CN118893828A

CN118893828A - Spray head control method and system based on continuous relation

Info

Publication number: CN118893828A
Application number: CN202411139992.6A
Authority: CN
Inventors: 何桂华; 洪英盛
Original assignee: Shenzhen Intelligent Technology Co ltd
Current assignee: Shenzhen Intelligent Technology Co ltd
Filing date: 2024-08-20
Publication date: 2024-11-05

Abstract

The invention discloses a spray head control method and a system based on a continuous relation, wherein the method comprises the following steps: continuously monitoring a plurality of working parameters related to a spray head of the 3D printing equipment in a preset time period to generate a numerical variation curve of each working parameter; according to the numerical variation curve of each working parameter, determining the working state of the spray head based on the continuous association relation among a plurality of working parameters; selecting parameter values of a preset number of time points from a plurality of continuously monitored working parameters, and calculating a working stability index of a spray head of the 3D printing equipment according to the parameter values; and controlling the spray head of the 3D printing equipment according to the working state and the working stability index. By utilizing the embodiment of the invention, a plurality of working parameters related to the spray head of the 3D printing equipment can be continuously monitored and analyzed, so that the working state of the spray head can be accurately judged and controlled, the stability and the product quality of 3D printing are improved, and the 3D printing technology is promoted to develop towards more intelligentization and autonomy.

Description

Spray head control method and system based on continuous relation

Technical Field

The invention belongs to the technical field of 3D printing, and particularly relates to a spray head control method and system based on a continuous relation.

Background

With the rapid development of 3D printing technology, the nozzle is used as a core component of the 3D printing device, and the performance and control precision play a critical role in printing quality and efficiency. In the 3D printing process, the nozzle needs to continuously adjust a plurality of working parameters such as extrusion speed, temperature, material flow and the like according to different material characteristics, printing modes and environmental conditions so as to ensure the quality and consistency of the final printed product. However, the operating state of the spray head is affected by a variety of factors including, but not limited to, the type of material, the spray head temperature, the printing speed, the external environment, and the mechanical properties of the device.

Conventional spray head control methods typically rely on empirical or fixed parameter settings. The designer presets specific parameter configurations for different print jobs, however these static settings cannot accommodate the changing working environment in real time. When parameter fluctuation or change occurs in the actual printing process, the working state of the spray head is difficult to timely and accurately adjust by the traditional method, so that the printing quality is unstable, such as material blockage, insufficient interlayer adhesion, surface defects and the like. The method not only increases material waste, but also can reduce production efficiency, and further affects popularization and development of the 3D printing technology in various application fields.

Disclosure of Invention

The invention aims to provide a spray head control method and system based on a continuous relation, which are used for solving the defects in the prior art, and can realize accurate judgment and control of the working state of a spray head by continuously monitoring and analyzing a plurality of working parameters related to the spray head of 3D printing equipment so as to improve the stability and the product quality of 3D printing and promote the development of a 3D printing technology to a more intelligent and autonomous direction.

One embodiment of the application provides a method for controlling a spray head based on a continuous relation, which comprises the following steps:

Continuously monitoring a plurality of working parameters related to a spray head of the 3D printing equipment in a preset time period to generate a numerical variation curve of each working parameter;

According to the numerical value change curve of each working parameter, determining the working state of the spray head of the 3D printing equipment based on continuous association relations among a plurality of working parameters, wherein the continuous association relations are association relations which show continuous mutual influence along with time change among the working parameters;

Selecting parameter values of a preset number of time points from a plurality of continuously monitored working parameters, and calculating a working stability index of a spray head of the 3D printing equipment according to the selected parameter values;

And controlling the spray head of the 3D printing equipment according to the working state and the working stability index.

Optionally, the determining, according to the numerical variation curve of each working parameter, the working state of the 3D printing device nozzle based on the continuous association relationship between the multiple working parameters includes:

acquiring historical parameter values and corresponding historical working states of continuous time points of different working parameters as a training data set, wherein the historical parameter values of a group of different parameters correspond to one historical working state;

Training a state prediction model based on artificial intelligence by utilizing the training data set, wherein the state prediction model can learn continuous association relations between different working parameters based on historical parameter values of the different working parameters and learn corresponding relations between the continuous association relations and the working states, when the historical working states are abnormal, the corresponding historical parameter values of a group of different parameters do not accord with the normal continuous association relations, and when the historical working states are normal, the corresponding historical parameter values of a group of different parameters accord with the normal continuous association relations;

and predicting the working state of the spray head of the 3D printing equipment based on the trained state prediction model according to the parameter values of the continuous time points of different parameters in the numerical variation curve.

Optionally, the calculation formula of the working stability index is:

the WSI is a working stability index, the sigma_i is a standard deviation of parameter values of all time points of an ith parameter, the mu_i is a mean value of parameter values of all time points of the ith parameter, the alpha_i is a weight coefficient of the ith parameter, the R_ij is a relative change rate of the j time point of the ith parameter and a previous time point, the beta_i is a correction coefficient of the ith parameter, the C_ij is a critical state factor of the ith parameter at the j time point, if the parameter value of the ith parameter at the j time point exceeds a normal range, C_ij=0, otherwise C_ij=1, the gamma_i is an influence coefficient of the ith parameter, the M is a preset number of time points, and the N is a working parameter number.

Optionally, when j=1, the relative change rate is R _ij =0, and when j > 1, the relative change rate is:

Wherein, p_ij is the parameter value of the ith parameter at the jth time point, and p_i { j-1} is the parameter value of the ith parameter at the (j-1) th time point.

Optionally, the controlling the nozzle of the 3D printing device according to the working state and the working stability index includes:

if the working state is normal, the spray head of the 3D printing equipment is not adjusted, or if the working state is normal and the working stability index does not exceed a preset stability threshold, the print spray head of the 3D printing equipment is adjusted so as to keep the working state normal, and meanwhile, the working stability index exceeds the preset stability threshold;

And if the working state is abnormal, adjusting a printing spray head of the 3D printing equipment to enable the working state to be normal, and enabling the working stability index to exceed a preset stability threshold.

Yet another embodiment of the present application provides a continuous relationship based spray head control system, the system comprising:

The monitoring module is used for continuously monitoring a plurality of working parameters related to the spray head of the 3D printing equipment in a preset time period and generating a numerical variation curve of each working parameter;

The determining module is used for determining the working state of the spray head of the 3D printing equipment based on continuous association relations among a plurality of working parameters according to the numerical variation curve of each working parameter, wherein the continuous association relations are association relations which show continuous mutual influence among the working parameters along with time variation;

the calculating module is used for selecting parameter values of a preset number of time points from a plurality of continuously monitored working parameters and calculating a working stability index of the spray head of the 3D printing equipment according to the selected parameter values;

And the control module is used for controlling the spray head of the 3D printing equipment according to the working state and the working stability index.

A further embodiment of the application provides a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the method of any of the preceding claims when run.

Yet another embodiment of the application provides an electronic device comprising a memory having a computer program stored therein and a processor configured to run the computer program to perform the method recited in any of the preceding claims.

Compared with the prior art, the spray head control method based on the continuous relation provided by the invention is used for continuously monitoring a plurality of working parameters related to the spray head of the 3D printing equipment in a preset time period, and generating a numerical variation curve of each working parameter; according to the numerical value change curve of each working parameter, determining the working state of the spray head of the 3D printing equipment based on continuous association relations among a plurality of working parameters, wherein the continuous association relations are association relations which show continuous mutual influence along with time change among the working parameters; selecting parameter values of a preset number of time points from a plurality of continuously monitored working parameters, and calculating a working stability index of a spray head of the 3D printing equipment according to the selected parameter values; according to the working state and the working stability index, the spray head of the 3D printing equipment is controlled, so that the working state of the spray head can be accurately judged and controlled by continuously monitoring and analyzing a plurality of working parameters related to the spray head of the 3D printing equipment, the stability and the product quality of 3D printing are improved, and the 3D printing technology is promoted to develop towards a more intelligent and autonomous direction.

Drawings

Fig. 1 is a hardware block diagram of a computer terminal of a shower nozzle control method based on a continuous relationship according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart of a method for controlling a spray head based on a continuous relationship according to an embodiment of the present invention;

fig. 3 is a schematic structural diagram of a spray head control system based on a continuous relationship according to an embodiment of the present invention.

Detailed Description

The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.

The embodiment of the invention firstly provides a spray head control method based on a continuous relation, which can be applied to electronic equipment such as a computer terminal, in particular to a common computer and the like.

The following describes the operation of the computer terminal in detail by taking it as an example. Fig. 1 is a hardware block diagram of a computer terminal according to a spray head control method based on a continuous relationship according to an embodiment of the present invention. As shown in fig. 1, the computer terminal may include one or more (only one is shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a microprocessor MCU or a processing device such as a programmable logic device FPGA) and a memory 104 for storing data, and optionally, a transmission device 106 for communication functions and an input-output device 108. It will be appreciated by those skilled in the art that the configuration shown in fig. 1 is merely illustrative and is not intended to limit the configuration of the computer terminal described above. For example, the computer terminal may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.

The memory 104 may be used to store software programs and modules of application software, such as program instructions/modules corresponding to the continuous-relation-based spray head control method in the embodiment of the present application, and the processor 102 executes the software programs and modules stored in the memory 104, thereby executing various functional applications and data processing, that is, implementing the method described above. Memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory remotely located relative to the processor 102, which may be connected to the computer terminal via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission means 106 is arranged to receive or transmit data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of a computer terminal. In one example, the transmission device 106 includes a network adapter (NetworkInterfaceController, NIC) that can connect to other network devices through a base station to communicate with the internet. In one example, the transmission device 106 may be a radio frequency (RadioFrequency, RF) module for communicating wirelessly with the internet.

Referring to fig. 2, an embodiment of the present invention provides a method for controlling a spray head based on a continuous relationship, which may include the steps of:

S201, continuously monitoring a plurality of working parameters related to a spray head of the 3D printing equipment in a preset time period to generate a numerical variation curve of each working parameter;

In 3D printing, the operating parameters associated with the control of the spray head include temperature, speed, pressure, material flow, etc. By continuously monitoring these parameters, their change over time throughout the printing process is recorded. These monitoring data will form a numerical variation curve for each parameter. Monitoring the change of the working parameters provides dynamic feedback information, is beneficial to capturing the performance of the spray head in the running process in real time, and further lays a foundation for the follow-up analysis work. The process has extremely important significance in a spray head control system, provides basic data for subsequent working state judgment, and can also help identify potential equipment faults and optimize a printing process. An implementation may include:

1. continuously monitoring working parameters:

-real-time data acquisition of a plurality of critical operating parameters of the 3D printing device with high precision sensors during a preset period of time. These operating parameters include the nozzle temperature, extrusion speed, material flow, ambient humidity, etc., which directly affect print quality and device performance.

The monitoring process needs to ensure that the data acquisition frequency is high enough to capture subtle parameter changes, usually selecting to record data once every second or every few seconds, forming a data stream.

2. Data storage and management:

The collected operating parameter data need to be effectively stored. A database system can be adopted to record the time stamp and the corresponding value of each parameter in time so as to ensure the integrity and traceability of the data.

In this step, it is necessary to design data management mechanisms, including data cleaning, denoising and outlier handling, to ensure the accuracy of the subsequent analysis.

3. Generating a numerical value change curve:

-drawing a numerical variation curve for each operating parameter from the collected real-time data. A data visualization tool may be used, with time as the abscissa and the value of the operating parameter as the ordinate, to form a clear graph.

These profiles will exhibit a dynamic evolution trend of the operating parameters over a preset period of time, providing intuitive information enabling the operator to quickly identify the fluctuation of the respective parameters.

4. Parameter fluctuation analysis:

by analysing the generated numerical variation curve, it is possible to identify periodic fluctuations, sudden changes or trending changes of the parameter. The fluctuation analysis can be performed by adopting a statistical method, such as calculating an average value, a standard deviation and the like, and evaluating the stability of the parameters.

Furthermore, normalization processes may be used to adjust the parameter values of different dimensions to the same range, to facilitate comparison and analysis between different parameters.

5. Marking key time points: on the numerical variation curve, some critical time nodes (for example, the moments when significant changes occur) are marked, providing reference data for the subsequent state prediction and control. These points in time can help analyze how the parameters interact in a particular situation.

6. Preparing for subsequent analysis:

After the generation of the numerical change curves, these curves are used as data inputs for the subsequent state prediction models and control strategies. By further analyzing the correlation between different operating parameters, a more accurate control algorithm can be established.

In addition, the generation of the numerical variation curve lays a foundation for the subsequent calculation of the working stability index, and is beneficial to timely and accurately dynamically monitoring the working state of the spray head.

In summary, through the continuous monitoring of a plurality of relevant working parameters of the spray head of the 3D printing equipment, the process of generating the numerical value change curve not only provides rich information for the subsequent working state judgment, but also lays a solid foundation for the subsequent control measures. The implementation of the method greatly improves the running stability of the equipment and ensures the high efficiency and quality of the printing process.

S202, determining the working state of a spray head of the 3D printing equipment based on continuous association relations among a plurality of working parameters according to a numerical variation curve of each working parameter, wherein the continuous association relations are association relations which are continuously and mutually influenced along with time variation among the working parameters;

And determining the working state of the spray head by analyzing the change relation among different parameters. For example, an increase in temperature may affect the flowability of the material, which in turn may affect print quality. This interrelated dynamic property is called a continuous association. The working state of the spray head is accurately identified, potential faults and material waste can be prevented, printing precision and quality are improved, and consistency and repeatability of products are ensured.

Specifically, historical parameter values and corresponding historical working states of continuous time points of different working parameters can be obtained to serve as a training data set, wherein the historical parameter values of one group of different parameters correspond to one historical working state;

And collecting values of different working parameters and corresponding working state data of the spray head in a period of time. These data will be used as the basis for model training. The history of the data can help understand how the various working parameters affect each other and their contribution to the working state, and is an important basis for learning the machine learning model.

a machine learning model (e.g., neural network or decision tree) is constructed that is capable of identifying the relationship between input data from different operating parameters and the operating state of the spray head. The model is continuously optimized in the training process so as to improve the accuracy of the prediction of the working state.

Through training, the model can identify the characteristic difference between the normal state and the abnormal state, so that the predicting capability of the spray head state is improved in real-time monitoring.

And processing the working parameters monitored in real time through a trained model to obtain the current working state prediction. The system can feed back the working state of the spray head in real time, so that the printing process can be timely adjusted and optimized, and the occurrence of abnormality is avoided. A state prediction model based on a Support Vector Machine (SVM) may be employed.

The method comprises the following steps:

1. and (3) data arrangement: and the collected working parameter data are arranged into a feature matrix and a tag array. The feature matrix contains historical values for a plurality of operating parameters, and the tag array corresponds to a historical operating state (normal or abnormal).

2. Feature selection and extraction: and (3) reducing the dimension of the feature matrix by adopting a Principal Component Analysis (PCA) method, and screening out features with larger influence on working state prediction so as to improve the efficiency and effect of model training.

3. Model training: training a support vector machine algorithm by using the sorted feature matrix and the label data set. And adjusting the hyper-parameters of the SVM, such as penalty parameter C and kernel function type, and optimizing the generalization capability of the model.

4. Model verification and test: and evaluating the performance of the trained model by using a cross-validation method, and ensuring the accuracy of the model on unseen data. And evaluating the performance of the model through indexes such as accuracy, recall rate, F1 score and the like.

5. And (3) real-time prediction: and inputting the working parameters monitored in real time into a trained SVM model, and outputting a current working state prediction result of the spray head by the model for reference of a subsequent control decision.

By the implementation of the technical means, the intelligent level of the working state monitoring and control of the 3D printing equipment can be effectively improved.

S203, selecting parameter values of a preset number of time points from a plurality of continuously monitored working parameters, and calculating a working stability index of a spray head of the 3D printing equipment according to the selected parameter values;

After continuous monitoring of the 3D printing device showerhead, real-time data for a plurality of operating parameters (e.g., temperature, flow, pressure, etc.) are collected. And selecting a certain number of time points from the continuously monitored data according to a preset time period and requirements, and extracting corresponding parameter values. These parameter values will be used in subsequent Work Stability Index (WSI) calculations. The significance of the action is as follows:

-data refinement: by selecting parameter values at specific points in time, redundancy of data may be reduced, thereby making the calculation process more efficient. The selected time point can be key instantaneous data, so that the working state of the spray head can be comprehensively estimated.

-Improving accuracy: by analyzing the parameters of a specific time period, a more representative sample is provided for the subsequent calculation of the work stability index, and the result is ensured to be more reliable.

-Dynamic reflection: the performance of the spray head at different stages can be revealed at the selected time points, so that the effect of dynamic monitoring is provided, and possible anomalies can be identified in time.

Specifically, a calculation formula of the working stability index may be:

the WSI is an index of working stability, is an important index for evaluating the working state of the spray head, and the higher the value is, the more stable the working state is.

The sigma_i is the standard deviation of parameter values of all time points of the ith parameter, reflects the fluctuation degree of the parameter in the monitoring period, and indicates that the working state is more stable as the standard deviation is smaller. The mu_i is the average value of parameter values of all time points of the ith parameter, and provides the overall level information of the parameter. The alpha_i is a weight coefficient of the ith parameter, reflects the relative importance of each parameter to the working stability, and ensures that the influence of the key parameter on the result is more remarkable.

The R_ij is the relative change rate of the jth time point of the ith parameter and the previous time point, the sensitivity of the dynamic change of the parameter is reflected, and the abnormality in operation can be reflected in time. And beta_i is a correction coefficient of the ith parameter, provides proper adjustment aiming at the characteristic of a specific parameter, and strengthens the adaptability of the whole model.

And c_ij is a critical state factor of the ith parameter at the jth time point, if the parameter value of the ith parameter at the jth time point exceeds a normal range, c_ij=0, otherwise, c_ij=1, and the method is used for evaluating whether the current state of each parameter is in an acceptable range. And the gamma_i is an influence coefficient of the ith parameter and is used for adjusting the influence degree of each parameter on the working stability index so as to ensure that the contribution of the important parameter to the overall stability evaluation is amplified.

And M is the preset number of time points, so that the state of the spray head is analyzed from multiple dimensions, and the reliability of the index is improved. And N is the number of working parameters and reflects the working performance change in a specific time period.

The formula comprehensively considers dynamic changes and relative change rates of a plurality of working parameters and critical factors of stable states to form an effective index for comprehensively evaluating the working stability of equipment. The multidimensional evaluation mode enables the WSI to accurately reflect the running state of the equipment.

Specifically, when j=1, the relative change rate is R _ij =0, and when j > 1, the relative change rate is:

By integrating the working parameters of multiple dimensions, a reliable working stability index is formed, and scientific basis is provided for the optimization and control of the 3D printing equipment.

S204, controlling the spray head of the 3D printing equipment according to the working state and the working stability index.

After monitoring of each working parameter of the 3D printing apparatus nozzle is completed and a corresponding Working Stability Index (WSI) is calculated, the system needs to analyze the current working state (normal or abnormal) and the value of WSI. Based on the analysis result, the system will decide whether adjustment or control of the nozzle is required to ensure smooth progress of the printing process. The significance of the action is as follows:

-improving print quality: the real-time monitoring and dynamic adjustment can ensure that the spray head operates in the optimal state, thereby improving the printing quality and reducing the defects and the rejection rate.

-Optimizing production efficiency: through the operating condition of intelligent control shower nozzle, can properly manage the printing process, reduce down time and print failure rate, promote whole production efficiency.

-Extending the service life of the device: the operation state of the spray head can be effectively controlled and adjusted, equipment abrasion caused by long-time unstable operation can be reduced, and the service life of equipment is prolonged.

-Improving the system response capability: by combining the working state and the WSI, the system can adapt to environmental changes and operation conditions more quickly, and the continuity and stability of the printing process are ensured, so that the customer satisfaction is enhanced.

Specifically, if the working state is normal, the spray head of the 3D printing device is not adjusted, or if the working state is normal and the working stability index does not exceed a preset stability threshold, the print spray head of the 3D printing device is adjusted to keep the working state normal, and meanwhile, the working stability index exceeds the preset stability threshold;

When the printer system monitors that the operating condition of the head is "normal", the system decides not to adjust the head, regardless of the current job stability index (WSI). This decision is based on the trust in the working condition of the nozzle, i.e. the normal state is sufficient to ensure a smooth progress of the printing process. The significance of the action is as follows:

-improving the operating efficiency: avoiding unnecessary adjustments can save time and operating costs, ensuring consistency of the printing process.

-Reducing equipment wear: frequent adjustments may cause wear on the equipment components, keeping the equipment in a normal state without adjustments reduces this risk and prolongs the service life of the equipment.

Or more preferably, even if the operating condition of the sprinkler head is evaluated as normal, the system will actively adjust the sprinkler head if the operating stability index (WSI) does not exceed the set stability threshold. This adjustment is to maintain the optimum operation of the head and ensure the print quality. The significance of the action is as follows:

Preventive maintenance: even under normal operating conditions, the system is still concerned with operational stability, ensuring that any potential problems can be discovered and resolved in time to prevent subsequent failure.

-Improving product quality consistency: by fine tuning the parameters of the spray head, the working state of the spray head is ensured to be maintained at the optimal level in the whole printing process, so that the quality consistency of the final product is improved.

Once the abnormal working state of the spray head is detected, the system immediately performs necessary adjustment on the spray head so as to quickly restore the spray head to the normal working state. At the same time, the adjustment is also focused on the control of the WSI, so that the WSI can be ensured to be in a reasonable range after adjustment. The significance of the action is as follows:

-fast response capability: when the nozzle is abnormal, measures can be taken rapidly, the influence of faults on the printing flow is reduced, and the material waste and the downtime are reduced.

-Enhancing system stability: by timely adjusting under the abnormal state, the stability and reliability of the whole 3D printing system are enhanced, and the trust and satisfaction of clients are improved.

By combining the analysis, an efficient and intelligent control strategy is provided for the spray head of the 3D printing equipment. Through the real-time monitoring and adjustment to the work state and the work stability index of the spray head, the spray head is ensured to be always kept in the optimal work state, the printing quality is improved, the production efficiency is optimized, and the equipment failure rate is reduced. The comprehensive method can effectively promote the intelligent development of the 3D printing technology, and provides higher-level printing service and experience for users.

As can be seen, continuously monitoring a plurality of working parameters related to the spray head of the 3D printing device within a preset time period to generate a numerical variation curve of each working parameter; according to the numerical value change curve of each working parameter, determining the working state of the spray head of the 3D printing equipment based on continuous association relations among a plurality of working parameters, wherein the continuous association relations are association relations which show continuous mutual influence along with time change among the working parameters; selecting parameter values of a preset number of time points from a plurality of continuously monitored working parameters, and calculating a working stability index of a spray head of the 3D printing equipment according to the selected parameter values; according to the working state and the working stability index, the spray head of the 3D printing equipment is controlled, so that the working state of the spray head can be accurately judged and controlled by continuously monitoring and analyzing a plurality of working parameters related to the spray head of the 3D printing equipment, the stability and the product quality of 3D printing are improved, and the 3D printing technology is promoted to develop towards a more intelligent and autonomous direction.

Still another embodiment of the present invention provides a continuous relationship based spray head control system, see fig. 3, which may include:

The monitoring module 301 is configured to continuously monitor a plurality of working parameters related to a nozzle of the 3D printing apparatus within a preset period of time, and generate a numerical variation curve of each working parameter;

The determining module 302 is configured to determine, according to a numerical variation curve of each working parameter, a working state of a nozzle of the 3D printing device based on a continuous association relationship between a plurality of working parameters, where the continuous association relationship is an association relationship that shows continuous mutual influence due to time variation between the working parameters;

A calculating module 303, configured to select parameter values of a preset number of time points from a plurality of continuously monitored working parameters, and calculate a working stability index of the 3D printing device nozzle according to the selected parameter values;

And the control module 304 is configured to control a nozzle of the 3D printing apparatus according to the working state and the working stability index.

The embodiment of the invention also provides a storage medium, in which a computer program is stored, wherein the computer program is configured to perform the steps of any of the method embodiments described above when run.

Specifically, in the present embodiment, the above-described storage medium may be configured to store a computer program for executing the steps of:

The present invention also provides an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.

Specifically, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.

Specifically, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:

The construction, features and effects of the present invention have been described in detail with reference to the embodiments shown in the drawings, but the above description is only a preferred embodiment of the present invention, but the present invention is not limited to the embodiments shown in the drawings, all changes, or modifications to the teachings of the invention, which fall within the meaning and range of equivalents are intended to be embraced therein, are intended to be embraced therein.

Claims

1. A method of controlling a spray head based on a continuous relationship, the method comprising:

2. The method according to claim 1, wherein the determining the operation state of the 3D printing apparatus head based on the continuous association relationship between the plurality of operation parameters according to the numerical variation curve of each operation parameter includes:

3. The method of claim 2, wherein the operational stability index is calculated by the formula:

4. A method according to claim 3, wherein when j = 1, the relative rate of change is R _ij = 0, and when j > 1, the relative rate of change is:

5. The method of claim 4, wherein controlling the head of the 3D printing device according to the operating state and the operating stability index comprises:

6. A continuous relationship-based spray head control system, the system comprising:

7. The system according to claim 6, wherein the determining module is specifically configured to:

8. The system of claim 7, wherein the operational stability index is calculated by the formula:

9. A storage medium having a computer program stored therein, wherein the computer program is arranged to perform the method of any of claims 1-5 when run.

10. An electronic device comprising a memory and a processor, wherein the memory has stored therein a computer program, the processor being arranged to run the computer program to perform the method of any of claims 1-5.