3D printing concrete temperature and curing state monitoring system combined with infrared imaging

Abstract

The present invention relates to the field of building automation technology, and specifically to a 3D printing concrete temperature and curing state monitoring system combined with infrared imaging, including a concrete conveying module, an infrared imaging module, a printing path planning module, a data analysis module, a dynamic printing adjustment module, and a state feedback adjustment module; wherein the concrete conveying module is used to control the flow and pressure of concrete according to printing parameters; the infrared imaging module is used to monitor the temperature distribution of the concrete layer in real time; the printing path planning module is used to dynamically adjust the printing path; the data analysis module is used to predict the optimal printing strategy; and the dynamic printing adjustment module is used to adjust the print head speed and concrete flow. The present invention significantly improves the printing accuracy and structural integrity by real-time monitoring of the temperature distribution of concrete and dynamically adjusting the printing parameters, while optimizing the use of materials and reducing waste, thereby enhancing the adaptability of the printing process.

Description

Technical Field

[0001] The present invention relates to the field of building automation technology, and in particular to a 3D printing concrete temperature and curing state monitoring system combined with infrared imaging. Background Art

[0002] In the construction industry, 3D printing concrete technology has been gradually adopted to increase the construction speed of building structures and reduce material waste. However, existing 3D printing technology has shortcomings in real-time monitoring and controlling the temperature and curing state of concrete during the printing process. Especially in large-scale printing operations, uneven curing speed and temperature distribution may lead to structural integrity problems and inconsistency in material properties.

[0003] Existing technologies usually rely on intermittent manual detection or simple sensor monitoring. These methods are not sufficient to provide detailed temperature distribution information inside the concrete layer, and cannot be adjusted in real time to adapt to complex environmental changes. In addition, traditional methods often lack the ability to predict and dynamically adjust the printing path, and cannot optimize the print head speed and concrete flow to adapt to real-time curing rate and temperature changes. These limitations not only reduce printing efficiency, but may also affect the quality of the final product.

[0004] The present invention aims to solve these problems in the prior art by providing a more accurate and reliable method to optimize the quality and efficiency of 3D printed concrete structures by real-time monitoring of the temperature distribution of the concrete layer and combining it with the ability to dynamically adjust the printing path and printing parameters. Summary of the invention

[0005] Based on the above objectives, the present invention provides a 3D printing concrete temperature and curing state monitoring system combined with infrared imaging.

[0006] The 3D printing concrete temperature and curing state monitoring system combined with infrared imaging includes a concrete delivery module, an infrared imaging module, a printing path planning module, a data analysis module, a dynamic printing adjustment module, and a state feedback adjustment module; among them,

[0007] Concrete delivery module: used to control the flow and pressure of concrete according to printing parameters;

[0008] Infrared imaging module: used to monitor the temperature distribution of the concrete layer in real time and generate high-resolution thermal images;

[0009] Print path planning module: uses the pre-set printing pattern and the data of the infrared imaging module to dynamically adjust the printing path to adapt to the material curing rate and temperature changes;

[0010] Data analysis module: Based on the data from the concrete delivery module and the printing path planning module, it uses advanced algorithms to analyze the curing process and predict the best printing strategy;

[0011] Dynamic printing adjustment module: According to the data predicted by the data analysis module, the print head speed and concrete flow rate are adjusted in real time to optimize the printing effect and curing speed;

[0012] State feedback adjustment module: monitors the concrete curing state through the sensor array, and feeds back the state information to the data analysis module for analysis to achieve closed-loop control.

[0013] Furthermore, the concrete delivery module includes a microprocessor control unit, a sensor unit, a variable frequency pump control unit and a data communication unit; wherein,

[0014] Microprocessor control unit: equipped with a printing parameter setting interface for receiving flow and pressure parameters set by the user;

[0015] Sensor unit: including a pressure sensor and a flow sensor, both of which are installed in the concrete delivery pipeline. The flow sensor can monitor the current concrete flow information in real time and feed back the information to the microprocessor control unit, and the pressure sensor can monitor the current pipeline pressure in real time and feed back the information to the microprocessor control unit;

[0016] Electric regulating valve: located in the concrete delivery pipeline, it adjusts the cross-sectional area of ​​concrete flow to control the flow rate through the instructions of the microprocessor control unit;

[0017] Variable frequency pump control unit: connected to the microprocessor control unit, adjusts the pump speed according to the received flow and pressure parameters to control the delivery speed and pressure of concrete;

[0018] Data communication unit: used to control data transmission between the microprocessor control unit and the flow sensor, pressure sensor, electric regulating valve and variable frequency pump control unit;

[0019] Among them, the microprocessor control unit can send instructions to the electric regulating valve and the variable frequency pump control system through the data communication unit according to the preset printing parameters to adjust the flow and pressure of concrete in real time. The flow sensor and the pressure sensor monitor the delivery status of concrete in real time and feed back the monitoring data to the microprocessor control unit so as to dynamically adjust the working status of the electric regulating valve and the variable frequency pump control system to ensure that the flow and pressure of concrete delivery meet the requirements of the printing process.

[0020] Furthermore, the infrared imaging module includes an infrared sensor unit, an optical focusing unit, a high-speed signal processor and a data interface unit; wherein,

[0021] Infrared sensor unit: equipped with multiple infrared sensors, each of which can detect infrared radiation of a specific wavelength to capture the temperature distribution of the concrete layer;

[0022] Optical focusing unit: comprising a set of lenses and reflectors for focusing the infrared radiation emitted from the surface of the concrete layer onto the infrared sensor array;

[0023] A high-speed signal processor: connected to the infrared sensor unit, used to receive data from the sensor and quickly process the data to generate a thermal image, wherein the high-speed signal processor is embedded with a thermal image generation software, which is used to convert the processed infrared data into a visual high-resolution thermal image;

[0024] Data interface unit: used to transmit the generated thermal imaging image to the printing path planning module and the data analysis module.

[0025] Furthermore, the printing path planning module includes a path planning processor, a temperature field analysis unit, a curing rate prediction model, a dynamic path adjustment unit and a path output interface; wherein,

[0026] Path planning processor: used to receive the pre-set 3D printing pattern and the real-time thermal imaging data provided by the infrared imaging module;

[0027] Temperature field analysis unit: used to convert the thermal image into a temperature field distribution map. The specific calculation formula is: T(x, y) = f(I(x, y)), where T represents the temperature field, I represents the pixel intensity of the thermal image, and (x, y) is the image coordinate;

[0028] Curing rate prediction model: The curing rate is predicted based on the temperature field distribution diagram and the concrete material properties. The specific prediction formula is: R(T) = g(T, P), where R represents the curing rate, T is the temperature, and P is the material property;

[0029] Dynamic path adjustment unit: Combines the curing rate prediction model with the pre-set 3D printing pattern to dynamically generate an adjusted printing path to adapt to real-time curing rate and temperature changes;

[0030] Path output interface: used to transmit the adjusted printing path to the dynamic printing adjustment module.

[0031] Furthermore, the specific steps of dynamically generating the adjusted printing path include:

[0032] S1: receiving the curing rate R(T) and temperature field distribution diagram T(x, y) output by the curing rate prediction model;

[0033] S2: Application path optimization formula: P opt(x, y) = h (T (x, y), R (T), C), where P opt represents the optimized printing path, and C represents the printing configuration parameter set;

[0034] S3: Path smoothing function S(P) based on concrete material properties and robot kinematics opt ) to generate a smooth path that conforms to the motion characteristics of the robot arm;

[0035] S4: Adopt real-time adjustment strategy A rt , according to the real-time position of the print head and the predetermined path, the printing path is dynamically adjusted to respond to the instantaneous change in curing rate. The strategy formula is:

[0036] P adj (t) = A rt (P opt , P current , ΔT),

[0037] Among them, P adj is the adjusted real-time path, P current is the current position of the print head, ΔT is the time change since the last path point;

[0038] S5: The dynamically adjusted path is again transmitted to the dynamic printing adjustment module through the path output interface.

[0039] Furthermore, the data analysis module includes a data collection unit, a curing model calculation unit, a printing strategy optimization algorithm unit, a prediction output unit and a data interface unit; wherein,

[0040] Data collection unit: used to receive concrete flow and pressure data from the concrete delivery module, and receive temperature field distribution and curing rate data from the printing path planning module;

[0041] Curing model calculation unit: using physical and chemical curing models M cure (T, R, P), where M cure represents the curing model, T represents the temperature data obtained from the infrared imaging module, R represents the curing rate, and P represents the material properties of concrete, which are used to analyze the curing process of concrete under different temperatures and pressures;

[0042] Printing strategy optimization algorithm unit: including printing strategy optimization algorithm O strat (M cure , C print ), where O strat is the optimized printing strategy, C print For printing configuration parameters, the algorithm is used to integrate the output of the curing model calculation unit and the printing configuration parameters to determine the optimal printing path and speed;

[0043] Prediction output unit: used to output the best printing strategy, which includes the recommended printing speed, path and concrete flow rate;

[0044] Learning Feedback Unit: Uses machine learning algorithms to continuously update the curing model and printing strategy optimization algorithm to improve the accuracy of predictions and the system's adaptability.

[0045] Furthermore, the machine learning algorithm continuously updates the curing model and the printing strategy optimization algorithm. The specific steps include:

[0046] a. Collect real-time data during the printing process, including concrete flow, pressure, print head speed, path selection, and temperature distribution data, as training data for the machine learning model;

[0047] b. Using supervised learning method, the data provided by the training data generator is used as input and the solidification effect is used as output. The machine learning model formula is expressed as: F learn (X)=Y, where X represents the input feature vector and Y represents the predicted result of the curing effect;

[0048] c. According to the deviation between the prediction results of the machine learning model and the actual printing results, adjust the model parameters. The optimization algorithm is expressed as: P new =P old +α·ΔF(X,Y actual ), where P new and P old Represent the new and old model parameters respectively, α is the learning rate, ΔF is the gradient of the loss function, and Y actual It is the actual curing effect.

[0049] Furthermore, the dynamic printing adjustment module includes an adjustment control unit, a print head speed controller and a flow regulator; wherein,

[0050] Adjustment control unit: responsible for receiving the optimal printing strategy data provided by the data analysis module, including the predicted curing speed and temperature distribution information;

[0051] Print head speed controller: According to the instruction of the control unit, the moving speed of the print head is adjusted in real time. The specific control formula is: V head (t) = V opt +k v ·(V pred -V current ), where V head (t) is the target speed of the print head, V opt is the optimal speed determined by the data analysis module, V pred is the predicted speed, V currentis the current speed, k v is the speed adjustment factor;

[0052] Flow regulator: connected to the adjustment control unit, adjusts the flow of concrete to match the print head speed and curing speed. The specific adjustment formula is: Q concrete (t) = Q opt +k q ·(Q pred -Q current ), where Q concrete (t) is the target flow rate of concrete, Q opt is the optimal flow rate, Q pred is the predicted flow, Q current is the current flow rate, k q is the flow adjustment factor.

[0053] Furthermore, the state feedback adjustment module includes a sensor array unit, a curing state evaluation unit, a feedback controller, a data communication unit and a user interface; wherein,

[0054] A sensor array unit: mounted adjacent to the print head, comprising a plurality of types of sensors, each sensor being specialized to monitor one or more specific curing parameters of the curing concrete;

[0055] Solidification state evaluation unit: receives data from the sensor array unit and uses the solidification state evaluation algorithm E cure (D sensor ), where E cure Indicates the curing status assessment result, D sensor represents data from a sensor array for analyzing the curing state of the current concrete layer;

[0056] Feedback controller: Generates the adjustment signal S based on the output of the curing state evaluation unit feedback (E cure ), and transmit the signal to the data analysis module and the dynamic printing adjustment module to adjust the printing parameters;

[0057] Data communication unit: used to control the real-time data transmission between the sensor array unit, the curing state evaluation unit, the feedback controller and the data analysis module;

[0058] User Interface: Provides visualization of real-time curing status information and allows the user to intervene and fine-tune feedback control parameters.

[0059] Beneficial effects of the present invention:

[0060] The present invention significantly improves the accuracy of the printing process by real-time monitoring of the temperature distribution of concrete and dynamically adjusting the printing path. This real-time adjustment capability ensures uniform curing of the concrete layer, thereby improving the integrity and durability of the structure. Using infrared imaging and advanced data analysis algorithms, the system can predict and adapt to changes in the curing rate, avoiding structural weaknesses caused by uneven curing.

[0061] The present invention ensures the effective use of materials and reduces over-pouring and material waste by precisely controlling the flow and pressure of the concrete delivery module. In addition, the ability to automatically adjust printing parameters also reduces the need for later corrections and polishing, further optimizing the use of materials and shortening the construction period.

[0062] The present invention can automatically adjust the printing strategy according to the real-time changes of environmental conditions and material properties. Through the continuous learning and optimization of the learning feedback unit, the adaptive ability of the system is enhanced over time, realizing the high automation and intelligence of the 3D printing process, thereby improving the operational efficiency and building quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0064] Figure 1 Schematic diagram of a concrete temperature and curing state monitoring system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0065] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0066] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0067] like Figure 1 As shown, the 3D printing concrete temperature and curing state monitoring system combined with infrared imaging includes a concrete delivery module, an infrared imaging module, a printing path planning module, a data analysis module, a dynamic printing adjustment module and a state feedback adjustment module; wherein,

[0068] Concrete delivery module: used to control the flow and pressure of concrete according to printing parameters;

[0069] Infrared imaging module: used to monitor the temperature distribution of the concrete layer in real time and generate high-resolution thermal images;

[0070] Print path planning module: uses the pre-set printing pattern and the data of the infrared imaging module to dynamically adjust the printing path to adapt to the material curing rate and temperature changes;

[0071] Data analysis module: Based on the data from the concrete delivery module and the printing path planning module, it uses advanced algorithms to analyze the curing process and predict the best printing strategy;

[0072] Dynamic printing adjustment module: According to the data predicted by the data analysis module, the print head speed and concrete flow rate are adjusted in real time to optimize the printing effect and curing speed;

[0073] State feedback adjustment module: monitors the concrete curing state through the sensor array, and feeds back the state information to the data analysis module for analysis to achieve closed-loop control.

[0074] The concrete delivery module includes a microprocessor control unit, a sensor unit, a variable frequency pump control unit and a data communication unit; wherein,

[0075] Microprocessor control unit: equipped with a printing parameter setting interface for receiving flow and pressure parameters set by the user;

[0076] Sensor unit: including pressure sensor and flow sensor, both of which are installed in the concrete delivery pipeline. The flow sensor can monitor and feed back the current concrete flow information to the microprocessor control unit in real time, and the pressure sensor can monitor and feed back the current pipeline pressure to the microprocessor control unit in real time;

[0077] Electric regulating valve: located in the concrete delivery pipeline, it adjusts the cross-sectional area of ​​concrete flow to control the flow rate through the instructions of the microprocessor control unit;

[0078] Variable frequency pump control unit: connected to the microprocessor control unit, adjusts the pump speed according to the received flow and pressure parameters to control the delivery speed and pressure of concrete;

[0079] Data communication unit: used to control data transmission between the microprocessor control unit and the flow sensor, pressure sensor, electric regulating valve and variable frequency pump control unit;

[0080] Among them, the microprocessor control unit can send instructions to the electric regulating valve and variable frequency pump control system through the data communication unit according to the preset printing parameters to adjust the flow and pressure of concrete in real time. The flow sensor and pressure sensor monitor the delivery status of concrete in real time and feed back the monitoring data to the microprocessor control unit to dynamically adjust the working status of the electric regulating valve and variable frequency pump control system to ensure that the flow and pressure of concrete delivery meet the requirements of the printing process. Such an adjustment mechanism uses a closed-loop control system to ensure the accuracy and responsiveness of concrete delivery and avoids printing quality problems caused by improper flow and pressure control.

[0081] The infrared imaging module includes an infrared sensor unit, an optical focusing unit, a high-speed signal processor and a data interface unit; wherein,

[0082] Infrared sensor unit: equipped with multiple infrared sensors, each of which can detect infrared radiation of a specific wavelength to capture the temperature distribution of the concrete layer;

[0083] Optical focusing unit: comprising a set of lenses and reflectors for focusing the infrared radiation emitted from the surface of the concrete layer onto the infrared sensor array;

[0084] High-speed signal processor: connected to the infrared sensor unit, used to receive data from the sensor and quickly process the data to generate a thermal image. The high-speed signal processor is embedded with thermal image generation software, which is used to convert the processed infrared data into a visual high-resolution thermal image.

[0085] Data interface unit: used to transmit the generated thermal imaging image to the printing path planning module and the data analysis module;

[0086] Among them, the infrared sensor unit captures the infrared radiation on the surface of the concrete layer through the optical focusing unit, converts it into electrical signals and then processes it by the high-speed signal processor. The thermal image generation software is responsible for converting these data into high-resolution images for further analysis. The data interface unit ensures the timely transmission of the thermal image to achieve real-time adjustment of the printing path and curing process.

[0087] The printing path planning module includes a path planning processor, a temperature field analysis unit, a curing rate prediction model, a dynamic path adjustment unit and a path output interface; wherein,

[0088] Path planning processor: used to receive the pre-set 3D printing pattern and the real-time thermal imaging data provided by the infrared imaging module;

[0089] Temperature field analysis unit: used to convert the thermal image into a temperature field distribution map. The specific calculation formula is: T(x, y) = f(I(x, y)), where T represents the temperature field, I represents the pixel intensity of the thermal image, and (x, y) is the image coordinate;

[0090] Curing rate prediction model: The curing rate is predicted based on the temperature field distribution diagram and the concrete material properties. The specific prediction formula is: R(T) = g(T, P), where R represents the curing rate, T is the temperature, and P is the material property;

[0091] Dynamic path adjustment unit: Combines the curing rate prediction model with the pre-set 3D printing pattern to dynamically generate an adjusted printing path to adapt to real-time curing rate and temperature changes;

[0092] Path output interface: used to transmit the adjusted printing path to the dynamic printing adjustment module;

[0093] Among them, the path planning processor first converts the thermal image received from the infrared imaging module into a temperature field distribution map through a temperature field analysis algorithm. Then, the curing rate prediction model calculates the curing rate of each point based on the temperature field and the specific material properties of concrete. The dynamic path adjustment algorithm uses these data to update the printing path to ensure that the material can be evenly cured during the printing process and adapt to temperature changes. The path output interface ensures that the adjusted path can be delivered to the printing device in a timely manner.

[0094] The specific steps of dynamically generating the adjusted printing path include:

[0095] S1: receiving the curing rate R(T) and temperature field distribution diagram T(x, y) output by the curing rate prediction model;

[0096] S2: Application path optimization formula: P opt(x, y) = h (T (x, y), R (T), C), where P opt represents the optimized printing path, and C represents the printing configuration parameter set;

[0097] S3: Path smoothing function S(P) based on concrete material properties and robot kinematics opt ) to generate a smooth path that conforms to the motion characteristics of the robot arm;

[0098] S4: Adopt real-time adjustment strategy A rt , according to the real-time position of the print head and the predetermined path, the printing path is dynamically adjusted to respond to the instantaneous change in curing rate. The strategy formula is:

[0099] P adj (t) = A rt (P opt , P current , ΔT),

[0100] Among them, P adj is the adjusted real-time path, P current is the current position of the print head, ΔT is the time change since the last path point;

[0101] S5: The dynamically adjusted path is again transmitted to the dynamic printing adjustment module through the path output interface.

[0102] The data analysis module includes a data collection unit, a solidification model calculation unit, a printing strategy optimization algorithm unit, a prediction output unit and a data interface unit; wherein,

[0103] Data collection unit: used to receive concrete flow and pressure data from the concrete delivery module, and receive temperature field distribution and curing rate data from the printing path planning module;

[0104] Curing model calculation unit: using physical and chemical curing models M cure (T, R, P), where M cure represents the curing model, T represents the temperature data obtained from the infrared imaging module, R represents the curing rate, and P represents the material properties of concrete, which are used to analyze the curing process of concrete under different temperatures and pressures;

[0105] Printing strategy optimization algorithm unit: including printing strategy optimization algorithm O strat (M cure , C print ), where O strat is the optimized printing strategy, C print For printing configuration parameters, the algorithm is used to integrate the output of the curing model calculation unit and the printing configuration parameters to determine the optimal printing path and speed;

[0106] Prediction output unit: used to output the best printing strategy, which includes the recommended printing speed, path and concrete flow rate;

[0107] Learning feedback unit: uses machine learning algorithms to continuously update the curing model and printing strategy optimization algorithm to improve the accuracy of prediction and the adaptive ability of the system;

[0108] Among them, the data collection unit ensures the real-time and integrity of the data. The curing model calculation unit and the printing strategy optimization algorithm unit are used in combination to analyze the curing process and predict the optimal printing strategy with scientific methods. The prediction output unit converts the optimization results into executable printing instructions, and the learning feedback unit optimizes the algorithm through historical data and real-time feedback to enhance the overall performance of the system.

[0109] The machine learning algorithm continuously updates the curing model and the printing strategy optimization algorithm. The specific steps include:

[0110] a. Collect real-time data during the printing process, including concrete flow, pressure, print head speed, path selection, and temperature distribution data, as training data for the machine learning model;

[0111] b. Using supervised learning method, the data provided by the training data generator is used as input and the solidification effect is used as output. The machine learning model formula is expressed as: F learn (X)=Y, where X represents the input feature vector and Y represents the predicted result of the curing effect;

[0112] c. According to the deviation between the prediction results of the machine learning model and the actual printing results, adjust the model parameters. The optimization algorithm is expressed as: P new =P old +α·ΔF(X,Y actual ), where P new and P old Represent the new and old model parameters respectively, α is the learning rate, ΔF is the gradient of the loss function, and Y actual It is the actual curing effect.

[0113] The dynamic printing adjustment module includes an adjustment control unit, a print head speed controller and a flow regulator; wherein,

[0114] Adjustment control unit: responsible for receiving the optimal printing strategy data provided by the data analysis module, including the predicted curing speed and temperature distribution information;

[0115] Print head speed controller: According to the instruction of the control unit, the moving speed of the print head is adjusted in real time. The specific control formula is: V head (t) = V opt +k v ·(Vpred -V current ), where V head (t) is the target speed of the print head, V opt is the optimal speed determined by the data analysis module, V pred is the predicted speed, V current is the current speed, k v is the speed adjustment factor;

[0116] Flow regulator: connected to the adjustment control unit, adjusts the flow of concrete to match the print head speed and curing speed. The specific adjustment formula is: Q concrete (t) = Q opt +k q ·(Q pred -Q current ), where Q concrete (t) is the target flow rate of concrete, Q opt is the optimal flow rate, Q pred is the predicted flow, Q current is the current flow rate, k q is the flow adjustment factor;

[0117] Among them, the recommended strategy of the comprehensive data analysis module of the control unit and the monitoring data of the real-time feedback monitoring unit are adjusted to continuously optimize the printing process through the precise control of the print head speed controller and flow regulator.

[0118] The state feedback adjustment module includes a sensor array unit, a curing state evaluation unit, a feedback controller, a data communication unit and a user interface; wherein,

[0119] A sensor array unit: mounted adjacent to the print head and including multiple types of sensors, each of which is specialized in monitoring one or more specific curing parameters of the curing concrete, such as temperature, moisture, and structural integrity;

[0120] Solidification state evaluation unit: receives data from the sensor array unit and uses the solidification state evaluation algorithm E cure (D sensor ), where E cure Indicates the curing status assessment result, D sensor represents data from a sensor array for analyzing the curing state of the current concrete layer;

[0121] Feedback controller: Generates the adjustment signal S based on the output of the curing state evaluation unit feedback (E cure ), and transmit the signal to the data analysis module and the dynamic printing adjustment module to adjust the printing parameters;

[0122] Data communication unit: used to control the real-time data transmission between the sensor array unit, the curing state evaluation unit, the feedback controller and the data analysis module;

[0123] User interface: Provides visualization of real-time curing status information and allows the user to intervene and fine-tune feedback control parameters;

[0124] Among them, the state feedback adjustment module forms a closed-loop control system through the real-time monitoring data of the sensor array, together with the real-time evaluation of the concrete curing state by the curing state evaluation algorithm, and the adjustment signal generated by the feedback controller. The system ensures that the printing parameters can be dynamically adjusted according to the real-time changes in the curing state, thereby optimizing the entire 3D printing process.

[0125] The present invention is intended to cover all such substitutions, modifications and variations that fall within the broad scope of the appended claims. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A 3D printing concrete temperature and curing state monitoring system combined with infrared imaging, characterized in that: It includes a concrete delivery module, an infrared imaging module, a printing path planning module, a data analysis module, a dynamic printing adjustment module and a state feedback adjustment module; among which, Concrete delivery module: used to control the flow and pressure of concrete according to printing parameters; Infrared imaging module: used to monitor the temperature distribution of the concrete layer in real time and generate high-resolution thermal images; Printing path planning module: using the pre-set printing pattern and the data of the infrared imaging module, dynamically adjust the printing path to adapt to the material curing rate and temperature changes. The printing path planning module includes a path planning processor, a temperature field analysis unit, a curing rate prediction model, a dynamic path adjustment unit and a path output interface; wherein, Path planning processor: used to receive the pre-set 3D printing pattern and the real-time thermal imaging data provided by the infrared imaging module; Temperature field analysis unit: used to convert the thermal image into a temperature field distribution map. The specific calculation formula is: T(x, y) = f(I(x, y)), where T represents the temperature field, I represents the pixel intensity of the thermal image, and (x, y) is the image coordinate; Curing rate prediction model: The curing rate is predicted based on the temperature field distribution diagram and the concrete material properties. The specific prediction formula is: R(T) = g(T, P), where R represents the curing rate, T is the temperature, and P is the material property; Dynamic path adjustment unit: Combines the curing rate prediction model with the pre-set 3D printing pattern to dynamically generate an adjusted printing path to adapt to real-time curing rate and temperature changes; Path output interface: used to transmit the adjusted printing path to the dynamic printing adjustment module; The specific steps of dynamically generating the adjusted printing path include: S1: receiving the curing rate R(T) and temperature field distribution diagram T(x, y) output by the curing rate prediction model; S2: Application path optimization formula: P opt (x, y) = h (T (x, y), R (T), C), where P opt represents the optimized printing path, and C represents the printing configuration parameter set; S3: Path smoothing function S(P) based on concrete material properties and robot kinematics opt ) to generate a smooth path that conforms to the motion characteristics of the robot arm; S4: Adopt real-time adjustment strategy A rt , according to the real-time position of the print head and the predetermined path, the printing path is dynamically adjusted to respond to the instantaneous change in curing rate. The strategy formula is: P adj (t)=A rt (P opt ,P current ,ΔT), Among them, P adj is the adjusted real-time path, P current is the current position of the print head, ΔT is the time change since the last path point; S5: The dynamically adjusted path is again transmitted to the dynamic printing adjustment module through the path output interface; Data analysis module: Analyzes the curing process and predicts the best printing strategy based on the data from the concrete delivery module and the printing path planning module; Dynamic printing adjustment module: According to the data predicted by the data analysis module, the print head speed and concrete flow rate are adjusted in real time to optimize the printing effect and curing speed; State feedback adjustment module: monitors the concrete curing state through the sensor array, and feeds back the concrete curing state information to the data analysis module for analysis to achieve closed-loop control.

2. The 3D printing concrete temperature and curing state monitoring system combined with infrared imaging according to claim 1 is characterized in that: The concrete delivery module includes a microprocessor control unit, a sensor unit, a variable frequency pump control unit and a data communication unit; wherein, Microprocessor control unit: equipped with a printing parameter setting interface for receiving flow and pressure parameters set by the user; Sensor unit: including a pressure sensor and a flow sensor, both of which are installed in the concrete delivery pipeline. The flow sensor can monitor the current concrete flow information in real time and feed back the information to the microprocessor control unit, and the pressure sensor can monitor the current pipeline pressure in real time and feed back the information to the microprocessor control unit; Electric regulating valve: located in the concrete delivery pipeline, it adjusts the cross-sectional area of ​​concrete flow to control the flow rate through the instructions of the microprocessor control unit; Variable frequency pump control unit: connected to the microprocessor control unit, adjusts the pump speed according to the received flow and pressure parameters to control the delivery speed and pressure of concrete; Data communication unit: used to control data transmission between the microprocessor control unit and the flow sensor, pressure sensor, electric regulating valve and variable frequency pump control unit; Among them, the microprocessor control unit can send instructions to the electric regulating valve and the variable frequency pump control system through the data communication unit according to the preset printing parameters to adjust the flow and pressure of concrete in real time. The flow sensor and the pressure sensor monitor the delivery status of concrete in real time and feed back the monitoring data to the microprocessor control unit so as to dynamically adjust the working status of the electric regulating valve and the variable frequency pump control system to ensure that the flow and pressure of concrete delivery meet the requirements of the printing process.

3. The 3D printing concrete temperature and curing state monitoring system combined with infrared imaging according to claim 2 is characterized in that: The infrared imaging module includes an infrared sensor unit, an optical focusing unit, a high-speed signal processor and a data interface unit; wherein, Infrared sensor unit: equipped with multiple infrared sensors, each of which can detect infrared radiation of a specific wavelength to capture the temperature distribution of the concrete layer; Optical focusing unit: comprising a set of lenses and reflectors for focusing the infrared radiation emitted from the surface of the concrete layer onto the infrared sensor array; A high-speed signal processor: connected to the infrared sensor unit, used to receive infrared sensor data and process the infrared sensor data to generate a thermal image, wherein the high-speed signal processor is embedded with thermal image generation software, and the thermal image generation software is used to convert the processed infrared data into a visual high-resolution thermal image; Data interface unit: used to transmit the generated thermal imaging image to the printing path planning module and the data analysis module.

4. The 3D printing concrete temperature and curing state monitoring system combined with infrared imaging according to claim 1 is characterized in that: The data analysis module includes a data collection unit, a curing model calculation unit, a printing strategy optimization algorithm unit, a prediction output unit and a data interface unit; wherein, Data collection unit: used to receive concrete flow and pressure data from the concrete delivery module, and receive temperature field distribution and curing rate data from the printing path planning module; Curing model calculation unit: using physical and chemical curing models M cure (T, R, P), where M cure represents the curing model, T represents the temperature data obtained from the infrared imaging module, R represents the curing rate, and P represents the material properties of concrete, which are used to analyze the curing process of concrete under different temperatures and pressures; Printing strategy optimization algorithm unit: including printing strategy optimization algorithm O strat (M cure , C print ), where O strat is the optimized printing strategy, C print For the printing configuration parameters, the printing strategy optimization algorithm is used to integrate the output of the curing model calculation unit and the printing configuration parameters to determine the optimal printing path and speed; Prediction output unit: used to output the best printing strategy, which includes the recommended printing speed, path and concrete flow rate; Learning Feedback Unit: Uses machine learning algorithms to continuously update the curing model and printing strategy optimization algorithm to improve prediction accuracy and the system's adaptability.

5. The 3D printing concrete temperature and curing state monitoring system combined with infrared imaging according to claim 4 is characterized in that: The specific steps of the machine learning algorithm continuously updating the curing model and the printing strategy optimization algorithm include: a. Collect real-time data during the printing process, including concrete flow, pressure, print head speed, path selection, and temperature distribution data, as training data for the machine learning model; b. Using supervised learning method, the data provided by the training data generator is used as input and the solidification effect is used as output. The machine learning model formula is expressed as: F learn (X) = Y, where X represents the input feature vector and Y represents the predicted result of the curing effect; c. According to the deviation between the prediction results of the machine learning model and the actual printing results, adjust the model parameters. The optimization algorithm is expressed as: P new =P old +α·ΔF(X,Y actual ), where P new and P old Represent the new and old model parameters respectively, α is the learning rate, ΔF is the gradient of the loss function, and Y actual It is the actual curing effect.

6. The 3D printing concrete temperature and curing state monitoring system combined with infrared imaging according to claim 5 is characterized in that: The dynamic printing adjustment module includes an adjustment control unit, a print head speed controller and a flow regulator; wherein, Adjustment control unit: responsible for receiving the optimal printing strategy data provided by the data analysis module, including the predicted curing speed and temperature distribution information; Print head speed controller: According to the instruction of the control unit, the moving speed of the print head is adjusted in real time. The specific control formula is: V head (t) = V opt +k v ·(V pred -V current ), where V head (t) is the target speed of the print head, V opt is the optimal speed determined by the data analysis module, V pred is the predicted speed, V current is the current speed, k v is the speed adjustment factor; Flow regulator: connected to the adjustment control unit, adjusts the flow of concrete to match the print head speed and curing speed. The specific adjustment formula is: Q concrete (t) = Q opt +k q ·(Q pred -Q current ), where Q concrete (t) is the target flow rate of concrete, Q opt is the optimal flow rate, Q pred is the predicted flow, Q current is the current flow rate, k q is the flow adjustment factor.

7. The 3D printing concrete temperature and curing state monitoring system combined with infrared imaging according to claim 6 is characterized in that: The state feedback adjustment module includes a sensor array unit, a curing state evaluation unit, a feedback controller, a data communication unit and a user interface; wherein, A sensor array unit: mounted adjacent to the print head, comprising a plurality of types of sensors, each sensor being specialized to monitor one or more specific curing parameters of the curing concrete; Solidification state evaluation unit: receives data from the sensor array unit and uses the solidification state evaluation algorithm E cure (D sensor ), where E cure Indicates the curing status assessment result, D sensor represents data from a sensor array for analyzing the curing state of the current concrete layer; Feedback controller: Generates the adjustment signal S based on the output of the curing state evaluation unit feedback (E cure ), and adjust the signal S feedback (E cure ) is passed to the data analysis module and the dynamic printing adjustment module to adjust the printing parameters; Data communication unit: used to control the real-time data transmission between the sensor array unit, the curing state evaluation unit, the feedback controller and the data analysis module; User Interface: Provides visualization of real-time curing status information and allows the user to intervene and fine-tune feedback control parameters.

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