喷墨打印设备，其中方法包括：S1，在打印开始以及打印过程中进行控制参数的校准，获取打印喷头的目标控制参数；S2，根据目标控制参数控制打印喷头进行喷墨打印；其中，S1具体包括：采集喷出的液滴图像以及实际控制参数；建立液滴特征与控制参数之间的逻辑关系；根据预设的目标液滴特征，获取目标控制参数。本发明中目标控制参数基于打印喷头当前状态下喷墨时的实际液滴特征以及实际控制参数推导获取的，实时性较强，更加适应打印喷头的当前状态；且有利于在打印过程中对喷墨液滴状态进行控制，实现了液滴质量监控与改善，有利于保证喷墨打印质量。
The present invention belongs to the technical field related to rapid prototyping, and discloses an inkjet printing droplet control method, device and binder inkjet printing equipment, wherein the method includes: S1, calibrating the control parameters at the beginning of printing and during the printing process to obtain the target control parameters of the print head; S2, controlling the print head to perform inkjet printing according to the target control parameters; wherein S1 specifically includes: collecting the ejected droplet image and the actual control parameters; establishing a logical relationship between the droplet characteristics and the control parameters; and obtaining the target control parameters according to the preset target droplet characteristics. In the present invention, the target control parameters are derived based on the actual droplet characteristics and the actual control parameters when the print head is spraying ink in the current state, and have strong real-time performance and are more adaptable to the current state of the print head; and are conducive to controlling the state of the inkjet droplets during the printing process, realizing droplet quality monitoring and improvement, and are conducive to ensuring the quality of inkjet printing.
Description
Technical Field
The invention belongs to the technical field of rapid prototyping, and particularly relates to an inkjet printing liquid drop control method and device and adhesive inkjet printing equipment.
Background
In the technical field of rapid prototyping, the three-dimensional prototyping technology of the binder spraying technology is to spray and print the binder on powder materials such as ceramic powder, metal powder, gypsum powder and the like through a micro-spray nozzle, bond the powder layer by layer and finally shape the powder. The jet printing mode of the adhesive spraying 3D printing device is that the adhesive enters the printing head from the ink box and is then extruded and sprayed to a working plane by piezoelectric ceramics in the printing head, and the adhesive spraying commonly has the following problems: the ink jet includes satellite droplets, droplets of uneven size, and powder scattering due to excessively large droplets. These problems not only affect the quality of the inkjet molded article, but also have a significant effect on the accuracy of large format printing. In addition, non-uniformity of the sprayed adhesive may also cause adhesive residues, resulting in nozzle clogging. In a high-precision printing process, the state of the inkjet droplet is a key factor affecting the printing quality.
At present, the existing related domestic patent mainly aims at the switching and angle adjustment of a spray head for solving the related problems of adhesive spray printing, for example, the scheme disclosed in the patent CN107097407B only adjusts when the spray head fails, and can not monitor the quality of ink drops in the printing process, so that the printing precision is affected; the scheme disclosed in CN113858835A uses an image processing algorithm to monitor the angle of the inkjet printhead in real time, and also cannot monitor the quality of ink drops in the printing process, and the situation that the printing quality is affected due to ink drop problems still occurs in the printing process. The existing control scheme of the ink-jet printing process can not control the state of liquid drops well, so that the problem of poor ink-jet quality still exists.
Disclosure of Invention
Aiming at the defects or improvement demands of the prior art, the invention provides an ink jet printing liquid drop control method, an ink jet printing liquid drop control device and an adhesive ink jet printing device, which are used for solving the problem that the existing control scheme of the ink jet printing process cannot control the liquid drop state well, so that the ink jet quality is poor, and the invention has the advantages of accurate liquid drop control and real-time and high-efficiency monitoring on an ink jet nozzle, and can effectively improve the problem of the poor ink jet quality of the prior art.
To achieve the above object, according to a first aspect of the present invention, there is provided an inkjet print droplet control method comprising:
S1, calibrating control parameters in the printing start and printing process, and acquiring target control parameters of a printing nozzle;
s2, controlling a printing nozzle to perform ink-jet printing according to the target control parameters;
the calibration of the control parameter in S1 specifically includes:
S11, controlling a printing nozzle to perform ink jet operation, and collecting an ejected liquid drop image and actual control parameters;
S12, acquiring actual droplet characteristics corresponding to the actual control parameters according to the droplet image analysis, and further establishing a logic relationship between the droplet characteristics and the control parameters;
S13, acquiring the target control parameters according to the logic relation between the droplet characteristics and the control parameters and the preset target droplet characteristics.
According to the ink jet printing droplet control method provided by the invention, the droplet characteristics comprise a plurality of droplet volumes, satellite droplet numbers, droplet speeds and aspect ratios; the control parameter is a driving voltage parameter of the print head, including a plurality of voltage amplitude, pulse width, and ejection frequency.
According to the ink jet printing droplet control method provided by the invention, S12 specifically includes: establishing a logic relationship between the droplet characteristics and the control parameters by adopting a machine learning algorithm; the machine learning algorithm specifically includes:
Establishing a data set according to the actual droplet characteristics and the corresponding actual control parameters;
selecting a machine learning algorithm, and establishing a model of the machine learning algorithm, wherein the model of the machine learning algorithm comprises a logic relation between liquid drop characteristics and control parameters;
Training a model of a machine learning algorithm using the data set to obtain a logical relationship between drop features and control parameters.
According to the ink jet printing droplet control method provided by the invention, before a data set is established according to the actual droplet characteristics and the corresponding actual control parameters, the method further comprises the following steps: carrying out normalization pretreatment on actual liquid drop characteristic data and actual control parameter data, wherein the treated data specifically comprises the following steps:
Wherein, Representing the processed actual control parameter vector; /(I)Representing the processed actual droplet feature vector; a ', w ' and f ' represent normalized control parameters; v ', N ' and λ ' represent normalized multiple drop features.
According to the ink jet printing droplet control method provided by the invention, S12 specifically includes: establishing a logic relationship between the droplet characteristics and the control parameters by adopting a support vector machine algorithm; the support vector machine algorithm specifically selects a Gaussian radial basis function as a kernel function for expressing a logical relation between droplet characteristics and control parameters, and establishes a model of the support vector machine algorithm.
According to the method for controlling the ink jet printing liquid drops, calibration of control parameters is carried out in the printing process in S1, and the method specifically comprises the following steps:
And performing calibration of multiple control parameters in the printing process, wherein printing of at least one layer is performed between the calibration of the control parameters of two adjacent times, and printing control is performed according to the target control parameters acquired by the calibration of the control parameters of the last time.
According to a second aspect of the present invention, there is provided an inkjet print drop control apparatus comprising:
The parameter calibration module is used for calibrating control parameters in the printing process and the printing start, and acquiring target control parameters of the printing nozzle;
the printing control module is used for controlling the printing nozzle to carry out ink-jet printing according to the target control parameters;
The parameter calibration module specifically comprises:
The data acquisition module is used for controlling the printing nozzle to perform ink jet operation and acquiring the ejected liquid drop image and actual control parameters;
the relation establishing module is used for acquiring the actual droplet characteristics corresponding to the actual control parameters according to the droplet image analysis, so as to establish the logic relation between the droplet characteristics and the control parameters;
and the parameter output module is used for acquiring the target control parameters according to the logic relation between the droplet characteristics and the control parameters and the preset target droplet characteristics.
According to a third aspect of the present invention, there is provided an adhesive inkjet printing apparatus comprising a base, a motion module, a jet printing module and a droplet monitoring module; the motion module comprises a first motion structure and a second motion structure, wherein the first motion structure is arranged along the length direction of the base, and the second motion structure is connected to the first motion structure and is arranged along the width direction; the spraying module comprises a printing spray head, a powder spreading roller, a powder storage cylinder and a working cylinder which are sequentially arranged along the length direction of the base, wherein the printing spray head is connected with the second moving structure, and the powder spreading roller is connected with the first moving structure and is arranged along the width direction; the liquid drop monitoring module comprises a monitoring cylinder arranged on the base, and a camera and a light source which are arranged in the monitoring cylinder.
According to the adhesive ink-jet printing equipment provided by the invention, the side wall of the monitoring cylinder is provided with an opening, and the camera is arranged at the opening; the light source is arranged at the bottom of the monitoring cylinder;
And/or, the cylinder bottoms of the powder storage cylinder and the working cylinder are respectively provided with a structure capable of moving up and down, and the bottoms are respectively connected with a lifting driving structure.
The binder ink-jet printing equipment provided by the invention further comprises an upper computer which is respectively connected with the motion module, the ink-jet printing module and the liquid drop monitoring module, wherein the upper computer is used for controlling the motion module, the ink-jet printing module and the liquid drop monitoring module to execute the ink-jet printing liquid drop control method.
In general, compared with the prior art, the above technical solutions contemplated by the present invention provide the inkjet printing droplet control method, apparatus and binder inkjet printing device:
1. The calibration of the control parameters is carried out for a plurality of times in the printing start and the printing process so as to update the optimal control parameters, so that the control parameters in the whole printing process are better, the printing effect is guaranteed, and the inkjet printing quality is improved;
2. The target control parameters are obtained based on the actual liquid drop characteristics and the actual control parameters when the ink is ejected in the current state of the printing nozzle, the real-time performance is high, the obtained target control parameters are more suitable for the current state of the printing nozzle, the printing control precision is improved, and the printing effect is guaranteed; the method monitors the actual droplet characteristics and acquires the target control parameters based on the droplet characteristic data, which is beneficial to controlling the state of the inkjet droplets in the printing process, realizes the monitoring and improvement of the droplet quality and is beneficial to ensuring the inkjet printing quality of the formed part;
3. the optimal parameters are obtained by machine learning of the drop data of the ink drops by an upper computer, and the data collection, calculation and parameter feedback are automatically completed by the machine in the printing operation without manual operation and shutdown;
4. The monitoring device is used for monitoring the liquid drops sprayed by the printing nozzle, so that the quality monitoring and improvement of the liquid drops in the printing process are realized, the high precision and excellent physical properties of the formed part are ensured, and the device has the advantages of high precision, good performance, production cost saving and the like of the formed part.
Drawings
FIG. 1 is a schematic flow chart of a method of controlling ink jet droplets according to the present invention;
FIG. 2 is a left side view of the construction of the adhesive ink jet printing apparatus provided by the present invention;
FIG. 3 is a right side view of the construction of the adhesive ink jet printing apparatus provided by the present invention;
FIG. 4 is a schematic diagram showing a state of the droplet monitoring module according to the present invention when monitoring a droplet;
FIG. 5 is a schematic diagram of the relationship of the modules in the adhesive ink jet printing apparatus provided by the present invention;
FIG. 6 is a schematic diagram of a machine learning algorithm for obtaining target control parameters according to the present invention;
FIG. 7 is a schematic diagram of a closed loop control method for ink jet printing droplets according to the present invention;
the same reference numbers are used throughout the drawings to reference like elements or structures, wherein:
1-a base; 2-a first motion slide rail; 3-mounting rack; 4-mounting plates; 5-a second motor; 6-a first motor; 7-a working cylinder; 8-a powder storage cylinder; 9-printing a spray head; 10-a powder spreading roller; 11-a first electric cylinder; 12-a second electric cylinder; 13-monitoring a cylinder; 14-high speed camera; 15-a light source; 16-a second motion slide.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention. In addition, the technical features of the embodiments of the present invention described below may be combined with each other as long as they do not collide with each other.
Referring to fig. 1, the present invention provides a method for controlling ink jet printing droplets, which includes:
S1, calibrating control parameters in the printing start and printing process to obtain target control parameters of a printing nozzle 9;
S2, controlling a printing nozzle 9 to perform ink-jet printing according to the target control parameters; that is, calibration of the control parameters is performed a plurality of times in the whole printing period, the target control parameters are updated after each calibration, and the printing process after calibration performs printing control of the printing head 9 according to the updated target control parameters.
In this embodiment, considering that the state of the printing head 9 changes as the printing process proceeds, for example, the printing head 9 changes due to ink droplet residue, head wear, etc., the ink ejection effect of the printing head 9, that is, the state of ejected droplets, changes under the control of the same control parameters, and if the printing control is performed according to the same control parameters, the state of droplets changes as the printing process proceeds, which may cause that the printing effect cannot be ensured and thus the printing quality is affected. Based on this, the present embodiment proposes that calibration of control parameters should be performed at the start of printing, so that the printing process is started under the superior control parameters; and the control parameters are required to be calibrated again in the printing process so as to update the optimal control parameters, so that the control parameters in the whole printing process are better, the printing effect is guaranteed, and the inkjet printing quality is improved.
The calibration of the control parameter in S1 specifically includes:
s11, controlling the printing nozzle 9 to perform ink jet operation, and collecting the ejected liquid drop image and actual control parameters;
S12, acquiring actual droplet characteristics corresponding to the actual control parameters according to the droplet image analysis, and further establishing a logic relationship between the droplet characteristics and the control parameters;
S13, acquiring the target control parameters according to the logic relation between the droplet characteristics and the control parameters and the preset target droplet characteristics.
In the calibration operation, the printing nozzle 9 in the current state can perform ink jet test operation to obtain a sprayed liquid drop image corresponding to the current nozzle state and corresponding actual control parameters; according to the liquid drop image, the actual liquid drop characteristics can be obtained through analysis, so that the corresponding relation between the actual liquid drop characteristics and the actual control parameters can be obtained, and then the logical relation between the liquid drop characteristics and the control parameters can be obtained through analysis based on the data related to the actual liquid drop characteristics and the actual control parameters, namely, the relation between the liquid drop characteristics and the control parameters can be established; and further deriving and acquiring target control parameters according to the logic relation between the two and the target droplet characteristics.
The target control parameters are obtained based on the actual liquid drop characteristics and the actual control parameters when the ink is ejected in the current state of the printing nozzle 9, the real-time performance is high, the obtained target control parameters are more suitable for the current state of the printing nozzle 9, the printing control precision is improved, and the printing effect is guaranteed; the method monitors the actual droplet characteristics and acquires the target control parameters based on the droplet characteristic data, which is beneficial to controlling the state of the inkjet droplets in the printing process, realizes the monitoring and improvement of the droplet quality and is beneficial to ensuring the inkjet printing quality of the formed part.
In some embodiments, the drop characteristics include a plurality of drop volumes, satellite drop numbers, drop velocities, and aspect ratios; the influence of the droplet characteristics on the printing quality is large, and the target control parameters are acquired based on the droplet characteristics, so that the control of the droplet characteristics is facilitated, and the printing effect is further ensured. The control parameters are driving voltage parameters of the printing head 9 including a plurality of voltage amplitude, pulse width, and ejection frequency. The printing nozzle 9 can be a piezoelectric nozzle, and the droplet state sprayed by the printing nozzle 9 can be controlled and regulated by controlling the driving voltage parameters, so that the effective control of the droplet state is realized.
In some embodiments, a logical relationship between the drop characteristics and the control parameters is established in S12 by a machine learning algorithm based on the actual control parameters and the corresponding actual drop characteristics. The machine learning algorithm specifically includes:
Establishing a data set according to the actual droplet characteristics and the corresponding actual control parameters;
selecting a machine learning algorithm, and establishing a model of the machine learning algorithm, wherein the model of the machine learning algorithm comprises a logic relation between liquid drop characteristics and control parameters;
Training a model of a machine learning algorithm using the data set to obtain a logical relationship between drop features and control parameters.
In some embodiments, S12 specifically includes: establishing a logic relationship between the droplet characteristics and the control parameters by adopting a support vector machine algorithm; the support vector machine algorithm specifically comprises:
selecting a Gaussian radial basis function as a kernel function used by a support vector machine algorithm, and establishing a model of the support vector machine algorithm; wherein the kernel function is a function representing a logical relationship between the droplet characteristics and the control parameters;
training a model of a support vector machine algorithm by using a data set to obtain a logic relationship between the droplet characteristics and the control parameters. The kernel function in the support vector machine algorithm is a specific relation model between input data and output data; in the process of training the model of the support vector machine algorithm, the input data and the output data can be actual control parameters and actual droplet characteristics, and the specific actual control parameters are not limited as input or output, so that the logic corresponding relation between the control parameters and the droplet characteristics can be obtained through training.
The corresponding relation between the control parameters and the droplet characteristics can be obtained through a machine learning algorithm, and then according to the relation, under the condition that the target droplet characteristics, namely the input data or the output data, are determined, the corresponding target control parameters, namely the output data or the input data, can be deduced and obtained. The volume, speed and aspect ratio parameters in the target droplet characteristics can be set according to the type of the inkjet material and the requirement of the molded part, and specific set values can be obtained according to theoretical deduction or empirical values so as to achieve better molding precision and quality of the molded part; the number of satellite liquid drops in the target liquid drop characteristics can be set to be less than or equal to the preset number, and the preset number can be 3-5, so that the target control parameters are acquired by taking the fewer satellite liquid drops as targets, the satellite liquid drop numbers in the liquid drops in actual ink jet are reduced, and the printing quality is ensured.
In other embodiments, the logical relationship between the droplet feature and the control parameter established in S12 may also be obtained by qualitative analysis, that is, according to the actual control parameter and the actual droplet feature, by data analysis to obtain a correspondence relationship between the control parameter and the droplet feature, for example, to obtain a control parameter adjustment policy capable of reducing the number of satellites in the droplet, a control parameter adjustment policy capable of increasing the volume of the liquid, etc., so as to obtain the adjustment policy of the control parameter according to the target droplet feature, and obtain the target control parameter based on the adjustment policy. That is, based on the actual control parameter and the actual droplet feature, the logical relationship between the droplet feature and the control parameter can be established in a plurality of ways, and the obtained logical relationship is not limited to a form, and aims to obtain a better control parameter as a target control parameter, and is not particularly limited, wherein the better control parameter is the control parameter capable of obtaining a better droplet state.
Further, before establishing the data set according to the actual droplet characteristics and the corresponding actual control parameters, the method further comprises: carrying out normalization pretreatment on actual liquid drop characteristic data and actual control parameter data, wherein the treated data specifically comprises the following steps:
Wherein, Representing the processed actual control parameter vector; /(I)Representing the processed actual droplet feature vector; a ', w ' and f ' represent normalized control parameters; v ', N ' and λ ' represent normalized multiple drop features. That is, the actual droplet characteristic data and the actual control parameter data are stored in vector form to form a data set through preprocessing. The data may also be cleaned prior to normalization to remove significant erroneous data.
In some embodiments, the kernel function is specifically:
Specifically:
K＝exp(-γ*([A′w′f′]T-[V′N′λ′]T)2)；
wherein γ represents a regularization parameter; A vector representing the input data, i.e., a processed actual control parameter vector; the vector representing the output data is the processed actual drop feature vector.
Further, where the drop feature comprises a drop volume, the volume of all but satellite drops in the liquid image may be acquired; when the drop characteristics include drop velocity, the velocity of all but satellite drops in the liquid image can be obtained; where the drop features include aspect ratios, the aspect ratios of all but satellite drops in the liquid image may be obtained; any of volume, speed, and aspect ratio may be used to build up a data set along with corresponding control parameters, thereby increasing the data volume of the data set. Multiple drop images can be obtained in one ink jet of the printing nozzle 9, or multiple drop images can be obtained by adjusting control parameters in one calibration, so that the data volume of a data set is improved, and the accuracy of a machine learning algorithm is further improved.
In some embodiments, the calibration of the control parameters during the printing process in S1 specifically includes:
And performing calibration of multiple control parameters in the printing process, wherein printing of at least one layer is performed between the calibration of the control parameters of two adjacent times, and printing control is performed according to the target control parameters acquired by the calibration of the control parameters of the last time. The ink-jet printing process is carried out layer by layer, and the calibration of control parameters can be carried out before each layer of printing, so that each layer of printing is controlled according to the target control parameters obtained by calibration; the calibration of the control parameters can also be performed once by multi-layer printing, namely, after the calibration of the control parameters is performed once, multi-layer printing is performed according to the target control parameters obtained by the calibration, the specific layer number can be a preset layer number, when the printing layer number reaches the preset layer number after the calibration, the calibration of the control parameters is performed again, and then the printing control is performed based on the target control parameters obtained by the latest calibration. The number of layers printed between two adjacent control parameter calibrations is not limited.
In some embodiments, the droplet image is acquired by the high speed camera 14 and the ink jet printing droplet control method is implemented by the host computer control, and the ink jet printing may be adhesive ink jet printing. The method for obtaining the optimal parameters of the adhesive spray head is that the upper computer analyzes the adhesive ink drop data shot by the high-speed camera 14 for machine learning. The core goal of machine learning is to establish a logical relationship of drop characteristics to the head drive parameters, i.e., control parameters. The method comprises the following specific steps: the upper computer software analyzes the image of the liquid drops shot by the high-speed camera 14 to obtain the characteristics of the liquid drops including but not limited to the volume, the satellite liquid drop number, the speed, the aspect ratio and the like; thereafter, the host computer software establishes the showerhead drive parameters using a machine learning algorithm including, but not limited to: the relation between the voltage amplitude, pulse width, ejection frequency and the like and the characteristic data of the liquid drops; finally, obtaining the optimal driving parameters of the spray heads for printing each layer in an on-line monitoring and on-line analysis mode, and sending the optimal parameters to the binder spray heads; in particular, each layer of printing requires the high-speed camera 14 to take a photograph of the droplet and the host computer to run a machine learning algorithm to obtain the driving parameters of the nozzle corresponding to the optimal droplet characteristics.
Further, the present invention also provides an inkjet print droplet control apparatus for implementing the inkjet print droplet control method according to any one of the above, the control apparatus being understood with reference to the above control method, the control apparatus comprising:
the parameter calibration module is used for calibrating control parameters at the beginning of printing and in the printing process, and acquiring target control parameters of the printing nozzle 9;
the printing control module is used for controlling the printing nozzle 9 to perform ink-jet printing according to the target control parameters;
The parameter calibration module specifically comprises:
The data acquisition module is used for controlling the printing nozzle 9 to perform ink jet operation and acquiring the ejected liquid drop image and actual control parameters;
the relation establishing module is used for acquiring the actual droplet characteristics corresponding to the actual control parameters according to the droplet image analysis, so as to establish the logic relation between the droplet characteristics and the control parameters;
and the parameter output module is used for acquiring the target control parameters according to the logic relation between the droplet characteristics and the control parameters and the preset target droplet characteristics.
Further, referring to fig. 2 and 3, the present invention also provides an adhesive inkjet printing apparatus including a base 1, a movement module, a jet printing module, and a droplet monitoring module; the motion module comprises a first motion structure arranged along the length direction of the base 1 and a second motion structure connected to the first motion structure and arranged along the width direction; the spraying module comprises a printing spray head 9, a powder spreading roller 10, and a powder storage cylinder 8 and a working cylinder 7 which are sequentially arranged along the length direction of the base 1, wherein the printing spray head 9 is connected with the second moving structure, and the powder spreading roller 10 is connected with the first moving structure and is arranged along the width direction; the liquid drop monitoring module comprises a monitoring cylinder arranged on the base 1, and a camera and a light source 15 arranged inside the monitoring cylinder.
Specifically, referring to fig. 4, the side wall of the monitoring cylinder is provided with an opening, and the camera is arranged at the opening; the light source 15 is arranged at the bottom of the monitoring cylinder 13.
The powder storage cylinder 8 and the cylinder bottom of the working cylinder 7 are respectively arranged to be of a structure capable of moving up and down, and the bottom is respectively connected with a lifting driving structure. The lifting driving structure may be a structure such as an electric cylinder capable of providing up-and-down lifting movement, and is not particularly limited. For example, the cylinder bottom of the working cylinder 7 can be connected with the first electric cylinder 11, the cylinder bottom of the powder storage cylinder 8 can be connected with the second electric cylinder 12, and the cylinder bottom is of a structure capable of sliding up and down along the cylinder wall, so that the up-and-down lifting adjustment of the cylinder bottom can be realized under the driving of the electric cylinder, and the printing process can be smoothly carried out.
When any layer of adhesive is subjected to ink-jet printing, the powder spreading roller 10 is initially positioned at one side of the powder storage cylinder 8 far away from the working cylinder 7, powder in the powder storage cylinder 8 is initially in a full state, the cylinder bottom of the working cylinder 7 is initially flush with the surface of the base 1, the powder spreading roller 10 is controlled to move along the length direction of the base 1, the powder spreading roller 10 sequentially passes through the powder storage cylinder 8 and the working cylinder 7 in the moving process, the powder in the powder storage cylinder 8 is paved on the cylinder bottom surface of the working cylinder 7, and the printing nozzle 9 can be moved to the working cylinder 7 for ink-jet printing; when the next layer of ink-jet printing is performed, the powder spreading roller 10 needs to be moved to one side of the powder storage cylinder 8 far away from the working cylinder 7 again, the cylinder bottom of the powder storage cylinder 8 is controlled to be lifted, the cylinder bottom of the working cylinder 7 is controlled to be lowered, and then the powder spreading roller 10 is controlled to move along the length direction of the base 1 to spread powder again.
The adhesive ink-jet printing device further comprises a mounting frame 3, wherein the mounting frame 3is connected to the first moving structure, and the second moving structure and the powder spreading roller 10 are respectively connected to the mounting frame 3.
Further, the adhesive ink-jet printing device further comprises an upper computer connected with the motion module, the ink-jet printing module and the liquid drop monitoring module respectively, wherein the upper computer is used for controlling the motion module, the ink-jet printing module and the liquid drop monitoring module to execute the ink-jet printing liquid drop control method.
In some embodiments, referring to fig. 2 and 3, an adhesive inkjet printing apparatus includes a base 1, a motion module, a jet printing module, a droplet monitoring module, and the like; the motion module comprises an x-axis motion slide rail, namely a first motion slide rail 2, a y-axis motion slide rail, namely a second motion slide rail 16, a sliding table mechanism, namely a mounting plate 4, a first motor 6 and a second motor 5; a first moving slide rail 2 is erected along the length edge direction of the base 1; a second moving slide rail 16 is arranged on the first moving slide rail 2; the second moving slide rail 16 is driven by the first motor 6 to move on the first moving slide rail 2 along the length direction; the second moving slide rail 16 is provided with a mounting plate 4; the mounting plate 4 is driven by the second motor 5 to move in the width direction on the second moving rail 16.
Specifically, a mounting frame 3 may be disposed on the base 1, the mounting frame 3 spans across the width direction of the base 1, the mounting frame 3 is slidably connected with the first moving rail 2, and the first motor 6 is used for driving the mounting frame 3 to move along the first moving rail 2. The second moving slide 16 is connectively arranged on the mounting 3.
The spraying module comprises a working cylinder 7, a powder storage cylinder 8, an adhesive printing spray head 9, a powder laying roller 10 and a lifting driving structure. The base 1 is provided with a working cylinder 7 and a powder storage cylinder 8; the mounting plate 4 is provided with an adhesive printing spray head 9, the powder spreading roller 10 is positioned at the rear side of the adhesive printing spray head 9, namely when the printing spray head 9 is positioned at one side of the working cylinder 7 facing the powder storage cylinder 8, the powder spreading roller 10 is positioned at one side of the printing spray head 9 far away from the working cylinder 7; the powder spreading roller 10 can be arranged along the width direction of the base 1 and can be connected with the mounting frame 3, so that the powder spreading roller can move along the length direction of the base 1 under the drive of the first motor 6, and the powder in the powder storage cylinder 8 can be spread in the working cylinder 7 in the moving process, so that the smooth printing is facilitated. The working cylinder 7 can be driven by the first electric cylinder 11 to move up and down; the powder storage cylinder 8 can be driven by the second electric cylinder 12 to move up and down.
Referring to fig. 4, the droplet monitoring module includes a monitoring cylinder 13, and a droplet monitoring device located in the monitoring cylinder 13; the liquid drop monitoring device includes: a high-speed camera 14 for monitoring the liquid drop sprayed by the adhesive spray head and a light source 15. The base 1 is provided with a groove, and a monitoring cylinder 13 is arranged in the groove; the liquid drop monitoring device is positioned in the monitoring cylinder 13, specifically, the high-speed camera 14 is positioned on the side surface of the monitoring cylinder 13 and is used for shooting the shape of liquid drops and uploading the shape of the liquid drops to the upper computer for processing; a light source 15 is located at the bottom surface of the monitoring cylinder 13 for providing illumination required for image capturing. Wherein, the first motor 6, the second motor 5, the first electric cylinder 11, the second electric cylinder 12, the printing nozzle 9, the high-speed camera 14 and the light source 15 are all controlled by an upper computer.
In this embodiment, referring to fig. 2,3 and 5, a closed-loop control method for an adhesive inkjet droplet based on machine learning includes the following steps:
In the printing operation process or at the beginning of printing, the x-axis movement sliding rail and the y-axis movement sliding rail driven by the first motor 6 and the second motor 5 move the adhesive printing spray head 9 on the sliding block mechanism to an on-line monitoring station, namely an area above the monitoring cylinder 13;
The adhesive spray head, namely the printing spray head 9 sprays a small amount of adhesive in a flash spraying mode, and in the process that adhesive ink drops fall into the monitoring cylinder 13, the high-speed camera 14 shoots the falling process of the adhesive ink drops and transmits data to the upper computer for processing;
After the upper computer finishes processing, the optimized control parameters are transmitted to the adhesive spray head, so that the adhesive spray head continuously prints according to the optimal parameters;
The method for obtaining the optimum parameters of the adhesive spray head is shown in fig. 6 and 7: first, the host computer analyzes the adhesive ink droplet data captured by the high-speed camera 14, and the analysis contents include: drop volume, satellite drop number, velocity, etc.; then, the upper computer performs machine learning by using a Support Vector Machine (SVM) algorithm written in Python language, calculates a classification decision function, and establishes a relation between a driving voltage parameter of the adhesive spray head and the characteristics of adhesive ink drops; finally, automatically calculating the optimal parameters of the adhesive spray head, namely target control parameters, according to the optimal liquid drop morphology, namely target liquid drop characteristics;
The driving voltage parameters in this embodiment are voltage amplitude, pulse width and injection frequency; the droplets are characterized by droplet volume, satellite droplet number, and droplet velocity. The specific process for realizing the SVM algorithm is as follows: storing the voltage amplitude, pulse width and jet frequency of the driving voltage parameter corresponding to each group of parameters into a multidimensional vector list as independent variables X, storing the volume of the binder ink drops, the number of satellite liquid drops and the speed into another multidimensional vector list as dependent variables Y, cleaning and preprocessing data in the list, and carrying out normalization processing on the data so that all the characteristics are on the same scale as shown in a formula (1);
Wherein A ' represents normalized driving voltage amplitude, w ' represents normalized pulse width, and f ' represents normalized injection frequency; v ' represents normalized drop volume, N ' represents normalized satellite drop number, and lambda ' represents normalized drop velocity;
next, a Gaussian Radial Basis Function (RBF) kernel function is selected for the data, and the Gaussian Radial Basis Function (RBF) kernel function used in the example is shown in formula (2):
Where γ represents a regularization parameter, a parameter used to control the complexity of the machine learning model and prevent overfitting; vector representing input data,/> And (3) representing a vector of output data, and introducing the result of the formula (1) into the formula (2) to obtain the formula (3):
K＝exp(-γ*([A′w′f′]T-[V′N′λ′]T)2) (3)
The dataset is then divided into a training set and a test set, and the SVM model is trained using the training set data and a kernel function shown in equation (3) using the Scikit-learn library, and the predictive performance of the model is then evaluated using the test set. Finally, selecting an optimal independent variable X list (parameters such as amplitude, pulse width, spraying frequency and the like of the driving voltage) as an optimal parameter, and sending the parameter to the adhesive spray head;
after the parameters are sent to the adhesive spray head, the adhesive spray head is moved by the first motor 6 and the second motor 5 so as to spray ink at a designated position, and therefore single-layer printing is completed on the paved powder bed;
After the single-layer printing is finished, the x-axis movement sliding rail and the y-axis movement sliding rail driven by the first motor 6 and the second motor 5 move the adhesive spray head on the sliding block mechanism to the outer side of the powder storage cylinder 8;
the working cylinder 7 is driven to descend, the powder storage cylinder 8 is driven to ascend, the x-axis moving slide rail and the y-axis moving slide rail driven by the first motor 6 and the second motor 5 move the adhesive spray head and the powder spreading roller of the sliding block mechanism 4 to an on-line monitoring station, namely, the area above the monitoring cylinder 13 is monitored, the powder spreading roller finishes powder spreading at the same time, and the adhesive spray head reaches the on-line monitoring station;
The above process is repeated in the printing program until the printing program ends.
The device utilizes the high-speed camera 14 and the light source 15 to monitor the liquid drops sprayed by the spray head of the adhesive spraying 3D printer on line, and transmits monitoring data to the upper computer for machine learning. And the upper computer transmits the optimal control voltage waveform obtained by machine learning back to the spray head, so that closed-loop control is realized. The invention can effectively adjust the ink-jet quality by collecting the spray head liquid drop picture and the machine learning algorithm, and can be used for on-line monitoring and adjusting and controlling the ink-jet of the adhesive-jet 3D printing device.
The optimal parameters of the adhesive spray head are obtained by machine learning of the drop data shot by the high-speed camera 14 by the upper computer, and the data collection, calculation and parameter feedback are automatically completed by the machine in the printing operation without manual operation or shutdown; the optimal parameters obtained by machine learning are adopted for each single-layer printing, and the single-layer printing quality of each layer with independent optimal parameters is far higher than the traditional single-layer printing quality with uniform parameters.
The invention creatively monitors the liquid drops sprayed by the binder spray head, realizes the quality monitoring and improvement of the liquid drops in the printing process, ensures the high precision and excellent physical properties of the formed part, and has the advantages of high precision, good performance of the formed part, production cost saving and the like.
It will be readily appreciated by those skilled in the art that the foregoing description is merely a preferred embodiment of the invention and is not intended to limit the invention, but any modifications, equivalents, improvements or alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (10)
1. An inkjet print drop control method, comprising:
S1, calibrating control parameters in the printing start and printing process, and acquiring target control parameters of a printing nozzle;
s2, controlling a printing nozzle to perform ink-jet printing according to the target control parameters;
the calibration of the control parameter in S1 specifically includes:
S11, controlling a printing nozzle to perform ink jet operation, and collecting an ejected liquid drop image and actual control parameters;
S12, acquiring actual droplet characteristics corresponding to the actual control parameters according to the droplet image analysis, and further establishing a logic relationship between the droplet characteristics and the control parameters;
S13, acquiring the target control parameters according to the logic relation between the droplet characteristics and the control parameters and the preset target droplet characteristics.
2. The inkjet print drop control method of claim 1, wherein the drop characteristics comprise a plurality of drop volumes, satellite drop numbers, drop velocities, and aspect ratios; the control parameter is a driving voltage parameter of the print head, including a plurality of voltage amplitude, pulse width, and ejection frequency.
3. The inkjet print drop control method according to claim 1, wherein S12 specifically includes: establishing a logic relationship between the droplet characteristics and the control parameters by adopting a machine learning algorithm; the machine learning algorithm specifically includes:
Establishing a data set according to the actual droplet characteristics and the corresponding actual control parameters;
selecting a machine learning algorithm, and establishing a model of the machine learning algorithm, wherein the model of the machine learning algorithm comprises a logic relation between liquid drop characteristics and control parameters;
Training a model of a machine learning algorithm using the data set to obtain a logical relationship between drop features and control parameters.
4. A method of inkjet print drop control according to claim 3, further comprising, prior to establishing the data set based on the actual drop characteristics and the corresponding actual control parameters: carrying out normalization pretreatment on actual liquid drop characteristic data and actual control parameter data, wherein the treated data specifically comprises the following steps:
Wherein, Representing the processed actual control parameter vector; /(I)Representing the processed actual droplet feature vector; a ', w ' and f ' represent normalized control parameters; v ', N ' and λ ' represent normalized multiple drop features.
5. The inkjet print drop control method according to claim 3, wherein S12 specifically includes: establishing a logic relationship between the droplet characteristics and the control parameters by adopting a support vector machine algorithm; the support vector machine algorithm specifically selects a Gaussian radial basis function as a kernel function for expressing a logical relation between droplet characteristics and control parameters, and establishes a model of the support vector machine algorithm.
6. The inkjet printing drop control method according to any one of claims 1 to 5 wherein calibration of control parameters is performed during printing in S1, specifically comprising:
And performing calibration of multiple control parameters in the printing process, wherein printing of at least one layer is performed between the calibration of the control parameters of two adjacent times, and printing control is performed according to the target control parameters acquired by the calibration of the control parameters of the last time.
7. An inkjet print drop control apparatus, comprising:
The parameter calibration module is used for calibrating control parameters in the printing process and the printing start, and acquiring target control parameters of the printing nozzle;
the printing control module is used for controlling the printing nozzle to carry out ink-jet printing according to the target control parameters;
The parameter calibration module specifically comprises:
The data acquisition module is used for controlling the printing nozzle to perform ink jet operation and acquiring the ejected liquid drop image and actual control parameters;
the relation establishing module is used for acquiring the actual droplet characteristics corresponding to the actual control parameters according to the droplet image analysis, so as to establish the logic relation between the droplet characteristics and the control parameters;
and the parameter output module is used for acquiring the target control parameters according to the logic relation between the droplet characteristics and the control parameters and the preset target droplet characteristics.
8. An adhesive ink-jet printing device is characterized by comprising a base, a motion module, an ink-jet printing module and a liquid drop monitoring module; the motion module comprises a first motion structure and a second motion structure, wherein the first motion structure is arranged along the length direction of the base, and the second motion structure is connected to the first motion structure and is arranged along the width direction; the spraying module comprises a printing spray head, a powder spreading roller, a powder storage cylinder and a working cylinder which are sequentially arranged along the length direction of the base, wherein the printing spray head is connected with the second moving structure, and the powder spreading roller is connected with the first moving structure and is arranged along the width direction; the liquid drop monitoring module comprises a monitoring cylinder arranged on the base, and a camera and a light source which are arranged in the monitoring cylinder.
9. The adhesive ink jet printing apparatus of claim 8 wherein the side wall of the monitoring cylinder is provided with an opening, the camera being provided at the opening; the light source is arranged at the bottom of the monitoring cylinder;
And/or, the cylinder bottoms of the powder storage cylinder and the working cylinder are respectively provided with a structure capable of moving up and down, and the bottoms are respectively connected with a lifting driving structure.
10. The adhesive ink jet printing apparatus of claim 8 further comprising a host computer connected to each of the motion module, the ink jet printing module and the drop monitoring module, the host computer being configured to control the motion module, the ink jet printing module and the drop monitoring module to perform the ink jet print drop control method of any one of claims 1-6.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119348299A (en) * | 2024-10-08 | 2025-01-24 | 深圳市中诚慧达科技有限公司 | An inkjet volume control system for inkjet printing equipment |
| CN120215430A (en) * | 2025-02-16 | 2025-06-27 | 安徽浙一南预印科技有限公司 | An intelligent printing process multi-parameter monitoring and optimization system |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119348299A (en) * | 2024-10-08 | 2025-01-24 | 深圳市中诚慧达科技有限公司 | An inkjet volume control system for inkjet printing equipment |
| CN120215430A (en) * | 2025-02-16 | 2025-06-27 | 安徽浙一南预印科技有限公司 | An intelligent printing process multi-parameter monitoring and optimization system |
| CN120215430B (en) * | 2025-02-16 | 2025-09-12 | 安徽浙一南预印科技有限公司 | Multi-parameter monitoring and optimizing system for intelligent printing process |
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