Method and system for optimizing extrusion volumetric flow of a printer

Abstract

The application discloses a kind of extrusion volume flow optimization method and system of printer, method includes: the running state of printer extrusion head in printing process is monitored in real time, and corresponding monitoring data are acquired, wherein the monitoring data at least include: temperature data and pressure data;According to the monitoring data, the nozzle fluidity index for evaluating the extrusion head nozzle extrusion fluency is calculated;Based on the nozzle fluidity index and the monitoring data, the printing fluidity index that combines nozzle fluidity and extrusion material flow characteristics is calculated;According to the printing fluidity index, current extrusion volume flow is optimized.Utilize the embodiment of the application, the printing fluidity index that combines nozzle fluidity and material flow characteristics can be calculated, and then the dynamic optimization of current extrusion volume flow is realized, and the reliability and efficiency of 3D printing are improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of printing, in particular to an extrusion volume flow optimization method and system of a printer. BACKGROUND

[0002] With the rapid development of 3D printing technology, its application prospect in manufacturing, medical, construction, aerospace and other fields is increasingly widespread. However, the optimization of extrusion volume flow in the 3D printing process is still one of the important challenges to ensure the quality and efficiency of printing.

[0003] In the 3D printing process, the performance of the extrusion head has a direct impact on the final printing quality. The stability and accuracy of the extrusion volume flow are directly related to the uniformity of the printing material, the interlayer adhesion strength and the surface quality of the finished product. If the extrusion volume flow is too low, it will cause a lack of printing material, resulting in printing defects; if the extrusion flow is too high, it may cause material overflow, model deformation and other problems. In addition, the temperature and pressure changes in the printing process also affect the flow characteristics of the material, thereby causing negative effects on the extrusion volume flow. In the prior art, although some methods try to adjust the heating temperature of the extrusion head or modify the feeding speed to optimize the extrusion volume flow, these methods often have the problems of response lag and insufficient real-time, and cannot effectively respond to instantaneous changes. SUMMARY

[0004] The purpose of the present application is to provide an extrusion volume flow optimization method and system of a printer to solve the problems in the prior art, which can calculate the printing fluidity index combining the nozzle fluidity and the flow characteristics of the material, and then realize the dynamic optimization of the current extrusion volume flow, thereby improving the reliability and efficiency of 3D printing.

[0005] One embodiment of the present application provides an extrusion volume flow optimization method of a printer, the method comprising:

[0006] real-time monitoring the running state of the extrusion head of the printer in the printing process and obtaining corresponding monitoring data, wherein the monitoring data at least includes temperature data and pressure data;

[0007] calculating a nozzle fluidity index for evaluating the extrusion fluidity of the nozzle of the extrusion head according to the monitoring data;

[0008] calculating a printing fluidity index combining the nozzle fluidity and the flow characteristics of the extruded material based on the nozzle fluidity index and the monitoring data;

[0009] optimizing the current extrusion volume flow according to the printing fluidity index.

[0010] Optionally, the calculating, according to the monitoring data, of a nozzle flowability index for evaluating the extrusion smoothness of the nozzle of the extrusion head comprises:

[0011] determining, according to the monitoring data, a monitoring value of a specific monitoring state related to the nozzle extrusion;

[0012] quantifying the monitoring value into a specific monitoring state score, and calculating, according to the specific monitoring state score, the nozzle flowability index for evaluating the extrusion smoothness of the nozzle of the extrusion head.

[0013] Optionally, the calculating, based on the nozzle flowability index and the monitoring data, of a printing fluidity index combining nozzle flowability and extrusion material flow characteristics comprises:

[0014] determining an ideal monitoring data value corresponding to a material characteristic coefficient, a material viscosity and a material optimal processing of the extrusion material;

[0015] calculating, according to the material characteristic coefficient, the material viscosity, the ideal monitoring data value, the nozzle flowability index and the monitoring data, the printing fluidity index combining nozzle flowability and extrusion material flow characteristics.

[0016] Optionally, the optimizing, according to the printing fluidity index, of the current extrusion volumetric flow rate comprises:

[0017] correcting the current extrusion volumetric flow rate by using the printing fluidity index to obtain a correction coefficient;

[0018] optimizing the current extrusion volumetric flow rate according to the correction coefficient to obtain an optimized extrusion volumetric flow rate based on material characteristics and the current operating state.

[0019] Yet another embodiment of the present application provides an extrusion volumetric flow rate optimization system of a printer, the system comprising:

[0020] a monitoring module configured to monitor the operating state of the extrusion head of the printer in real time during printing and obtain corresponding monitoring data, wherein the monitoring data at least includes temperature data and pressure data;

[0021] a first calculation module configured to calculate, according to the monitoring data, a nozzle flowability index for evaluating the extrusion smoothness of the nozzle of the extrusion head;

[0022] a second calculation module configured to calculate, based on the nozzle flowability index and the monitoring data, a printing fluidity index combining nozzle flowability and extrusion material flow characteristics;

[0023] an optimization module configured to optimize, according to the printing fluidity index, the current extrusion volumetric flow rate.

[0024] Yet another embodiment of the present application provides a storage medium having a computer program stored therein, wherein the computer program is configured to execute the method described in any of the above embodiments when run.

[0025] Yet another embodiment of the present application provides an electronic device comprising a memory having a computer program stored therein and a processor configured to execute the computer program to perform the method described in any of the above embodiments.

[0026] Compared with the prior art, the extrusion volume flow optimization method of the printer provided by the present application can monitor the running state of the extrusion head of the printer in real time during the printing process and obtain corresponding monitoring data, wherein the monitoring data at least includes temperature data and pressure data; according to the monitoring data, a nozzle flow index for evaluating the extrusion flow of the nozzle of the extrusion head is calculated; based on the nozzle flow index and the monitoring data, a printing flow index combining the nozzle flow and the flow characteristics of the extrusion material is calculated; and according to the printing flow index, the current extrusion volume flow is optimized, so that the printing flow index combining the nozzle flow and the flow characteristics of the material is calculated, and then the dynamic optimization of the current extrusion volume flow is realized, and the reliability and efficiency of 3D printing are improved. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 A hardware structure block diagram of a computer terminal of the extrusion volume flow optimization method of the printer provided by the embodiment of the present application is provided.

[0028] Figure 2 A flowchart of the extrusion volume flow optimization method of the printer provided by the embodiment of the present application is provided.

[0029] Figure 3 A structure diagram of the extrusion volume flow optimization system of the printer provided by the embodiment of the present application is provided. DETAILED DESCRIPTION

[0030] The embodiments described below with reference to the drawings are exemplary and are only used to explain the present application, and cannot be explained as a limitation of the present application.

[0031] The embodiment of the present application first provides an extrusion volume flow optimization method of a printer, which can be applied to an electronic device such as a computer terminal, specifically, a general computer, etc.

[0032] The following will be described in detail taking the running on the computer terminal as an example. Figure 1 A hardware structure block diagram of a computer terminal of the extrusion volume flow optimization method of the printer provided by the embodiment of the present application is provided. As shown in the figure, Figure 1As shown, the computer device includes a processor, a memory and a network interface connected through a system bus, wherein the memory can include a non-volatile storage medium and an internal memory.

[0033] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions which, when executed, can cause the processor to perform any one of the extrusion volume flow optimization methods of the printer.

[0034] The processor is used to provide computing and control capabilities to support the operation of the entire computer device.

[0035] The internal memory provides an environment for the execution of the computer program in the non-volatile storage medium, which, when executed by the processor, can cause the processor to perform any one of the extrusion volume flow optimization methods of the printer.

[0036] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand that, Figure 1 The structure shown in the figure is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0037] It should be understood that the processor can be a central processing unit (CPU), and the processor can also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0038] Referring to Figure 2 The embodiments of the present application provide an extrusion volume flow optimization method of a printer, which can include the following steps:

[0039] S201, the running state of the extrusion head of the printer in the printing process is monitored in real time, and corresponding monitoring data is obtained, wherein the monitoring data at least includes temperature data and pressure data;

[0040] In the 3D printing process, real-time monitoring of the operating state of the printer extrusion head is an important step to ensure printing quality and efficiency. Specifically, the monitoring data should at least include temperature data and pressure data, and should also cover other related parameters such as material feeding speed, nozzle vibration, ambient temperature and humidity, etc. These monitoring data jointly affect the flow characteristics of the material and the working state of the nozzle. Temperature data can reflect the melting state of the material in real time, ensuring that the material is extruded within the appropriate temperature range to prevent material performance damage caused by overheating or overcooling. Pressure data provides information on the flow state of the material in the nozzle, and excessive pressure can cause nozzle blockage, while low pressure can affect the uniform supply of material. In addition, the feeding speed of the material determines the flow rate of the material from the hopper to the nozzle, and the vibration of the nozzle can affect the uniformity and interlayer adhesion of the material. Other environmental parameters (such as temperature and humidity) also affect the flowability of the material and the printing effect. Therefore, comprehensive consideration of these multi-dimensional monitoring data helps to fully understand the working state of the extrusion head, thereby optimizing the current extrusion volume flow.

[0041] Specifically, in order to achieve comprehensive monitoring of the printer extrusion head, first, various types of sensors need to be installed in the extrusion head and related components. Specifically, temperature sensors and pressure sensors are essential, the former can use thermocouples or thermal resistance type sensors, and the latter can use piezoelectric or resistance type sensors. In addition, flow sensors should also be considered at the material feeding port and nozzle to monitor the feeding speed of the material in real time; vibration sensors should be provided around the nozzle to evaluate the working state and vibration characteristics of the nozzle; in addition, ambient temperature and humidity sensors can also provide data on the influence of external conditions on the flowability of the material and the printing effect.

[0042] The core of the monitoring system is the data acquisition and analysis module. The data acquisition module needs to record and store the temperature, pressure, flow and vibration data provided by various sensors in real time. To ensure the accuracy and real-time nature of the data, a high-frequency acquisition scheme can be set, that is, multiple data are collected per second, and the data are preprocessed to eliminate noise and outliers. The data analysis module is responsible for real-time analysis of the multi-dimensional data collected, compares with the set threshold, and generates corresponding alarm signals or feedback information. In the data processing process, machine learning or algorithm models can be used to identify patterns, such as the best flow state of the material and the printing conditions.

[0043] Real-time monitoring of the operating status of the printer extrusion head and obtaining various monitoring data is of great significance. First of all, ensuring the printing quality has always been the core goal of 3D printing. By comprehensively monitoring key parameters, problems can be found and adjusted in time, thereby reducing printing defects and improving the qualified rate of finished products. Secondly, this diversified monitoring method helps to improve production efficiency by quickly responding to changes in material flow state, effectively reducing downtime. In addition, real-time monitoring data analysis can also support dynamic adjustment of the printing process, such as optimizing material supply rate and nozzle working temperature, thereby improving material utilization and reducing waste. At the same time, this monitoring system not only enhances the user's control of the printing process, but also provides instant feedback through a data visualization interface to help users make more reasonable printing settings and improve the overall printing experience.

[0044] S202, calculating a nozzle flow index for evaluating the extrusion smoothness of the nozzle of the extrusion head according to the monitoring data;

[0045] During the operation of the printer extrusion head, the flow of the nozzle is directly related to the printing quality and the smooth extrusion of the material. Therefore, by real-time monitoring of temperature data, pressure data and other related parameters, the nozzle flow index can be calculated. This index is achieved by evaluating specific monitoring states related to nozzle extrusion, with the purpose of quantifying the working efficiency and material flow of the nozzle in the actual printing process. Monitoring data provides the actual performance of the nozzle during operation, and the nozzle flow index converts these data into an easy-to-understand composite index, which is convenient for subsequent flow optimization and printing parameter adjustment.

[0046] Specifically, according to the monitoring data, the monitoring value of the specific monitoring state related to the nozzle extrusion can be determined;

[0047] In the first step, specific monitoring data needs to be extracted from the real-time monitoring system, and these data must be directly related to the extrusion state of the nozzle. Relevant monitoring states may include temperature, pressure, material supply rate, nozzle vibration, etc. The selection of monitoring values aims to ensure that all key parameters affecting the flow of the nozzle are covered. These values will be the basis for evaluating the performance of the nozzle. For example, the temperature of the nozzle may affect the flow of the material, and the pressure of the nozzle is directly related to whether the material can be smoothly extruded. By accurately determining these monitoring values, a solid foundation can be laid for subsequent quantitative scoring.

[0048] The significance of this process lies in ensuring that key data closely related to the performance of the nozzle is obtained. Accurate monitoring values can provide a reasonable starting point for subsequent flow evaluation, helping to identify problems related to flow and timely identify potential blockages or flow problems. This will provide data support for the performance optimization of the nozzle, thereby effectively improving the printing quality and efficiency.

[0049] quantifying the monitoring values into specific monitoring state scores, according to which a nozzle flowability index is calculated for assessing the extrusion flowability of the extrusion head nozzle.

[0050] In the second step, the monitoring values collected in the first step need to be quantified into specific scores, in order to assess the nozzle flowability more intuitively. This process usually involves setting up scoring criteria for each monitoring state, ensuring that each criterion can reflect the impact of the state on the nozzle performance. For example, if the nozzle temperature is within the set optimal range, it may score higher; while exceeding or falling below the range may deduct points. In theory, the quantified scores should consider the weights of different monitoring states, which reflect the importance of each monitoring value in the actual printing process. Finally, according to the quantified scores, the nozzle flowability index (NBI) is calculated by comprehensive calculation, which will be used to assess the flow performance of the nozzle. The higher the nozzle flowability index, the better the extrusion material flowability of the nozzle in the current state.

[0051] For example, suppose the material used is PLA (Polylactic Acid), and its ideal nozzle temperature range is 180°C to 220°C. Set the scoring criteria, that is, divide the scores according to the relative position of the nozzle temperature to the ideal temperature range. The following scoring criteria can be set:

[0052] Temperature between 180°C and 220°C: Score 10;

[0053] Temperature between 175°C and 180°C or 220°C and 225°C: Score 8;

[0054] Temperature between 170°C and 175°C or 225°C and 230°C: Score 6;

[0055] Temperature between 165°C and 170°C or 230°C and 235°C: Score 4;

[0056] Temperature below 165°C or above 235°C: Score 0.

[0057] Other monitoring state scores can be set with corresponding criteria in this way. The implementation of this step provides a quantitative evaluation tool for nozzle flowability, making the evaluation of nozzle performance no longer dependent on subjective judgment, but based on data. This quantitative index can help users quickly identify and adjust possible flow problems in actual operation, thereby improving the quality and efficiency of printing. In addition, by continuously monitoring the changes in the nozzle flowability index, important reference data can also be provided for the maintenance and optimization of the printer.

[0058] For example, a nozzle flowability index can be:

[0059]

[0060] Through this formula design, multiple monitoring data that affect the nozzle flow state can be combined into a comprehensive index, facilitating rapid evaluation of nozzle performance. This weighted sum form allows different monitoring parameters to have different influence weights in the calculation, reflecting their different degrees of influence in the actual printing process, thereby providing a scientific basis for subsequent optimization and adjustment.

[0061] wherein the is the nozzle flowability index, which is the final flowability evaluation result, reflecting the comprehensive performance of the nozzle working state and material flow condition, achieved through weighted summation. The is the specific monitoring state score of the i-th specific monitoring state, which reflects the score corresponding to the specific monitoring value (such as temperature, pressure, etc.) related to nozzle flowability, representing the actual performance of the nozzle under specific conditions. The is the weight factor of the i-th specific monitoring state, and the n is the number of specific monitoring states.

[0062] The main significance of calculating the nozzle flowability index is to improve the control ability of the printing process. Through quantitative evaluation of nozzle flowability, potential blockage or poor flow problems can be found in time, so that appropriate measures can be taken to optimize the extrusion process. This not only helps to ensure the printing quality, but also improves the production efficiency and reduces the waste of materials. In addition, the calculation of the nozzle flowability index also lays the foundation for the calculation of the subsequent printing flowability index, making the entire optimization process more scientific and systematic, thereby providing data support for achieving high-quality 3D printing.

[0063] S203, based on the nozzle flowability index and the monitoring data, calculating a printing flowability index combining nozzle flowability and extrusion material flow characteristics;

[0064] This step of calculation not only considers the working state of the nozzle, but also combines the characteristics and flow of the extrusion material to more comprehensively evaluate the material flowability in the printing process. First, the material characteristic coefficient, material viscosity, and ideal monitoring data value corresponding to the best processing condition of the extrusion material are determined. These parameters are crucial for understanding the performance of the material under the current working conditions. Next, the nozzle flowability index is combined with these material characteristics to form a printing flowability index, which provides a scientific basis for optimizing the extrusion volume flow.

[0065] Specifically, the material characteristic coefficient, material viscosity, and ideal monitoring data value corresponding to the best processing of the extrusion material can be determined.

[0066] In this step, the first requirement is to obtain the material property coefficients and viscosity through experiments or literature. These parameters are crucial for understanding the material's behavior during the extrusion process. Material property coefficients are usually related to the material's physical properties, chemical composition, and flow behavior, while viscosity is an important indicator of the material's flow resistance. Next, the ideal monitoring data value refers to the value that the material should achieve under optimal processing conditions. These ideal values serve as a benchmark for subsequent printing flowability index calculations and can be set beforehand. This step ensures that the material properties and state used are compatible with the actual printing process.

[0067] The specific role of determining material property coefficients, viscosity, and ideal monitoring data values is to provide the basis data for the calculation of the printing flowability index. These parameters can help adjust the extrusion conditions so that the material is processed in the best state, thereby improving the printing quality and efficiency. By accurately grasping these key parameters, changes in the material during the extrusion process can be detected in a timely manner, effectively preventing problems such as blockage and poor flow. In addition, the scientific nature and data-driven nature of this process provide the necessary basis for subsequent flow optimization, ensuring that the final output of the printing effect meets expectations.

[0068] Based on the material property coefficients, the material viscosity, the ideal monitoring data value, the nozzle flowability index, and the monitoring data, a printing flowability index is calculated that combines the nozzle flowability and the flow characteristics of the extruded material.

[0069] The core of this step is to combine the obtained material properties with the nozzle flowability index and other monitoring data to form a comprehensive printing flowability index (PFI). These data are calculated through a formula that combines material property coefficients with material viscosity, nozzle flowability, and ideal monitoring data values for comparison, ultimately generating a quantitative flowability index. The purpose of this is to establish a clear link between the performance of the nozzle and the flow characteristics of the material used, allowing for quick assessment of the impact of current conditions on the printing process in actual operation and dynamic adjustment of extrusion parameters.

[0070] By calculating the printing flowability index, the adaptability and stability of material flow under specific printing conditions can be effectively identified. This index calculation provides real-time feedback for the actual printing process, ensuring that the extrusion process runs in the best state and reducing the risk of printing failure. At the same time, this dynamic evaluation mechanism enables the printer to maintain high production efficiency under different materials and different environments, reducing failures caused by material property mismatches, and further promoting the application range and industrialization process of 3D printing technology.

[0071] For example, a printing flowability index can be:

[0072]

[0073] wherein the is the print flowability index, which measures the flowability of the material under current printing conditions. The higher the PFI, the better the material's flowability under current conditions, making it suitable for high-quality printing. The is the material characteristic coefficient, which reflects the basic flow characteristics of the material, usually measured by experiments. The value of k directly affects the size of PFI, and the higher the material characteristic coefficient, the better the flowability of the material. The is the material viscosity, which is a physical quantity that describes the flow resistance of the material. The higher the viscosity, the worse the flowability of the material, and the lower the PFI. mu plays a role in offsetting the flowability in the formula, ensuring that the calculation of the flowability index accurately reflects the actual situation. The is the data of the jth monitoring parameter, which is collected during real-time monitoring of various parameters such as temperature, pressure, etc., and is directly related to the flow performance of the material. Changes in each monitoring parameter will affect the overall flowability assessment. The is the ideal monitoring data value corresponding to the jth monitoring parameter. By comparing the ideal value, the degree of deviation from the current condition can be evaluated. The ideal monitoring data value provides a reference point to help determine the adaptability of the material flow. The m is the number of monitoring parameters.

[0074] wherein the numerator part : The numerator part contains the product of the material characteristic coefficient (k) and the nozzle flowability index (NBI), reflecting the combined influence of the material's intrinsic flow ability and the nozzle's working state on the extrusion flow. By multiplying, it emphasizes that when the material is optimized and the nozzle performance is good, the flowability performance will be better. This part ensures that the defined flowability index can be dynamically adjusted according to the specific material and nozzle characteristics.

[0075] The denominator part mu: The viscosity mu of the material appears in the denominator, directly affecting the size of PFI. The viscosity is taken as the denominator in order to punish materials with high viscosity. The higher the viscosity, the worse the flowability of the material, which helps to reflect the flow resistance of the material under actual printing conditions. This design makes PFI more accurately reflect the changes in flow performance.

[0076] The exponential part : This part is designed to quantify the deviation of different monitoring parameters from the ideal state and calculate a penalty factor. By introducing the exponential function, especially in the form of negative exponent, PFI can be quickly reduced when the parameter deviates from the ideal value. This design aims to reflect the importance of deviating from the ideal state (such as temperature, pressure, etc.) in the actual printing process, ensuring that the flowability index accurately reflects the decline in flowability when these conditions are not ideal.

[0077] The main significance of calculating the printing fluidity index is that it provides a quantitative basis for adjusting and optimizing the extrusion process. By combining nozzle fluidity and material properties, it can more accurately assess the fluidity problems that may be encountered in actual printing and make timely adjustments. This comprehensive approach not only improves print quality but also reduces material waste, reduces failure rates, and ensures more efficient production processes. This index improves the adaptability of the printer to different materials and conditions, making it more flexible to meet various printing needs.

[0078] S204, optimizing the current extrusion volumetric flow according to the printing fluidity index.

[0079] Optimizing the current extrusion volumetric flow according to the printing fluidity index (PFI) is to ensure that the material fluidity in the printing process remains at the best state. The printing fluidity index considers the nozzle fluidity, material properties, and deviation of actual monitoring data, allowing the operator to accurately assess whether the current extrusion volumetric flow is suitable for the material's flow characteristics. Through real-time monitoring of PFI, a practical adjustment basis for extrusion volumetric flow can be provided. When PFI indicates that the current extrusion state is not ideal, the operator can adjust the extrusion volumetric flow to match the material properties and nozzle state. This process aims to improve print quality and reduce the occurrence of clogging and poor flow.

[0080] Specifically, the printing fluidity index can be used to correct the current extrusion volumetric flow to obtain a correction factor (FAI).

[0081] By using the printing fluidity index (PFI) to correct the current extrusion volumetric flow, the value of PFI is mapped to a correction factor (FAI), which is used to adjust the current extrusion volume. The value of PFI reflects the fluidity of the material under current conditions. If the PFI value is low, it indicates that the current fluidity is poor, which may lead to insufficient extrusion volume, and the extrusion volumetric flow needs to be increased through correction. Conversely, if PFI is high, it may mean that the fluidity is good and the extrusion volume is excessive. Through this correction process, precise adjustment of the extrusion volumetric flow can be achieved to adapt to real-time printing conditions.

[0082] The importance of this modification step lies in its provision of a dynamic adaptation mechanism, enabling the printer to self-adjust based on real-time feedback. This process not only enhances print quality but also reduces error rates and material waste. Through the introduction of the modification coefficient, operators can flexibly adjust the extrusion volume under different materials and printing conditions, ensuring the stability and consistency of the printing process. This intelligent modification strategy provides strong support for the application of modern 3D printing technology, further improving the production efficiency and flexibility of the industry.

[0083] In specific implementation, the printer software will collect monitoring data in real time during the printing process and calculate the printing fluidity index (PFI). According to the numerical range of PFI, the system will set the corresponding modification coefficient (FAI), such as setting a linear relationship or a nonlinear relationship, in order to map the changes of PFI to FAI. Subsequently, the operator can quickly adjust the current extrusion volume flow according to the generated FAI, thereby optimizing the printing effect. In this process, multiple adjustment parameters can be preset according to different material properties and printing requirements to achieve more flexible adjustment.

[0084] According to the modification coefficient, the current extrusion volume flow is optimized to obtain an optimized extrusion volume flow based on material properties and current operating state.

[0085] This step is achieved by applying the modification coefficient (FAI) obtained in the first step to the current extrusion volume flow (Q_current), thereby calculating a new, optimized extrusion volume flow (Q_new). The core of this optimization process is to adjust the current flow to better match the material properties and the real working state of the nozzle. Through the introduction of the modification coefficient FAI, the extrusion volume can be flexibly adjusted, so that the fluidity of the material during extrusion is improved, ultimately achieving higher quality printing results.

[0086] The significance of this optimization step lies in ensuring that the extrusion volume can adapt to various changing factors such as material properties, environmental conditions, and equipment state in real time during the printing process. Through intelligent optimization mechanisms, printing defects caused by the inappropriateness of the set extrusion volume flow to the current state are avoided, thereby improving the quality stability of the finished product. This method can also reduce material waste, lower production costs, and further improve overall production efficiency and benefits.

[0087] In practical applications, the printer control system will generate an optimized extrusion volume flow (Q_new) based on the correction factor (FAI) calculated in the previous step and the current extrusion volume flow (Q_current) using a pre-defined algorithm. This algorithm can be linear or non-linear, dynamically calculating the optimal flow setting based on the current printing state. Finally, the optimized extrusion volume flow will be fed back to the printer's operating system to adjust the actual power and speed of the extrusion head, ensuring the stability and quality of the printing process.

[0088] For example, a correction factor and an optimized extrusion volume flow can be:

[0089]

[0090]

[0091] The formula forms a correction factor FAI by reversing the printing fluidity index PFI (the higher the value, the better the fluidity) and multiplying it by an adjustment parameter alpha. The purpose of this formula is to directly convert the feedback of the fluidity index into an operational correction amount, so that it can effectively affect the current extrusion volume flow.

[0092] The formula adds a correction amount to the current extrusion volume flow (Q_current) to calculate the optimized extrusion volume flow (Q_new). In this way, the extrusion amount can be dynamically adjusted to adapt to changes in material properties and operating conditions.

[0093] wherein the is a correction factor used to adjust the current extrusion volume flow to adapt to real-time printing conditions. The larger the FAI value, the more correction is needed. The is the optimized extrusion volume flow, the is the current extrusion volume flow, the , the is the corresponding adjustment parameter. By adjusting the value of , the strength of the correction can be adjusted to meet the needs of different materials and printing conditions; by adjusting , the change range of the final flow can be affected to adapt to different printing environments and material properties.

[0094] Through the optimization step, the printer can dynamically adjust the extrusion volume flow according to real-time data and liquidity index, so as to achieve higher printing efficiency and quality. This optimization method based on the liquidity index provides an intelligent control means for the printing process, reducing the complexity of manual adjustment. This can ensure the stability of the material during the extrusion process, minimize the failure rate, and improve the quality and consistency of the finished product. In addition, the optimized extrusion volume flow can effectively reduce the waste of materials, thereby reducing production costs and improving resource utilization.

[0095] It can be seen that the running state of the printer extrusion head in the printing process is monitored in real time, and corresponding monitoring data is obtained, wherein the monitoring data at least includes temperature data and pressure data;According to the monitoring data, a nozzle fluidity index for evaluating the extrusion fluidity of the nozzle of the extrusion head is calculated;Based on the nozzle fluidity index and the monitoring data, a printing liquidity index combining nozzle fluidity and extrusion material flow characteristics is calculated;According to the printing liquidity index, the current extrusion volume flow is optimized, so that the printing liquidity index combining nozzle fluidity and material flow characteristics is calculated, and the dynamic optimization of the current extrusion volume flow is realized, and the reliability and efficiency of 3D printing are improved.

[0096] Another embodiment of the application provides an extrusion volume flow optimization system of a printer, referring to Figure 3 , the system can include:

[0097] The monitoring module 301 is used for monitoring the running state of the printer extrusion head in the printing process in real time, and obtaining corresponding monitoring data, wherein the monitoring data at least includes temperature data and pressure data;

[0098] The first calculation module 302 is used for calculating the nozzle fluidity index for evaluating the extrusion fluidity of the nozzle of the extrusion head according to the monitoring data;

[0099] The second calculation module 303 is used for calculating the printing liquidity index combining nozzle fluidity and extrusion material flow characteristics based on the nozzle fluidity index and the monitoring data;

[0100] The optimization module 304 is used for optimizing the current extrusion volume flow according to the printing liquidity index.

[0101] It can be seen that the running state of the printer extrusion head in the printing process is monitored in real time, and corresponding monitoring data is obtained, wherein the monitoring data at least includes temperature data and pressure data; a nozzle flow index for evaluating the extrusion flow degree of the nozzle of the extrusion head is calculated according to the monitoring data; a printing flow index combining nozzle flow and material flow characteristics is calculated based on the nozzle flow index and the monitoring data; and the current extrusion volume flow is optimized according to the printing flow index, so that the printing flow index combining nozzle flow and material flow characteristics is calculated, and then the dynamic optimization of the current extrusion volume flow is realized, thereby improving the reliability and efficiency of 3D printing.

[0102] The embodiment of the present application also provides a storage medium, wherein the storage medium stores a computer program, and the computer program is arranged to execute the steps in any of the method embodiments.

[0103] Specifically, in the embodiment, the storage medium can be arranged to store a computer program for executing the following steps:

[0104] S201, the running state of the printer extrusion head in the printing process is monitored in real time, and corresponding monitoring data is obtained, wherein the monitoring data at least includes temperature data and pressure data;

[0105] S202, a nozzle flow index for evaluating the extrusion flow degree of the nozzle of the extrusion head is calculated according to the monitoring data;

[0106] S203, a printing flow index combining nozzle flow and material flow characteristics is calculated based on the nozzle flow index and the monitoring data;

[0107] S204, the current extrusion volume flow is optimized according to the printing flow index.

[0108] It can be seen that the running state of the printer extrusion head in the printing process is monitored in real time, and corresponding monitoring data is obtained, wherein the monitoring data at least includes temperature data and pressure data; a nozzle flow index for evaluating the extrusion flow degree of the nozzle of the extrusion head is calculated according to the monitoring data; a printing flow index combining nozzle flow and material flow characteristics is calculated based on the nozzle flow index and the monitoring data; and the current extrusion volume flow is optimized according to the printing flow index, so that the printing flow index combining nozzle flow and material flow characteristics is calculated, and then the dynamic optimization of the current extrusion volume flow is realized, thereby improving the reliability and efficiency of 3D printing.

[0109] The embodiment of the present application also provides an electronic device comprising a memory and a processor, the memory storing a computer program, and the processor is configured to run the computer program to execute the steps in any of the above method embodiments.

[0110] Specifically, the electronic device can further comprise a transmission device connected with the processor and an input / output device connected with the processor.

[0111] Specifically, in the embodiment, the processor can be configured to execute the following steps through the computer program:

[0112] S201, real-time monitoring of the running state of the printer extrusion head in the printing process is performed, and corresponding monitoring data is obtained, wherein the monitoring data at least includes temperature data and pressure data;

[0113] S202, a nozzle flow index for evaluating the extrusion fluency of the nozzle of the extrusion head is calculated according to the monitoring data;

[0114] S203, a printing fluidity index combining the nozzle fluency and the flow characteristics of the extrusion material is calculated based on the nozzle flow index and the monitoring data;

[0115] S204, the current extrusion volume flow is optimized according to the printing fluidity index.

[0116] It can be seen that the running state of the printer extrusion head in the printing process is real-time monitored, and corresponding monitoring data is obtained, wherein the monitoring data at least includes temperature data and pressure data; a nozzle flow index for evaluating the extrusion fluency of the nozzle of the extrusion head is calculated according to the monitoring data; a printing fluidity index combining the nozzle fluency and the flow characteristics of the extrusion material is calculated based on the nozzle flow index and the monitoring data; and the current extrusion volume flow is optimized according to the printing fluidity index, so that the printing fluidity index combining the nozzle fluency and the flow characteristics of the material is calculated, and the dynamic optimization of the current extrusion volume flow is realized, thereby improving the reliability and efficiency of 3D printing.

[0117] The above embodiments according to the drawings illustrate the structure, features and effects of the present application, and the above description is only the preferred embodiment of the present application, but the present application is not limited by the drawings, any change or modification made according to the concept of the present application, or the equivalent embodiment with equivalent changes, still within the scope of the present application.

Claims

1. A method of extrusion volumetric flow optimization of a printer, characterized in that, The method comprises: real-time monitoring of the running state of the printer extrusion head in the printing process, and obtaining corresponding monitoring data, wherein the monitoring data at least includes temperature data and pressure data; calculating a nozzle flow index for evaluating the extrusion smoothness of the nozzle of the extrusion head according to the monitoring data; wherein the monitoring value of a specific monitoring state related to nozzle extrusion is determined according to the monitoring data; the monitoring value is quantified as a specific monitoring state score, and the nozzle flow index for evaluating the extrusion smoothness of the nozzle of the extrusion head is calculated according to the specific monitoring state score; calculating a printing flow index combining nozzle flow and extrusion material flow characteristics based on the nozzle flow index and the monitoring data; wherein the material characteristic coefficient, material viscosity, and ideal monitoring data value corresponding to the best processing of the extrusion material are determined; the printing flow index combining nozzle flow and extrusion material flow characteristics is calculated according to the material characteristic coefficient, the material viscosity, the ideal monitoring data value, the nozzle flow index, and the monitoring data; optimizing the current extrusion volume flow according to the printing flow index, wherein the printing flow index is used to correct the current extrusion volume flow to obtain a correction coefficient; the current extrusion volume flow is optimized according to the correction coefficient to obtain an optimized extrusion volume flow based on material characteristics and the current running state.

2. An extrusion volumetric flow optimization system for a printer, characterized by, The system comprises: a monitoring module for real-time monitoring of the running state of the printer extrusion head in the printing process, and obtaining corresponding monitoring data, wherein the monitoring data at least includes temperature data and pressure data; a first calculation module for calculating a nozzle flow index for evaluating the extrusion smoothness of the nozzle of the extrusion head according to the monitoring data; wherein the first calculation module is specifically configured to determine the monitoring value of a specific monitoring state related to nozzle extrusion according to the monitoring data; the monitoring value is quantified as a specific monitoring state score, and the nozzle flow index for evaluating the extrusion smoothness of the nozzle of the extrusion head is calculated according to the specific monitoring state score; a second calculation module for calculating a printing flow index combining nozzle flow and extrusion material flow characteristics based on the nozzle flow index and the monitoring data; wherein the second calculation module is specifically configured to determine the material characteristic coefficient, material viscosity, and ideal monitoring data value corresponding to the best processing of the extrusion material; and calculate the printing flow index combining nozzle flow and extrusion material flow characteristics according to the material characteristic coefficient, the material viscosity, the ideal monitoring data value, the nozzle flow index, and the monitoring data; an optimization module for optimizing the current extrusion volume flow according to the printing flow index, wherein the optimization module is specifically configured to use the printing flow index to correct the current extrusion volume flow to obtain a correction coefficient; and optimize the current extrusion volume flow according to the correction coefficient to obtain an optimized extrusion volume flow based on material characteristics and the current running state.

3. A storage medium, characterized by The storage medium stores a computer program, and the computer program is configured to execute the method in claim 1 when running.

4. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method in claim 1 by running the computer program.

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