Method and system for optimizing extrusion volume flow rate of printer

Abstract

The invention discloses an extrusion volume flow optimization method and system for a printer, and the method comprises the steps: monitoring the operation state of an extrusion head of the printer in the printing process in real time, and obtaining corresponding monitoring data which at least comprises temperature data and pressure data; according to the monitoring data, a nozzle fluency index used for evaluating the extrusion fluency degree of the extrusion head nozzle is calculated; based on the nozzle fluency index and the monitoring data, calculating a printing fluidity index combining nozzle fluency and extrusion material flow characteristics; and optimizing the current extrusion volume flow according to the printing fluidity index. By means of the 3D printing method and device, the printing fluidity index combining the nozzle fluency and the material flow characteristic can be calculated, then dynamic optimization of the current extrusion volume flow is achieved, and the reliability and efficiency of 3D printing are improved.

Description

Technical Field

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

[0002] With the rapid development of 3D printing technology, its application prospects in manufacturing, medical, construction, aerospace and other fields are becoming more and more extensive. However, the optimization of extrusion volume flow in the 3D printing process is still one of the important challenges to ensure printing quality and efficiency. In the 3D printing process, the performance of the extruder has a direct impact on the final printing quality. The stability and accuracy of the extrusion volume flow rate are directly related to the uniformity of the printed material, the interlayer bonding strength and the surface quality of the finished product. If the extrusion volume flow rate is too low, it will lead to insufficient printing materials and cause printing defects; if the extrusion flow rate is too high, it may cause problems such as material overflow and model deformation. In addition, changes in temperature and pressure during the printing process will also affect the flow characteristics of the material, thereby negatively affecting the extrusion volume flow rate. In the prior art, although some methods have attempted to optimize the extrusion volume flow rate by adjusting the heating temperature of the extruder head or modifying the feeding speed, these methods often have problems with response lag and lack of real-time performance, and cannot effectively respond to instantaneous changes. Summary of the invention

[0003] The purpose of the present invention is to provide a method and system for optimizing the extrusion volume flow of a printer to address the deficiencies in the prior art. The method and system can calculate a printing fluidity index that combines nozzle fluidity and material flow characteristics, thereby achieving dynamic optimization of the current extrusion volume flow and improving the reliability and efficiency of 3D printing.

[0004] One embodiment of the present application provides a method for optimizing the extrusion volume flow rate of a printer, the method comprising: Performing real-time monitoring of the operating state of the printer extruder during the printing process and acquiring corresponding monitoring data, wherein the monitoring data at least includes: temperature data and pressure data; Calculating a nozzle smoothness index for evaluating the smoothness of extrusion from an extrusion head nozzle according to the monitoring data; Calculating a printing fluidity index combining nozzle fluidity and extrusion material flow characteristics based on the nozzle fluidity index and the monitoring data; According to the printing fluidity index, the current extrusion volume flow rate is optimized.

[0005] Optionally, the calculating, based on the monitoring data, a nozzle fluency index for evaluating the extrusion fluency of the extrusion head nozzle includes: Determining a monitoring value of a specific monitoring state related to nozzle extrusion based on the monitoring data; The monitoring value is quantified into a specific monitoring state score, and a nozzle smoothness index for evaluating the extrusion smoothness of an extrusion head nozzle is calculated according to the specific monitoring state score.

[0006] Optionally, the calculating, based on the nozzle fluency index and the monitoring data, a printing fluidity index combining nozzle fluency and flow characteristics of the extruded material comprises: Determine the ideal monitoring data values ​​corresponding to the material property coefficients, material viscosity, and optimal material processing of the extruded material; A printing fluidity index combining nozzle fluidity and extrusion material flow characteristics is calculated based on the material property coefficient, the material viscosity, the ideal monitoring data value, the nozzle fluidity index and the monitoring data.

[0007] Optionally, optimizing the current extrusion volume flow rate according to the printing fluidity index includes: Using the printing fluidity index, correcting the current extrusion volume flow rate to obtain a correction coefficient; The current extrusion volume flow rate is optimized according to the correction coefficient to obtain an optimized extrusion volume flow rate based on material properties and the current operating state.

[0008] Another embodiment of the present application provides an extrusion volume flow optimization system for a printer, the system comprising: A monitoring module, used to monitor the operating status of the printer extruder in real time during the printing process and obtain corresponding monitoring data, wherein the monitoring data at least includes: temperature data and pressure data; A first calculation module, used for calculating a nozzle smoothness index for evaluating the extrusion smoothness of an extrusion head nozzle according to the monitoring data; A second calculation module, for calculating a printing fluidity index combining nozzle fluidity and flow characteristics of extruded material based on the nozzle fluidity index and the monitoring data; The optimization module is used to optimize the current extrusion volume flow rate according to the printing fluidity index.

[0009] Yet another embodiment of the present application provides a storage medium, wherein the storage medium stores a computer program, wherein the computer program is configured to execute any of the above methods when running.

[0010] Yet another embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute any of the methods described above.

[0011] Compared with the prior art, the present invention provides a method for optimizing the extrusion volume flow of a printer, which monitors the operating status of the printer extruder head in real time during the printing process and obtains corresponding monitoring data, wherein the monitoring data at least includes: temperature data and pressure data; based on the monitoring data, a nozzle fluency index for evaluating the extrusion smoothness of the extrusion head nozzle is calculated; based on the nozzle fluency index and the monitoring data, a printing fluidity index combining the nozzle fluency and the flow characteristics of the extruded material is calculated; based on the printing fluidity index, the current extrusion volume flow is optimized, so that by calculating the printing fluidity index combining the nozzle fluency and the material flow characteristics, the current extrusion volume flow can be dynamically optimized, thereby improving the reliability and efficiency of 3D printing. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 A hardware structure block diagram of a computer terminal for a method for optimizing the extrusion volume flow of a printer provided by an embodiment of the present invention; Figure 2 A schematic flow chart of a method for optimizing the extrusion volume flow rate of a printer provided by an embodiment of the present invention; Figure 3 A schematic structural diagram of an extrusion volume flow optimization system for a printer provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0013] The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, but should not be construed as limiting the present invention.

[0014] The embodiment of the present invention firstly provides a method for optimizing the extrusion volume flow of a printer. The method can be applied to electronic devices, such as computer terminals, specifically ordinary computers, etc.

[0015] The following describes it in detail by taking running on a computer terminal as an example. Figure 1 The hardware structure block diagram of a computer terminal of a method for optimizing the extrusion volume flow of a printer provided by an embodiment of the present invention is shown in FIG. Figure 1 As shown, the computer device includes a processor, a memory, and a network interface connected via a system bus, wherein the memory may include a non-volatile storage medium and an internal memory.

[0016] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions, and when the program instructions are executed, the processor can execute any one of the methods for optimizing the extrusion volume flow of a printer.

[0017] The processor is used to provide computing and control capabilities and support the operation of the entire computer equipment.

[0018] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any method for optimizing the extrusion volume flow of a printer.

[0019] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 1 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0020] It should be understood that the processor may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0021] See also Figure 2 , an embodiment of the present invention provides a method for optimizing the extrusion volume flow of a printer, which may include the following steps: S201, monitoring the operating state of the printer extruder during the printing process in real time, and acquiring corresponding monitoring data, wherein the monitoring data at least includes: temperature data and pressure data; In the 3D printing process, real-time monitoring of the operating status of the printer extruder is an important part of ensuring 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. These monitoring data work together on the flow characteristics of the material and the working status of the nozzle. Temperature data can reflect the melting state of the material in real time, ensuring that the material is extruded within a suitable temperature range to prevent damage to the material performance caused by overheating or overcooling. Pressure data provides information on the flow state of the material in the nozzle. Too high pressure may cause nozzle blockage, while too low pressure may affect the uniform supply of the material. In addition, the material feeding speed determines the flow rate of the material from the hopper to the nozzle, while the vibration of the nozzle may affect the uniformity of the material and the interlayer adhesion. Other environmental parameters (such as temperature and humidity) will also affect the fluidity of the material and the printing effect. Therefore, comprehensive consideration of these multi-dimensional monitoring data will help to fully understand the working status of the extruder head, thereby optimizing the current extrusion volume flow rate.

[0022] Specifically, in order to achieve comprehensive monitoring of the printer extruder head, it is first necessary to install various types of sensors in the extruder head and related components. Specifically, temperature sensors and pressure sensors are indispensable. The former can use thermocouples or thermistor sensors, and the latter can use piezoelectric or resistive sensors. In addition, it should also be considered to install flow sensors at the material feed port and nozzle to monitor the material feeding speed in real time; equip vibration sensors around the nozzle to evaluate the working status and vibration characteristics of the nozzle; in addition, ambient temperature and humidity sensors can also provide data on the impact of external conditions on material fluidity and printing effects. The core of the monitoring system is the data acquisition and analysis module. The data acquisition module needs to record and store data such as temperature, pressure, flow, and vibration 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 up, that is, data is collected multiple times per second, and the data is pre-processed to remove noise and outliers. The data analysis module is responsible for real-time analysis of the collected multi-dimensional data, comparing it with the set threshold, and generating corresponding alarm signals or feedback information. During the data processing process, machine learning or algorithm models can be used to identify patterns, such as the optimal flow state and printing conditions of the material.

[0023] It is of great significance to monitor the operating status of the printer extruder in real time and obtain a variety of monitoring data. First of all, ensuring printing quality has always been the core goal of 3D printing. By comprehensively monitoring key parameters, problems can be discovered and adjusted in a timely manner, 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 the flow state of materials, it can effectively reduce downtime. In addition, real-time monitoring data analysis can also provide support for dynamic adjustments to the printing process, such as optimizing the material supply rate and the operating temperature of the nozzle, thereby improving material utilization and reducing waste. At the same time, this monitoring system can not only enhance the user's sense of control over the printing process, but also provide instant feedback through the data visualization interface, helping users make more reasonable print setting choices and improve the overall printing experience.

[0024] S202, calculating a nozzle fluency index for evaluating the extrusion fluency of an extruder nozzle according to the monitoring data; During the operation of the printer extruder, the fluency of the nozzle is directly related to the print quality and the smooth extrusion of the material. To this end, the nozzle fluency index can be calculated by real-time monitoring of temperature data, pressure data and other relevant parameters. This index is achieved by evaluating specific monitoring states related to nozzle extrusion, with the aim of quantifying the nozzle's working efficiency and material fluidity during the actual printing process. The monitoring data provides the actual performance of the nozzle during operation, and the nozzle fluency index converts this data into an easy-to-understand synthetic indicator for subsequent flow optimization and printing parameter adjustment.

[0025] Specifically, a monitoring value of a specific monitoring state related to nozzle extrusion may be determined based on the monitoring data; In the first step, specific monitoring data needs to be extracted from the real-time monitoring system, which must be directly related to the extrusion status of the nozzle. Relevant monitoring status may include temperature, pressure, material feed rate, nozzle vibration, etc. The selection of monitoring values ​​is intended to ensure that all key parameters that affect nozzle fluidity are covered. These values ​​will become the basic data for evaluating nozzle performance. For example, nozzle temperature may affect the fluidity of the material, while nozzle pressure is directly related to whether the material can be extruded smoothly. By accurately determining these monitoring values, a solid foundation can be laid for subsequent quantitative scoring.

[0026] The significance of this process is to ensure that key data closely related to nozzle performance is obtained. Accurate monitoring values ​​can provide a reasonable starting point for subsequent fluidity evaluation, help identify problems related to fluidity, and promptly discover potential blockages or flow problems. This will provide data support for nozzle performance optimization, thereby effectively improving printing quality and efficiency.

[0027] The monitoring value is quantified into a specific monitoring state score, and a nozzle smoothness index for evaluating the extrusion smoothness of an extrusion head nozzle is calculated according to the specific monitoring state score.

[0028] In the second step, the monitoring values ​​collected in the first step need to be quantified and converted into specific scores in order to more intuitively evaluate the fluidity of the nozzle. This process usually involves developing scoring criteria for each monitoring state to ensure that each criterion reflects 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 reduce the score. In theory, the quantitative score should take into account the weight of different monitoring states, which will reflect the importance of each monitoring value in the actual printing process. Finally, based on the quantitative score, the nozzle fluency index (NBI) is obtained through comprehensive calculation, which will be used to evaluate the flow performance of the nozzle. The higher the nozzle fluency index, the better the fluidity of the nozzle in extruding the material in the current state.

[0029] 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. You can set the following scoring criteria: Temperature between 180°C and 220°C: score 10; Temperature between 175°C and 180°C or 220°C and 225°C: score 8; Temperature between 170°C and 175°C or 225°C and 230°C: score 6; Temperature between 165°C and 170°C or 230°C and 235°C: score 4; Temperature below 165°C or above 235°C**: Score 0.

[0030] The corresponding standards for other monitoring status scores can be set in the same way. The implementation of this step provides a quantitative evaluation tool for nozzle fluency, so that the evaluation of nozzle performance no longer relies on subjective judgment, but is based on data. This quantitative index can help users quickly identify and adjust possible flow problems in actual operations, thereby improving the quality and efficiency of printing. In addition, by continuously monitoring the changes in the nozzle fluency index, it can also provide important reference data for printer maintenance and optimization.

[0031] For example, a nozzle fluency index could be:

[0032] Through this formula design, multiple monitoring data that affect the nozzle flow state can be combined into a comprehensive index, which is convenient for quickly evaluating the performance of the nozzle. This weighted sum form allows different monitoring parameters to have different influence weights in the calculation, reflecting the different degrees of influence they may bring in the actual printing process, thereby providing a scientific basis for subsequent optimization and adjustment.

[0033] Among them, the The nozzle fluency index is the final fluency evaluation result, which reflects the comprehensive performance of the nozzle working state and material flow, and is achieved through weighted summation. The specific monitoring state score of the i-th specific monitoring state reflects the score corresponding to the specific monitoring value (such as temperature, pressure, etc.) related to the nozzle fluency, and represents the actual performance of the nozzle under specific conditions. is the weight factor of the i-th specific monitoring state, and n is the number of specific monitoring states.

[0034] The main significance of calculating the nozzle fluency index is to improve the control ability of the printing process. Through the quantitative evaluation of nozzle fluency, potential blockages or poor flow problems can be discovered in time, so that corresponding measures can be taken to optimize the extrusion process. This not only helps to ensure printing quality, but also improves production efficiency and reduces material waste. In addition, the calculation of the nozzle fluency index also lays the foundation for the subsequent calculation of the printing fluidity index, making the entire optimization process more scientific and systematic, thereby providing data support for achieving high-quality 3D printing.

[0035] S203, calculating a printing fluidity index combining nozzle fluidity and flow characteristics of extruded material based on the nozzle fluidity index and the monitoring data; The calculation of this step not only takes into account the working status of the nozzle, but also combines the characteristics and flow of the extruded material to more comprehensively evaluate the material fluidity during printing. First, the material property coefficients of the extruded material, the material viscosity, and the ideal monitoring data values ​​corresponding to the material under optimal processing conditions are determined. These parameters are crucial to understanding the performance of the material under current working conditions. Next, the nozzle fluency index is combined with these material characteristics to form a printing fluidity index, which provides a scientific basis for optimizing the extrusion volume flow rate.

[0036] Specifically, the material property coefficient of the extruded material, the material viscosity, and the ideal monitoring data values ​​corresponding to the optimal processing of the material can be determined; In this step, you first need to obtain the characteristic coefficients and viscosity of the materials used through experiments or literature. These parameters are crucial to understanding the performance of the material during the extrusion process. The material characteristic coefficients are usually related to the physical properties, chemical composition and flow behavior of the material, while viscosity is an important indicator to describe the flow resistance of the material. Next, the ideal monitoring data value refers to the monitoring parameter value that the material should reach under the optimal processing conditions. These ideal values ​​provide a benchmark for the subsequent calculation of the printing fluidity index and can be set in advance. This step ensures that the characteristics and state of the materials used are compatible with the actual printing process.

[0037] The specific role of determining the material characteristic coefficient, viscosity and ideal monitoring data value is that it provides basic data for the calculation of the printing fluidity index. These parameters can help adjust the extrusion conditions so that the material can be 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 discovered in time, thereby effectively preventing problems such as blockage and poor flow. In addition, the scientific and data-driven nature of this process provides the necessary basis for subsequent flow optimization, ensuring that the final output printing effect meets expectations.

[0038] A printing fluidity index combining nozzle fluidity and extrusion material flow characteristics is calculated based on the material property coefficient, the material viscosity, the ideal monitoring data value, the nozzle fluidity index and the monitoring data.

[0039] The core of this step is to combine the obtained material properties with the nozzle fluidity index and other monitoring data to form a comprehensive printing fluidity index (PFI). These data are calculated by formula, combining the material property coefficient with the material viscosity, nozzle fluidity and the ideal monitoring data value compared with it, and finally generating a quantitative fluidity index. The purpose of this is to form a clear connection between the working performance of the nozzle and the flow characteristics of the material used, so that in actual operation, the impact of current conditions on the printing process can be quickly evaluated and the extrusion parameters can be dynamically adjusted.

[0040] By calculating the printing fluidity index, the adaptability and stability of material flow under specific printing conditions can be effectively identified. The calculation of this index 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, reduce failures caused by mismatched material properties, and further promote the application scope and industrialization process of 3D printing technology.

[0041] For example, a printing fluidity index could be:

[0042] Among them, the The PFI is the print fluidity index, which is used to measure the fluidity of the material under the current printing conditions. The higher the PFI, the better the fluidity of the material under the current conditions, and the more suitable it is for high-quality printing. The material characteristic coefficient reflects the basic flow characteristics of the material and is usually measured by experiment. The value of k directly affects the size of PFI. The higher the material characteristic coefficient, the better the fluidity of the material. is the material viscosity. Viscosity is a physical quantity that describes the material's resistance to flow. The greater the viscosity, the worse the material's fluidity, and the lower the PFI will be. mu in the formula plays a role in offsetting fluidity, ensuring that the calculation of the fluidity index accurately reflects the actual situation. is the data of the jth monitoring parameter, which are various parameters collected during real-time monitoring, such as temperature, pressure, etc., which are directly related to the flow properties of the material. The change of each monitoring parameter will affect the overall flow evaluation. is the ideal monitoring data value corresponding to the jth monitoring parameter. By comparing with the ideal value, the degree of deviation of the current condition can be evaluated. The ideal monitoring data value provides a reference point to help determine the adaptability of material flow. The m is the number of monitoring parameters.

[0043] Among them, the molecular part :The numerator contains the product of the material characteristic coefficient (k) and the nozzle fluidity index (NBI), which reflects the combined influence of the intrinsic flow ability of the material and the working state of the nozzle on the extrusion flow rate. By multiplying, it emphasizes that when the material optimization is combined with good nozzle performance, its flow performance will be better. This part ensures that the defined flow index can be dynamically adjusted according to the characteristics of the specific material and nozzle.

[0044] Denominator mu: The viscosity of the material, mu, appears in the denominator and directly affects the size of PFI. The viscosity is used as the denominator to make the flow index penalize materials with high viscosity. The higher the viscosity, the worse the material flowability, which helps to reflect the flow resistance of the material under actual printing conditions. This design allows PFI to more realistically reflect changes in flow performance.

[0045] Index part :This part is designed to quantify the deviation of different monitored parameters from the ideal state and calculate a penalty factor. By introducing exponential functions, especially negative exponential forms, the PFI can be quickly reduced when the parameters deviate from the ideal value. This design is intended to reflect the importance of deviations from the ideal state (such as temperature, pressure, etc.) in the actual printing process, ensuring that when these conditions are not good, the fluidity index can accurately reflect the decline in fluidity.

[0046] The main significance of calculating the print fluidity index is that it provides a quantitative basis for adjusting and optimizing the extrusion process. By combining nozzle fluidity and material properties, it is possible to more accurately evaluate the fluidity problems that may be encountered in actual printing and make corresponding adjustments in a timely manner. This comprehensive approach not only improves printing quality, but also reduces material waste, reduces failure rates, and ensures a more efficient production process. This index makes the printer more adaptable to different materials and conditions, thereby more flexibly meeting various printing needs.

[0047] S204, optimizing the current extrusion volume flow rate according to the printing fluidity index.

[0048] Optimizing the current extrusion volume flow rate based on the Print Fluidity Index (PFI) is to ensure that the material fluidity during the printing process remains at an optimal state. The Print Fluidity Index takes into account the nozzle fluidity, material properties and deviations from actual monitoring data, allowing operators to accurately assess whether the current extrusion volume flow rate is suitable for the flow characteristics of the material. The PFI obtained through real-time monitoring can provide a practical basis for adjusting the extrusion volume flow rate. When the PFI indicates that the current extrusion state is not ideal, the operator can adjust the extrusion volume flow rate to match the material properties and nozzle state. This process is designed to improve printing quality and reduce the occurrence of blockages and poor flow.

[0049] Specifically, the printing fluidity index can be used to correct the current extrusion volume flow rate to obtain a correction coefficient; The process of correcting the current extrusion volume flow rate by using the print fluidity index (PFI) is mainly to map the PFI value to a correction factor (FAI), which is used to adjust the current extrusion volume. The PFI value reflects the fluidity of the material under the current conditions. If the PFI value is low, it means that the current fluidity is poor, which may lead to insufficient extrusion. At this time, correction is needed to increase the extrusion volume flow rate; conversely, if the PFI is high, it may mean good fluidity and excessive extrusion. Through this correction process, the extrusion volume flow rate can be accurately adjusted to adapt to real-time printing conditions.

[0050] The importance of this correction step is that it provides a dynamic adaptation mechanism that enables the printer to adjust itself based on real-time feedback. This process not only improves the printing quality, but also reduces the error rate and material waste. By introducing the correction coefficient, the operator can flexibly adjust the extrusion amount under different materials and printing conditions to ensure the stability and consistency of the printing process. This intelligent correction strategy provides strong support for the application of modern 3D printing technology and further improves the production efficiency and flexibility of the industry.

[0051] In the specific implementation, the printer software will collect monitoring data during the printing process in real time and calculate the print fluidity index (PFI). According to the numerical range of PFI, the system will set the corresponding correction factor (FAI), such as setting a linear relationship or a nonlinear relationship, so as to map the change of PFI to FAI. Subsequently, the operator can quickly adjust the current extrusion volume flow rate according to the generated FAI to optimize the printing effect. In this process, multiple adjustment parameters can be preset according to different material characteristics and printing requirements to achieve more flexible adjustments.

[0052] The current extrusion volume flow rate is optimized according to the correction coefficient to obtain an optimized extrusion volume flow rate based on material properties and the current operating state.

[0053] This step is to calculate a new, optimized extrusion volume flow rate (Q_new) by applying the correction factor (FAI) obtained in the first step to the current extrusion volume flow rate (Q_current). The core of this optimization process is to adjust the current flow rate to make it more consistent with the material characteristics and the actual working state of the nozzle. By introducing the correction factor FAI, the extrusion volume can be flexibly adjusted, so that the fluidity of the material during the extrusion process can be improved, and ultimately a higher quality printing effect can be achieved.

[0054] The significance of this optimization step is to ensure that the extrusion volume can adapt to various changing factors in real time during the printing process, such as material properties, environmental conditions and equipment status. Through the intelligent optimization mechanism, printing defects caused by the set extrusion volume flow rate not being suitable for the current state can be avoided, thereby improving the quality stability of the finished product. This method can also reduce material waste, reduce production costs, and further improve overall production efficiency and benefits.

[0055] In actual applications, the printer control system will generate the optimized extrusion volume flow rate (Q_new) based on the correction factor (FAI) calculated in the previous step and the current extrusion volume flow rate (Q_current) through a preset algorithm. The algorithm may be in a linear or nonlinear form and can dynamically calculate the optimal flow setting based on the current printing status. Ultimately, the optimized extrusion volume flow rate will be fed back to the printer's operating system to adjust the actual power and speed of the extruder head to ensure the stability and quality of the printing process.

[0056] Exemplarily, a correction factor and an optimized extrusion volume flow rate may be:

[0057]

[0058] The formula forms the correction factor FAI by inverting the print 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 actionable correction value so that it can effectively affect the current extrusion volume flow rate.

[0059] The formula is designed to add a correction to the current extrusion volume flow (Q_current) , in order to calculate the optimized extrusion volume flow rate (Q_new). In this way, the extrusion volume can be dynamically adjusted to adapt to changes in material properties and operating conditions.

[0060] Among them, the It is a correction factor used to adjust the current extrusion volume flow rate to adapt it to the real-time printing conditions. The larger the FAI value, the more correction is needed. is the optimized extrusion volume flow rate, is the current extrusion volume flow rate, , is the corresponding adjustment parameter. The value of can adjust the correction strength to meet the needs of different materials and printing conditions; by adjusting , which can affect the variation of the final flow rate in order to adapt to different printing environments and material properties.

[0061] Through this optimization step, the printer can dynamically adjust the extrusion volume flow rate according to real-time data and fluidity index, thereby achieving higher printing efficiency and quality. This optimization method based on fluidity index provides an intelligent control method 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 rate can effectively reduce material waste, thereby reducing production costs and improving resource utilization.

[0062] It can be seen that the operating state of the printer extruder head during 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 fluency index for evaluating the extrusion smoothness of the extruder head nozzle is calculated; based on the nozzle fluency index and the monitoring data, a printing fluidity index combining the nozzle fluency and the flow characteristics of the extruded material is calculated; according to the printing fluidity index, the current extrusion volume flow rate is optimized, so that by calculating the printing fluidity index combining the nozzle fluency and the material flow characteristics, the current extrusion volume flow rate can be dynamically optimized, thereby improving the reliability and efficiency of 3D printing.

[0063] Another embodiment of the present invention provides an extrusion volume flow optimization system for a printer, see Figure 3 , the system may include: The monitoring module 301 is used to monitor the operating state of the printer extruder in real time during the printing process and obtain corresponding monitoring data, wherein the monitoring data at least includes: temperature data and pressure data; A first calculation module 302 is used to calculate a nozzle smoothness index for evaluating the extrusion smoothness of the extrusion head nozzle according to the monitoring data; A second calculation module 303, for calculating a printing fluidity index combining nozzle fluidity and extrusion material flow characteristics based on the nozzle fluidity index and the monitoring data; The optimization module 304 is used to optimize the current extrusion volume flow rate according to the printing fluidity index.

[0064] It can be seen that the operating state of the printer extruder head during 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 fluency index for evaluating the extrusion smoothness of the extruder head nozzle is calculated; based on the nozzle fluency index and the monitoring data, a printing fluidity index combining the nozzle fluency and the flow characteristics of the extruded material is calculated; according to the printing fluidity index, the current extrusion volume flow rate is optimized, so that by calculating the printing fluidity index combining the nozzle fluency and the material flow characteristics, the current extrusion volume flow rate can be dynamically optimized, thereby improving the reliability and efficiency of 3D printing.

[0065] An embodiment of the present invention further provides a storage medium, in which a computer program is stored, wherein the computer program is configured to execute the steps of any of the above method embodiments when running.

[0066] Specifically, in this embodiment, the above storage medium may be configured to store a computer program for performing the following steps: S201, monitoring the operating state of the printer extruder during the printing process in real time, and acquiring corresponding monitoring data, wherein the monitoring data at least includes: temperature data and pressure data; S202, calculating a nozzle fluency index for evaluating the extrusion fluency of an extruder nozzle according to the monitoring data; S203, calculating a printing fluidity index combining nozzle fluidity and flow characteristics of extruded material based on the nozzle fluidity index and the monitoring data; S204, optimizing the current extrusion volume flow rate according to the printing fluidity index.

[0067] It can be seen that the operating state of the printer extruder head during 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 fluency index for evaluating the extrusion smoothness of the extruder head nozzle is calculated; based on the nozzle fluency index and the monitoring data, a printing fluidity index combining the nozzle fluency and the flow characteristics of the extruded material is calculated; according to the printing fluidity index, the current extrusion volume flow rate is optimized, so that by calculating the printing fluidity index combining the nozzle fluency and the material flow characteristics, the current extrusion volume flow rate can be dynamically optimized, thereby improving the reliability and efficiency of 3D printing.

[0068] An embodiment of the present invention further provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0069] Specifically, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0070] Specifically, in this embodiment, the processor may be configured to perform the following steps through a computer program: S201, monitoring the operating state of the printer extruder during the printing process in real time, and acquiring corresponding monitoring data, wherein the monitoring data at least includes: temperature data and pressure data; S202, calculating a nozzle fluency index for evaluating the extrusion fluency of an extruder nozzle according to the monitoring data; S203, calculating a printing fluidity index combining nozzle fluidity and flow characteristics of extruded material based on the nozzle fluidity index and the monitoring data; S204, optimizing the current extrusion volume flow rate according to the printing fluidity index.

[0071] It can be seen that the operating state of the printer extruder head during 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 fluency index for evaluating the extrusion smoothness of the extruder head nozzle is calculated; based on the nozzle fluency index and the monitoring data, a printing fluidity index combining the nozzle fluency and the flow characteristics of the extruded material is calculated; according to the printing fluidity index, the current extrusion volume flow rate is optimized, so that by calculating the printing fluidity index combining the nozzle fluency and the material flow characteristics, the current extrusion volume flow rate can be dynamically optimized, thereby improving the reliability and efficiency of 3D printing.

[0072] The above describes in detail the structure, features and effects of the present invention based on the embodiments shown in the drawings. The above is only a preferred embodiment of the present invention, but the present invention is not limited to the scope of implementation shown in the drawings. Any changes made according to the concept of the present invention, or modifications to equivalent embodiments with equivalent changes, which still do not exceed the spirit covered by the description and drawings, should be within the protection scope of the present invention.

Claims

1. A method for optimizing the extrusion volume flow of a printer, characterized in that: The method comprises: Performing real-time monitoring of the operating state of the printer extruder during the printing process and acquiring corresponding monitoring data, wherein the monitoring data at least includes: temperature data and pressure data; Calculating a nozzle smoothness index for evaluating the smoothness of extrusion from an extrusion head nozzle according to the monitoring data; Calculating a printing fluidity index combining nozzle fluidity and extrusion material flow characteristics based on the nozzle fluidity index and the monitoring data; According to the printing fluidity index, the current extrusion volume flow rate is optimized.

2. The method according to claim 1, characterized in that The nozzle fluency index for evaluating the extrusion fluency of the extruder nozzle is calculated based on the monitoring data, including: Determining a monitoring value of a specific monitoring state related to nozzle extrusion based on the monitoring data; The monitoring value is quantified into a specific monitoring state score, and a nozzle smoothness index for evaluating the extrusion smoothness of an extrusion head nozzle is calculated according to the specific monitoring state score.

3. The method according to claim 2, characterized in that The step of calculating the printing fluidity index combining nozzle fluidity and extrusion material flow characteristics based on the nozzle fluidity index and the monitoring data includes: Determine the ideal monitoring data values ​​corresponding to the material property coefficients, material viscosity, and optimal material processing of the extruded material; A printing fluidity index combining nozzle fluidity and extrusion material flow characteristics is calculated based on the material property coefficient, the material viscosity, the ideal monitoring data value, the nozzle fluidity index and the monitoring data.

4. The method according to claim 3, characterized in that The step of optimizing the current extrusion volume flow rate according to the printing fluidity index comprises: Using the printing fluidity index, correcting the current extrusion volume flow rate to obtain a correction coefficient; The current extrusion volume flow rate is optimized according to the correction coefficient to obtain an optimized extrusion volume flow rate based on material properties and the current operating state.

5. A system for optimizing the extrusion volume flow of a printer, characterized in that: The system comprises: A monitoring module, used to monitor the operating status of the printer extruder in real time during the printing process and obtain corresponding monitoring data, wherein the monitoring data at least includes: temperature data and pressure data; A first calculation module, used for calculating a nozzle smoothness index for evaluating the extrusion smoothness of an extrusion head nozzle according to the monitoring data; A second calculation module, for calculating a printing fluidity index combining nozzle fluidity and flow characteristics of extruded material based on the nozzle fluidity index and the monitoring data; The optimization module is used to optimize the current extrusion volume flow rate according to the printing fluidity index.

6. The system according to claim 5, characterized in that The first calculation module is specifically used for: Determining a monitoring value of a specific monitoring state related to nozzle extrusion based on the monitoring data; The monitoring value is quantified into a specific monitoring state score, and a nozzle smoothness index for evaluating the extrusion smoothness of an extrusion head nozzle is calculated according to the specific monitoring state score.

7. The system according to claim 6, characterized in that The second calculation module is specifically used for: Determine the ideal monitoring data values ​​corresponding to the material property coefficients, material viscosity, and optimal material processing of the extruded material; A printing fluidity index combining nozzle fluidity and extrusion material flow characteristics is calculated based on the material property coefficient, the material viscosity, the ideal monitoring data value, the nozzle fluidity index and the monitoring data.

8. The system according to claim 7, characterized in that The optimization module is specifically used for: Using the printing fluidity index, correcting the current extrusion volume flow rate to obtain a correction coefficient; The current extrusion volume flow rate is optimized according to the correction coefficient to obtain an optimized extrusion volume flow rate based on material properties and the current operating state.

9. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the method according to any one of claims 1 to 4 when executed.

10. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to perform the method according to any one of claims 1 to 4.

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