Temperature control system for 3D printers

Abstract

The present invention discloses a temperature control system applied to a 3D printer, relates to the field of printing control technology, and is used to solve the problem that most current 3D printing devices use static preset proportional control, which cannot be adjusted according to the real-time heating situation or changes in the external environment. This fixed strategy may lead to waste of resources in the heating process, or extend the preheating time, and reduce the printing efficiency. By introducing influencing factors such as heating rate, PID adjustment feedback and ambient temperature, the heating timing of the nozzle is intelligently adjusted to achieve adaptive optimization of the preheating process. According to the actual heating situation of the hot bed and material requirements, this method ensures that the hot bed and the nozzle temperature are synchronized, avoids the nozzle from entering a high temperature state too early, reduces the risk of material blockage and degradation, thereby shortening the preheating time, improving heating efficiency and ensuring printing quality.

Description

Technical Field

[0001] The present invention relates to the field of printing control technology, and more specifically, to a temperature control system applied to a 3D printer. Background Art

[0002] The preheating process of a 3D printer is one of the key steps to ensure successful printing. In FDM (fused deposition modeling) 3D printers, it is usually necessary to heat the hot bed and nozzle separately so that the printing material can be extruded smoothly at the appropriate temperature and adhere to the surface of the printing bed. Printing materials (such as PLA, ABS, etc.) have different melting characteristics under different heating conditions, so how to effectively control the heating process is crucial to the final printing quality.

[0003] In current 3D printing equipment, the preheating process is usually divided into two stages:

[0004] Heated bed heating: The heated bed is responsible for providing bottom temperature to prevent warping and poor adhesion caused by material cooling too quickly. The temperature of the heated bed is controlled within the specific range of the printed material.

[0005] Nozzle heating: The nozzle is heated to the melting temperature of the material, allowing the material to be extruded and stacked smoothly.

[0006] In order to avoid the nozzle heating too early, which may cause the material to melt, clog or even degrade in the nozzle for a long time, many 3D printing devices are designed to heat the hot bed first. When the hot bed reaches a certain percentage of the target temperature, the nozzle heating starts. This ensures the synchronization of the heating process and reduces the risk of the nozzle entering a high temperature state too early.

[0007] The prior art has the following deficiencies:

[0008] Currently, most 3D printing devices use static preset proportional control, which cannot be adjusted according to real-time heating conditions or changes in the external environment. This fixed strategy may lead to waste of resources during the heating process, or extend the preheating time and reduce printing efficiency. With the popularization and diversification of 3D printing technology, the control of the preheating process has gradually become more important. Especially in scenarios involving multiple materials, complex geometric structures and precise control requirements, how to dynamically adjust the heating timing of the nozzle and the hot bed according to the actual heating conditions has become the key to improving 3D printing efficiency and quality.

[0009] In view of the above problems, the present invention proposes a solution. Summary of the invention

[0010] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a temperature control system applied to a 3D printer to solve the problems raised in the above-mentioned background technology.

[0011] To achieve the above object, the present invention provides the following technical solutions:

[0012] The temperature control system used in 3D printers includes a hot bed control module, a nozzle control module, an environmental monitoring module, a PID control module, and a data feedback and optimization module, and signal connections between the modules;

[0013] Hot bed control module: responsible for adjusting the temperature of the hot bed in real time and monitoring the temperature status of the hot bed through sensors;

[0014] Nozzle control module: dynamically adjusts the heating timing of the nozzle according to the temperature change of the hot bed to ensure that the hot bed and the nozzle are heated in a synchronous state;

[0015] Environmental monitoring module: monitors the temperature, humidity and air flow of the external environment in real time through sensors, and adjusts the heating scheme of the system;

[0016] PID control module: dynamically adjusts the heating power of the hot bed according to the comprehensive feedback of the hot bed heating rate, heating rate limit and environmental factors;

[0017] Data feedback and optimization module: responsible for real-time feedback and storage of data during the temperature control process, and optimizing control strategies based on historical data.

[0018] In a preferred embodiment, the PID control module is used to dynamically adjust the heating power of the hot bed according to the heating rate of the hot bed, the heating rate limit and the comprehensive feedback of environmental factors to ensure that the temperature control process is stable and efficient; the specific control method is as follows:

[0019] The PID controller corrects the hot bed preheating by adjusting the heating power;

[0020] The PID controller control formula is: ; In the formula, K is the total error input of the comprehensive feedback of various error factors. p , K i , K d They are proportional term, integral term and differential term of PID regulation respectively. is the heating power of the hot bed;

[0021] The total error input is determined by the weighted sum of the heating rate error, heating rate limit error, and environmental factor error, and its calculation expression can be: ;

[0022] In the formula, , and They are the preset proportional coefficients of heating rate error, heating rate limit error and environmental factor error respectively.

[0023] In a preferred embodiment, the nozzle control module determines whether to delay or advance nozzle heating control according to the total error input:

[0024] If the total error input If the value is greater than the preset error input threshold and the bed temperature rise is less than the preset heating rate lower limit threshold, the nozzle heating will be postponed; if the total error input If the value is greater than the preset error input threshold and the bed temperature rises greater than the upper threshold of the heating rate, the nozzle is heated in advance.

[0025] In a preferred embodiment, the data feedback and optimization module further includes optimizing the PID adjustment cut-in timing during the hot bed preheating phase:

[0026] After completing a print, the data feedback and optimization module determines the heating coordination status of the hot bed and the nozzle according to the heating time difference between the two, and determines whether the PID adjustment cut-in timing of the next hot bed preheating stage should be changed through fuzzy rules based on the heating coordination status of the hot bed and the nozzle and the total error input of the PID adjustment in the hot bed preheating stage.

[0027] In a preferred embodiment, the data feedback and optimization module defines the heating time difference between the hot bed and the nozzle and the total PID adjustment error input during the hot bed preheating phase as fuzzy rule input variables, and divides them into different fuzzy sets respectively;

[0028] Define the PID adjustment cut-in time as the output variable and divide it into fuzzy sets;

[0029] A set of fuzzy rules is formulated to describe the influence of the heating time difference between the hot bed and the nozzle and the total error input of PID regulation during the hot bed preheating stage on the timing of PID regulation cut-in;

[0030] Perform fuzzy reasoning based on fuzzy rules to determine the timing for PID regulation to start.

[0031] The technical effects and advantages of the temperature control system of the present invention applied to a 3D printer are as follows:

[0032] The present invention is a dynamic nozzle heating control method based on multiple factors such as the real-time heating state of the hot bed. By introducing influencing factors such as the heating rate, PID adjustment feedback and ambient temperature, the heating timing of the nozzle is intelligently adjusted to achieve adaptive optimization of the preheating process. According to the actual heating situation of the hot bed and material requirements, this method ensures that the temperature of the hot bed and the nozzle is synchronized, while avoiding the nozzle from entering a high temperature state too early, reducing the risk of material blockage and degradation, thereby shortening the preheating time, improving heating efficiency and ensuring printing quality. This dynamic control method can adapt to changes in different materials and external conditions, so that 3D printing equipment can operate efficiently and stably in complex environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0034] Figure 1 The figure is a schematic diagram of the structure of the temperature control system of the present invention applied to a 3D printer. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0036] The present invention is a dynamic nozzle heating control method based on multiple factors such as the real-time heating state of the hot bed. By introducing influencing factors such as the heating rate, PID adjustment feedback and ambient temperature, the heating timing of the nozzle is intelligently adjusted to achieve adaptive optimization of the preheating process. According to the actual heating situation of the hot bed and material requirements, this method ensures that the temperature of the hot bed and the nozzle is synchronized, while avoiding the nozzle from entering a high temperature state too early, reducing the risk of material blockage and degradation, thereby shortening the preheating time, improving heating efficiency and ensuring printing quality. This dynamic control method can adapt to changes in different materials and external conditions, so that 3D printing equipment can operate efficiently and stably in complex environments.

[0037] Specifically, the present invention is applied to a temperature control system of a 3D printer such as Figure 1 As shown, it includes a hot bed control module, a nozzle control module, an environmental monitoring module, a PID control module, and a data feedback and optimization module, and the signals between the modules are connected.

[0038] The present invention is implemented based on the following system hardware architecture, specifically the system includes the following hardware modules:

[0039] Hot bed control module: responsible for adjusting the temperature of the hot bed in real time and monitoring the temperature status of the hot bed through sensors.

[0040] Nozzle control module: dynamically adjusts the heating timing of the nozzle according to the temperature change of the hot bed, ensuring that the hot bed and nozzle are heated in a synchronous state to prevent material blockage and quality problems.

[0041] Environmental monitoring module: Through sensors, it monitors the temperature, humidity and air flow of the external environment in real time, adjusts the system's heating scheme, and ensures efficient temperature control in different environments.

[0042] PID control module: Dynamically adjust the heating power of the hot bed according to the comprehensive feedback of the hot bed heating rate, heating rate limit and environmental factors to ensure a smooth and accurate heating process.

[0043] Data feedback and optimization module: responsible for real-time feedback and storage of data during the temperature control process, and optimizing control strategies based on historical data.

[0044] Each hardware module includes the following hardware configuration:

[0045] The hot bed control module is responsible for real-time monitoring and control of the hot bed heating process to ensure that the hot bed temperature rises steadily and reaches the set target; including:

[0046] Hot bed temperature sensor: real-time collection of hot bed temperature data , fed back to the PID control module;

[0047] Heater and power control unit: According to the feedback from the PID control module, adjust the heating power Pbed of the hot bed to ensure that the temperature of the hot bed is heated at the set rate;

[0048] Heating rate limiting module: ensures that the heating rate of the hot bed Rbed does not exceed the set maximum heating rate Rmax, to avoid excessive heating that damages the material or causes other problems.

[0049] This module can ensure that the temperature of the hot bed rises steadily during the preheating process, avoiding the problem of heating up too quickly or too slowly, improving the printing quality and shortening the preheating time.

[0050] The nozzle control module is responsible for determining the start time of nozzle heating according to the real-time status of the hot bed to avoid premature melting or clogging of the material; including:

[0051] Nozzle temperature sensor: monitors the nozzle temperature Tnozzle in real time and coordinates with the heating process of the hot bed;

[0052] Heater control unit: The nozzle heating start timing is dynamically adjusted based on the historical temperature rise and PID feedback results to ensure that the nozzle is heated when the hot bed approaches the target temperature.

[0053] Therefore, the nozzle control module can ensure the precise timing of nozzle heating, prevent the material from melting too early, and avoid blockage or material degradation caused by asynchronous heating.

[0054] The environmental monitoring module is used to monitor external environmental factors in real time, such as ambient temperature, humidity, wind speed, etc., and dynamically adjust the heating strategy to ensure stability under different environmental conditions; including:

[0055] Ambient temperature sensor: monitors the external temperature Tambient and feeds back to the PID control module;

[0056] Humidity sensor: monitors humidity and detects the impact of the environment on temperature control;

[0057] Wind speed sensor: monitors the air flow Vwind, especially the impact of wind speed changes on the hot bed temperature in the printing environment.

[0058] Thus, through the real-time data from the environmental monitoring module, the system can make dynamic adjustments under different environmental conditions to ensure temperature stability during the printing process and maintain temperature control accuracy even when the external temperature fluctuates greatly.

[0059] The PID control module is used to dynamically adjust the heating power of the hot bed according to the comprehensive feedback of the heating rate of the hot bed, the heating rate limit and environmental factors, ensuring a smooth and efficient temperature control process.

[0060] Heating rate limit means controlling the temperature rise rate of the hot bed or nozzle during the heating process, so that it does not exceed a preset maximum rate. This limit is to avoid the temperature rising too fast during the heating process, thereby preventing adverse effects on the material or equipment, such as uneven thermal expansion, material deformation or system oscillation. Heating rate limit ensures that the temperature rise process is more stable and controllable, improving printing quality and equipment safety.

[0061] The specific control methods are as follows:

[0062] The PID controller corrects the hot bed preheating by adjusting the heating power.

[0063] The control formula of PID controller is: ; In the formula, K is the total error input of the comprehensive feedback of various error factors. p , K i , K d They are proportional term, integral term and differential term of PID regulation respectively. is the heating power of the hot bed; the proportional term immediately responds to the current total error input and directly affects the adjustment of the heating power. The integral term is adjusted by accumulating historical errors to eliminate long-term deviations in the system. The differential term is adjusted by the error change rate to prevent system oscillation or overshoot.

[0064] The proportional control part adjusts the heating power of the hot bed according to the total error input at the current moment, ensuring that the heating power increases or decreases in proportion to the current error. This part can respond to errors quickly and correct the deviation of the heating power; if the total error input is large, the proportional control part will adjust the heating power significantly to quickly reduce the error, otherwise it will adjust the heating process with a smaller power for fine control.

[0065] The integral control part is used to accumulate the error before the current moment to eliminate the steady-state error. This part adjusts the heating power by accumulating the error over a long period of time, so that the hot bed gradually approaches the target temperature; the integral control will eliminate small deviations in the system, especially after reaching the steady state, helping the hot bed temperature to reach the set target more accurately.

[0066] The differential control part adjusts the heating power according to the error change rate to reduce the oscillation and fluctuation during the temperature change process. It predicts the future trend of the system in advance according to the speed of error change to avoid over-adjustment; if the error change rate is large, the differential control part will reduce the heating power in advance to prevent the system from over-adjusting or over-adjusting.

[0067] The comprehensive feedback of multiple error factors includes heating rate error, heating rate limit error and environmental factor error.

[0068] The heating rate error reflects the difference between the heating rate of the hot bed and the expected one, which is mainly based on the thermal conductivity of the hot bed material, the stability of the power supply and the degree of equipment aging. The calculation expression of the real-time heating rate of the hot bed can be: ; In the formula, Δt is the sampling interval; the calculation expression of the hot bed target heating rate can be: ; In the formula, is the target temperature of the hot bed. is the expected heating time; is the initial temperature of the hot bed; the calculation expression of the heating rate error can be: ; By monitoring the temperature rise rate error, ensure that the temperature rise speed is consistent with expectations, and avoid the effect of temperature regulation affected by equipment aging or unstable power supply.

[0069] Heating rate limit error The actual heating rate is compared with the set maximum heating rate Rmax. If the actual heating rate exceeds the limit, a positive error will be generated and the system will reduce the heating power. The specific calculation expression is: ;

[0070] like , the heating rate limit error is 0, which does not affect the heating power. Otherwise, the error is positive and the system will reduce the heating power to prevent excessive heating.

[0071] Environmental factor error It reflects the influence of the external environment (temperature, humidity, air flow) on the heating of the hot bed. When the external environment conditions are poor, the heating rate of the hot bed will decrease, and additional heating power will be required. The calculation formula is: ;

[0072] In the formula, is the ambient temperature, is the ambient humidity, is the ambient wind speed, is the current temperature, is the reference humidity, is the reference wind speed.

[0073] Furthermore, the comprehensive feedback of multiple error factors is determined by weighted summing of the heating rate error, the heating rate limit error and the environmental factor error, and its calculation expression can be: ;

[0074] In the formula, , and They are respectively the preset proportional coefficients of the heating rate error, the heating rate limit error and the environmental factor error, which are set according to the actual situation and will not be elaborated here.

[0075] The nozzle control module determines whether to delay or advance nozzle heating control based on the total error input.

[0076] If the total error input If the value is greater than the preset error input threshold and the bed temperature rise is less than the preset heating rate lower limit threshold, the nozzle heating will be postponed; if the total error input If the value is greater than the preset error input threshold and the bed temperature rises greater than the upper threshold of the heating rate, the nozzle is heated in advance.

[0077] Furthermore, the data feedback and optimization module includes optimizing the PID adjustment cut-in timing during the hot bed preheating phase, specifically:

[0078] After completing a print, the data feedback and optimization module determines the heating coordination status of the hot bed and the nozzle according to the heating time difference between the two, and determines whether the PID adjustment cut-in timing of the next hot bed preheating stage should be changed through fuzzy rules based on the heating coordination status of the hot bed and the nozzle and the total error input of the PID adjustment in the hot bed preheating stage.

[0079] That is, the heating time difference between the hot bed and the nozzle and the total PID adjustment error input in the hot bed preheating stage are defined as fuzzy rule input variables, which are divided into different fuzzy sets.

[0080] For example, "Large", "Normal", "Small" are for the heating time difference between the hot bed and the nozzle, "Large", "Normal", "Small" are for the total PID adjustment error input during the hot bed preheating stage.

[0081] Define the PID regulation cut-in timing as the output variable and divide it into fuzzy sets, for example, "postpone", "maintain", "advance" for PID regulation cut-in.

[0082] Formulate a set of fuzzy rules to describe the heating time difference between the hot bed and the nozzle and the influence of the total PID adjustment error input during the hot bed preheating phase on the PID adjustment cut-in timing. The definition of rules can be based on professional knowledge or obtained through data analysis and experiments. For example:

[0083] Rule 1: If (the heating time difference between the hot bed and the nozzle is large) and (the total error input of the PID regulation in the hot bed preheating stage is large) then (the PID regulation cut-in timing is advanced);

[0084] Rule 2: If (the heating time difference between the hot bed and the nozzle is small) and (the total error input of the PID regulation in the hot bed preheating stage is small) then (the timing of PID regulation cut-in is delayed);

[0085] …

[0086] Finally, fuzzy reasoning is performed according to fuzzy rules to determine the timing for PID regulation to start.

[0087] It should be noted that the division of fuzzy sets can be adjusted according to actual conditions. For example, although the present embodiment takes three fuzzy sets as examples, in fact, the heating time difference between the hot bed and the nozzle, the total error input of the PID regulation in the hot bed preheating stage, and the PID regulation cut-in timing can be divided into more than three sets to facilitate better precise adjustment according to different temperatures.

[0088] Furthermore, for the judgment of whether the heating time difference between the hot bed and the nozzle and the total error input of the PID adjustment during the hot bed preheating stage is large, normal, or small, a threshold value can be set according to the actual situation. For example, when the heating time difference between the hot bed and the nozzle exceeds 30 seconds, it is marked as "large", etc., which will not be elaborated here.

[0089] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0090] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product.

[0091] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application of the technical solution and the invention constraints. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0092] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0093] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0094] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A temperature control system applied to a 3D printer, characterized in that; It includes hot bed control module, nozzle control module, environment monitoring module, PID control module and data feedback and optimization module, and the signal connection between each module; Hot bed control module: responsible for adjusting the temperature of the hot bed in real time and monitoring the temperature status of the hot bed through sensors; Nozzle control module: dynamically adjusts the heating timing of the nozzle according to the temperature change of the hot bed to ensure that the hot bed and the nozzle are heated in a synchronous state; Environmental monitoring module: monitors the temperature, humidity and air flow of the external environment in real time through sensors, and adjusts the heating scheme of the system; PID control module: dynamically adjusts the heating power of the hot bed according to the comprehensive feedback of the hot bed heating rate, heating rate limit and environmental factors; Data feedback and optimization module: responsible for real-time feedback and storage of data during the temperature control process, and optimizing control strategies based on historical data.

2. The temperature control system for a 3D printer according to claim 1, characterized in that: The PID control module is used to dynamically adjust the heating power of the hot bed according to the heating rate of the hot bed, the heating rate limit and the comprehensive feedback of environmental factors to ensure that the temperature control process is stable and efficient; the specific control method is as follows: The PID controller corrects the hot bed preheating by adjusting the heating power; The control formula of PID controller is: ; In the formula, K is the total error input of the comprehensive feedback of various error factors. p , K i , K d They are proportional term, integral term and differential term of PID regulation respectively. is the heating power of the hot bed; The total error input is determined by the weighted sum of the heating rate error, heating rate limit error, and environmental factor error. The calculation expression is: ; In the formula, , and They are the preset proportional coefficients of heating rate error, heating rate limit error and environmental factor error respectively.

3. The temperature control system for a 3D printer according to claim 2, characterized in that: The nozzle control module determines whether to delay or advance nozzle heating control based on the total error input: If the total error input If the value is greater than the preset error input threshold and the bed temperature rise is less than the preset heating rate lower limit threshold, the nozzle heating will be postponed; if the total error input If the value is greater than the preset error input threshold and the bed temperature rises greater than the upper threshold of the heating rate, the nozzle is heated in advance.

4. The temperature control system for a 3D printer according to claim 3, characterized in that ； The data feedback and optimization module also includes optimizing the timing of PID adjustment during the hot bed preheating phase: After completing a print, the data feedback and optimization module determines the heating coordination status of the hot bed and the nozzle according to the heating time difference between the two, and determines whether the PID adjustment cut-in timing of the next hot bed preheating stage should be changed through fuzzy rules based on the heating coordination status of the hot bed and the nozzle and the total error input of the PID adjustment in the hot bed preheating stage.

5. The temperature control system for a 3D printer according to claim 4, characterized in that: The data feedback and optimization module defines the heating time difference between the hot bed and the nozzle and the total PID adjustment error input during the hot bed preheating phase as fuzzy rule input variables, and divides them into different fuzzy sets respectively; Define the PID adjustment cut-in time as the output variable and divide it into fuzzy sets; A set of fuzzy rules is formulated to describe the influence of the heating time difference between the hot bed and the nozzle and the total error input of PID regulation during the hot bed preheating stage on the timing of PID regulation cut-in; Perform fuzzy reasoning based on fuzzy rules to determine the timing for PID regulation to start.

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