Path optimization method for concrete 3D printing

Abstract

The invention relates to the field of concrete 3D printing, and discloses a path optimization method for concrete 3D printing, which comprises the following steps: firstly, slicing a three-dimensional model of a to-be-printed concrete member, converting the sliced model into a geometric model, and initializing position information of geometric points in the geometric model; according to a graph theory principle, dividing the geometric model into a plurality of areas which can be printed at one time; the method comprises the following steps: constructing slices of a printing model into geometric figures which can be identified by a computer, extracting and numbering vertexes of the geometric figures, respectively recording coordinates of the vertexes, setting an adjacent matrix to describe a connection condition between the vertexes, then storing the vertexes into a partition matrix according to a rule, the partitions can be traversed at a time; finding out a shortest printing path in the plurality of divided areas by using an ant colony algorithm; and the printing platform is controlled to move according to the planned optimal printing path.

Description

Technical Field

[0001] The present invention relates to the field of concrete 3D printing, and particularly to a path optimization method for concrete 3D printing. Background Art

[0002] 3D printing technology, which is a kind of rapid prototyping technology and also known as additive manufacturing, is a technology that uses digital model files as the basis and uses bondable materials such as concrete and gypsum to print three-dimensional entities layer by layer. In recent years, 3D printing technology has made remarkable progress in many fields, such as medicine, metal manufacturing, and aerospace. However, in the field of civil engineering, especially the application of concrete 3D printing technology is still in its infancy.

[0003] Traditional 3D printing path planning methods usually print according to a pre-planned regular path. However, for complex 3D printing components, this method often leads to frequent jumps of the print head, generating too many print breakpoints, which in turn affects the forming quality of the 3D printing components.

[0004] In view of the above problems, there is an urgent need for an effective path optimization method to reduce print breakpoints, shorten the forming time, and improve the printing quality. Summary of the Invention

[0005] The purpose of the present invention is to provide a path optimization method for concrete 3D printing to solve the above technical problems.

[0006] The purpose of the present invention can be achieved by the following technical solutions:

[0007] A path optimization method for concrete 3D printing includes:

[0008] S1. Slice the three-dimensional model of the concrete component to be printed, convert the sliced model into a geometric model, and initialize the position information of the geometric points in the geometric model;

[0009] S2. According to the graph theory principle, divide the geometric model into multiple regions that can be printed in one go;

[0010] First, construct the slices of the printing model into geometric figures recognizable by a computer. Secondly, extract and number the vertices of the geometric figures, record the coordinates of each vertex respectively, and set an adjacency matrix to describe the connection situation between each vertex. Then, store each vertex into the partition matrix according to the rules to form partitions that can be traversed in one go;

[0011] S3. Use the ant colony algorithm to find the shortest printing path in the divided multiple regions;

[0012] S4. Connect to the printing platform and receive the shortest printing path in S3, control the printing platform to move according to the planned optimal printing path, and at the same time control the supply rate of the concrete material to ensure the continuity and stability of the printing process.

[0013] As a further technical solution, the specific steps of S3 are as follows:

[0014] S31. Initialize the parameters of the ant colony algorithm, including the number of ants, the initial concentration of pheromone, the pheromone evaporation factor, the pheromone importance factor, and the maximum number of iterations;

[0015] S32. Construct the solution space and randomly place each ant on the starting vertex of the sub-region;

[0016] S33. Calculate the next vertex to be visited by each ant according to the pheromone concentration and distance heuristic information;

[0017] S34. Update the pheromone concentration, record the shortest path length and the corresponding path in the current iteration;

[0018] S35. Compare the number of iterations that have been performed with the preset maximum number of iterations. Once the maximum number of iterations is reached, terminate the iteration;

[0019] S36. Output the optimal printing path, which consists of a series of consecutive vertices and represents the movement trajectory of the print head during the printing process.

[0020] As a further technical solution, the process of calculating the next vertex to be visited by each ant is as follows:

[0021] Denote the vertex where the k-th ant is currently located as i, and the next vertex to be visited as j. Then the transition probability for the k-th ant to transfer from vertex i to vertex j

[0022] is calculated by the formula:

[0023]

[0024] is calculated as;

[0025] where s is the s-th vertex to be visited, n is the total number of vertices to be visited, φ ij (t) is the pheromone concentration on the path between vertex i and vertex j at time t, A and B are the pheromone importance factor and the heuristic information importance factor respectively, δ is (t) is the pheromone concentration on the path between vertex i and the s-th vertex to be visited, θ is is the distance heuristic information between vertex i and the s-th vertex to be visited, θ ijThe heuristic information of the distance between vertex i and vertex j, with the expression:

[0026]

[0027] where d(i, j) is the distance between vertex i and vertex j, and x i and x j are the abscissas of vertex i and vertex j respectively, and y i and y j are the ordinates of vertex i and vertex j respectively;

[0028] Arrange the multiple calculated transition probabilities in descending order, and take the vertex corresponding to the transition probability ranked first as the next vertex to be visited.

[0029] As a further technical solution, the calculation formula for updating the pheromone concentration is:

[0030] δ ij (t + 1) = (1 - R) * δ ij (t) + Δδ ij

[0031] where R is the pheromone evaporation rate, R is a constant, and R < 1, and Δδ ij is the increase in pheromone, δ ij (t + 1) is the updated pheromone concentration, and δ ij (t) is the pheromone concentration before update.

[0032] As a further technical solution, the process of obtaining the increase in pheromone Δδ ij is as follows:

[0033] After the k-th ant completes a round of search and constructs a complete path, the pheromone increment of each edge (i, j) on this path is

[0034]

[0035] calculated by the formula:

[0036] where W is the pheromone release amount, which is a constant representing the total amount of pheromone released by each ant onto the path after a complete search, and L k is the total length of the path constructed by ant k;

[0037] In each iteration, after all ants complete the search and construct the paths, it is necessary to update the pheromone on all paths;

[0038] For each edge (i, j), the pheromone increment Δδ ijis the sum of the pheromone increments contributed by all the ants passing through this edge:

[0039]

[0040] where m is the total number of ants passing through this edge.

[0041] As a further technical solution, the process of controlling the supply rate of the concrete material is as follows:

[0042] Obtain the width a of the printing path, the height b of the printing path, and the length c of the printed path in real time;

[0043] Substitute into the formula:

[0044] F = a * b * c

[0045] Calculate the amount of concrete F for the print head;

[0046] Substitute into the following formula:

[0047]

[0048] Calculate the supply rate Q of the concrete material;

[0049] where V is the moving speed of the print head;

[0050] Compare the calculated supply rate Q of the concrete material with the supply rate threshold interval [Q - , Q + , and comprehensively judge whether it is necessary to control the supply rate of the concrete material according to the comparison result and in combination with whether the predicted supply rate of the concrete material shows a stable trend.

[0051] As a further technical solution, the process of comprehensively judging whether it is necessary to control the supply rate of the concrete material is as follows:

[0052] Compare the calculated supply rate Q of the concrete material with the supply rate threshold interval [Q - , Q + ;

[0053] If Q > Q + and the variation coefficient Qf of the supply rate of the concrete material is ≥ the preset warning threshold Qf 0 , then it is judged that the current supply rate of the concrete material is high, and the current supply rate of the concrete material is controlled to decrease;

[0054] If Q ∈ [Q - , Q + and the variation coefficient Qf of the supply rate of the concrete material is < the preset warning threshold Qf 0, it is determined that the supply rate of the current concrete material is normal, and the supply rate of the current concrete material is maintained unchanged;

[0055] If Q < Q - and the variation coefficient Qf of the concrete material supply rate ≥ the preset warning threshold Qf 0 , it is determined that the supply rate of the current concrete material is low, and the supply rate of the current concrete material is controlled to increase.

[0056] As a further technical solution, the process of obtaining the variation coefficient of the concrete material supply rate is as follows:

[0057] Obtain the curve Q(t) of the supply rate of the concrete material changing with time within M monitoring periods;

[0058] Obtain N supply rates Qg of the concrete material sampled at preset time intervals within each monitoring period;

[0059] Through the formula:

[0060]

[0061] Calculate to obtain the variation coefficient Qf of the concrete material supply rate;

[0062] where Qe q is the fluctuation coefficient of the concrete material supply rate within each monitoring period, μ 1 , μ 2 is the preset weight coefficient, q is the qth monitoring period, t q -t q+1 are the two time endpoints of any monitoring period;

[0063] Compare the variation coefficient Qf of the concrete material supply rate with the preset warning threshold Qf 0 ; if Qf ≥ Qf 0 , it is predicted that the concrete material supply rate shows an unstable trend; if Qf < Qf 0 , it is predicted that the concrete material supply rate shows a stable trend.

[0064] The beneficial effects of the present invention:

[0065] The concrete 3D printing path optimization method of the present invention can significantly improve the printing efficiency and quality. First, slice the three-dimensional model and convert it into a geometric model, divide the printable area at one time according to the graph theory principle, and reduce interruptions and repeated operations. Second, use the ant colony algorithm to find the shortest printing path within the area to ensure the optimal path and reduce time and material waste. By closely connecting with the printing platform, accurately plan the printing path, and reasonably control the concrete supply rate to ensure the continuity and stability of the printing process and avoid printing quality problems caused by unreasonable paths or improper material supply. In addition, the optimization method makes the movement of the print head smoother, reduces printing defects, and improves the printing quality. At the same time, it reduces energy consumption and material waste, and significantly reduces the printing cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The present invention will be further described below with reference to the accompanying drawings.

[0067] Figure 1 It is a flowchart of the method steps of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0068] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0069] Please refer to Figure 1 As shown, the present invention is a path optimization method for concrete 3D printing, including:

[0070] S1. Perform slicing processing on the three-dimensional model of the concrete component to be printed, convert the sliced model into a geometric model, and initialize the position information of the geometric points in the geometric model;

[0071] S2. According to the graph theory principle, divide the geometric model into multiple areas that can be printed at one time;

[0072] First, construct the slices of the printing model into geometric figures that can be recognized by a computer. Secondly, extract and number the vertices of the geometric figures, record the coordinates of each vertex respectively, and set an adjacency matrix to describe the connection situation between each vertex. Then, store each vertex into the partition matrix according to the rules to form a partition that can be traversed at one time;

[0073] S3. Use the ant colony algorithm to find the shortest printing path within the divided multiple areas;

[0074] The specific steps of S3 are as follows:

[0075] S31. Initialize the parameters of the ant colony algorithm, including the number of ants, the initial pheromone concentration, the pheromone evaporation factor, the pheromone importance factor, and the maximum number of iterations;

[0076] S32. Construct the solution space and randomly place each ant on the starting vertex of the sub-region;

[0077] S33. Calculate and obtain the next vertex to be visited by each ant according to the pheromone concentration and the distance heuristic information;

[0078] S34. Update the pheromone concentration, and record the shortest path length and the corresponding path in the current iteration;

[0079] S35. Compare the number of iterations that have been performed with the preset maximum number of iterations. Once the maximum number of iterations is reached, terminate the iteration;

[0080] S36. Output the optimal printing path, which consists of a series of consecutive vertices and represents the movement trajectory of the print head during the printing process;

[0081] S4. Connect to the printing platform and receive the shortest printing path in S3, control the printing platform to move according to the planned optimal printing path, and at the same time control the supply rate of the concrete material to ensure the continuity and stability of the printing process.

[0082] In this embodiment, by slicing the three-dimensional model of the concrete component to be printed and converting it into a geometric model, and then dividing the geometric model into multiple regions that can be printed at one time according to the graph theory principle, the interruptions and repeated operations during the printing process are greatly reduced, thereby significantly improving the printing efficiency; the ant colony algorithm is used to find the shortest printing path in the divided multiple regions, ensuring that the path of the print head during movement is the shortest and optimal, further reducing the printing time and material waste, and at the same time improving the printing accuracy;

[0083] Meanwhile, by precisely planning the printing path and closely connecting with the printing platform, it can ensure that the print head moves along the optimal planned path, reasonably control the supply rate of the concrete material, thus guaranteeing the continuity and stability of the printing process, and avoiding printing quality problems caused by unreasonable paths or improper material supply; due to the implementation of the path optimization method, the print head can print more smoothly and continuously during movement, reducing printing defects caused by path mutations or print head jitters, etc., thereby improving the printing quality and making the printed concrete components more in line with the design requirements; by optimizing the printing path and reducing the printing time, it can significantly reduce the energy consumption and material waste of concrete 3D printing, thus reducing the printing cost and improving the economic benefits. Through the above technical solutions, the path optimization method for concrete 3D printing not only improves the printing efficiency and accuracy, but also enhances the stability and continuity of the printing process, while reducing the printing cost.

[0084] The process of calculating the next vertex to be visited by each ant is as follows:

[0085] Denote the vertex where the k-th ant is currently located as i, and the next vertex to be visited as j. Then the transition probability for the k-th ant to transfer from vertex i to vertex j

[0086] is calculated through the formula:

[0087]

[0088] and is obtained by calculation;

[0089] where s is the s-th vertex to be visited, n is the total number of vertices to be visited, δ ij (t) is the pheromone concentration on the path between vertex i and vertex j at time t, and A and B are the pheromone importance factor and heuristic information importance factor respectively, which are determined by comprehensively considering historical data and experimental data. δ is (t) is the pheromone concentration on the path between vertex i and the s-th vertex to be visited, and θ is is the distance heuristic information between vertex i and the s-th vertex to be visited, and θ ij is the distance heuristic information between vertex i and vertex j, and the expression is:

[0090]

[0091] where d(i, j) is the distance between vertex i and vertex j, and x i and x j are the abscissas of vertex i and vertex j respectively, and y i and y j are the ordinates of vertex i and vertex j respectively;

[0092] Arrange the calculated multiple transition probabilities in descending order, and take the vertex corresponding to the transition probability ranked first as the next vertex to be visited.

[0093] The calculation formula for updating the pheromone concentration is:

[0094] δ ij (t + 1) = (1 - R) * δ ij (t) + Δδ ij

[0095] where R is the pheromone evaporation rate, R is a constant, and R < 1, and Δδ ij is the increase in pheromone, and δ ij (t + 1) is the updated pheromone concentration, and δ ij (t) is the pheromone concentration before update.

[0096] The process of obtaining the increase in pheromone Δδ ij is as follows:

[0097] After the k-th ant completes a round of search and constructs a complete path, the pheromone increment of each edge (i, j) on this path is calculated through the formula:

[0098]

[0099] is obtained;

[0100] where W is the pheromone release amount, which is a constant representing the total amount of pheromone released by each ant onto the path after a complete search, and L k is the total length of the path constructed by ant k;

[0101] In each iteration, after all ants complete the search and construct the paths, it is necessary to update the pheromone on all paths;

[0102] For each edge (i, j), the pheromone increment Δδ ij is the sum of the pheromone increments contributed by all ants passing through this edge:

[0103]

[0104] where m is the total number of ants passing through this edge.

[0105] In this embodiment, by comprehensively considering the pheromone concentration and heuristic information, ants can avoid blind and repeated searches when choosing paths, significantly improving the search efficiency. This characteristic enables the algorithm to find better solutions in a short time, especially suitable for dealing with large-scale and complex path optimization problems. The introduction of pheromone concentration in the algorithm endows it with memory ability, recording high-quality path information in historical searches, guiding ants to preferentially choose these paths in subsequent searches, thereby enhancing the global optimization ability.

[0106] Meanwhile, the guidance of heuristic information prompts ants to continuously search in a better direction, further improving the algorithm performance. The parameters of the ant colony algorithm can be adjusted according to specific problems and requirements, showing extremely strong adaptability. Regardless of the type of path optimization problem, the algorithm can flexibly handle it and demonstrate good performance. In concrete 3D printing, the ant colony algorithm can calculate the optimal printing path composed of a series of continuous vertices, ensuring the continuity and stability of the printing process. It not only improves the printing quality and efficiency but also provides strong support for the development of concrete 3D printing technology.

[0107] The process of controlling the supply rate of concrete materials is as follows:

[0108] Obtain the width a of the printing path, the height b of the printing path, and the length c of the printed path in real time;

[0109] Substitute into the formula:

[0110] F = a * b * c

[0111] Calculate the amount of concrete F for the print head;

[0112] Substitute into the following formula:

[0113]

[0114] Calculate the supply rate Q of concrete materials;

[0115] Where V is the moving speed of the print head;

[0116] Compare the calculated supply rate Q of concrete materials with the supply rate threshold interval [Q - , Q + , and comprehensively judge whether it is necessary to control the supply rate of concrete materials according to the comparison result and combined with whether the predicted supply rate of concrete materials shows a stable trend.

[0117] The process of comprehensively judging whether it is necessary to control the supply rate of concrete materials is as follows:

[0118] Compare the calculated supply rate Q of concrete materials with the supply rate threshold interval [Q - , Q +Make a comparison;

[0119] If Q > Q + and the coefficient of variation Qf of the concrete material supply rate ≥ the preset warning threshold Qf 0 , then it is determined that the current supply rate of the concrete material is high, and the current supply rate of the concrete material is controlled to decrease;

[0120] If Q ∈ [Q - , Q + and the coefficient of variation Qf of the concrete material supply rate < the preset warning threshold Qf 0 , then it is determined that the current supply rate of the concrete material is normal, and the current supply rate of the concrete material is maintained unchanged;

[0121] If Q < Q - and the coefficient of variation Qf of the concrete material supply rate ≥ the preset warning threshold Qf 0 , then it is determined that the current supply rate of the concrete material is low, and the current supply rate of the concrete material is controlled to increase.

[0122] The process of obtaining the coefficient of variation of the concrete material supply rate is as follows:

[0123] Obtain the curve Q(t) of the supply rate of the concrete material changing with time within M monitoring periods;

[0124] Obtain the supply rates Qg of N concrete materials sampled at preset time intervals within each monitoring period;

[0125] Through the formula:

[0126]

[0127] Calculate the coefficient of variation Qf of the concrete material supply rate;

[0128] where Qe q is the fluctuation coefficient of the concrete material supply rate within each monitoring period, μ 1 , μ 2 are preset weight coefficients, q is the qth monitoring period, t q -t q+1 are the two time endpoints of any one monitoring period;

[0129] Compare the coefficient of variation Qf of the concrete material supply rate with the preset warning threshold Qf 0 ; if Qf ≥ Qf 0 , then it is predicted that the concrete material supply rate shows an unstable trend; if Wf < Qf 0 , then it is predicted that the concrete material supply rate shows a stable trend.

[0130] In this embodiment, the formula F = a * b * c for the amount of concrete required by the print head can accurately calculate the required amount of concrete, avoiding material waste or shortage. At the same time, the supply rate formula calculates the concrete supply rate according to the printing requirements to ensure that the print head continuously obtains an appropriate amount of material. The combined action of the two formulas not only optimizes the material use, reduces the cost, but also maintains the continuity and stability of the printing process. In addition, it can play a role in reasonably distributing concrete materials, optimizing the printing speed, improving the construction efficiency, and shortening the construction period. Moreover, the stable supply rate and accurate material calculation help to maintain the printing accuracy, improve the construction quality, and ensure the building safety;

[0131] At the same time, by analyzing the historical data, the trend of the concrete material supply rate in the subsequent printing process can be predicted. If the predicted supply rate is unstable and the calculated supply rate Q of the concrete material exceeds the preset supply rate threshold interval [W - , Q + 0, it is determined that the current supply rate of the concrete material is high and the current supply rate of the concrete material needs to be controlled to decrease; if the predicted supply rate is unstable and Q < Q - , it is determined that the current supply rate of the concrete material is low and the current supply rate of the concrete material is controlled to increase; if the predicted supply rate is stable and Q ∈ [Q - , Q + , it is determined that the current supply rate of the concrete material is normal and the current supply rate of the concrete material remains unchanged. Through the trend prediction of the concrete material supply rate, it is possible to prepare in advance for the adjustment of the attack speed of the print head to prevent as much as possible the situation of insufficient supply caused by print head blockage or the situation of excessive supply caused by print head leakage, comprehensively improving the stability of concrete printing.

[0132] It should be noted that: the calculation formulas and each parameter participating in the operation in the present invention are all pre-dimensionless processed, and the process of dimensionless processing is well known in the industry and will not be described here.

[0133] The above has described a detailed description of an embodiment of the present invention, but the content described is only a preferred embodiment of the present invention and cannot be considered as limiting the scope of implementation of the present invention. All equivalent changes and improvements made according to the scope of the present invention application should still fall within the scope covered by the patent of the present invention.

Claims

1. A path optimization method for concrete 3D printing, characterized in that: include: S1, slicing the three-dimensional model of the concrete component to be printed, converting the sliced ​​model into a geometric model, and initializing the position information of the geometric points in the geometric model; S2. Based on the principles of graph theory, the geometric model is divided into multiple areas that can be printed at one time; First, the slices of the printed model are constructed into geometric figures that can be recognized by the computer. Then, the vertices of the geometric figures are extracted and numbered, the coordinates of each vertex are recorded separately, and an adjacency matrix is ​​set to describe the connection between the vertices. Then, the vertices are stored in the partition matrix according to the rules to form partitions that can be traversed at one time. S3, using the ant colony algorithm to find the shortest printing path in the divided multiple areas; S4, connects to the printing platform and receives the shortest printing path in S3, controls the printing platform to move according to the planned optimal printing path, and controls the supply rate of the concrete material to ensure the continuity and stability of the printing process.

2. The path optimization method for concrete 3D printing according to claim 1, characterized in that: The specific steps of S3 are as follows: S31, initializing the parameters of the ant colony algorithm, including the number of ants, the initial concentration of pheromones, the pheromone volatility factor, the pheromone importance factor, and the maximum number of iterations; S32, construct the solution space, and randomly place each ant on the starting vertex of the sub-region; S33, calculating and obtaining the next vertex to be visited by each ant according to the pheromone concentration and distance heuristic information; S34, updating the pheromone concentration, recording the shortest path length and the corresponding path in the current iteration number; S35, comparing the number of iterations completed with a preset maximum number of iterations, and terminating the iteration once the maximum number of iterations is reached; S36. Output an optimal printing path, which is composed of a series of continuous vertices and represents the movement trajectory of the print head during the printing process.

3. The path optimization method for concrete 3D printing according to claim 2, characterized in that: The process of calculating the next vertex to be visited by each ant is: The current vertex of the kth ant is recorded as i, and the next vertex to be visited is recorded as j. Then the transfer probability of the kth ant from vertex i to vertex j is By formula: Calculated; Among them, s is the sth vertex to be visited, n is the total number of vertices to be visited, δ ij (t) is the pheromone concentration on the path between vertex i and vertex j at time t, A and B are the pheromone importance factor and heuristic information importance factor respectively, δ is (t) is the pheromone concentration on the path between vertex i and the sth vertex to be visited, θ is is the distance heuristic information between vertex i and the sth vertex to be visited, θ ij is the distance heuristic information between vertex i and vertex j, expressed as: Where d(i, j) is the distance between vertex i and vertex j, x i 、x j are the horizontal coordinates of vertex i and vertex j, y i ,y j are the ordinates of vertex i and vertex j respectively; The multiple transition probabilities obtained will be calculated Arrange them in descending order, and take the vertex corresponding to the first-ranked transition probability as the next vertex to be visited.

4. The path optimization method for concrete 3D printing according to claim 3, characterized in that: The calculation formula for updating pheromone concentration is: d ij (t+1)=(1-R)*δ ij (t)+Δδ ij Among them, R is the pheromone volatility, R is a constant, and R<1, Δδ ij is the increase in pheromone, δ ij (t+1) is the updated pheromone concentration, δ ij (t) is the pheromone concentration before updating.

5. The path optimization method for concrete 3D printing according to claim 4, characterized in that: The increase in the amount of the pheromone Δδ ij The acquisition process is: After the kth ant completes a round of search and builds a complete path, the pheromone increment of each edge (i, j) on the path By formula: Calculated; Where W is the pheromone release amount, which is a constant representing the total amount of pheromone released by each ant on the path after a complete search. k is the total length of the path constructed by ant k; In each iteration, after all ants have completed searching and building paths, they need to update the pheromones on all paths; For each edge (i, j), the pheromone increment Δδ ij It is the sum of the pheromone increments contributed by all ants passing through this edge: Among them, m is the total number of ants passing through this edge.

6. The path optimization method for concrete 3D printing according to claim 1, characterized in that: The process of controlling the feed rate of concrete material is: Obtain the width a of the printing path, the height b of the printing path, and the length c of the printed path in real time; Substituting into the formula: F=a*b*c The amount of concrete F on the print head is calculated; Substitute the following formula: The supply rate Q of concrete material is calculated; Wherein, V is the moving speed of the print head; The calculated concrete material supply rate Q and supply rate threshold interval [Q - , Q + ] for comparison, and based on the comparison results and combined with the prediction of whether the concrete material supply rate shows a stable trend, a comprehensive judgment can be made as to whether the concrete material supply rate needs to be controlled.

7. The path optimization method for concrete 3D printing according to claim 6, characterized in that: The process of comprehensively judging whether it is necessary to control the supply rate of concrete materials is as follows: The calculated concrete material supply rate Q and supply rate threshold interval [Q - , Q + ] for comparison; If Q>Q + If the change coefficient Qf of the concrete material supply rate is greater than or equal to the preset warning threshold Qf0, it is determined that the current concrete material supply rate is high, and the current concrete material supply rate is controlled to decrease; If Q∈[Q - , Q + ] and the change coefficient Qf of the concrete material supply rate is less than the preset warning threshold Qf0, then it is judged that the current concrete material supply rate is normal, and the current concrete material supply rate is maintained unchanged; If Q<Q - If the variation coefficient Qf of the concrete material supply rate is greater than or equal to the preset warning threshold Qf0, it is determined that the current concrete material supply rate is low, and the current concrete material supply rate is controlled to increase.

8. The path optimization method for concrete 3D printing according to claim 7, characterized in that: The process of obtaining the coefficient of variation of concrete material supply rate is: Obtain the curve Q(t) of the supply rate of concrete material changing with time during M monitoring periods; Obtaining the supply rate Qg of N concrete materials sampled at preset time intervals in each monitoring cycle; By formula: The coefficient of variation of the concrete material supply rate Qf is calculated; Among them, Qe q is the fluctuation coefficient of the concrete material supply rate in each monitoring period, μ1 and μ2 are the preset weight coefficients, q is the qth monitoring period, t q -t q+1 are the two time endpoints of any monitoring cycle; Compare the variation coefficient Qf of the concrete material supply rate with the preset warning threshold Qf0; if Qf ≥ Qf0, it is predicted that the concrete material supply rate shows an unstable trend; if Qf < Qf0, it is predicted that the concrete material supply rate shows a stable trend.

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