CN117774537A - Printing quality improvement method, device and storage medium for depth vision technology - Google Patents
Printing quality improvement method, device and storage medium for depth vision technology Download PDFInfo
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Abstract
The invention discloses a printing quality improving method, equipment and a storage medium of a depth vision technology, and relates to the technical field of inkjet printing; the method comprises the following steps: s1: depth vision data acquisition, S2: image processing and distortion correction, S3: print parameter optimization, S4: printing waveform adjustment, S5: real-time feedback and control and S6: experiment verification and optimization; the invention ensures the high quality surface texture of the printed object by three-dimensional reconstruction and real-time parameter adjustment of the object, reduces the possibility of reduction of printing quality, eliminates the image distortion and distortion possibly occurring in printing of different printing planes by distortion correction technology, and improves the accuracy of the printed object; the printing method can also adapt to different materials and different printing surfaces, so that high-quality printing is realized in various application scenes, the method is automatic, manual intervention is not needed, and the printing method has real-time performance, can be used for real-time adjustment in the printing process, and improves the production efficiency.
Description
Technical Field
The invention relates to the technical field of ink-jet printing, in particular to a printing quality improving method, equipment and a storage medium of a depth vision technology.
Background
The relative positions of the nozzle and the printed object of the traditional ink-jet printer have great influence on the printing quality, particularly in uneven planes, different printing parameters such as the amplitude of the driving waveform of the nozzle, the rising and falling slope, the waveform shape and the like need to be modified according to different heights, and on the other hand, if the geometric form of the printing surface can be known in advance, the printed picture can be preprocessed to achieve the preset printing effect.
For example, the printing surface is a bottle, the picture is moderately cut and adjusted under the condition that the upper part of the special-shaped bottle is narrow and the lower part of the special-shaped bottle is wide, meanwhile, the high spray waveform is switched, and the distance between the bottleneck part and the spray head is increased.
Disclosure of Invention
The invention aims to provide a printing quality improving method, equipment and storage medium of depth vision technology, which provide a printing solution with higher quality and more flexibility for the printing industry and are suitable for various complex printing requirements.
The aim of the invention can be achieved by the following technical scheme:
the embodiment of the application provides a printing quality improving method of depth vision technology, which comprises the following steps:
s1: the method comprises the steps of obtaining depth vision data, scanning and three-dimensionally reconstructing an object to be printed by using a depth camera or other depth vision sensors, and processing the acquired data by using three-dimensional reconstruction software or algorithm to generate an accurate three-dimensional model of the object, wherein the accurate three-dimensional model of the object comprises surface curvature and geometric shape of the object;
s2: image processing and distortion correction, wherein an image to be printed is combined with a three-dimensional object model, distortion correction is carried out through an image processing algorithm, the image processing method is suitable for printing surfaces with different shapes, and a distortion correction algorithm suitable for specific printing surfaces is developed;
s3: optimizing printing parameters, automatically adjusting the printing parameters according to the geometric information of the three-dimensional model and the material characteristics of the surface of the object, formulating a printing parameter optimization scheme, designing an algorithm or a system, and automatically adjusting the printing parameters according to different surface materials and geometric forms;
s4: printing waveform adjustment, namely adjusting printing waveform in real time or in advance based on the shape and surface characteristics of an object, adjusting the spraying position, strength and angle of a spray head in real time according to the shape of the object, designing a self-adaptive printing waveform control system, and dynamically adjusting the working mode of the spray head to adapt to diversified printing surfaces;
s5: real-time feedback and control, in the printing process, continuously acquiring depth vision data, acquiring and feeding back the data in real time, adjusting printing parameters and waveforms in real time, developing a feedback control system, and adjusting the printing parameters and waveforms in real time according to the depth vision data and the real-time printing effect;
s6: and (3) experimental verification and optimization, wherein the experimental verification is carried out, the different printing surfaces, shapes and materials are tested, the effect of the method is evaluated, and the self-adaptive capacity and the printing quality are improved through a continuous optimization algorithm and system.
Preferably, according to the three-dimensional reconstruction in step S1, depth information of the object surface can be obtained by a depth camera or other depth vision sensor, and the sensor measures a time difference between light rays from the camera to the object surface or an offset of the light rays to obtain depth data of the object;
scanning and reconstructing an object by using three-dimensional reconstruction software or algorithm through a depth image acquired by a depth vision sensor, converting the depth image into point cloud data, wherein the coordinate of each point represents one space point on the surface of the object, generating a surface grid by using the point cloud data to form the geometric shape of the object, and finally, corresponding the color image and the surface grid to generate an object three-dimensional model with a texture map;
generating accurate three-dimensional models of objects for computer-aided detection and analysis has a variety of applications in printing systems;
in the depth vision data acquisition and three-dimensional reconstruction process, data processing and precision control are carried out, and post-processing and repairing are carried out on the reconstruction result.
Preferably, according to the image processing and distortion correction described in step S2, an image to be printed needs to be acquired first, distortion detection and analysis are performed on the acquired image, and the distortion type existing in the image is determined;
establishing a corresponding three-dimensional object model according to the shape and texture information of the printing surface, mapping the acquired image onto the three-dimensional object model, correcting distortion, and correcting by adopting a distortion correction algorithm and technology according to different distortion types;
on the basis of distortion correction, the image is further processed and optimized, and the image after distortion correction and image processing optimization is sent to the printing equipment for output.
Preferably, according to the optimization of the printing parameters in the step S3, geometric information of the three-dimensional model and material property data of the object surface are collected, and the collected data are processed and modeled to generate a corresponding geometric model and material properties;
selecting optimized printing parameters according to the established geometric model and material properties, and setting a range and a step length for each parameter;
designing a printing parameter optimization algorithm through a particle swarm algorithm, searching and optimizing in a parameter range, and finding out an optimal parameter combination;
defining an evaluation function or index, wherein the evaluation function is related to printing parameters and is used for distinguishing the differences of different surface materials and geometric forms;
and (3) carrying out parameter searching and adjustment according to feedback of the evaluation function by using a designed optimization algorithm, comparing the merits of different parameter combinations by calculating the evaluation function value in each iteration, and updating the current optimal solution.
Preferably, according to the adjustment of the printing waveform in the step S4, a self-adaptive control algorithm is designed, the working mode of the spray head is adjusted based on real-time feedback information, according to the surface characteristics, the shape data and the printing requirement of an object are combined, the printing waveform parameters, the ink-jet position, the strength and the angle are dynamically adjusted through a closed-loop feedback mechanism of a control system, then the printing waveform is adjusted according to the surface characteristics and the printing requirement, and the working mode of the spray head is dynamically adjusted by changing the waveform parameters;
the closed loop feedback mechanism is used for adjusting the working mode of the spray head according to the real-time feedback information, monitoring the system output in real time and comparing the system output with an expected value, then adjusting the system output according to the difference so as to enable the system output to approach the expected value, calculating an error signal according to the mean square error so as to quantify the deviation between the actual output and the expected value, and using the signal for adjusting control parameters so as to enable the system output to gradually approach the expected value;
the mean square error is: MSE= (1/n) Σ (y-y_hat) 2 ；
Where n is the number of samples, y is the actual output value, and y_hat is the desired output value.
Preferably, a feedback control algorithm is designed and implemented according to the development feedback control system described in step S5, the depth vision data is compared with the expected value, an error signal is calculated, and the printing parameters and waveforms are adjusted according to the PID control error signal,
the PID control algorithm is as follows: output = Kp deviation + Ki accumulated deviation + Kd deviation rate of change;
the output value is an adjusted printing parameter or waveform, the deviation is a current error, namely, the difference between the depth vision data and the expected value, the accumulated deviation is an accumulated value of historical errors, the accumulated deviation is used for eliminating a system steady-state error, the deviation change rate is a change rate of the current error, the error change trend in the future is predicted, kp, ki and Kd are adjusting parameters of a PID controller, and the influences of proportion, integral and differential terms are balanced.
Preferably, the continuous optimization algorithm and system according to step S6 includes algorithm parameter adjustment, and parameter adjustment in the algorithm is performed according to the results of experimental verification and data analysis;
algorithm improvement, namely improving a feedback control algorithm according to experimental verification and data analysis results;
data preprocessing, in which data preprocessing is performed in a depth vision data acquisition stage;
the real-time feedback mechanism is optimized, and the accuracy and timeliness of real-time feedback information are improved;
system hardware and software are improved, and the system hardware and software are improved according to the experimental verification and data analysis results;
automation and intellectualization, and automation and intellectualization technologies are introduced, so that the printing system can automatically adapt to different printing surfaces, shapes and materials;
and (3) experimental verification and iterative optimization, wherein the experimental verification is continuously carried out, and the iterative optimization is carried out according to the result.
Preferably, the printing quality improving method of the depth vision technology further comprises a mobile platform and a printer, wherein the mobile platform is in bidirectional connection with the printer, the mobile platform comprises a pitch angle control mechanism, a Z-axis integral lifting mechanism, a turnover angle control mechanism, a laser radar/RGBD camera, a gyroscope, a spray head and ultrasonic waves, the laser radar/RGBD camera scans a printing surface through a camera acquisition surface, and the spray head is arranged on the printing surface through ink jetting.
A print quality enhancement device for depth vision technology comprising a printer, at least one processor, at least one memory and computer program instructions stored in the memory, which when executed by the processor, implement the method described above.
A storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method described above.
The beneficial effects of the invention are as follows:
(1) The high-quality printing ensures the high-quality surface texture of the printed object through three-dimensional reconstruction and real-time parameter adjustment of the object, reduces the possibility of reduction of printing quality, eliminates the image distortion and distortion possibly occurring in printing on different printing planes (such as the neck of a bottle) through a distortion correction technology, and improves the accuracy of the printed object;
(2) The method can be suitable for different materials and different printing surfaces, so that high-quality printing is realized in various application scenes, the method is automatic, manual intervention is not needed, and the method has instantaneity, can be adjusted in real time in the printing process, and improves the production efficiency.
Drawings
For a better understanding and implementation, the technical solutions of the present application are described in detail below with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method for improving printing quality of depth vision technology according to embodiment 1 of the present application;
fig. 2 is a system block diagram of a print quality improvement method of depth vision technology provided in embodiment 1 of the present application.
Detailed Description
For further explanation of the technical means and effects adopted by the present invention for achieving the intended purpose, exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present application. Rather, they are merely examples of methods and systems that are consistent with aspects of the present application, as detailed in the accompanying claims.
The terminology used in the present application is for the purpose of describing particular embodiments only and is not intended to be limiting of the present application. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.
The following detailed description of specific embodiments, features and effects according to the present invention is provided with reference to the accompanying drawings and preferred embodiments.
Example 1
Referring to fig. 1-2, the present embodiment provides a printing quality improvement method, apparatus and storage medium for depth vision technology, which provides a printing solution with higher quality and more flexibility for the printing industry, and is suitable for various complex printing requirements.
The invention provides a printing quality improving method of depth vision technology, which comprises the following steps:
s1: the method comprises the steps of obtaining depth vision data, scanning and three-dimensionally reconstructing an object to be printed by using a depth camera or other depth vision sensors, and processing the acquired data by using three-dimensional reconstruction software or algorithm to generate an accurate three-dimensional model of the object, wherein the accurate three-dimensional model of the object comprises surface curvature and geometric shape of the object;
s2: image processing and distortion correction, wherein an image to be printed is combined with a three-dimensional object model, distortion correction is carried out through an image processing algorithm so as to adapt to printing surfaces with different shapes, a distortion correction algorithm suitable for a specific printing surface is developed, and the image is ensured not to be distorted or deformed in the printing process;
s3: the printing parameters are optimized, the printing parameters are automatically adjusted according to the geometric information of the three-dimensional model and the material characteristics of the surface of the object, a printing parameter optimization scheme is formulated, the printing parameters comprise nozzle speed, temperature and the like, and an algorithm or system is designed, so that the printing parameters can be automatically adjusted according to different surface materials and geometric forms, and the high-quality surface texture of the printed object is ensured;
s4: the printing waveform is adjusted, the printing waveform is adjusted in real time or in advance based on the shape and the surface characteristics of the object, the spraying position, the strength and the angle of the spray head are adjusted in real time according to the shape of the object, and an adaptive printing waveform control system is designed, so that the working mode of the spray head can be dynamically adjusted to adapt to diversified printing surfaces, and the method can comprise the steps of adjusting the spraying strength and the position of the ink jet to adapt to different printing surfaces and materials;
s5: real-time feedback and control, in the printing process, continuously collecting depth vision data, realizing real-time data collection and feedback, adjusting printing parameters and waveforms in real time, developing a feedback control system, and adjusting the printing parameters and waveforms in real time according to the depth vision data and the real-time printing effect so as to ensure that the printing quality is always at a high level;
s6: and (3) experimental verification and optimization are carried out, the experimental verification is carried out, the different printing surfaces, shapes and materials are tested, the effect of the method is evaluated, the self-adaptive capacity and the printing quality are improved through a continuous optimization algorithm and system, and the applicability and the reliability of the method in different scenes are ensured.
In this embodiment, according to the three-dimensional reconstruction described in step S1, depth information of the object surface may be obtained by a depth camera or other depth vision sensor, and the sensor may measure a time difference between light rays from the camera and the object surface or an offset of the light rays by transmitting infrared light, structured light, or time flight, so as to obtain depth data of the object;
scanning and reconstructing an object by using three-dimensional reconstruction software or algorithm through a depth image acquired by a depth vision sensor, wherein the reconstruction process comprises the steps of point cloud generation, surface grid generation, texture mapping and the like, firstly, converting the depth image into point cloud data, wherein the coordinate of each point represents one space point on the surface of the object, then, generating the surface grid by using the point cloud data to form the geometric shape of the object, and finally, corresponding the color image with the surface grid to generate the three-dimensional model of the object with the texture mapping;
generating an accurate three-dimensional model of an object can have various applications in printing systems, for example, can be used for virtual simulation and visualization, help users preview and adjust printing results, can also be used for tasks such as model alignment, fitting matching and assembly verification in automated design and manufacturing processes, and the like, and can also be used for computer-aided detection and analysis, such as size measurement, surface defect detection and the like;
in the depth vision data acquisition and three-dimensional reconstruction process, attention is paid to the processing and accuracy control of the data. The method comprises the steps of removing noise, filling holes, smoothing point cloud data and the like, and carrying out post-processing and repairing on a reconstruction result, and meanwhile, factors such as the precision of a sensor, sampling density and the like are also required to be considered so as to ensure that a generated object three-dimensional model has enough accuracy and detail.
Through depth vision data acquisition and three-dimensional reconstruction technology, an accurate three-dimensional model of an object can be acquired, including the surface curvature and the geometric shape of the object, more accurate input data is provided for a printing system, printing parameters can be optimized, printing quality is improved, and personalized customization, rapid prototyping and other applications can be realized.
In this embodiment, according to the image processing and distortion correction described in step S2, an image to be printed needs to be acquired first, distortion detection and analysis are performed on the acquired image, and the distortion types, such as radial distortion, tangential distortion, and the like, existing in the image are determined, which may be implemented by a specific algorithm, model, or calibration method;
according to the shape and texture information of the printing surface, a corresponding three-dimensional object model is established, the acquired image is mapped onto the three-dimensional object model, distortion correction is carried out, and according to different distortion types, a distortion correction algorithm and technology are adopted for correction, such as camera calibration, geometric transformation, texture mapping and the like, so that the image can keep accurate shape and texture when projected onto the three-dimensional surface, and the image can adapt to printing surfaces with different shapes;
on the basis of distortion correction, the image is further processed and optimized, such as contrast enhancement, color balance adjustment, noise removal and the like, and the processing operations aim at improving the image quality so as to obtain a better printing effect, the image after the distortion correction and the image processing optimization can be sent to a printing device for output, and in the printing process, the shape of the printing surface is ensured to be matched with a three-dimensional object model, so that the final printing result is ensured not to be distorted or deformed.
The image processing and distortion correction technology can enable the image to be printed to be combined with the three-dimensional object model, adapt to printing surfaces with different shapes, ensure that the image is not distorted or deformed in the printing process, and achieve the expected printing effect.
In this embodiment, according to the print parameter optimization described in step S3, geometric information of the three-dimensional model and material property data of the object surface are collected, and the collected data are processed and modeled to generate a corresponding geometric model and material properties;
according to the established geometric model and material properties, selecting optimized printing parameters such as nozzle speed, temperature and the like, setting a range and a step length for each parameter so as to search in the subsequent optimization process;
the particle swarm optimization is used for designing an algorithm for optimizing printing parameters, searching and optimizing can be carried out in a parameter range, an optimal parameter combination is found, and when the algorithm is designed, the relevance among parameters and constraint conditions need to be considered;
defining an evaluation function or index to measure the surface texture of the printing quality, wherein the evaluation function is based on quantitative or qualitative indexes in aspects of visual effect, smoothness, detail retention and the like, is related to printing parameters and can distinguish the differences of different surface textures and geometric forms;
and (3) carrying out parameter searching and adjustment according to feedback of the evaluation function by using a designed optimization algorithm, comparing the merits of different parameter combinations by calculating the evaluation function value in each iteration, updating the current optimal solution, and increasing the randomness or self-adaptive strategy to improve the searching efficiency.
An algorithm or system capable of automatically adjusting printing parameters according to different surface materials and geometric forms is designed, and the algorithm or system automatically optimizes parameters such as nozzle speed, temperature and the like according to specific requirements and constraint conditions so as to ensure high-quality surface texture of a printed object.
In this embodiment, according to the adjustment of the printing waveform in step S4, an adaptive control algorithm is designed, the working mode of the spray head is adjusted based on real-time feedback information, according to the surface characteristics, shape data and printing requirements of an object are combined, the printing waveform parameters, the ink-jet position, the strength, the angle and the like are dynamically adjusted through a closed-loop feedback mechanism of a control system, then according to the surface characteristics and the printing requirements, the printing waveform is adjusted, and by changing waveform parameters such as the jet strength, the position, the angle and the like of the ink-jet, the dynamic adjustment of the working mode of the spray head is realized, so as to adapt to different printing surfaces and materials;
the closed loop feedback mechanism is used for adjusting the working mode of the spray head according to the real-time feedback information, monitoring the system output in real time and comparing the system output with an expected value, then adjusting the system output according to the difference so as to enable the system output to approach the expected value, calculating an error signal according to the mean square error so as to quantify the deviation between the actual output and the expected value, and using the signal for adjusting control parameters so as to enable the system output to gradually approach the expected value;
the mean square error is: MSE= (1/n) Σ (y-y_hat) 2 ；
Where n is the number of samples, y is the actual output value, and y_hat is the desired output value.
In this embodiment, according to the development feedback control system described in step S5, a feedback control algorithm is designed and implemented, the depth vision data is compared with the expected value, an error signal is calculated, and the printing parameters and waveforms are adjusted according to the PID control error signal,
the PID control algorithm is as follows: output = Kp deviation + Ki accumulated deviation + Kd deviation rate of change;
the output value is an adjusted printing parameter or waveform, the deviation is a current error, namely, the difference between the depth vision data and the expected value, the accumulated deviation is an accumulated value of historical errors, the accumulated deviation is used for eliminating a system steady-state error, the deviation change rate is a change rate of the current error, the error change trend in the future is predicted, kp, ki and Kd are adjusting parameters of a PID controller, and the influences of proportion, integral and differential terms are balanced.
In practical application, the PID control algorithm needs to be improved and adjusted to adapt to specific printing requirements and real-time feedback information, for example, strategies such as saturation limitation, integral separation and the like can be introduced to optimize the performance of the PID control algorithm; by designing and implementing a PID control algorithm and comparing the depth vision data with the expected value, an error signal is calculated, and the printing parameters and waveforms can be dynamically adjusted to improve the printing quality and meet different printing requirements.
In this embodiment, the continuous optimization algorithm and system according to step S6 includes algorithm parameter adjustment, and parameters in the algorithm are adjusted according to the results of experimental verification and data analysis, for example, the proportional coefficient, integral coefficient and differential coefficient in the PID control algorithm are optimized to obtain better control performance and adaptability;
algorithm improvement, namely improving a feedback control algorithm according to experimental verification and data analysis results; more complex control strategies or new algorithmic models may be introduced to improve the adaptation ability and print quality;
data preprocessing, in the stage of deep vision data acquisition, data preprocessing is performed to improve data quality and accuracy and improve data reliability and stability;
the real-time feedback mechanism is optimized, the accuracy and timeliness of real-time feedback information are ensured, and optimization in the aspects of sensor selection, sampling frequency setting, data transmission, processing speed and the like is related;
system hardware and software improvements, such as upgrading the shower head equipment, improving the ink-jet control circuit, optimizing the response speed and stability of the system, etc., to improve the performance of the whole system, according to the results of experimental verification and data analysis;
automation and intellectualization, and an automation and intellectualization technology is introduced, so that a printing system can automatically adapt to different printing surfaces, shapes and materials, for example, a machine learning algorithm is used for analyzing and processing real-time feedback information, and more accurate printing parameter adjustment is realized;
experiment verification and iterative optimization are carried out continuously, the experiment verification is carried out continuously, the iterative optimization is carried out according to the result, the problems encountered in practical application are solved by continuously improving the algorithm and the system, and the printing quality and the self-adaptive capacity are improved gradually.
The continuous optimization algorithm and the system are a progressive process, and based on experimental verification and data analysis, the printing quality and the self-adaption capability are improved by adjusting parameters, improving the algorithm and improving the system. This requires continuous effort and practice to ensure applicability and reliability of the method in different scenarios.
In this embodiment, still include mobile platform and printer, mobile platform and printer both-way connection, mobile platform includes pitch angle control mechanism, Z axle integral lifting mechanism, flip angle control mechanism, laser radar/RGBD camera, gyroscope, shower nozzle and ultrasonic wave, laser radar/RGBD camera passes through camera collection face scanning printing face, the shower nozzle passes through the inkjet on the printing face.
A print quality enhancement device for depth vision technology comprising a printer, at least one processor, at least one memory and computer program instructions stored in the memory, which when executed by the processor, implement the method described above.
A storage medium having stored thereon computer program instructions which, when executed by a processor, implement the method described above.
Example 2
In the textile printing scene, the embodiment applies the depth vision technology to textile printing, improves printing quality and accuracy, and realizes clearer and high-quality printing effect.
A print quality improving method of depth vision technology comprises
Depth vision data acquisition, namely performing real-time three-dimensional depth image acquisition on textiles to be printed by using a depth camera or other depth vision sensors, wherein the depth vision data can capture the shape, texture and detail information of the surfaces of the textiles;
and preprocessing and analyzing the data, and preprocessing and analyzing the acquired depth vision data. For example, operations such as noise removal, filtering processing, data enhancement, etc., to improve data quality and accuracy;
and (5) extracting textile characteristics, and extracting and analyzing the textile characteristics according to the depth vision data. The more accurate textile description information is obtained by identifying and modeling the characteristics of the textile such as texture, pattern and the like;
and optimizing printing parameters, namely optimizing printing parameters of printing based on recognition and modeling results of textile characteristics. For example, parameters such as ink jet position, angle, ink jet force and the like are adjusted so as to improve printing precision and definition;
waveform parameters are optimized, and printing waveform parameters are optimized according to recognition and modeling results of textile characteristics. The dynamic adjustment of the working mode of the spray head is realized by adjusting the parameters such as the spray intensity, the position, the angle and the like of the ink jet so as to adapt to the requirements of different textile materials and patterns;
real-time feedback control, which uses real-time depth vision data and combines a feedback control algorithm to adjust real-time printing parameters and waveforms, continuously monitors printing effects, and dynamically adjusts the printing parameters and waveforms according to real-time feedback information so as to keep printing quality at a high level all the time;
iterative optimization and test verification, through experimental verification and test, the effect of the method is evaluated, potential problems are identified, iterative optimization is carried out according to the verification result, and algorithms and systems are continuously improved, so that the quality and reliability of textile printing are improved.
The present invention is not limited to the above embodiments, but is capable of modification and variation in detail, and other modifications and variations can be made by those skilled in the art without departing from the scope of the present invention.
Claims (10)
1. A printing quality improving method of depth vision technology is characterized in that: the method comprises the following steps:
s1: the method comprises the steps of obtaining depth vision data, scanning and three-dimensionally reconstructing an object to be printed by using a depth camera or other depth vision sensors, and processing the acquired data by using three-dimensional reconstruction software or algorithm to generate an accurate three-dimensional model of the object, wherein the accurate three-dimensional model of the object comprises surface curvature and geometric shape of the object;
s2: image processing and distortion correction, wherein an image to be printed is combined with a three-dimensional object model, distortion correction is carried out through an image processing algorithm, the image processing method is suitable for printing surfaces with different shapes, and a distortion correction algorithm suitable for specific printing surfaces is developed;
s3: optimizing printing parameters, automatically adjusting the printing parameters according to the geometric information of the three-dimensional model and the material characteristics of the surface of the object, formulating a printing parameter optimization scheme, designing an algorithm or a system, and automatically adjusting the printing parameters according to different surface materials and geometric forms;
s4: printing waveform adjustment, namely adjusting printing waveform in real time or in advance based on the shape and surface characteristics of an object, adjusting the spraying position, strength and angle of a spray head in real time according to the shape of the object, designing a self-adaptive printing waveform control system, and dynamically adjusting the working mode of the spray head to adapt to diversified printing surfaces;
s5: real-time feedback and control, in the printing process, continuously acquiring depth vision data, acquiring and feeding back the data in real time, adjusting printing parameters and waveforms in real time, developing a feedback control system, and adjusting the printing parameters and waveforms in real time according to the depth vision data and the real-time printing effect;
s6: and (3) experimental verification and optimization, wherein the experimental verification is carried out, the different printing surfaces, shapes and materials are tested, the effect of the method is evaluated, and the self-adaptive capacity and the printing quality are improved through a continuous optimization algorithm and system.
2. The printing quality improvement method of depth vision technique according to claim 1, characterized in that: according to the three-dimensional reconstruction in the step S1, depth information of the surface of the object can be obtained through a depth camera or other depth vision sensors, and the sensors measure the time difference between light rays from the camera to the surface of the object or the offset of the light rays to obtain the depth data of the object;
scanning and reconstructing an object by using three-dimensional reconstruction software or algorithm through a depth image acquired by a depth vision sensor, converting the depth image into point cloud data, wherein the coordinate of each point represents one space point on the surface of the object, generating a surface grid by using the point cloud data to form the geometric shape of the object, and finally, corresponding the color image and the surface grid to generate an object three-dimensional model with a texture map;
generating accurate three-dimensional models of objects for computer-aided detection and analysis has a variety of applications in printing systems;
in the depth vision data acquisition and three-dimensional reconstruction process, data processing and precision control are carried out, and post-processing and repairing are carried out on the reconstruction result.
3. The printing quality improvement method of depth vision technique according to claim 1, characterized in that: according to the image processing and distortion correction in the step S2, firstly, an image to be printed needs to be acquired, distortion detection and analysis are carried out on the acquired image, and the distortion type in the image is judged;
establishing a corresponding three-dimensional object model according to the shape and texture information of the printing surface, mapping the acquired image onto the three-dimensional object model, correcting distortion, and correcting by adopting a distortion correction algorithm and technology according to different distortion types;
on the basis of distortion correction, the image is further processed and optimized, and the image after distortion correction and image processing optimization is sent to the printing equipment for output.
4. The printing quality improvement method of depth vision technique according to claim 1, characterized in that: according to the printing parameter optimization in the step S3, collecting geometric information of the three-dimensional model and material property data of the object surface, and processing and modeling the collected data to generate a corresponding geometric model and material properties;
selecting optimized printing parameters according to the established geometric model and material properties, and setting a range and a step length for each parameter;
designing a printing parameter optimization algorithm through a particle swarm algorithm, searching and optimizing in a parameter range, and finding out an optimal parameter combination;
defining an evaluation function or index, wherein the evaluation function is related to printing parameters and is used for distinguishing the differences of different surface materials and geometric forms;
and (3) carrying out parameter searching and adjustment according to feedback of the evaluation function by using a designed optimization algorithm, comparing the merits of different parameter combinations by calculating the evaluation function value in each iteration, and updating the current optimal solution.
5. The printing quality improvement method of depth vision technique according to claim 1, characterized in that: according to the printing waveform adjustment in the step S4, a self-adaptive control algorithm is designed, the working mode of the spray head is adjusted based on real-time feedback information, according to the surface characteristics, the shape data and the printing requirements of an object are combined, the printing waveform parameters, the ink-jet position, the strength and the angle are dynamically adjusted through a closed-loop feedback mechanism of a control system, then the printing waveform is adjusted according to the surface characteristics and the printing requirements, and the working mode of the spray head is dynamically adjusted by changing the waveform parameters;
the closed loop feedback mechanism is used for adjusting the working mode of the spray head according to the real-time feedback information, monitoring the system output in real time and comparing the system output with an expected value, then adjusting the system output according to the difference so as to enable the system output to approach the expected value, calculating an error signal according to the mean square error so as to quantify the deviation between the actual output and the expected value, and using the signal for adjusting control parameters so as to enable the system output to gradually approach the expected value;
the mean square error is: MSE= (1/n) Σ (y-y_hat) 2 ；
Where n is the number of samples, y is the actual output value, and y_hat is the desired output value.
6. The printing quality improvement method of depth vision technique according to claim 1, characterized in that: according to the development feedback control system of step S5, a feedback control algorithm is designed and implemented, the depth vision data is compared with the expected value, an error signal is calculated, and the printing parameters and waveforms are adjusted according to the PID control error signal,
the PID control algorithm is as follows: output = Kp deviation + Ki accumulated deviation + Kd deviation rate of change;
the output value is an adjusted printing parameter or waveform, the deviation is a current error, namely, the difference between the depth vision data and the expected value, the accumulated deviation is an accumulated value of historical errors, the accumulated deviation is used for eliminating a system steady-state error, the deviation change rate is a change rate of the current error, the error change trend in the future is predicted, kp, ki and Kd are adjusting parameters of a PID controller, and the influences of proportion, integral and differential terms are balanced.
7. The printing quality improvement method of depth vision technique according to claim 1, characterized in that: according to the continuous optimization algorithm and system in the step S6, algorithm parameter adjustment is included, and parameters in the algorithm are adjusted according to experimental verification and data analysis results;
algorithm improvement, namely improving a feedback control algorithm according to experimental verification and data analysis results;
data preprocessing, in which data preprocessing is performed in a depth vision data acquisition stage;
the real-time feedback mechanism is optimized, and the accuracy and timeliness of real-time feedback information are improved;
system hardware and software are improved, and the system hardware and software are improved according to the experimental verification and data analysis results;
automation and intellectualization, and automation and intellectualization technologies are introduced, so that the printing system can automatically adapt to different printing surfaces, shapes and materials;
and (3) experimental verification and iterative optimization, wherein the experimental verification is continuously carried out, and the iterative optimization is carried out according to the result.
8. The printing quality improvement method of depth vision technique according to claim 1, characterized in that: the printing quality improvement method of the depth vision technology further comprises a mobile platform and a printer, wherein the mobile platform is in bidirectional connection with the printer, the mobile platform comprises a pitch angle control mechanism, a Z-axis integral lifting mechanism, a turnover angle control mechanism, a laser radar/RGBD camera, a gyroscope, a spray head and ultrasonic waves, the laser radar/RGBD camera scans a printing surface through a camera acquisition surface, and the spray head is arranged on the printing surface through ink jet.
9. A print quality improvement apparatus of depth vision technology, characterized in that: comprising at least one processor, at least one memory and computer program instructions stored in the memory, which when executed by the processor, implement the method.
10. A storage medium having stored thereon computer program instructions, characterized by: the above-described method is implemented when the computer program instructions are executed by a processor.
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