Concrete 3D printing defect detection method based on image data analysis

Abstract

The invention relates to the technical field of defect detection, and discloses a concrete 3D printing defect detection method, which comprises the following steps of: in a 3D printing process, sequentially acquiring a side view image and a top view image of a concrete 3D printing piece when each layer is constructed through a double-camera acquisition system; whether a material excessive deposition defect or a potential material excessive deposition defect risk exists in the 3D printing process or not is detected based on the side view image, and whether a printing layer discontinuous defect acquirer has a potential printing layer discontinuous defect risk or not in the 3D printing process or not is detected based on the real-time image data of the top view image. Through real-time data and continuous data, defects and potential defects in the printing process are found and processed in time, the time and cost of manual inspection are reduced, and the production efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of defect detection, and in particular to a concrete 3D printing defect detection method based on image data analysis. Background Art

[0002] The application of 3D printing technology in the field of construction is becoming more and more extensive. Among them, concrete 3D printing, as an emerging construction method, has the advantages of fast construction speed, low cost and high customization.

[0003] Most existing concrete 3D printed part defect detection methods are based on the detection and analysis of finished products. However, in the actual printing process, due to the influence of various factors (such as nozzle movement rate, material extrusion rate, material properties, etc.), concrete 3D printed parts may have various defects, such as discontinuous printing layers and excessive material deposition risks. These defects not only affect the appearance quality of the printed parts, but also may affect their structural performance and service life. Therefore, the present invention proposes a concrete 3D printing defect detection method based on image data analysis. Summary of the invention

[0004] The purpose of the present invention is to provide a concrete 3D printing defect detection method based on image data analysis to solve the above technical problems.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A method for detecting defects in 3D concrete printing based on image data analysis, the method comprising the following steps:

[0007] Step S1, using a dual-camera image acquisition system to periodically acquire images of the concrete 3D printed part during the 3D printing process, including side view images and top view images, to obtain a number of monitoring images of the concrete 3D printed part;

[0008] Step S2, preprocessing the collected monitoring image of the concrete 3D printed part, including grayscale processing, noise reduction processing, and binarization processing, so as to improve the image quality and facilitate subsequent defect identification;

[0009] Step S3: analyzing whether there is a material over-deposition defect in concrete 3D printing based on the continuous change of the side view image;

[0010] Step S4: Analyze whether there is a discontinuous printing layer defect in the concrete 3D printing based on the continuous change of the top view image.

[0011] As a further description of the solution of the present invention, the specific working process of step S1 is as follows:

[0012] Get the total number of layers set in the 3D printing process and number them in the following order: 1, 2, ..., n;

[0013] When each layer is completed, the dual-camera acquisition system is used to obtain the side view and top view images of the concrete 3D printed part.

[0014] As a further description of the solution of the present invention, the specific process of step S3 includes:

[0015] When the concrete 3D printing completes the i-th layer construction, the side view image of the current concrete 3D printed part is obtained, and based on the side view image data of the concrete 3D printed part, the actual height h of the i-th layer construction of the concrete 3D printed part is obtained. i and the actual width d i , and obtain the time consumed by concrete 3D printing to complete the i-th layer construction, where i belongs to n;

[0016] Get the preset concrete 3D printing model of the system, and based on the preset concrete 3D printing model data of the system, get the preset height h of the i-th layer of the concrete 3D printed part i0 and preset width d i0 ;

[0017] Construct a mathematical model of material over-deposition defect coefficient, the expression is:

[0018]

[0019] In the formula, α and β are the weight coefficients corresponding to the height and width respectively, σ i Build material over-deposition defect coefficient for layer i of concrete 3D print.

[0020] As a further description of the solution of the present invention, the specific process of step S3 also includes:

[0021] The over-deposition defect coefficient σ of the i-th layer of the concrete 3D printed part is i The over-deposition defect coefficient threshold σ of the i-th layer of concrete 3D printed parts preset by the system ith By comparison, if the over-deposition defect coefficient σ of the i-th layer of building material i Greater than or equal to the system preset threshold value σ of the excessive deposition defect coefficient of the i-th layer of the concrete 3D printed part ith , indicating that there is a material over-deposition defect when the i-th layer is built. If the i-th layer material over-deposition defect coefficient σ i Less than the system preset threshold value σ of the over-deposition defect coefficient of the i-th layer of the concrete 3D printed part ith , then we can further judge whether there is a potential material over-deposition defect in the concrete 3D printing process.

[0022] As a further description of the solution of the present invention, the specific process of further determining whether there is a potential material over-deposition defect in the concrete 3D printing process includes:

[0023] The mathematical model of potential material over-deposition defect coefficient of concrete 3D printing is constructed, and the expression is:

[0024]

[0025] Where, T i is the time it takes for concrete 3D printing to complete the i-th layer, m is the total number of layers currently completed by concrete 3D printing, where i belongs to m, m belongs to n, and T S is the time required by the system to complete the construction of m layers of concrete 3D printing, h S is the height of the concrete 3D printed part when the system presets the concrete 3D printing to complete the m-layer construction, σ m is the potential material over-deposition defect coefficient of concrete 3D printing, k i The weight coefficient corresponding to the i-th construction layer.

[0026] As a further description of the solution of the present invention, the specific process of further determining whether there is a potential material over-deposition defect in the concrete 3D printing process also includes:

[0027] The potential material over-deposition defect coefficient σ of concrete 3D printing m Compared with the system preset concrete 3D printing potential material over-deposition defect coefficient threshold σ mth By comparison, if the potential material over-deposition defect coefficient σ of concrete 3D printing is m Greater than or equal to the system preset concrete 3D printing potential material over-deposition defect coefficient threshold σ mth , it means that there is a risk of potential material over-deposition defects in the concrete 3D printing process. Otherwise, it means that there is no risk of potential material over-deposition defects in the concrete 3D printing process.

[0028] As a further description of the solution of the present invention, the specific process of step S4 includes:

[0029] When each layer of concrete 3D printing is completed, the top view image of the concrete 3D printed part is obtained in sequence, and the top view image of each layer of construction is input into the trained neural network model, and the deviation index of each construction layer is obtained as output;

[0030] The deviation index of each building layer is compared with the corresponding standard deviation index range of each building layer preset by the system in turn. If the deviation index of any building layer does not meet the standard deviation index range, it indicates that there is a discontinuous printing layer defect in the concrete 3D printing process;

[0031] If there is no construction layer whose deviation index does not meet the standard range of the deviation index, it is further determined whether there is a potential printing layer discontinuity defect in the concrete 3D printing process.

[0032] As a further description of the solution of the present invention, the specific process of further determining whether there is a potential printing layer discontinuity defect in the concrete 3D printing process includes:

[0033] The mathematical model of discontinuity defect coefficient of potential printing layer of concrete 3D printing is constructed, and the expression is:

[0034]

[0035] Where, T i is the time it takes for concrete 3D printing to complete the i-th layer, m is the total number of layers currently completed by concrete 3D printing, where i belongs to m, m belongs to n, and T S is the time required by the system to complete the construction of m layers of concrete 3D printing, k i is the weight coefficient corresponding to the i-th construction layer, S i is the deviation index of the i-th construction layer, S i0 is the standard value of the deviation index of the i-th construction layer preset by the system, G i is the preset difference reference value.

[0036] As a further description of the solution of the present invention, the specific process of further determining whether there is a potential printing layer discontinuity defect in the concrete 3D printing process also includes:

[0037] The potential discontinuity defect coefficient of concrete 3D printing layer ρ m The potential discontinuity defect coefficient threshold ρ of concrete 3D printing preset by the system mth By comparison, if the potential discontinuity defect coefficient of concrete 3D printing layer is m Greater than or equal to the system preset concrete 3D printing potential printing layer discontinuity defect coefficient threshold ρ mth , it means that there is a risk of potential discontinuity of printing layers in the concrete 3D printing process. Otherwise, it means that there is no risk of potential discontinuity of printing layers in the concrete 3D printing process.

[0038] Beneficial effects of the present invention: The present invention provides a concrete 3D printing defect detection method. In the 3D printing process, the present invention uses a dual-camera acquisition system to sequentially acquire the side view image and the top view image of the concrete 3D print when each layer of construction is completed, and calculates the material over-deposition defect coefficient based on the real-time image data of the side view image. The material over-deposition defect coefficient is used to calculate whether there is a material over-deposition defect in the concrete 3D printing at present. If there is no material over-deposition defect at present, the potential material over-deposition defect coefficient of the concrete 3D printing is calculated based on the continuous change of the side view image. The potential material over-deposition defect coefficient of the concrete 3D printing is used to judge whether there is a potential material over-deposition defect in the 3D printing process. In the case of the risk of excessive material deposition defects, the deviation index of each building layer is obtained based on the real-time image data of the overhead image. According to the deviation index of each building layer, it is judged whether there is a printing layer discontinuity defect in the concrete 3D printing at present. If there is no printing layer discontinuity defect at present, the potential printing layer discontinuity defect coefficient of concrete 3D printing is calculated based on the continuous change of the overhead image. The potential printing layer discontinuity defect coefficient of concrete 3D printing is used to judge whether there is a risk of potential printing layer discontinuity defect in the 3D printing process. Through real-time data and continuous data, defects and potential defects in the printing process can be discovered and handled in time, which reduces the time and cost of manual inspection and improves production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The present invention will be further described below in conjunction with the accompanying drawings.

[0040] Figure 1 It is a partial flow chart of the concrete 3D printing defect detection method based on image data analysis provided by the present invention. DETAILED DESCRIPTION

[0041] 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.

[0042] See also Figure 1 The present invention is a concrete 3D printing defect detection method based on image data analysis, the method comprising the following steps:

[0043] Step S1, using a dual-camera image acquisition system to acquire images of a 3D printed concrete part during the 3D printing process, including side view images and top view images, to obtain a number of monitoring images of the 3D printed concrete part;

[0044] Step S2, preprocessing the collected monitoring image of the concrete 3D printed part, including grayscale processing, noise reduction processing, and binarization processing, so as to improve the image quality and facilitate subsequent defect identification;

[0045] Step S3: analyzing whether there is a material over-deposition defect in concrete 3D printing based on the continuous change of the side view image;

[0046] Step S4: Analyze whether there is a discontinuous printing layer defect in the concrete 3D printing based on the continuous change of the top view image.

[0047] Through the above technical scheme, the present invention provides a concrete 3D printing defect detection method. In the 3D printing process, the present invention sequentially collects the side view image and the top view image of the concrete 3D printed part when each layer of construction is completed through a dual-camera acquisition system, calculates the material over-deposition defect coefficient based on the real-time image data of the side view image, calculates whether there is a material over-deposition defect in the concrete 3D printing at present through the material over-deposition defect coefficient, if there is no material over-deposition defect at present, calculates the potential material over-deposition defect coefficient of the concrete 3D printing based on the continuous change of the side view image, judges whether there is a risk of potential material over-deposition defect in the 3D printing process through the potential material over-deposition defect coefficient of the concrete 3D printing, obtains the deviation index of each construction layer based on the real-time image data of the top view image, judges whether there is a printing layer discontinuity defect in the concrete 3D printing at present according to the deviation index of each construction layer, if there is no printing layer discontinuity defect at present, calculates the potential printing layer discontinuity defect coefficient of the concrete 3D printing based on the continuous change of the top view image, and judges whether there is a risk of potential printing layer discontinuity defect in the 3D printing process through the potential printing layer discontinuity defect coefficient of the concrete 3D printing.

[0048] The specific working process of step S1 is as follows:

[0049] Get the total number of layers set in the 3D printing process and number them in the following order: 1, 2, ..., n;

[0050] When each layer is completed, the dual-camera acquisition system is used to obtain the side view and top view images of the concrete 3D printed part.

[0051] The specific process of step S3 includes:

[0052] When the concrete 3D printing completes the i-th layer construction, the side view image of the current concrete 3D printed part is obtained, and based on the side view image data of the concrete 3D printed part, the actual height h of the i-th layer construction of the concrete 3D printed part is obtained. i and the actual width d i , and obtain the time consumed by concrete 3D printing to complete the i-th layer construction, where i belongs to n;

[0053] Get the preset concrete 3D printing model of the system, and based on the preset concrete 3D printing model data of the system, get the preset height h of the i-th layer of the concrete 3D printed part i0 and preset width d i0 ;

[0054] Construct a mathematical model of material over-deposition defect coefficient, the expression is:

[0055]

[0056] In the formula, α and β are the weight coefficients corresponding to the height and width respectively, σ i Build material over-deposition defect coefficient for layer i of concrete 3D print.

[0057] The specific process of step S3 also includes:

[0058] The over-deposition defect coefficient σ of the i-th layer of the concrete 3D printed part is i The over-deposition defect coefficient threshold σ of the i-th layer of concrete 3D printed parts preset by the system ith By comparison, if the over-deposition defect coefficient σ of the i-th layer of building material i Greater than or equal to the system preset threshold value σ of the excessive deposition defect coefficient of the i-th layer of the concrete 3D printed part ith , indicating that there is a material over-deposition defect when the i-th layer is built. If the i-th layer material over-deposition defect coefficient σ i Less than the system preset threshold value σ of the over-deposition defect coefficient of the i-th layer of the concrete 3D printed part ith , then we can further judge whether there is a potential material over-deposition defect in the concrete 3D printing process.

[0059] The specific process of further determining whether there is a potential material over-deposition defect in the concrete 3D printing process includes:

[0060] The mathematical model of potential material over-deposition defect coefficient of concrete 3D printing is constructed, and the expression is:

[0061]

[0062] Where, T i is the time it takes for concrete 3D printing to complete the i-th layer, m is the total number of layers currently completed by concrete 3D printing, where i belongs to m, m belongs to n, and T S is the time required by the system to complete the construction of m layers of concrete 3D printing, h S is the height of the concrete 3D printed part when the system presets the concrete 3D printing to complete the m-layer construction, σm is the potential material over-deposition defect coefficient of concrete 3D printing, k i The weight coefficient corresponding to the i-th construction layer.

[0063] The specific process of further determining whether there is a potential material over-deposition defect in the concrete 3D printing process also includes:

[0064] The potential material over-deposition defect coefficient σ of concrete 3D printing m Compared with the system preset concrete 3D printing potential material over-deposition defect coefficient threshold σ mth By comparison, if the potential material over-deposition defect coefficient σ of concrete 3D printing is m Greater than or equal to the system preset concrete 3D printing potential material over-deposition defect coefficient threshold σ mth , it means that there is a risk of potential material over-deposition defects in the concrete 3D printing process. Otherwise, it means that there is no risk of potential material over-deposition defects in the concrete 3D printing process.

[0065] Through the above technical solution, this embodiment provides a method for detecting excessive material deposition defects in a concrete 3D printing process, and obtains the actual height h of the i-th layer of the concrete 3D printed part. i and the actual width d i , calculate the over-deposition defect coefficient σ of the i-th layer of the concrete 3D printed part based on the obtained parameters i , the over-deposition defect coefficient σ of the i-th layer of the concrete 3D printed part i The over-deposition defect coefficient threshold σ of the i-th layer of concrete 3D printed parts preset by the system ith By comparison, if the over-deposition defect coefficient σ of the i-th layer of building material i Greater than or equal to the system preset threshold value σ of the excessive deposition defect coefficient of the i-th layer of the concrete 3D printed part ith , indicating that there is a material over-deposition defect when the i-th layer is built. If the i-th layer material over-deposition defect coefficient σ i Less than the system preset threshold value σ of the over-deposition defect coefficient of the i-th layer of the concrete 3D printed part ith , the potential material over-deposition defect coefficient σ of concrete 3D printing is calculated based on the acquired continuous image data m , m is the number of layers currently completed, and the potential material over-deposition defect coefficient of concrete 3D printing is σ m Compared with the system preset concrete 3D printing potential material over-deposition defect coefficient threshold σ mth By comparison, if the potential material over-deposition defect coefficient σ of concrete 3D printing is m Greater than or equal to the system preset concrete 3D printing potential material over-deposition defect coefficient threshold σmth , it means that there is a risk of potential material over-deposition defects in the concrete 3D printing process. Otherwise, it means that there is no risk of potential material over-deposition defects in the concrete 3D printing process.

[0066] The specific process of step S4 includes:

[0067] When each layer of concrete 3D printing is completed, the top view image of the concrete 3D printed part is obtained in sequence, and the top view image of each layer of construction is input into the trained neural network model, and the deviation index of each construction layer is obtained as output;

[0068] The deviation index of each building layer is compared with the corresponding standard deviation index range of each building layer preset by the system in turn. If the deviation index of any building layer does not meet the standard deviation index range, it indicates that there is a discontinuous printing layer defect in the concrete 3D printing process;

[0069] If there is no construction layer whose deviation index does not meet the standard range of the deviation index, it is further determined whether there is a potential printing layer discontinuity defect in the concrete 3D printing process.

[0070] The specific process of further determining whether there is a potential printing layer discontinuity defect in the concrete 3D printing process includes:

[0071] The mathematical model of discontinuity defect coefficient of potential printing layer of concrete 3D printing is constructed, and the expression is:

[0072]

[0073] Where, T i is the time it takes for concrete 3D printing to complete the i-th layer, m is the total number of layers currently completed by concrete 3D printing, where i belongs to m, m belongs to n, and T S is the time required by the system to complete the construction of m layers of concrete 3D printing, k i is the weight coefficient corresponding to the i-th construction layer, S i is the deviation index of the i-th construction layer, S i0 is the standard value of the deviation index of the i-th construction layer preset by the system, G i is the preset difference reference value.

[0074] The specific process of further determining whether there is a potential printing layer discontinuity defect in the concrete 3D printing process also includes:

[0075] The potential discontinuity defect coefficient of concrete 3D printing layer ρ m The potential discontinuity defect coefficient threshold ρ of concrete 3D printing preset by the system mthBy comparison, if the potential discontinuity defect coefficient of concrete 3D printing layer is m Greater than or equal to the system preset concrete 3D printing potential printing layer discontinuity defect coefficient threshold ρ mth , it means that there is a risk of potential discontinuity of printing layers in the concrete 3D printing process. Otherwise, it means that there is no risk of potential discontinuity of printing layers in the concrete 3D printing process.

[0076] Through the above technical scheme, this embodiment provides a method for detecting discontinuous defects in printing layers during concrete 3D printing, obtains a top view image of a concrete 3D printed part, inputs a top view image of each layer of the completed construction into a trained neural network model, outputs a deviation index of each construction layer, and sequentially compares the deviation index of each construction layer with a corresponding standard interval of deviation indexes preset by the system for each construction layer. If the deviation index of any construction layer does not satisfy the standard interval of deviation indexes, it indicates that there is a discontinuous defect in printing layers during concrete 3D printing. If the deviation index of any construction layer does not satisfy the standard interval of deviation indexes, a potential discontinuous defect coefficient of concrete 3D printing is calculated according to the deviation index of each construction layer, and the potential discontinuous defect coefficient of concrete 3D printing is calculated. m The potential discontinuity defect coefficient threshold ρ of concrete 3D printing preset by the system mth By comparison, if the potential discontinuity defect coefficient of concrete 3D printing layer is m Greater than or equal to the system preset concrete 3D printing potential printing layer discontinuity defect coefficient threshold ρ mth , it means that there is a risk of potential discontinuity of printing layers in the concrete 3D printing process. Otherwise, it means that there is no risk of potential discontinuity of printing layers in the concrete 3D printing process.

[0077] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for detecting defects in concrete 3D printing based on image data analysis, characterized in that: The method comprises the following steps: Step S1, using a dual-camera image acquisition system to periodically acquire images of the concrete 3D printed part during the 3D printing process, including side view images and top view images, to obtain a number of monitoring images of the concrete 3D printed part; Step S2, preprocessing the collected monitoring image of the concrete 3D printed part, including grayscale processing, noise reduction processing, and binarization processing, so as to improve the image quality and facilitate subsequent defect identification; Step S3: analyzing whether there is a material over-deposition defect in concrete 3D printing based on the continuous change of the side view image; Step S4: Analyze whether there is a discontinuous printing layer defect in the concrete 3D printing based on the continuous change of the top view image.

2. A method for detecting defects in 3D printing of concrete based on image data analysis according to claim 1, characterized in that: The specific working process of step S1 is as follows: Get the total number of layers set in the 3D printing process and number them in the following order: 1, 2, ..., n; When each layer is completed, the dual-camera acquisition system is used to obtain the side view and top view images of the concrete 3D printed part.

3. The method for detecting defects in 3D printing of concrete based on image data analysis according to claim 1, characterized in that: The specific process of step S3 includes: When the concrete 3D printing completes the i-th layer construction, the side view image of the current concrete 3D printed part is obtained, and based on the side view image data of the concrete 3D printed part, the actual height h of the i-th layer construction of the concrete 3D printed part is obtained. i and the actual width d i , and obtain the time consumed by concrete 3D printing to complete the i-th layer construction, where i belongs to n; Get the preset concrete 3D printing model of the system, and based on the preset concrete 3D printing model data of the system, get the preset height h of the i-th layer of the concrete 3D printed part i0 and preset width d i0 ; Construct a mathematical model of material over-deposition defect coefficient, the expression is: In the formula, α and β are the weight coefficients corresponding to the height and width respectively, σ i Build material over-deposition defect coefficient for layer i of concrete 3D print.

4. A method for detecting defects in 3D printing of concrete based on image data analysis according to claim 3, characterized in that: The specific process of step S3 also includes: The over-deposition defect coefficient σ of the i-th layer of the concrete 3D printed part is i The over-deposition defect coefficient threshold σ of the i-th layer of concrete 3D printed parts preset by the system ith By comparison, if the over-deposition defect coefficient σ of the i-th layer of building material i Greater than or equal to the system preset threshold value σ of the excessive deposition defect coefficient of the i-th layer of the concrete 3D printed part ith , indicating that there is a material over-deposition defect when the i-th layer is built. If the i-th layer material over-deposition defect coefficient σ i Less than the system preset threshold value σ of the over-deposition defect coefficient of the i-th layer of the concrete 3D printed part ith , then we can further judge whether there is a potential material over-deposition defect in the concrete 3D printing process.

5. A method for detecting defects in 3D printing of concrete based on image data analysis according to claim 4, characterized in that: The specific process of further determining whether there is a potential material over-deposition defect in the concrete 3D printing process includes: The mathematical model of potential material over-deposition defect coefficient of concrete 3D printing is constructed, and the expression is: Where, T i is the time it takes for concrete 3D printing to complete the i-th layer, m is the total number of layers currently completed by concrete 3D printing, where i belongs to m, m belongs to n, and T S is the time required by the system to complete the construction of m layers of concrete 3D printing, h S is the height of the concrete 3D printed part when the system presets the concrete 3D printing to complete the m-layer construction, σ m is the potential material over-deposition defect coefficient of concrete 3D printing, k i The weight coefficient corresponding to the i-th construction layer.

6. The method for detecting defects in 3D printing of concrete based on image data analysis according to claim 5, characterized in that: The specific process of further determining whether there is a potential material over-deposition defect in the concrete 3D printing process also includes: The potential material over-deposition defect coefficient σ of concrete 3D printing m Compared with the system preset concrete 3D printing potential material over-deposition defect coefficient threshold σ mth By comparison, if the potential material over-deposition defect coefficient σ of concrete 3D printing is m Greater than or equal to the system preset concrete 3D printing potential material over-deposition defect coefficient threshold σ mth , it means that there is a risk of potential material over-deposition defects in the concrete 3D printing process. Otherwise, it means that there is no risk of potential material over-deposition defects in the concrete 3D printing process.

7. The method for detecting defects in concrete 3D printing based on image data analysis according to claim 1, characterized in that: The specific process of step S4 includes: When each layer of concrete 3D printing is completed, the top view image of the concrete 3D printed part is obtained in sequence, and the top view image of each layer of construction is input into the trained neural network model, and the deviation index of each construction layer is obtained as output; The deviation index of each building layer is compared with the corresponding standard deviation index range of each building layer preset by the system in turn. If the deviation index of any building layer does not meet the standard deviation index range, it indicates that there is a discontinuous printing layer defect in the concrete 3D printing process; If there is no construction layer whose deviation index does not meet the standard range of the deviation index, it is further determined whether there is a potential printing layer discontinuity defect in the concrete 3D printing process.

8. The method for detecting defects in concrete 3D printing based on image data analysis according to claim 7, characterized in that: The specific process of further determining whether there is a potential printing layer discontinuity defect in the concrete 3D printing process includes: The mathematical model of discontinuity defect coefficient of potential printing layer of concrete 3D printing is constructed, and the expression is: Where, T i is the time it takes for concrete 3D printing to complete the i-th layer, m is the total number of layers currently completed by concrete 3D printing, where i belongs to m, m belongs to n, and T S is the time required by the system to complete the construction of m layers of concrete 3D printing, k i is the weight coefficient corresponding to the i-th construction layer, S i is the deviation index of the i-th construction layer, S i0 is the standard value of the deviation index of the i-th construction layer preset by the system, G i is the preset difference reference value.

9. The method for detecting defects in 3D printing of concrete based on image data analysis according to claim 8, characterized in that: The specific process of further determining whether there is a potential printing layer discontinuity defect in the concrete 3D printing process also includes: The potential discontinuity defect coefficient of concrete 3D printing layer ρ m The potential discontinuity defect coefficient threshold ρ of concrete 3D printing preset by the system mth By comparison, if the potential discontinuity defect coefficient of concrete 3D printing layer is m Greater than or equal to the system preset concrete 3D printing potential printing layer discontinuity defect coefficient threshold ρ mth , it means that there is a risk of potential discontinuity of printing layers in the concrete 3D printing process. Otherwise, it means that there is no risk of potential discontinuity of printing layers in the concrete 3D printing process.

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