3D Concrete Printing Quality Monitoring and Control System and Method

Abstract

The quality monitoring and control system for concrete 3D printers is used in conjunction with a 3D concrete printer having a print head equipped with a nozzle for extruding concrete. The system includes a camera assembly with one or more cameras sensitive to a specific wavelength range, configured to capture the concrete layer surface and image data from the concrete layer surface. The system further includes a computing device that communicates with the camera assembly. This computing device includes a communication module for receiving image data, a storage device for storing image analysis commands and algorithm commands, and a processing device that generates one or more surface state parameters from the image data based on the image analysis commands and generates analysis results (e.g., setting progress and predicted interlayer adhesion strength) based on one or more surface state parameters as a result of the algorithm commands.

Description

Detailed Description of the Invention

[0001] (Reference to Related Applications) This application claims the priority of U.S. Provisional Patent Application No. 63 / 518,430, filed on August 9, 2023, the entire content of which is incorporated herein by reference in its entirety.

[0002] (Technical Field) The present disclosure relates to systems and methods for 3D concrete printing quality monitoring and control. More specifically, the present disclosure relates to systems and methods for monitoring and controlling the quality of 3D concrete printing considering environmental factors by acquiring and using image data of a concrete surface (such as a surface on which concrete will be printed).

[0003] (Background) With the spread and increasing usefulness of 3D printing processes, new additive manufacturing processes for other materials have been developed. In fact, since the first proof-of-concept project regarding the additive process using concrete, numerous studies have been conducted on approaches, devices, and methods related to 3D concrete printing (3DCP). These research efforts have been driven by potentially significant economic and environmental benefits. In fact, the use of 3DCP usually involves eliminating the need for formwork, minimizing labor, shortening the construction period, and reducing environmental impact.

[0004] Research on 3DCP has made remarkable progress and discoveries, but most of them are in a controlled environment such as a laboratory or a factory. However, structures produced using 3DCP are generally heavy and cannot be easily transported. Therefore, the majority of applications of any 3DCP system and project will be carried out in a generally uncontrolled environment, the site. There are numerous uncontrollable environmental factors at the site, such as temperature, sunlight exposure, wind, humidity, dust, etc., which generally do not exist in a controlled factory or laboratory.

[0005] A crucial aspect of any 3D Cement Printing (3DCP) system and operation is interlayer adhesion strength, the ability of printed concrete layers to adhere to previous layers. Interlayer adhesion strength is particularly important for the structural capability of structures such as walls and significantly impacts the mechanical properties and durability of printed structures under various environmental conditions. Interlayer adhesion strength is influenced by many factors, including the properties of the cement mixture, the mixing process, the pouring speed, the curing method, and plasticity shrinkage. In addition, interlayer adhesion strength is also affected by environmental factors. Aspects that are even more important in any 3DCP system and operation, and are also influenced by factors including those mentioned above, are concrete setting progress, surface roughness, and concrete bead quality.

[0006] Currently, methodologies related to 3DCP involve conservative and strict control conditions regarding water-cement ratio and time. Deviating from these strict control conditions, especially those related to time, will, at best, require additional measures to aid interlayer adhesion, and at worst, mean the failure of the entire project.

[0007] However, such strict control does not take into account all factors, particularly environmental factors, that affect critical aspects of 3DCP, such as concrete setting progress, surface roughness, concrete bead quality, and interlayer adhesion strength. Furthermore, these strict controls do not provide an informed and effective quality monitoring and control system (which can provide accurate and timely information about the work based on current printing operations). In fact, the ideal printing interval between layers varies depending on environmental factors and (although not in practice) can be determined if the concrete setting progress is known and monitored. Moreover, an effective quality monitoring and control system can facilitate the adaptation of future regulations that have not yet been determined into appropriate controls that are not unnecessarily conservative.

[0008] Therefore, a quality monitoring and control system is needed to provide consistency to 3DCP projects, offering effective, data-driven information for 3D concrete printing, including concrete setting progress, surface roughness, concrete bead quality, and interlayer adhesion strength, while considering environmental factors, and providing better guidance for parameters related to the printing of each concrete layer.

[0009] overview This summary is provided to introduce concepts that are further elaborated in the detailed description below in a simplified form. This summary is not intended to identify any important or essential features of the claimed subject matter, nor should it be construed as limiting the scope of the claimed subject matter.

[0010] From the above perspective, one of the objectives of this quality monitoring and control system is to provide useful and effective information for 3DCP, such as concrete setting progress, surface roughness, concrete bead quality, and interlayer adhesion strength, taking environmental factors into consideration, and to comprehensively improve the guidelines for determining parameters related to the concrete printing process.

[0011] According to some embodiments, a 3DCP quality monitoring and control system for use in a 3D concrete printer equipped with a print head terminated at a nozzle having an opening for spraying concrete includes a camera assembly comprising one or more cameras configured to be sensitive to at least one specific wavelength range and having a field of view including at least a portion of the concrete layer surface. The one or more cameras are configured to capture image data from the concrete layer surface. In the embodiments, the quality monitoring and control system includes a computing device that communicates with the camera assembly. This computing device includes a communication module that receives image data transmitted from the camera assembly, one or more storage devices that store the image data, and instructions that include at least image analysis instructions and algorithm instructions. The processing unit is configured to generate one or more surface state parameters from the stored image data using the image analysis instructions and to generate analysis results based on at least one or more surface state parameters using the algorithm instructions.

[0012] In the embodiments, the camera assembly comprises a mount for fixing and supporting one or more cameras, and the field of view of one or more cameras is independent of the movement of the nozzle. In certain embodiments, both the mount and the field of view of one or more cameras are fixed. In other embodiments, at least one of the mount and the field of view of one or more cameras is movable. In certain embodiments, at least one of the mount and one or more cameras is configured to move based on direct user operation, motorized operation based on user commands, or an automated program (e.g., automatic raising and lowering of cameras to maintain a set distance).

[0013] In additional embodiments, one or more cameras include at least one camera fixed to the print head of the 3D concrete printer and configured to capture image data from the concrete layer surface adjacent to the nozzle of the 3D concrete printer. In fact, in certain embodiments, one or more cameras include two cameras fixed to opposing sides of the print head. In certain embodiments, one or more cameras include a plurality of cameras arranged radially around the print head. In that particular embodiment, the processing unit is configured to combine the image data captured by each of the plurality of cameras into one or more stitched images of the concrete layer surface, based on an image analysis command.

[0014] In various embodiments, the processing unit is configured to standardize the image data before generating one or more surface state parameters.

[0015] In yet another embodiment, the camera assembly further includes a light source. In a particular embodiment, the processing unit is configured to standardize the image data before generating one or more surface state parameters based on a comparison of a first image dataset collected when the light source is inactive with a second image dataset collected when the light source is active.

[0016] In certain embodiments, the system further includes a reference member positioned within the field of view of one or more cameras, and the processing unit is configured to standardize the image data based on the image data of the reference member before generating one or more surface state parameters.

[0017] In yet another embodiment, the camera assembly further includes an optical manipulator that includes a filter positioned adjacent to the camera lens of one or more cameras.

[0018] In yet another embodiment, the camera assembly further includes an optical manipulator that includes a spectrometer positioned adjacent to or integrated with one or more cameras. The spectrometer is configured to generate a plurality of component wavelengths that include at least one specific range to which the camera equipped with the spectrometer is sensitive.

[0019] In yet another embodiment, the analysis results generated by the processing unit based on algorithmic instructions include at least one value indicating the progress of concrete setting, surface roughness, concrete bead quality, and interlayer adhesion strength.

[0020] In one embodiment, the system further includes an input device configured to capture or receive additional data, which includes at least one of environmental condition data and concrete mixing data. A communication module is further configured to receive additional data transmitted by the input device. One or more storage devices are further configured to store the additional data. A processing unit is configured to generate analysis results based on the additional data and one or more surface condition parameters, utilizing algorithmic instructions. In a particular embodiment, the additional data includes environmental condition data, and the input device includes one or more sensors designed to sense one or more of temperature, sunlight, wind, humidity, and dust. In a particular embodiment, the additional data includes concrete mixing data, and the input device includes one or more sensors designed to sense one or more of viscosity, rheology, temperature, weight, moisture, and resistivity. In yet another embodiment, the input device is configured to accept user input.

[0021] In various embodiments, one or more cameras include cameras that utilize sensors based on colloidal quantum dot thin-film photodiodes monolithically fabricated on a silicon readout wafer.

[0022] In certain embodiments, one or more cameras include cameras that utilize an indium gallium arsenide sensor.

[0023] In yet another embodiment, at least one specific wavelength range is in the range of 800 nm to 3000 nm and includes a first narrower subrange.

[0024] Furthermore, in a further embodiment, at least one specific wavelength range is in the range of 300 nm to 3000 nm and includes a first subrange that is narrower than that. In fact, in at least one embodiment, at least one specific wavelength range further includes a second subrange that is between 300 nm and 3000 nm but does not overlap with the first subrange.

[0025] In yet another embodiment, the camera assembly communicates wirelessly with the computing device. In yet another embodiment, the camera assembly communicates wired with the computing device.

[0026] In additional embodiments, the analysis results are transmitted to a user device operationally connected to the computing device. In certain embodiments, the user device is configured to display the analysis results to the user and to accept input from the user to adjust a controller operationally connected to a 3D concrete printer based on the analysis results.

[0027] In various embodiments, the analysis results are transmitted to a controller operatively connected to the 3D concrete printer. In certain embodiments, the controller is configured to utilize the analysis results to adjust at least one parameter or setting related to the 3D concrete printer. In other embodiments, the controller is configured to receive position data regarding the nozzle from one or more sensors and transmit the position data to a computing device. Here, the computing device is configured to associate the position data with imaging data and store the position data in one or more storage devices. In certain embodiments, the controller is also operatively connected to an adaptive batching device in fluid communication with the 3D concrete printing head and is configured to adjust the components of the concrete to be printed or directly apply the components to the concrete surface layer.

[0028] In yet another embodiment, the one or more storage devices also store additional data including at least one of environmental condition data and concrete mix data. In various embodiments, the processing device is configured to generate analysis results based on the additional data and one or more surface condition parameters. In a more specific embodiment, the additional data is adjustable or replaceable based on input data received from an input device or the 3D concrete printer communicating with a computing device. In fact, the 3D concrete printer itself or another input device includes one or more sensors designed to detect any one or more of the mixing temperature, pressure associated with concrete discharge from the nozzle, water-cement ratio, resistivity, and transmit that information to the computing device if available.

[0029] In one aspect, the 3DCP quality monitoring and control method includes taking one or more images using a camera assembly that includes one or more cameras with a field of view that includes at least a portion of the surface of a first concrete layer applied through the print head and nozzle of a 3D concrete printer. The 3D concrete printer also includes a controller configured to control the application of the concrete layer, and one of the one or more cameras is configured to have sensitivity in at least one specific wavelength range. Further, the method includes transmitting the acquired one or more images to a computing device having one or more storage devices. The storage device is configured to store the one or more images and includes a set of instructions including at least image analysis instructions and algorithm instructions, and a processing unit that utilizes the set of instructions. Also, aspects of the method include processing the one or more images by the processing unit based on the image analysis instructions. Specifically, the one or more images are trimmed by cropping one or more portions outside a region of interest that includes the surface portion of the first concrete layer. In yet another aspect, the method includes analyzing the one or more images by the processing unit based on the image analysis instructions. Specifically, surface state parameters are identified from the one or more images, and a composite value is calculated from the identified surface state parameters. Further, the method includes generating an analysis result through the processing unit based on algorithm instructions configured to utilize the composite value. The analysis result includes a value representing at least one of the degree of concrete coagulation progress, surface roughness, quality of the concrete bead, and interlayer adhesion strength. Finally, aspects of the method include associating the analysis result with at least time data based on the time when the one or more images were acquired and storing the analysis result in the one or more storage devices.

[0030] In a particular aspect, the field of view is illuminated by ambient light.

[0031] Furthermore, the camera assembly further includes a light source, and the field of view is illuminated by light from the light source. In a particular embodiment, the step of acquiring one or more images further includes the step of acquiring a first image of at least a portion of the surface of a first concrete layer illuminated by ambient light, and the step of acquiring a second image of the first concrete layer illuminated by light from the light source, and the step of standardizing the pixel intensity of one or more images includes the processing unit identifying the difference in reflectivity between the first image and the second image based on an image analysis command, and correcting one or more images based on this.

[0032] In a particular embodiment, the step of acquiring one or more images further includes acquiring a first image of at least a portion of the surface of the first concrete layer in the field of view before applying the second concrete layer. In a particular embodiment, the step of acquiring one or more images further includes acquiring a second image of at least a portion of the surface of the first concrete layer in the field of view at a second time point before applying the second concrete layer. Furthermore, the step of acquiring one or more images further includes acquiring an additional image of the portion of the first concrete layer in the field of view at a third time point before applying the second concrete layer. In a particular embodiment, the step of acquiring one or more images further includes acquiring a second image of the portion of the surface of the second concrete layer at a second time point after the application of the second concrete layer, with the portion of the surface of the second concrete layer aligned perpendicularly to the portion of the surface of the first concrete layer, after the second concrete layer has been applied to the surface portion of the first concrete layer. In another embodiment, the step of acquiring one or more images further includes the steps of acquiring a first image of a first portion of the surface of a first concrete layer and acquiring a second image of a second portion of the surface of a second concrete layer, where the first and second images are acquired simultaneously and the first and second portions are positioned ahead and behind the movement of the nozzle.

[0033] Furthermore, the camera assembly further includes a reference member positioned within the field of view of one or more cameras. Here, standardizing the pixel intensity of one or more images includes correcting one or more images by equalizing the reflectivity of the reference member using a processing unit based on an image analysis command.

[0034] In yet another embodiment, the process of processing one or more images includes combining at least one image obtained from each of one or more cameras into one or more composite images.

[0035] In various embodiments, the identification of surface state parameters includes identifying a first surface state parameter value from one or more images taken at a first time point, identifying a second surface state parameter value from another or more images taken at a second time point, and calculating at least one composite value using the first and second surface state parameter values.

[0036] In certain respects, this method further includes transmitting the analysis results to the user's device, allowing the user to observe the results.

[0037] In various embodiments, this method further includes transmitting analysis results to a controller, which is configured to control concrete 3D printing parameters using the analysis results. In certain embodiments, the controller is also operably connected to an adaptive batching device that is in fluid communication with the print head and is configured to adjust the concrete components applied through the print head and nozzles, or to apply components directly to the concrete surface, based on the analysis results.

[0038] In one aspect, the processing of one or more images by the processing unit further includes standardizing the pixel brightness of one or more images.

[0039] Furthermore, the analysis of one or more images by the processing unit includes dividing one or more images into sub-regions, and identifying surface state parameters from one or more images includes identifying surface state parameters from each sub-region. In certain embodiments, the analysis of one or more images includes grouping the identified surface state parameters based on the characteristics of the sub-regions and calculating a composite value for each group.

[0040] Brief explanation of the drawing The above information and the following detailed explanation will be easier to understand when read in conjunction with the attached drawings. The drawings show exemplary embodiments, but the subject matter currently disclosed is not limited to the specific methods and means disclosed.

[0041] The embodiments illustrated, described and discussed herein are illustrative of the present invention. As these embodiments are described with reference to the drawings, those skilled in the art will recognize various modifications or adaptations to the described methods and / or specific structures. It will be understood that these modifications and variations are within the scope of the appended claims, without departing from the spirit and intended scope of the teachings above. All modifications, adaptations, or variations that rely on the teachings of the present invention and advance the art as a result of these teachings are considered to be within the spirit and scope of the present invention. Accordingly, these descriptions and drawings should not be construed as restrictive, and it should be understood that the present invention is not limited to the illustrated embodiments. Embodiments of the present invention are shown with reference to the drawings below.

[0042] Figure 1 is a front view of a 3D concrete printing system in the process of printing a concrete layer, illustrating a typical moment in the 3D concrete printing process.

[0043] Figure 2A is a top view of a robotic arm-type 3D concrete fabrication system used to fabricate 3D concrete structures.

[0044] Figure 2B is a top view of a gantry-type 3D concrete molding system used to create 3D concrete structures.

[0045] Figure 3 is a perspective view of a three-dimensional concrete structure assembly, with one of the three layers incomplete and annotated to identify the interlayer bonding area.

[0046] Figure 4 is a front view of a 3D concrete printing system in the process of printing a concrete layer, including a quality monitoring and control system according to one or more embodiments of this specification.

[0047] Figure 5 is a system diagram of a 3D concrete printing quality monitoring and control system according to one or more embodiments of this specification.

[0048] Figures 6A to 6C are plan views of camera assemblies of a quality monitoring and control system according to one or more embodiments.

[0049] Figure 7 is an exploded front view of the main components of a camera assembly of a quality monitoring and control system according to one or more embodiments of this specification.

[0050] Figures 8A-8C are top views of a robotic arm 3D concrete printing system equipped with a quality monitoring and control system according to one or more embodiments.

[0051] Figures 9A-C are top views of a gantry-type 3D concrete printing system equipped with a quality monitoring and control system according to one or more embodiments.

[0052] Figure 10 is a top view showing the surface of a printed concrete layer, with a grid overlay. This illustrates one of many possible ways in which a computing device generates one or more surface condition parameters.

[0053] Figures 11A and 11B are flowcharts illustrating the use of a quality monitoring and control system in one or more embodiments of a 3D concrete printing process. (Modes for carrying out the invention) Detailed explanation The following descriptions and drawings are illustrative and should not be interpreted restrictively. Many specific details are described to ensure a full understanding of the disclosure. However, in certain cases, well-known or prior art details are omitted to avoid obscuring the description. Any reference in this specification to “one embodiment” or “embodiment” means that a particular function, structure, or characteristic described in relation to that embodiment is included in at least one embodiment of the disclosure. While the phrase “in one embodiment” appears throughout the specification, these do not necessarily all refer to the same embodiment, nor are separate or alternative embodiments mutually exclusive with other embodiments. Furthermore, various features are described that are shown in some embodiments but not in others. Similarly, various requirements are described that are necessary in some embodiments but not in others.

[0054] definition The terms used herein generally have their common meanings in the art within the context of the disclosure and in the specific context in which each term is used. Specific terms used to describe the disclosure are discussed below or elsewhere in the specification to provide additional guidance to practitioners regarding the description of the disclosure. It should be understood that the same event can be expressed in multiple ways.

[0055] For any or more terms discussed herein, alternative expressions or synonyms may be used. There is no special significance in whether or not a term is detailed herein. Synonyms for specific terms are provided. Listing one or more synonyms does not preclude the use of other synonyms. Any examples in this specification (including examples of terms discussed herein) are for illustrative purposes only and are not intended to further limit the scope or meaning of the disclosed content or the exemplified terms. Similarly, the disclosed content is not limited to the various embodiments shown herein.

[0056] In this specification, the term "3D concrete printing" refers to various technologies using 3D printing techniques to manufacture buildings, building components, infrastructure, and other products by extruding concrete from a nozzle to form multi-layered structures. This process may also be referred to by other names, such as laminated concrete structures, 3D printed concrete, digital fabrication using concrete, laminated manufacturing for concrete, and extruded laminated structures.

[0057] In this specification, “concrete” refers to concrete, mortar, or paste. Concrete is generally a material made by setting a mixture of cement, activators, fine aggregate, and coarse aggregate. Mortar is generally similar to concrete but does not contain coarse aggregate. Paste is generally similar to mortar but does not contain fine aggregate either. Admixtures can be added to any of these materials to modify the material during the setting process. Therefore, concrete, mortar, or paste may contain these admixtures.

[0058] In this specification, the term “cement” (and “cementaceous material”) refers to the material mixed with an activator to bind together the materials that make up concrete. This cement may be Portland cement or mixed hydraulic cement. Alternatively, this cement may be an alternative cement, which is an inorganic cement that can be used to replace some or all of Portland cement or mixed hydraulic cement.

[0059] In this specification, "activator" refers to an additive mixed with cement in the process of converting cement into a concrete binder. In Portland cement or mixed hydraulic cement, the activator is water. In alternative cements, the activator may be water or an additive other than water.

[0060] In this specification, the term "surface condition parameters" refers to specific characteristics of the concrete surface, such as reflectance and roughness, and indicates the relationship between image data and analysis results.

[0061] In this specification, "concrete setting progress" refers to measuring the rate at which concrete reaches its initial setting point. Setting is often quantified by the penetration resistance of a needle or plunger, and can be physically measured in various ways.

[0062] In this specification, the term "surface roughness" refers to a measure of the texture of a concrete surface. This is quantified by the vertical deviation of the concrete surface from an ideal plane. The measure of surface roughness increases as these deviations become larger.

[0063] The term "concrete bead quality" refers to the condition of the extruded concrete surface in terms of surface defects such as voids, cracks, insufficient extrusion, and excessive extrusion.

[0064] The term "interlaminar adhesion strength" refers to the degree of adhesion or fusion between two consecutive layers and affects the load transfer capacity through the interlaminar adhesive region. Interlaminar adhesion strength is directly related to the ability of a printed element to function as a load-bearing structure. This strength is typically measured by applying load for at least 7 days after printing, most commonly 28 days, until the test specimen is fractured.

[0065] In this specification, the term “multispectral” in relation to imaging refers to acquiring image data within a small number of wavelength bands on the electromagnetic spectrum, including light with frequencies beyond the visible light range.

[0066] In this specification, the term "hyperspectral" refers to acquiring image data from a series of consecutive spectral bands with fine wavelength resolution. These bands cover the entire wavelength range of the electromagnetic spectrum and include light with frequencies beyond the visible light range.

[0067] The terms "machine vision" and "computer vision" sometimes overlap in their definitions. Here, "machine vision" is defined as a systems engineering approach encompassing technologies and methods used primarily in industrial automation applications to automatically extract information from images. The term "computer vision" is defined as an interdisciplinary approach based on computer science that automatically extracts, analyzes, and processes images through algorithms to build a higher-level understanding of useful information. Similarly, the term "digital twin" is a computer-based model of a proposed or actual physical product, system, or process that reproduces the performance aspects of its proposed or actual counterpart. Based on the above definitions, this quality monitoring and control system uses machine vision and / or computer vision to generate a digital twin of a portion of the 3D concrete printing process. This digital twin can be used in real time to optimize various elements of 3D concrete printing, such as concrete setting progress, surface roughness, concrete bead quality, and / or interlayer adhesion strength.

[0068] Overview of 3D concrete printing 3D concrete printing (3DCP) offers a prime opportunity to revolutionize the construction of facilities and infrastructure. In military applications, 3DCP brings significant improvements over conventional methods in terms of logistics, materials, labor, cost, training, and time required for the construction and repair of facilities and infrastructure, facilitating the rapid development and maintenance of base deployment needs. In commercial applications, 3DCP improves productivity, addresses labor shortages, reduces waste, and lowers the carbon footprint of the construction industry.

[0069] In a typical 3D concrete printing operation, the printer 100 is fluidically connected to a fluidizing system 106, which includes a storage tank, a pump, and a mixing device (e.g., an adaptive batching device 108 (Figure 4)). This supplies concrete fluid, which is discharged through the print head 110 and then through the nozzle 112. Concrete beads 114 are ejected from the opening of the nozzle 112, forming one or more concrete layers 116 as shown in Figure 1. These layers are stacked to construct the printed wall 120. Generally, the printer 100, including the fluidizing system 106, is controlled by a printer controller 102 via a communication link 104. Generally, the printer controller 102 may adjust parameters of the 3D concrete printer in real time, such as mixing ratio, printing speed, and flow rate. In some embodiments, one or more of these potential adjustments may be performed by a part of the printer 100, while other adjustments may be performed by a part of the fluidizing system 106. In the embodiments and in Figure 1, the adaptive batching device 108 is considered part of the fluidizer 106 (whereas in Figure 4, the adaptive batching device 108 is identified separately). In various embodiments, the adaptive batching device 108 can adjust the ratio and composition of the cement-based mixture. For example, it can adjust the water-cement ratio, add admixtures, or add adhesives. In the embodiment shown in Figure 4, the adaptive batching device 108 is an in-line system positioned near the nozzle 112 of the concrete printer 100, adding material to the concrete mixture immediately before the concrete is dispensed by the printer 100. In another embodiment, the adaptive batching device 108 can be positioned in-line with the rest of the fluidizer 106 or within the concrete mixing system, adding material to the concrete during the mixing process. In yet another embodiment, the adaptive batching device 108 is positioned adjacent to the nozzle 112, applying material to the surface of the concrete layer 116 after placement to adjust the properties of the concrete.

[0070] Currently, as shown in Figures 2A and 2B, there are two types of 3D concrete printers that are commonly used. As shown in Figure 2A, the type commonly called a robotic arm printer has a print head 110 and nozzles 112 fixed to a robotic arm 122, extending from there and being moved by the robotic arm. The other type is commonly known as a gantry printer, as shown in Figure 2B, where the print head 110 and nozzles 112 are fixed to a gantry 124, extending from the gantry and moving along the gantry. These technologies are evolving, and it is expected that additional types will be developed in the future.

[0071] In fact, 3DCP is an actively developing technology. Therefore, much of the development and use related to 3DCP has taken place in controlled environments such as laboratories and manufacturing facilities where environmental conditions are generally controllable. Furthermore, structures created using 3DCP are generally large and heavy, making them difficult to transport from manufacturing facilities to required or desired locations. Therefore, it is desirable to perform 3DCP directly at the site where the structure will be installed. However, environmental conditions in the field are usually uncontrollable. This can lead to significant mechanical damage to structures created with 3DCP. Unfortunately, the methods currently commonly used to demonstrate the quality of structures formed with 3DCP only consider the cement mixture and interlayer printing time. In other words, high-quality structures created with 3DCP are currently considered to be those that adhere strictly to control, particularly regarding interlayer printing time.

[0072] To enhance the usefulness of 3DCP, it is necessary to develop quality control processes that enable on-site production under a wide range of environmental conditions, material properties, and equipment configurations. In fact, the industry is demanding the development of "in-line and automated quality control and monitoring technologies," and efforts are being made to promote large-scale implementation, focusing not only on cement-based mixtures and interlayer time, but especially on the interlayer adhesion area.

[0073] Figure 3 shows a printed concrete wall 120, which shows concrete layers 116 formed from deposited concrete beads 114. On the top surface of each layer 116, there is an interlayer bonding zone 118 as an area where an additional layer 116 can be printed. The interlayer bonding zones 118 are located between each layer 116, connecting them. In other words, a series of layers 116 constitute the printed wall 120, with interlayer bonding zones 118 between all adjacent layers 116. Without considering environmental factors, 3DCP is limited to situations where environmental parameters are within a strictly controlled range and is not optimal for on-site construction. The same is true when speed is critical or automation is desirable. However, this current approach cannot meet the demands for scaling up in on-site construction, such as residential construction, commercial construction, and the emergency deployment of military bases in harsh environments.

[0074] In reality, quality control regarding concrete setting progress, surface roughness, concrete bead quality, and interlayer adhesion strength is currently very limited or nonexistent, despite the fact that defects in these parameters can lead to structural failure. Generally, this is because many factors influence the outcome, including the properties of the cement mixture, the mixing process, construction speed, curing methods, plastic shrinkage, temperature, and evaporation due to wind and humidity. While these factors can be strictly controlled in laboratories and manufacturing facilities, controlling many elements, particularly environmental factors, is difficult in the field, creating a need for better field-based quality control methods and information.

[0075] System in a broad sense Without any intention to limit the scope of the disclosure, examples of apparatus, devices, methods, and related results according to embodiments of this disclosure are shown below. Titles and subheadings may be used for the convenience of the reader, but these do not in any way limit the scope of the disclosure.

[0076] In this embodiment, a quality monitoring and control system 200 as shown in Figure 4 is disclosed. This system generally utilizes machine vision and / or computer vision to generate a digital twin of a portion of the 3DCP process. In this embodiment, this digital twin can be used in real time to optimize various aspects of the 3DCP process, such as concrete setting progress, surface roughness, concrete bead quality, and / or interlayer adhesion strength. Therefore, this embodiment of the 3DCP quality monitoring and control system 200 can provide better information even in field environments where environmental factors are generally not controlled. In fact, this embodiment of the quality monitoring and control system 200 achieves simpler, more efficient, and cost-effective 3DCP operation by identifying and correlating surface condition parameters 308 of the concrete layer 116, interlayer adhesion zones 118, and surface condition parameters 308 of the concrete layer 116 immediately after printing. This makes it possible to predict, monitor, and control the remaining time until printing the next layer, concrete setting progress, surface roughness, concrete bead quality, interlayer adhesion strength, etc.

[0077] In this embodiment, System 200 is designed to take environmental conditions into account. These can have a substantial impact on the ideal time for printing another layer, concrete setting progress, surface roughness, concrete bead quality, and interlayer adhesion strength. In this embodiment, System 200 is designed to provide a better method for determining the quality of 3DCP manufactured structures and to enable the intelligent tuning of the 3DCP process to produce high-quality 3DCP manufactured structures without relying solely on strict control for quality verification. In this embodiment, System 200 is designed to provide an easy-to-learn 3DCP process. This process maintains a digital record of the printing process, which can be used for code official approval, forensic analysis, process improvement, and other purposes.

[0078] In the embodiment, the quality monitoring and control system 200 is shown in Figure 4. Its components are arranged on and integrated with the 3DCP printer 100 shown in Figure 1. In the embodiment, the system 200 includes a camera assembly 202 with one or more cameras 204. The cameras 204 are positioned to capture a portion of the surface of the concrete layer 116 (e.g., the portion forming the wall 120) within a field of view 206 (Figure 6). In the embodiment, each camera 204 used in the camera assembly 202 is sensitive to one or more specific wavelength ranges. Furthermore, the system 200 includes a computer 224 that communicates with the camera assembly 202 via a communication link 104. The cameras 204 capture image data 300 (Figure 5) of the surface of the concrete layer 116, including the interlayer bonding zone 118, and transmit the image data 300 to the computer 224 via the link 104.

[0079] In this embodiment, the computing device 224 comprises a communication module 226, one or more storage devices 228, and a processing unit 230, as shown in Figure 5. As shown in Figure 5, in this embodiment, the image data 300 is stored in one or more storage devices 228. In fact, the storage device 228 also stores instructions 302, such as image analysis instructions 304 and algorithm instructions 306, which the processing unit 230 uses to provide surface state parameters 308 from the image data 300 based on at least the image analysis instructions 304. It also stores analysis results 310 from the surface state parameters 308 based on the algorithm instructions 306. These are used by the processing unit 230 to generate surface state parameters 308 from the image data 300 based on the image analysis instructions 304, and analysis results 310 from the surface state parameters 308 based on the algorithm instructions 306.

[0080] Detailed explanation of specific elements Camera assembly As described above, the camera assembly 202 comprises, in an embodiment, at least one camera 204. Similar to Figure 6A, the camera assembly 202 also comprises, in an embodiment, a mount 218 configured to fix and support the camera 204 independently of the printer 100 (which typically includes a movable print head 110 and nozzles 112).

[0081] In the embodiment, the mount 218 may have a generally fixed nature, as shown in Figures 8A and 9A. For example, the mount 218 may be fixed to the floor or may have a portion that selectively connects to the ground to fix the mount 218 and, by extension, the camera 204. In the embodiment, the fixed mount 218 can provide a fixed field of view 206 of one or more cameras 204 fixed thereto. In this embodiment, the fixed camera 204 collects image data 300 of the process of a concrete layer 116 solidifying in one location. Thereafter, when the next layer 116 is poured in that location, the camera continues to collect data of the next layer 116. The image data 300 from the first pass may be used to create a reference image to assist in image analysis in the next pass. This data may be used to predict concrete setting progress, surface roughness, concrete bead quality, and interlayer adhesion strength.

[0082] In one embodiment, the camera 204 is fixed to the mount 218 via a mounting arm 220, as shown in Figure 6A. In this embodiment, the mounting arm 220 is attached to a single camera 204 and holds the camera in a fixed position. In another embodiment, the mounting arm 220 is fixed to the camera 204, and the position of the camera 204 is adjustable. This makes it possible to move the field of view 206 by manipulating the camera 204, even if the mount 218 is fixed. In yet another embodiment, the camera 204 is detachably attached to the mounting arm 220, allowing the camera 204 to be replaced.

[0083] In some embodiments, the mount 218 may also be movable. That is, the mount 218 can be moved from a first position to a second position based on direct user operation (for example, the user lifting or sliding the mount 218). In fact, in some embodiments, the mount 218 may have wheels or other structures that enable movement. In at least one embodiment, the mount 218 may be motorized and controllable, similar to an RC car. Thus, the camera 204 and field of view 206 may be moved and operated by the movement of the mount 218 itself. In fact, in some embodiments, the mount 218 is movable and the mounting arm 220 is operable, similar to the robotic arm 122 in a robotic arm type concrete printer. In some embodiments, either or both of the mount 218 and the mounting arm 220 may be programmed to move automatically based on factors such as the camera 204 being located at a predetermined distance from the surface of the concrete layer 116. However, in these embodiments, the mount 218 is operable largely independently of the printer 100 and its components, and the movement of the field of view 206 is performed independently of the movement of the print head 110 and nozzles 112.

[0084] However, in the embodiment, the camera assembly 202 may be fixed to a component of the printer 100, such as the print head 110 or nozzles 112. In fact, in Figures 4, 6B-C, 8B-C, and 9B-C, each camera 204 of the camera assembly 202 is fixed and positioned relative to the print head 110 and nozzles 112 by its respective mounting arm 220. Furthermore, the print head 110 and nozzles 112 can be moved by the movement of the robot arm 122 as shown in Figures 8B and 8C, or along the gantry 124 as shown in Figures 9B and 9C. Therefore, in the embodiment, the camera assembly 202 fixed to the print head 110 can also be moved by the robot arm 122 or along the gantry 124. It should also be understood that a particular camera assembly 202 may have a camera 204 fixed to a mount 218 in addition to the camera 204 fixed to the print head 110 in the embodiment. Furthermore, in the embodiment, the camera may be fixed to the print head 110 by means other than via the mounting arm 220. Thus, in the embodiment, the camera assembly 202 may have at least one camera 204 that is stationary relative to the print head 110 and nozzles 112 of the printer 100 and movable with the print head 110 or nozzles 112 of the printer 100. In yet another embodiment, the camera assembly 202 may include a plurality of cameras 204 positioned in alternate locations to provide image data useful for monitoring and controlling the quality of the 3DCP process. For example, additional cameras 204 may be positioned at various locations along the gantry 124 to which the print head 110 of the 3D concrete printer 100 is mounted. Furthermore, the additional cameras 204 can be individually positioned at set intervals along the planned path of the 3DCP process. Thus, image data 300 can be acquired at intermediate time intervals between the time when layer 116 is about to be applied and the time immediately after layer 116 has been applied.

[0085] Furthermore, embodiments of the camera assembly 202 may have a single camera 204 as shown in Figure 6A, two cameras 204 as shown in Figure 6B, or more than one camera 204 as shown in Figure 6C. While the camera assembly 202 in Figure 6A is shown with a single camera 204 fixed to the mount 218, it should be understood that in other embodiments, any number of cameras 204 can be fixed to the mount 218. Similarly, while the camera assembly 202 mounted on the print head 110 may have only one camera 204, although Figure 6B shows two cameras 204 and Figure 6C shows six cameras 204. In embodiments, the cameras 204 are arranged radially around a structure mounted on the mounting arm 220. That is, in Figure 6B, the camera assembly 202 has two cameras 204, which are positioned ahead and behind the movement of the nozzle 112 on the print head 110 to which the mounting arm 220 is fixed. In one embodiment, the cameras 204 can be positioned facing each other relative to the nozzle 112 by arranging them in a leading and trailing position. This allows the cameras 204 to acquire image data from the front and rear of the nozzle 112 during the 3DCP process. Similarly, in Figure 6C, the camera assembly 202 comprises six cameras 204, each arranged radially around the print head 110 to which the mounting arms 220 are fixed. This allows the camera assembly 202 to achieve a complete 360-degree field of view with overlapping fields of view 206. This allows the computing unit 224 to combine the images to create a single continuous image. In fact, in a particular embodiment, the cameras 204 are arranged at equal intervals around a structure fixed to the mounting arms 220 to achieve a complete 360-degree field of view.

[0086] In the embodiment, the position of one or more cameras 204 of the camera assembly 202 is assumed to be radially adjustable. This allows some or all of the cameras 204 not to be located opposite each other or equidistant from each other. In at least one embodiment, the mounting arm 220 is detachably attached to a part of the printer 100, for example, the print head 110. This allows for the use of different mounting arms 220. Also in at least one embodiment, the mounting arm is fixed to the printer (e.g., the print head 110) via a fastener or mating connection to an opening on a sleeve or bracket fixed to a part of the printer 100 (e.g., the print head 110). In additional embodiments, the mounting arm 220 may be length-adjustable, such as an arm 220 having a telescopic segment. Furthermore, the mounting arm 220 is assumed to be angle-adjustable relative to the sleeve, bracket, mount 218, and print head 110, and can be folded into a storage position when not in use and deployed when ready for use. Furthermore, although six are shown in Figure 6C, it should be noted that the camera assembly 202 may have more or fewer cameras 204 than six. Various embodiments of the camera assembly 202 shown in Figures 6B and 6C are shown in their unfolded state with different types of printers 100 in Figures 8B-C and 9B-C, respectively.

[0087] In the embodiment, the camera assembly 202 has one or more cameras 204 configured to be sensitive to at least one specific wavelength range. In the embodiment, one or more cameras 204 of the assembly 202 can capture image data 300 from light, i.e., light waves, i.e., light, that are sensitive to the near-infrared (NIR) and / or short-wavelength infrared (SWIR) range, for example, in the wavelength range of approximately 800 nm to 3000 nm. In certain embodiments, one or more cameras 204 of the assembly 202 can capture image data 300 from light waves in a portion of the visible spectrum, in addition to or instead of light in the NIR and / or SWIR spectrum. For example, in one embodiment, at least one of the cameras 204 of the camera assembly 202 is sensitive to light in the visible range and the NIR / SWIR range. These are typically defined as light having a wavelength range of approximately 300 nm to 3000 nm. In another embodiment, at least one of the cameras 204 in the camera assembly 202 may be sensitive only to light in the visible range, for example, to light in the wavelength range of approximately 300 nm to 800 nm.

[0088] In at least one embodiment, at least one of the cameras 204 in the camera assembly 202 may utilize a monolithically fabricated colloidal quantum dot (CQD) thin-film photodiode on a silicon readout wafer. In certain embodiments, similar to those utilizing CQD photodiodes, the photodiode array can achieve higher resolution, smaller pixel pitch, wider bandwidth, lower noise, and lower inter-pixel crosstalk compared to conventionally known and utilized cameras in wavelength ranges such as the SWIR spectrum. Such embodiments offer the ability to make the quality monitoring and control system 200 low-cost and mass-producible by eliminating the very expensive hybridization process inherent in other sensors, for example, those utilizing indium gallium arsenide cameras. However, in the embodiments, the camera assembly 202 may actually include one or more indium gallium arsenide cameras 204, or other types of cameras 204 sensitive to light in the near-infrared, short-wavelength infrared, and / or visible spectrum. In other embodiments, at least one of the cameras 204 may utilize a digital image sensor, such as an active pixel sensor using complementary metal-oxide-semiconductor (CMOS) technology or charge-coupled device (CCD) technology.

[0089] Furthermore, in the embodiment, the camera assembly 202 may further include one or more additional temperature controllers to provide temperature control to the camera to maintain consistent high-quality image data and sensitivity. These additional temperature controllers may be separate from or in addition to those included in the camera 204 itself.

[0090] In the embodiment, the camera 204 is an area scan camera or a line scan camera and can operate in single-wavelength mode, multispectral mode, or hyperspectral mode to acquire image data. That is, in the embodiment, each camera 204 has a specific range, which is a subrange within the range of 300 nm to 3000 nm, from which image data 300 (single wavelength) is acquired. In other embodiments, each camera 204 has multiple specific ranges, which are all subranges within the range of 300 nm to 3000 nm, from which image data 300 (multispectral) is acquired. For example, one camera 204 captures image data 300 from a first subset range (900 nm to 1000 nm) and a second subset range (1800 nm to 2000 nm). Alternatively, the camera assembly 202 may include a single camera 204 for the first subset range and a single camera 204 for the second subset range. In the embodiment, the subset ranges may be discrete and separated from each other. Camera 204 may be limited to a specific range, such as a subset range within the NIR / SWIR spectrum, by using one or more optical manipulators 210, such as filters or spectrometers. In fact, as shown in Figure 7, camera 204 is positioned adjacent to the optical manipulators 210. These optical manipulators 210 are at least part of the camera assembly 202 and, in certain embodiments, are also considered part of camera 204. In embodiments, one or more filters may be used as optical manipulators 210 to control the bandwidth of light reaching the camera body 216 and therefore control the light collected as part of the image data 300. In embodiments, the optical manipulators 210 can effectively remove light of a specific bandwidth and allow light within one band (single-band) or multiple subband ranges (multispectral) to pass through. That is, camera 204 may be sensitive to light in the entire range from 300 nm to 3000 nm. However, filters may be designed to allow only light within a first and / or second subband range to pass through the lens of camera 204. Examples include single-band mode or multispectral mode.In the embodiment, the camera 204 includes a lens 208 and one or more optical manipulators 210 positioned adjacent to it, as shown in Figure 7. That is, in the embodiment, the camera 204 may be fitted with one or more filters configured to transmit only light from one or more narrowband wavelength ranges to the camera lens 208, thereby collecting it in the image data 300. By narrowing the range, the image data 300 will contain only light waves that are particularly important for generating useful surface state parameters 308. In fact, by utilizing a specific narrow range, the system 200 can operate under a variety of lighting and environmental conditions. The camera lens 208 is configured to focus the passing light into a format suitable for the camera 204 and internal sensors located within the camera body 216.

[0091] In various embodiments, the optical manipulator 210 within the camera assembly 202 functions as a spectrograph as part of the camera 204, allowing the camera 204 to operate as a line-scan camera. That is, the optical manipulator 210 may be a spectrograph in addition to, or instead of, one or more filters. A spectrograph is a device used to decompose or disperse light from an object into constituent wavelengths. In embodiments, when the camera 204 operates as a line-scan camera, the light can be decomposed into a number of small sub-wavelength ranges (hyperspectral). In at least one embodiment, the camera 204 has limited sensitivity and generates image data 300 from only one or a few of the many small sub-wavelength ranges generated by the spectrograph. Alternatively, one or more filters may be used on the spectrograph output. For example, as part of the optical manipulator 210, the camera 204 may receive only light within a desired subset range, minimizing light pollution and noise from ambient wavelengths. Thus, the optical manipulator 210 can provide one, two, three, or more specific wavelength ranges to which the camera 204 is sensitive, from which image data 300 can be generated.

[0092] In the embodiment, the camera assembly 202 further includes a light source 212 (e.g., a light). The use of the light source 212 enables the standardization of the image data 300, as described later, and provides the ability to reduce, manipulate, or remove shadows that affect the image data 300. Furthermore, in the embodiment, the light source 212 can provide light within a specific wavelength band to ensure useful image data 300. Thus, in the embodiment, the assembly 202 may have one or more light sources 212 to provide light within the field of view 206 of the camera 204. This minimizes changes in ambient light in the image data 300, or is taken into account in the processing unit 230 by comparing the image data 300 under ambient light conditions with the image data 300 under conditions where the ambient light is complemented by the light source 212. Furthermore, it should be understood that while the light source 212 helps extend the usefulness of the system 200, it is not necessarily required for operation under various environmental conditions, such as when ambient light is sufficient. Also, in the embodiment, one or more additional light sources 212 provide illumination control to the camera, maintaining consistent high-quality image data and sensitivity. These additional light sources 212 are either separate from the camera body 204 or can be attached to the camera body. These light sources 212 are controlled by the computing unit 224, the controller 102, or the user device 234, and can be changed or adapted based on specific operating conditions.

[0093] In certain embodiments, the camera assembly 202 further comprises a reference member 214, which is positioned within the field of view 206 of one or more cameras 204. The reference member 214 provides a segment of image data 300 that the processing unit 230 can use to standardize the image data 300, as will be described later. For example, the reference member 214 is expected to return a specific reference image data 300, and any deviation from this will indicate the necessary corrections to the image data. In fact, in one embodiment, the image data 300 may require a specific correction to equalize the reflectivity of the reference member 214 to an expected level, and this correction may indicate other corrections necessary to standardize the image data 300 before generating surface state parameters 308.

[0094] computing device As described above, an embodiment of the quality monitoring and control system 200 includes a computing device 224 as shown in Figure 5. In this embodiment, the computing device communicates with the camera assembly 202 via a communication link 104. This allows the computing device 224 to receive image data 300 from the camera assembly 202 and, in certain embodiments, to provide specific instructions to the camera assembly 202. For example, in at least one embodiment, the computing device 224 can instruct the movement of one or more cameras 204 of the camera assembly 202, particularly in embodiments where the mount 218 is motorized and configured to accept operation commands to move it. Furthermore, the computing device 224 can also communicate with the printer controller 102 via the communication link 104 and instruct the operation of the printer 100 or its various components. In fact, in at least one embodiment, as will be described later, the computing device 224 can provide analysis results 310 to the controller 102 and be configured to control the operation of the printer 100 based on the analysis results 310. In fact, in one embodiment, the computing device 224 provides the controller 102 with analysis results 310 indicating that the adaptive batching device 108 should modify the concrete mixture to improve interlayer adhesion strength, and the controller 102 can provide specific modification commands to the batching device 108 to facilitate this action. In an embodiment, the adaptive batching device 108 is configured to apply a material such as adhesive to the surface of the concrete layer 116, and the controller 102 can provide specific commands to the adaptive batching device 108 to facilitate this action. Generally, the printer controller 102 can adjust parameters such as the mixing ratio, printing speed, and flow rate of the 3D concrete printer 100 in real time in an embodiment based on the analysis results. In an embodiment, the computing device 224 may receive data from the printer controller 102 that identifies the position of the nozzle 112 and the operation of the printer 100, and this data is used by the processing unit 230 to assist in generating analysis results 310 and creating a record of the printing process.

[0095] In the embodiment, the computing device 224 as described herein includes a communication module 226, one or more storage devices 228, and a processing unit 230. In the embodiment, the communication module 226 is configured to send and receive data for the computing device 224, and one or more storage devices 228 are configured to store data including data received through the communication module 226 (such as image data 300) and data generated by the processing unit 230. In the embodiment, one or more storage devices 228 are also configured to store instructions 302, including image analysis instructions 304 and algorithm instructions 306. These are utilized by the processing unit 230.

[0096] In the embodiment, the processing unit 230 processes and analyzes image data 300 using image analysis commands 304 to identify surface state parameters 308. For example, the processing unit 230 can identify surface state parameters 308 within the image data 300 using image analysis commands 304. These specific surface state parameters 308 are stored in one or more storage devices 228 and further utilized by the processing unit 230. In the embodiment, the processing unit 230 can determine analysis results 310 based on algorithm commands 306. In the embodiment, the processing unit 230 uses algorithm commands 306 to algorithmically generate analysis results 310 based at least on surface state parameters 308, and further on environmental condition data 312, concrete mixing data 314, position data, etc. All of this data is obtained from one or more storage devices 228 or via a communication link 104 with other devices such as an input device 232 or a user device 234, which will be described later.

[0097] In the embodiment, the image analysis command 304 instructs the processing unit 230 to process image data from multiple cameras 204. Specifically, it performs an image stitching procedure to form a single image from multiple overlapping images. In fact, in a particular embodiment such as Figure 6C, image stitching can provide a 360-degree image centered on the print head 110 and nozzle 112. Furthermore, in the embodiment, the processing unit 230 may rely solely on image data 300 to perform the image stitching procedure based on the image analysis command 304. However, in a particular embodiment, the processing unit 230 may also utilize positional data receivable from the controller 102 or camera assembly 202 to further facilitate the image stitching procedure. In the embodiment, the image analysis command may also instruct the processing unit to trim, remove, or ignore image data that may be outside the region of interest. For example, image data 300 related to a region outside the surface of a particular concrete layer 116 within the field of view 206 may be removed or ignored in the trimming process. Furthermore, the image analysis command 304 can instruct the processing unit 230 to standardize the image data 300 to make it more precise, accurate, and / or useful. In one embodiment, the image analysis command 304 can instruct the processing unit 230 to modify the image data 300 based on the necessary modifications to equalize the reflectivity of the reference member 214 located within the field of view 206 of the camera 204 and included in the image data 300. In another embodiment, the image analysis command 304 can instruct the processing unit 230 to modify the image data 300 based on the difference between the reflectivity of a specific region of the image data 300 related to ambient light conditions and the reflectivity of the image data 300 with added illumination from the light source 212. Based on the above, the image analysis command 304 can prepare image data for further analysis.

[0098] In fact, in some embodiments, the image analysis command 304 can instruct the processing unit 230 to divide the image data 300 of the region of interest into smaller sub-regions. For each sub-region, the image analysis command 304 can instruct the processing unit 230 to capture the average pixel intensity (reflectance) and surface area (roughness). For example, it can instruct it to capture surface condition parameters 308. The image analysis command 304 then instructs the processing unit 230 to calculate a composite value of these surface condition parameters 308 based on different time points or locations. For example, the composite surface condition parameter 308 is calculated by the processing unit 230 based on the image analysis command 304, using the difference between the parameter immediately after the concrete bead 114 is applied and layer 116 is formed, and the parameter immediately before a new layer 116 is applied. Furthermore, the composite surface condition parameter 308 is calculated by the processing unit 230 based on the image analysis command 304 by combining subregions that are in similar locations or have similar characteristics, such as the edge regions of the concrete bead 114 or the coarse grid regions.

[0099] In an embodiment, the processing unit 230 uses algorithmic instruction 306 to algorithmically calculate analysis results 310, such as values ​​representing the concrete setting progress, surface roughness, concrete bead quality, and / or interlayer adhesion strength, from at least the surface condition parameters 308 (e.g., the composite surface condition parameters 308 described above). In an embodiment, the algorithmic instruction 306 may also instruct the processing unit 230 to use additional data, such as environmental condition data 312 and concrete mixing data 314, in the algorithmic calculation. Thus, the processing unit 230 receives input data including the surface condition parameters 308 and optionally additional data, and generates analysis results 310 that can provide indicators of concrete setting progress, surface roughness, concrete bead quality, and / or interlayer adhesion strength. These analysis results are available for monitoring and controlling the 3DCP process and provide feedback on the acceptability of a particular concrete layer 116 used as the foundation for another layer 116, and the acceptability of the entire structure produced by 3DCP. Therefore, this feedback provides far better results and indicators than current methods that involve blind adherence to strict timeframes, environmental conditions, and mixed compositions.

[0100] Input device / User device In an embodiment, the system 200 further includes one or more input devices 232 and one or more user devices 234, which are connected to a computing device 224 via a communication link 104. In an embodiment, the input devices can acquire or receive additional data such as environmental condition data 312 and concrete mixing data 314. This data is transmitted to the computing device 224 and stored in one or more storage devices 228 or utilized by a processing unit 230. The processing unit 230 determines the analysis results 310, along with surface condition parameters 308, by calculation based on algorithm instructions 306. In an embodiment, the input device 232 may be a sensor designed to measure one or more of the following factors affecting concrete setting: temperature, sunlight, wind speed / direction, humidity, dust, and other potential factors, as environmental condition data 312. In yet another embodiment, the input device 232 may be a sensor designed to measure one or more of the following properties of the concrete mixture as concrete mixing data 314: viscosity, rheology, temperature, weight, moisture content, application pressure (pressure of the concrete bead 114 discharged from the nozzle 112), water-cement ratio, resistivity, or other properties of the concrete mixture. In yet another embodiment, the printer 100 itself may include sensors for determining and generating environmental condition data 312 and concrete mixing data 314. In certain embodiments, the input device 232 and / or the printer itself may include one or more user interfaces for receiving user input for each part of the data. That is, in the embodiment, the user can input values ​​into the input device 232 or the printer 100 to replace, adjust, or provide one or more data points that constitute the environmental condition data 312 and concrete mixing data 314.

[0101] However, in the embodiment, the system 200 can receive and verify the analysis results 310 using the user device 234. That is, in the embodiment, the analysis results 310 are transmitted from the computing device 224 to the user device 234 and displayed to the user. Furthermore, in the embodiment, the user device 234 can accept user input. This input is used to set or edit data such as environmental condition data 312 and concrete mixing data 314 via the communication link 104 with the computing device 224, or to provide operation instructions to the controller 102. In other words, in the embodiment, the user can instruct the controller 102 on the operation of the 3DCP process by passing commands from the user device 234 to the controller 102 via the computing device 224. However, in some cases, the user device 234 may connect directly to the controller 102 via the communication link 104.

[0102] In this embodiment, the communication link 104 connecting the various components may be either wired or wireless, if beneficial or desirable.

[0103] How to use In a particular embodiment, the instructions 302 stored and used in the computing device 224 include or are based on an algorithm that instructs a processing unit with either or both of the following: a method for generating surface state parameters, such as an image analysis instruction 304, and an algorithm instruction 306 for generating analysis results. For example, an image analysis instruction 304 may cause the processing unit 230 to perform various image analysis tasks on image data 300 associated with a specific wavelength. This specific wavelength may constitute a portion of the image data 300. This generates a profile of the average gray level of individual sub-regions 1002 at a distance along a specific direction on the surface 1001 of the concrete layer 116 (see Figure 10). The instruction 302 uses one or more profile data over time to generate surface state parameters 308 or to generate analysis results 310.

[0104] In a particular embodiment, the algorithm instruction 306 causes the processing unit 230 to correlate surface condition parameters 308 with specific calculated analysis results 310 (e.g., concrete setting progress, surface roughness, concrete bead quality, interlayer adhesion strength, etc.) based on the algorithm.

[0105] In one embodiment, the concrete setting progress can provide guidance for predicting the remaining time or period for printing an additional concrete layer 116 on top of the previous layer 116 via 3DCP. In yet another embodiment, algorithm instruction 306 causes the processing unit 230 to associate a surface condition parameter 308 with surface roughness. In this embodiment, surface roughness can provide guidance for predicting interlayer adhesion strength and determining whether the surface roughness is within an acceptable range.

[0106] In a similar embodiment, algorithm instruction 306 causes processing unit 230 to correlate surface condition parameters 308 with concrete bead quality. In this embodiment, concrete bead quality provides guidance for predicting the limits of the mixing design and printing process, as well as the interlayer adhesion strength, and also provides guidance for predicting whether the bead quality is within acceptable parameters.

[0107] In another embodiment, algorithm instruction 306 instructs processing unit 230 to correlate surface condition parameter 308 with interlaminar adhesion strength. This is based on an algorithm for generating interlaminar adhesion strength predictions. Interlaminar adhesion strength predictions may provide measurements and / or guidelines for determining whether the interlaminar adhesion strength is within an acceptable range.

[0108] In the embodiment, one or more of the image analysis command 304 and algorithm command 306 may utilize additional data other than the image data 300 to determine the surface condition parameters 308 and / or the analysis results 310. In fact, in the embodiment, command 302 instructs the processing unit 230 to generate either or both of the surface condition parameters 308 and / or the analysis results 310, taking into account the environmental condition data 312 and / or the concrete mixture data 314. These various data points are stored in the storage device 228 of the computing device 224 in the embodiment. Furthermore, in the embodiment, one or more of the environmental condition data 312 and the concrete mixture data 314 may be adjusted or replaced based on additional data received from the input device 232. In certain embodiments, command 302 may cause the processing unit 230 to generate new analysis results 310 and surface condition parameters 308 whenever one or more of the stored data points are updated. Thus, the computing device 224 operates in real time. In some embodiments, historical values ​​of some or all of the data stored in the computing device 224 (including those generated or created by it) may also be stored in the storage device 228. In fact, in certain embodiments, the processing unit 230 may generate a graphical representation of the historical values, such as a heatmap or a time-series plot, and transmit it to the user device 234 for display. In some embodiments, these historical values ​​form a digital record of the 3DCP process and are accessible at each stage to verify the acceptability of the structures produced by a particular 3DCP process.

[0109] In at least one use, the system 200 is used in method 1100, as shown in Figure 11, to generate analysis results 310 based on image data 300, such as values ​​representing the concrete setting progress, surface roughness, concrete bead quality, and interlayer adhesion strength. In an embodiment, method 1100 includes step 1102 of acquiring one or more images (image data 300) using a camera assembly including one or more cameras. This camera assembly has a field of view including at least a portion of the surface of a first concrete layer to be applied via the print head and nozzles of a 3D concrete printer. Here, the 3D concrete printer includes a controller configured to control the application of the concrete layer. In addition, one or more cameras are configured to be sensitive to at least one specific wavelength range. In an embodiment, method 1100 further includes step 1104 of transmitting the acquired one or more images to a computing device having one or more storage devices. The storage device is configured to store one or more images (image data 300) and includes instructions including at least image analysis instructions and algorithm instructions, and a processing unit that utilizes the instructions. Method 1100, in embodiments, continues processing one or more images by a processing unit based on an image analysis command (step 1106). Specifically, it standardizes the pixel intensity of one or more images (image data 300) (step 1108), processes one or more images (image data 300) through the processing unit, and trims one or more images (image data 300) to remove one or more portions outside the region of interest 1110, which includes a portion of the surface of the concrete layer. Then, in embodiments, Method 1100 further includes step 1112, which analyzes one or more images (image data 300) based on an image analysis command by the processing unit. Specifically, it divides one or more images into sub-regions (step 1114), identifies surface condition parameters from each sub-region (step 1116), and calculates composite values ​​from the identified surface condition parameters (step 1118). Furthermore, embodiments of Method 1100 further include step 1120, which generates analysis results through the processing unit based on an algorithm command configured to utilize the composite values.Here, the analysis results include values ​​representing at least one of the concrete setting progress, surface roughness, concrete bead quality, and interlayer adhesion strength. In an additional embodiment, method 1100 further includes steps 1122 to associate the analysis results with at least time data based on when one or more images were acquired, and steps 1124 to store the analysis results in one or more storage devices.

[0110] In a particular embodiment, the step 1102 for acquiring one or more images further includes the steps of acquiring a first image of at least a portion of the surface of a first concrete layer illuminated by ambient light, and acquiring a second image of the first concrete layer illuminated by light from a light source which is part of a camera assembly. The step 1108 for standardizing the pixel brightness of one or more images also includes the steps of identifying the difference in reflectivity between the first image and the second image through a processing unit based on an image analysis command, and correcting one or more images based on this.

[0111] In at least one embodiment, the image acquisition step 1102 further includes acquiring a first image of at least a portion of the surface of the first concrete layer in the field of view before applying the second concrete layer. In another embodiment based thereon, the image acquisition step 1102 further includes acquiring a second image of at least a portion of the surface of the second concrete layer in the field of view after applying the second concrete layer. In yet another embodiment, the image acquisition step 1102 further includes acquiring an additional image of at least a portion of the second concrete layer in the field of view before applying an additional concrete layer.

[0112] In a particular embodiment, step 1108 for standardizing the pixel brightness of one or more images includes correcting one or more images through a processing unit based on an image analysis command by equalizing the reflectivity of a reference member placed within the field of view of any of the cameras of the camera assembly.

[0113] In yet another embodiment, the image processing step 1106 further includes the step of combining at least one image from each of the one or more cameras into a single composite image.

[0114] In yet another embodiment, the processing step 1116 for identifying surface state parameters from each sub-region includes identifying a first surface state parameter value from one or more images taken at a first time point, identifying a second surface state parameter value from one or more images taken at a second time point, and calculating at least one composite value using the first and second surface state parameter values.

[0115] In certain embodiments, step 1112 of analyzing one or more images further includes grouping the identified surface condition parameters based on the characteristics of any of the sub-regions and calculating a composite value for each group. In other embodiments, method 1100 further includes transmitting the analysis results to a user device so that the user can observe the analysis results. In similar embodiments, method 1100 further includes transmitting the analysis results to a controller, which is configured to control concrete printing using the analysis results. In certain embodiments, the controller is also operably connected to an adaptive batching device that is in fluid communication with the print head and is configured to adjust the composition of the concrete applied through the print head and nozzles based on the analysis results, or by directly applying components such as adhesives to the surface of the concrete beads and / or concrete layers.

[0116] Further understanding In various embodiments, data is transmitted and received between different parts of the system. For example, environmental condition data 312 is transmitted from the input device 232 to the computing device 224, and image data 300 is transmitted from the camera assembly 202 to the computing device 224. In embodiments, the transmission and reception of data between different parts of the system takes place over a network. In some cases, the network link is identified as a communication link 104. The network can include any combination of wired or wireless networks, such as a Wi-Fi® router connected to the Internet or a cellular base station connected to the Internet. For example, different parts of the system may be connected by USB cables or Ethernet® cables. In fact, a camera 204 attached to the print head 110 may, in one example, be connected to the computing device 232 via a fiber optic cable. However, additional cameras 204 installed and used independently may be connected to the computing device 232 via a wireless network.

[0117] Furthermore, in this embodiment, the computing device 224 may include a backend server. Various client devices, such as the user device 234, the controller 102, and other computing devices 224, can connect to this backend server to receive data and transmit instructions. For example, the analysis results 310 are stored on a server that constitutes part of the network and, upon request from a user who wants to display them, are sent to the user device 234 for display. In addition, the server that constitutes part of the network may also provide storage for historical data.

[0118] Generally, the networks through which various parts of a system communicate can be open networks such as cellular networks, broadband networks, telephone networks, and the Internet; private networks such as intranets and extranets; or a combination thereof. For example, the Internet can provide services such as file transfer, remote login, email, news, RSS, cloud-based services, instant messaging, visual voicemail, push mail, VoIP, and other services through known or convenient protocols such as, but not limited to, TCP / IP, UDP, HTTP, DNS, FTP, UPnP, NSF, ISDN, PDH, RS-232, SDH, and SONET.In fact, communication can be achieved via, but is not limited to, WiMAX, Local Area Networks (LANs), Wireless Local Area Networks (WLANs), Personal Area Networks (PANs), Campus Area Networks (CANs), Metropolitan Area Networks (MANs), Wide Area Networks (WANs), Wireless Wide Area Networks (WWANs), or any broadband network, and is further realized by technologies such as: Global Systems for Mobile Communications (GSM®), Personal Communication Services (PCS), Bluetooth®, WiFi®, Fixed Wireless Data, 2G, 2.5G, 3G (e.g., WCDMA® / UMTS-based 3G networks), 4G, IMT-Advanced, Pre-4G, LTE Advanced, 5G, Mobile WiMAX, WiMAX 2, WirelessMAN-Advanced networks, and GSM®-Advanced data for evolution. Messaging protocols such as Rate (EDGE), General-Purpose Packet Radio Service (GPRS), Extended GPRS, iBurst, UMTS, HSPDA, HSUPA, HSPA, HSPA+, UMTS-TDD, 1xRTT, EV-DO, TCP / IP, SMS, MMS, Extensible Messaging Presence Protocol (XMPP), Real-Time Messaging Protocol (RTMP), Instant Messaging Presence Protocol (IMPP), Instant Messaging, USSD, IRC, and other wireless data networks, broadband networks, and messaging protocols.

[0119] A network is a collection of separate networks that work together, fully or partially, to provide connectivity to various parts of various devices and systems, and may appear as one or more networks to various parts and devices. In one embodiment, communication with various parts and / or devices is achieved by open networks such as the internet, or private networks such as intranets and / or extranets, or broadband networks. In one embodiment, communication is achieved by secure communication protocols such as Secure Sockets Layer (SSL) or Transport Layer Security (TLS).

[0120] As experts in the relevant field will understand, the aspects of the technology described herein may be embodied as systems, methods, or computer program products. Accordingly, these aspects of the technology may take the form of entirely hardware embodiments, entirely software embodiments (including firmware, resident software, microcode, etc.), or embodiments combining software and hardware aspects, which are collectively referred to herein as “circuits,” “modules,” “units,” or “systems.” Furthermore, the aspects of the technology may take the form of computer program products embodied in one or more computer-readable media containing computer-readable program code. Here, references to programs or code may also include and refer to “instructions,” “algorithms,” or “algorithmic instructions” of the present embodiment of the system.

[0121] Any combination of one or more computer-readable media, including, for example, storage devices and / or storage devices, as specified in embodiments of this system, may be used. Computer-readable media may be computer-readable signal media or computer-readable storage media (including, but not limited to, non-temporary computer-readable storage media). Computer-readable storage media include, but are not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, devices, or appropriate combinations thereof. More specific examples (non-exclusive list) of computer-readable storage media include: electrical connections with one or more wires, portable computer floppy disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or appropriate combinations thereof. In this specification, computer-readable storage medium means any tangible medium capable of holding or storing programs used by or in connection with an instruction execution system, apparatus, or device.

[0122] Computer-readable signaling media may include, for example, propagating data signals that embody computer-readable program code, such as as part of a baseband or carrier wave. Such propagating signals may take various forms, including, but are not limited to, electromagnetic, optical, or appropriate combinations thereof. Computer-readable signaling media are not computer-readable storage media, but any computer-readable medium on which programs used by or in connection with instruction execution systems, apparatus, or devices can be transmitted, propagated, or transported.

[0123] Program code, such as instructions and algorithms, can be embodied in a computer-readable medium and transmitted using wireless, wired, fiber optic cables, RF, or other means that appropriately combine these.

[0124] Instructions, algorithms, and other computer program code for performing operations related to aspects of this technology may be written in any combination of one or more programming languages, including object-oriented programming languages ​​and / or procedural programming languages. These programming languages ​​include, but are not limited to, Ruby®, JavaScript®, Java®, Python®, PHP, C, C++, C#, Objective-C®, Go®, Scala®, Swift®, Kotlin®, OCaml®, G-code, M-code, or similar languages. The program code, instructions, and algorithms may run entirely on the user's computer, partially on the user's computer as a standalone software package, partially on the user's computer and partially on a remote computer or the user's computer, or fully on a remote computer or server. In the latter scenario, the remote computer is connected to the user's computer via any of the aforementioned networks.

[0125] These computer program instructions are provided to a processing unit of a general-purpose computer, a dedicated computer, or other programmable data processing device to generate a machine. The instructions are then executed via the computer or other programmable data processing device's processing unit, creating a means to implement the functions / operations specified in this system description.

[0126] These computer program instructions may also be stored on a computer-readable medium that can instruct a computer, other programmable data processing device, or other device to operate in a particular way. In this case, the instructions stored on the computer-readable medium will produce a product containing instructions that implement the functions / operations specified in this system description.

[0127] Computer program instructions can also be loaded into a computer, other programmable data processing device, or other device, causing a series of operations to be performed on the computer, other programmable device, or other device. This generates a computer implementation process in which instructions executed on the computer or other programmable device provide a process for implementing the functions / operations specified in the description of this system.

[0128] The dimensions expressed or implied in the drawings and this description are provided for illustrative purposes only. Therefore, not all embodiments within the scope of the drawings and this description are constructed according to such exemplary dimensions. The drawings are not necessarily constructed to actual size. Therefore, not all embodiments within the scope of the drawings and this description are constructed according to the ostensible scale of the drawings with respect to relative dimensions within the drawings. However, for each drawing, at least one embodiment is constructed according to the ostensible relative scale of the drawings.

[0129] The descriptions of the various embodiments of this disclosure are presented for illustrative purposes only and are not limited to the embodiments disclosed. Those skilled in the art will understand that many modifications and variations are possible without departing from the scope and spirit of the embodiments described. The terms used herein have been selected to best describe the principles of the embodiments, their practical applications and technical improvements to the technology on the market, or to enable those skilled in the art to understand the embodiments disclosed herein.

[0130] In this specification, terms such as “first,” “second,” etc., may be used to describe various elements, but it will be understood that these elements should not be limited by these terms. These terms are used simply to distinguish one element from another. For example, the first element may be referred to as the second element, and similarly, the second element may be referred to as the first element, and these do not depart from the scope of the subject matter of the invention. In this specification, the term “and / or” encompasses all combinations that include one or more of the relevant enumerated items.

[0131] When an element is described as being "connected" or "joined" to another element, it should be understood that the element is either directly connected or joined to the other element, or that an intermediate element may exist. In contrast, when an element is described as being "directly connected" or "directly joined" to another element, there is no intermediate element.

[0132] When an element or layer is described as "on top of" another element or layer, that element or layer may exist directly on the other element or layer, or there may be an intermediate element or layer. Conversely, when an element is described as "directly on top of" another element or layer, there is no intermediate element or layer.

[0133] To facilitate the explanation of the spatial relationships between the illustrated elements and features, this specification may use spatially relative terms such as "down," "below," "low," "up," and "top." It should be understood that spatially relative terms are intended to encompass not only the orientation shown in the drawings but also different orientations of the device in use or operation. Throughout the specification, the same reference numerals in the drawings refer to the same elements.

[0134] Embodiments of the present invention will be described with reference to plan views and perspective views. These are schematic or schematic diagrams illustrating idealized embodiments of the present invention. Therefore, variations from the illustrated shapes are to be expected, for example, as a result of manufacturing techniques and / or tolerances. Accordingly, the subject matter of the invention should not be limited to the illustrated shapes, but should include deviations in shape resulting from manufacturing processes, etc. Therefore, the illustrated objects are of a schematic nature, and their shapes are not intended to represent the actual shapes of the areas of the apparatus, nor are they intended to limit the scope of the subject matter of the invention.

[0135] The terms used herein are for illustrative purposes only and are not intended to limit the subject matter of the invention. In this specification, the singular forms “a,” “an,” and “the” are intended to include the plural form unless the context clearly indicates otherwise. Furthermore, the terms “include,” “contain,” “include,” and / or “contain” as used herein are used to identify the presence of the described features, elements, processes, operations, components, and / or parts. However, they do not preclude the presence or addition of one or more other features, elements, processes, operations, components, and / or groups thereof.

[0136] Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as those commonly understood by those skilled in the art in the field to which the subject matter of the present invention pertains. Furthermore, terms used herein are to be interpreted in the context of this specification and the related art, and not to be interpreted in an idealized or overly formal sense unless expressly defined herein. In this specification, the term “plural” is used to indicate that there are two or more items being referred to. Methods, apparatus, and materials similar or equivalent to those described herein may be used in carrying out or testing the subject matter currently disclosed, but representative methods, apparatus, and materials are described below.

[0137] The drawings and specification disclose typical preferred embodiments of the subject matter of the present invention, and where specific terms are used, they are used only in a general and descriptive sense and not intended to be limiting, and the scope of the subject matter of the present invention is defined in the following claims.

[0138] All means or processes + functional elements in the following claims are intended to include any structures, materials, actions, and equivalents that perform their function in combination with any other elements specifically described in the claims. The description of the invention is presented for illustrative and explanatory purposes only and is not intended to be exhaustive or restrictive of the disclosed forms of the invention. Those skilled in the art will understand that many modifications and variations are possible without departing from the scope and spirit of the invention. The examples are selected and described to best illustrate the principles and practical applications of the invention and to enable those skilled in the art to understand the invention in various embodiments with various modifications suitable for specific intended uses. [Brief explanation of the drawing]

[0139] [Figure 1] This is a front view of a 3D concrete printing system in the process of printing a concrete layer, illustrating a typical moment in the 3D concrete printing process. [Figure 2A] This is a top view of a robotic arm-type 3D concrete modeling system used to create 3D concrete structures. [Figure 2B] This is a top view of a gantry-type 3D concrete modeling system used to create 3D concrete structures. [Figure 3] This is a perspective view of a three-dimensional concrete structure assembly, with one of the three layers incomplete and annotated to identify the interlayer bonding area. [Figure 4] This is a front view of a 3D concrete printing system in the process of printing a concrete layer, including a quality monitoring and control system according to one or more embodiments of this specification. [Figure 5] This is a system diagram of a 3D concrete printing quality monitoring and control system according to one or more embodiments of this specification. [Figure 6A] This is a plan view of a camera assembly for a quality monitoring and control system according to one or more embodiments. [Figure 6B] This is a plan view of a camera assembly for a quality monitoring and control system according to one or more embodiments. [Figure 6C] This is a plan view of a camera assembly for a quality monitoring and control system according to one or more embodiments. [Figure 7] This is an exploded front view of the main components of a camera assembly for a quality monitoring and control system according to one or more embodiments of this specification. [Figure 8A] This is a top view of a robotic arm 3D concrete printing system equipped with a quality monitoring and control system according to one or more embodiments. [Figure 8B] This is a top view of a robotic arm 3D concrete printing system equipped with a quality monitoring and control system according to one or more embodiments. [Figure 8C] This is a top view of a robotic arm 3D concrete printing system equipped with a quality monitoring and control system according to one or more embodiments. [Figure 9A] This is a top view of a gantry-type 3D concrete printing system equipped with a quality monitoring and control system according to one or more embodiments. [Figure 9B] This is a top view of a gantry-type 3D concrete printing system equipped with a quality monitoring and control system according to one or more embodiments. [Figure 9C] This is a top view of a gantry-type 3D concrete printing system equipped with a quality monitoring and control system according to one or more embodiments. [Figure 10] This is a top view showing the surface of a printed concrete layer, with a grid overlay. It illustrates one of numerous possible methods by which a computing device generates one or more surface condition parameters. [Figure 11A]This is a flowchart illustrating the use of a quality monitoring and control system in one or more embodiments of a 3D concrete printing process. [Figure 11B] This is a flowchart illustrating the use of a quality monitoring and control system in one or more embodiments of a 3D concrete printing process.

Claims

1. A 3D concrete printing quality monitoring and control system for use in a 3D concrete printer equipped with a print head terminating at a nozzle having an opening for dispensing concrete, A camera assembly comprising one or more cameras configured to be sensitive to at least one specific wavelength range and having a field of view including at least a portion of the concrete layer surface, wherein the one or more cameras are configured to capture image data from the concrete layer surface, The system comprises a computer that communicates with the camera assembly, The aforementioned computing device is A communication module configured to receive the image data transmitted from the camera assembly, One or more storage devices configured to store the aforementioned image data, having a set of instructions including at least image analysis instructions and algorithm instructions, A 3D concrete printing quality monitoring and control system, comprising: a processing unit configured to generate one or more surface condition parameters from the stored image data using the image analysis command, and to generate analysis results based on at least one or more surface condition parameters using the algorithm command.

2. The quality monitoring and control system according to claim 1, wherein the camera assembly includes a mount for fixing and supporting one or more cameras, and the fields of view of the one or more cameras are independent of the movement of the nozzle.

3. The quality monitoring and control system according to claim 2, wherein both the mount and the field of view of one or more cameras are fixed.

4. The quality monitoring and control system according to claim 2, wherein at least one of the mount and the field of view of the one or more cameras is movable.

5. The quality monitoring and control system according to claim 4, wherein at least one of the mount and the one or more cameras is configured to move based on at least one of direct operation by a user and motorized operation.

6. The quality monitoring and control system according to claim 1, wherein the one or more cameras include at least one camera fixed to the print head of the 3D concrete printer and configured to capture image data from the concrete layer surface adjacent to the nozzle of the 3D concrete printer.

7. The quality monitoring and control system according to claim 6, wherein the one or more cameras include two cameras fixed to opposing sides of the print head.

8. The quality monitoring and control system according to claim 6, wherein the one or more cameras include a plurality of cameras arranged radially around the print head.

9. The quality monitoring and control system according to claim 8, wherein the processing unit is configured to combine image data captured by each of the plurality of cameras with one or more stitched images of the concrete layer surface based on the image analysis command.

10. The quality monitoring and control system according to claim 1, wherein the processing unit is configured to standardize the image data before generating the one or more surface condition parameters.

11. The quality monitoring and control system according to claim 1, wherein the camera assembly further comprises a light source.

12. The quality monitoring and control system according to claim 11, wherein the processing unit is configured to standardize the image data based on a comparison between a first image dataset collected when the light source is inactive and a second image dataset collected when the light source is active, before generating the one or more surface state parameters.

13. The quality monitoring and control system according to claim 1, further comprising a reference member disposed within the field of view of one or more cameras, wherein the processing unit is configured to standardize the image data based on the image data of the reference member before generating the one or more surface state parameters.

14. The quality monitoring and control system according to claim 1, wherein the camera assembly further comprises an optical operating device including a filter positioned adjacent to the camera lens of one of the one or more cameras.

15. The quality monitoring and control system according to claim 1, wherein the camera assembly further comprises an optical operating device including a spectrometer positioned adjacent to or integrated with the first camera among the one or more cameras, the spectrometer being configured to generate a plurality of component wavelengths including at least one specific wavelength range to which the first camera is sensitive.

16. The quality monitoring and control system according to claim 1, wherein the analysis results generated by the processing unit based on the algorithm instructions include at least one value representing the concrete setting progress, surface roughness, concrete bead quality, or interlayer adhesion strength.

17. The quality monitoring and control system according to claim 1, further comprising an input device configured to capture or receive additional data including at least one of environmental condition data and concrete mixing data, the communication module further configured to receive the additional data transmitted from the input device, one or more storage devices further configured to store the additional data, and the processing unit configured to generate analysis results based on the additional data and one or more surface condition parameters using the algorithm instructions.

18. The quality monitoring and control system according to claim 17, wherein the additional data includes environmental condition data, and the input device includes one or more sensors designed to sense one or more of temperature, sunlight, wind, humidity, and dust.

19. The quality monitoring and control system according to claim 17, wherein the additional data includes concrete mixing data, and the input device includes one or more sensors designed to sense one or more of viscosity, rheology, temperature, weight, moisture content, and resistivity.

20. The quality monitoring and control system according to claim 17, wherein the input device is configured to accept user input.

21. The quality monitoring and control system according to claim 1, wherein the one or more cameras include cameras that utilize sensors based on colloidal quantum dot thin-film photodiodes monolithically manufactured on a silicon readout wafer.

22. The quality monitoring and control system according to claim 1, wherein the one or more cameras include cameras utilizing indium gallium arsenide sensors.

23. The quality monitoring and control system according to claim 1, wherein the at least one specific wavelength range is in the range of 800 nm to 3000 nm and includes a first narrower subrange.

24. The quality monitoring and control system according to claim 1, wherein the at least one specific wavelength range is in the range of 300 nm to 3000 nm and includes a first narrower subrange.

25. The quality monitoring and control system according to claim 24, wherein the at least one specific wavelength range further includes a second subrange that does not overlap with the first subrange and is in the range of 300 nm to 3000 nm.

26. The quality monitoring and control system according to claim 1, wherein the camera assembly communicates wirelessly with the computing device.

27. The quality monitoring and control system according to claim 1, wherein the camera assembly is wired to the computing device.

28. The quality monitoring and control system according to claim 1, wherein the analysis results are transmitted to a user device operably connected to the computing device.

29. The quality monitoring and control system according to claim 28, wherein the user device is configured to display the analysis results to the user, and the user device is configured to accept input from the user which is used to adjust a controller operably connected to the 3D concrete printer based on the analysis results.

30. The quality monitoring and control system according to claim 1, wherein the analysis results are transmitted to a controller connected to the 3D concrete printer.

31. The quality monitoring and control system according to claim 30, wherein the controller is configured to adjust at least one parameter or setting related to the 3D concrete printer using the analysis results.

32. The quality monitoring and control system according to claim 30, wherein the controller is further operationally connected to an adaptive batching device that is in fluid communication with the print head, and is configured to adjust the components of the concrete applied through the nozzle or to apply components directly to the surface of the concrete layer.

33. The quality monitoring and control system according to claim 1, wherein the controller is configured to transmit the nozzle position data to the computing device, the computing device is configured to associate the position data with the image data, and store the position data in one or more storage devices.

34. The quality monitoring and control system according to claim 1, wherein one or more storage devices also store additional data, including at least one of environmental condition data and concrete mixing data.

35. The quality monitoring and control system according to claim 34, wherein the processing unit is configured to generate the analysis results based on the additional data and one or more surface condition parameters.

36. The quality monitoring and control system according to claim 35, wherein the stored additional data is adjustable or replaceable based on input data received from an input device or from the 3D concrete printer communicating with the computing device.

37. A step of acquiring one or more images using a camera assembly, wherein the camera assembly includes one or more cameras having a field of view that includes at least a portion of the surface of a first concrete layer applied via a print head and nozzle of a 3D concrete printer, the 3D concrete printer includes a controller configured to control the application of the concrete layer, and one of the one or more cameras is configured to be sensitive to at least one specific wavelength range. A step of transmitting one or more acquired images to a computing device, wherein the computing device is configured to store the one or more images and includes one or more storage devices including a set of instructions including at least image analysis instructions and algorithm instructions, and a processing unit configured to utilize these instructions. The process involves processing the one or more images through the processing unit based on an image analysis command by cropping the one or more images and removing one or more portions outside the region of interest that include a part of the surface of the first concrete layer, The process involves identifying surface state parameters from one or more images, analyzing the one or more images through a processing unit based on an image analysis command, and calculating a composite value from the identified surface state parameters. A step of generating analysis results through a processing unit based on an algorithm instruction configured to utilize composite values, wherein the analysis results include a value representing at least one of the concrete setting progress, surface roughness, concrete bead quality, and interlayer adhesion strength. The steps include associating the analysis results with at least time data based on the time when one or more images were acquired, A method for monitoring and controlling the quality of 3D concrete printing, comprising the step of saving the analysis results to one or more storage devices.

38. The quality monitoring and control method according to claim 37, wherein the field of view is illuminated by ambient light.

39. The quality monitoring and control method according to claim 37, wherein the camera assembly further includes a light source, and the field of view is illuminated by light from the light source.

40. The quality monitoring and control method according to claim 39, wherein the step of acquiring one or more images further includes the step of acquiring a first image of at least a portion of the surface of the first concrete layer illuminated by ambient light, and the step of standardizing the pixel intensity of the one or more images includes the step of the processing unit identifying the difference in reflectance between the first image and the second image based on an image analysis command, and correcting the one or more images based on this.

41. The quality monitoring and control method according to claim 37, wherein the step of acquiring one or more images further includes the step of acquiring a first image of at least a portion of the surface of the first concrete layer in the field of view at a first point in time before applying the second concrete layer.

42. The quality monitoring and control method according to claim 41, wherein the step of acquiring one or more images further includes the step of acquiring a second image of the portion of the surface of the first concrete layer in the first image at a second time point, before applying the second concrete layer.

43. The quality monitoring and control method according to claim 42, wherein the step of acquiring one or more images further includes the step of acquiring additional images of the portion of the surface of the first concrete layer in the first image at a third time point, before applying the second concrete layer.

44. The quality monitoring and control method according to claim 41, wherein the step of acquiring one or more images further includes the step of acquiring a second image of the surface portion of the second concrete layer applied to the surface portion of the first concrete layer at a second time point after the application of the second concrete layer, wherein the surface portion of the second concrete layer is arranged perpendicularly to the surface portion of the first concrete layer.

45. The quality monitoring and control method according to claim 37, wherein the step of acquiring one or more images further includes the steps of acquiring a first image of the first portion of the surface of the first concrete layer and acquiring a second image of the second portion of the surface of the second concrete layer, before applying the second concrete layer to the first portion of the surface of the first concrete layer, wherein the first image and the second image are captured simultaneously, and the first portion and the second portion are positioned as a preceding position and a succeeding position with respect to the movement of the nozzle.

46. The quality monitoring and control method according to claim 37, wherein the camera assembly further includes a reference member disposed within the field of view of one or more cameras, and the step of standardizing the pixel intensity of one or more images includes the step of correcting one or more images by equalizing the reflectivity of the reference member through the processing unit based on an image analysis command.

47. The quality monitoring and control method according to claim 37, wherein the step of processing one or more images further includes the step of stitching at least one image obtained from each of the one or more cameras into one or more combined images.

48. The quality monitoring and control method according to claim 37, further comprising the steps of: identifying a first surface state parameter value from one or more images captured at a first time point; identifying a second surface state parameter value from one or more other images captured at a second time point; and calculating at least one composite value using the first surface state parameter value and the second surface state parameter value.

49. The quality monitoring and control method according to claim 37, further comprising the step of transmitting the analysis results to a user device, thereby enabling the user to observe the analysis results.

50. The quality monitoring and control method according to claim 37, further comprising the step of transmitting the analysis results to the controller, wherein the controller is configured to control concrete 3D printing parameters using the analysis results.

51. The quality monitoring and control method according to claim 50, wherein the controller is operably connected to an adaptive batching device that is in fluid communication with the print head, and is configured to adjust the components of the concrete applied through the nozzle or to directly apply the components to at least one of the surface of the first concrete layer or the surface of a subsequent concrete layer based on the analysis results.

52. The quality monitoring and control method according to claim 37, wherein the processing of one or more images by the processing unit further includes a step of standardizing the pixel brightness of the one or more images.

53. The quality monitoring and control method according to claim 37, wherein the analysis of one or more images by the processing unit further includes the step of dividing the one or more images into sub-regions, and the step of identifying the surface state parameters from the one or more images further includes the step of identifying the surface state parameters from each sub-region.

54. The quality monitoring and control method according to claim 53, wherein the step of analyzing one or more images further includes the step of grouping the identified surface state parameters based on the characteristics of any of the sub-regions and calculating a composite value for each group.

Images