Hybrid QR Marker with pH-Sensitive Color-Changing Region and Non-destructive Monitoring System for Concrete Carbonation Depth Using the Same

Abstract

A carbonation depth monitoring system according to the present invention is a system for estimating the carbonation depth of a concrete structure in a non-destructive manner, comprising: a QR marker (100) attached to the surface of the structure and including identification information of the structure and a measurement target area; an image acquisition unit (200) that acquires image data by photographing the QR marker (100) in a non-contact manner; a color analysis unit (300) that receives the image data acquired by the image acquisition unit (200), analyzes color information, and can correct or normalize the color characteristics of the image based on the color information included in the QR marker (100); a pH calculation unit (400) that calculates a value corresponding to the hydrogen ion concentration (pH) of the concrete surface using the color information processed by the color analysis unit (300), and can calculate the pH using a correspondence relationship between the color value and the pH or a pre-set model; and a depth estimation unit (500) that calculates the carbonation depth reflecting the carbonation progress state inside the concrete using the pH value calculated by the pH calculation unit (400). and includes a data management unit (600) that stores the above pH value and carbonation depth value, manages data at multiple points in time for the same location, or can be used for time series analysis.

Description

Technology Field

[0001] The present invention relates to a technology for measuring the carbonation progression of a concrete structure in a non-destructive manner, and more specifically, to a monitoring system that estimates carbonation depth based on imaging using a hybrid QR marker including a pH-sensitive color change. Background Technology

[0003] Carbonation in concrete structures is a phenomenon caused by a chemical reaction in which atmospheric carbon dioxide penetrates the concrete and converts calcium hydroxide (Ca(OH)2) into calcium carbonate (CaCO3). This reduces the alkalinity of the concrete, leading to corrosion of internal reinforcement and a decrease in structural durability. This carbonation generally begins on the surface of the concrete and progresses gradually inward, and the depth of carbonation serves as an important criterion for evaluating structural safety and establishing maintenance plans.

[0004] In particular, the pH inside concrete is a key indicator for determining whether carbonation is progressing; generally, rebar does not corrode in strongly alkaline conditions with a pH of 11 or higher, but if the pH drops to 9 or lower, rebar corrosion can proceed rapidly. Therefore, accurately measuring the carbonation depth of concrete is essential for predicting the lifespan of structures and determining the timing of repairs.

[0005] Conventionally, to measure the depth of carbonation, a method has been widely used in which a hole is formed in the concrete or a core is taken, and then a phenolphthalein solution is sprayed to visually check for discoloration. However, this method has limitations in that it causes physical damage to the structure and provides only one-time data limited to the time of measurement, making long-term monitoring difficult.

[0006] Furthermore, drilling-based measurement methods have drawbacks, such as potential deviations in results depending on operator skill level and the difficulty of quantitatively analyzing carbonation trends over time due to the challenge of repeated measurements at the same location. Moreover, repeatedly drilling key parts of a structure can lead to a decrease in structural stability, thereby limiting its practical application.

[0007] Meanwhile, although there have recently been increasing attempts to diagnose the condition of structures in a non-contact manner using image acquisition devices such as drones or smartphones, there are limitations in directly identifying quantitative information, particularly regarding the chemical state inside concrete and changes in pH, using only simple image data.

[0008] Prior art 1 proposes a structure for measuring carbonation depth by inserting a measuring cylinder into a measuring hole formed in concrete and capturing an internal image using a camera. However, since this technology still relies on drilling, it fails to meet the requirement of non-destructive measurement.

[0009] In addition, prior art 2 and 3 propose a method for estimating carbonation depth by collecting crushed powder generated during the concrete drilling process, reacting it with a reagent, and checking for discoloration. However, since this also presupposes drilling and reagent reaction, it cannot avoid structural damage, and it has limitations in that the measurement process is complex and worker intervention is essential.

[0010] Furthermore, even when utilizing color changes, conventional technology remains at the level of merely visually determining whether discoloration has occurred, and no technical structure is presented for quantitatively calculating pH values ​​from color information or calculating carbonation depth based thereon.

[0011] In other words, conventional technology remains within a technological paradigm of "physical sampling + reagent reaction + visual identification" and has not expanded into a technological trend of quantitatively estimating the internal condition of concrete from non-contact image-based data.

[0012] Furthermore, a correction structure that accounts for color distortion issues caused by the shooting environment (illumination, shadows, camera performance, etc.) and integration with a maintenance system that accumulates data from the same location to perform time-series analysis were also not sufficiently considered. Prior art literature

[0014] Registered Patent No. 10-1938860, Registered Patent No. 10-2639594, Published Patent No. 10-2025-0170478 The problem to be solved

[0015] The present invention aims to provide a non-destructive monitoring system capable of quantitatively calculating carbonation depth based on imaging without causing damage to concrete structures.

[0016] In addition, the purpose is to provide a system that calculates consistent pH values ​​by correcting color distortion caused by the shooting environment and automatically manages the history by measurement location using QR codes.

[0017] Furthermore, unlike conventional technology that relies on visual determination of simple color changes, the purpose is to provide a data-based analysis structure capable of quantitatively calculating the pH value of the concrete surface using color information extracted from captured images and calculating the carbonation depth inside the concrete based on this.

[0018] In addition, the purpose is to provide a monitoring system that can analyze the progression of carbonation over time and predict the deterioration state of a structure by ensuring that measurement results are not limited to a specific point in time but can be repeatedly accumulated for the same location.

[0019] In addition, the purpose is to enable efficient diagnosis of structures that are difficult to access or large structures by enabling remote measurement using various image acquisition devices such as drones and smartphones.

[0020] Furthermore, the purpose is to implement a system capable of providing objective and reproducible analysis results by excluding the subjective judgment of the measurer, through the integration of the correspondence relationship between color information and pH values ​​and the process of calculating carbonation depth using this relationship.

[0021] The problems solved by the present invention are not limited to those mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below. means of solving the problem

[0023] To solve the above problem, the present invention provides a system that extracts color information from an image captured using a hybrid QR marker attached to the surface of a concrete structure, quantitatively calculates the pH value of the concrete surface based on the color information, and calculates the carbonation depth inside the concrete using the calculated pH value.

[0024] Specifically, the present invention is configured to acquire an image of a hybrid QR marker in a non-contact manner through an image acquisition unit, correct color distortion according to the shooting environment and simultaneously extract color values ​​of the target area for analysis through a color analysis unit, calculate a pH value using the correspondence relationship between the color value and pH through a pH calculation unit, and calculate the carbonation depth using the pH value as input through a depth estimation unit.

[0025] In addition, the pH value and carbonation depth value are stored through the data management unit, and time-series data for the same location is accumulated, thereby enabling continuous monitoring of the carbonation progress status of the structure.

[0026] As such, the present invention implements the normalization of color information, the quantification of pH values, and the calculation of carbonation depth into an integrated processing structure, thereby enabling quantitative and repeatable carbonation depth calculation in a non-destructive manner, unlike conventional physical sampling or simple color change verification methods.

[0027] A carbonation depth monitoring system according to the present invention is a system for estimating the carbonation depth of a concrete structure in a non-destructive manner, comprising: a QR marker (100) attached to the surface of the structure and including identification information of the structure and a measurement target area; an image acquisition unit (200) that acquires image data by photographing the QR marker (100) in a non-contact manner; a color analysis unit (300) that receives the image data acquired by the image acquisition unit (200), analyzes color information, and can correct or normalize the color characteristics of the image based on the color information included in the QR marker (100); a pH calculation unit (400) that calculates a value corresponding to the hydrogen ion concentration (pH) of the concrete surface using the color information processed by the color analysis unit (300), and can calculate the pH using a correspondence relationship between the color value and the pH or a pre-set model; and a depth estimation unit (500) that calculates the carbonation depth reflecting the carbonation progress state inside the concrete using the pH value calculated by the pH calculation unit (400). and includes a data management unit (600) that stores the above pH value and carbonation depth value, manages data at multiple points in time for the same location, or can be used for time series analysis.

[0028] Preferably, the QR marker (100) includes an identification information area (110) for storing identification information of a structure or providing it to be readable by an external device.

[0029] Preferably, the QR marker (100) includes a pH-sensitive area (120) that changes color according to the pH change of the concrete surface to visually reflect the chemical state of the location.

[0030] Preferably, the QR marker (100) includes a reference color area (130) for correcting color distortion due to external illumination or shooting environment.

[0031] Preferably, the color analysis unit (300) processes the chromaticity information and illuminance information separately by converting the RGB data into LAB data in order to quantitatively analyze the color information of the input image data.

[0032] Preferably, the depth estimation unit (500) calculates the carbonation depth using a diffusion model, and the image acquisition unit (200) includes a drone.

[0033] In addition, the carbonation depth measurement method according to the present invention is a method for measuring the carbonation depth of a concrete structure in a non-destructive manner, comprising: a step (S210) in which an image acquisition unit (200) captures a QR marker (100) attached to the surface of the structure in a non-contact manner to acquire image data; a step (S220) in which a color analysis unit (300) receives the image data and corrects or normalizes the color and brightness based on color information included in the QR marker (100) and extracts the color value of the area to be analyzed; a step (S230) in which a pH calculation unit (400) calculates the pH value of the concrete surface using the color value, wherein the pH is calculated using a correspondence relationship between the color value and the pH or a non-linear model; and a step (S240) in which a depth estimation unit (500) calculates the carbonation depth inside the concrete using the pH value as input, wherein the carbonation penetration depth is estimated by applying a diffusion model or a calculation model equivalent thereto. The method includes a step (S250) in which the data management unit (600) stores the pH value and carbonation depth value, and accumulates and manages data from multiple points in time for the same location or uses it for analysis.

[0034] Preferably, the color normalization step (S220) is characterized by correcting white balance and brightness using the difference between the reference color value of the reference color area and the captured color value.

[0035] Preferably, the carbonation depth calculation step (S240) is characterized by calculating the rate of change over time using carbonation depth data measured at multiple points in time and predicting the future carbonation depth based thereon. Effects of the invention

[0037] According to the present invention, carbonation depth can be measured solely through imaging without damaging the structure, thereby enabling non-destructive diagnosis.

[0038] In addition, through color correction and pH quantification processes, subjective judgment by the measurer is excluded, and deviations due to the shooting environment or equipment are minimized, thereby securing objective and reproducible data.

[0039] Furthermore, since information by measurement location can be automatically managed using a QR-based identification structure, repeated measurements and data accumulation for the same location are possible, thereby enabling continuous analysis of the carbonation progress of the structure over time.

[0040] In particular, through an integrated analysis structure that extracts color information from a captured image, converts it into a pH value, and then converts it into carbonation depth, it is possible to provide quantitative and numerical analysis results, unlike conventional simple discoloration verification methods.

[0041] In addition, since various image acquisition devices such as drones or smartphones can be utilized, efficient diagnosis is possible even for high-altitude or large structures that are difficult to access, and the deployment of on-site workers can be minimized.

[0042] Furthermore, since the rate of carbonation progression can be analyzed or the remaining lifespan of the structure predicted based on time-series data accumulated through the data management department, it is possible to support more rational decision-making in establishing maintenance plans and determining repair timing.

[0043] In addition, by adopting a non-contact measurement structure, not only can physical damage to the structure be prevented, but repeated measurements at the same location are also possible, allowing it to be utilized as a long-term monitoring system.

[0044] In addition, through an automated processing structure that integrates color correction, pH calculation, and depth calculation, the efficiency of the measurement process can be improved and data processing time reduced, thereby significantly enhancing field applicability.

[0045] The effects of the present invention are not limited to those mentioned above, and other unmentioned problems will be clearly understood by those skilled in the art from the description below. Brief explanation of the drawing

[0047] FIG. 1 is a block diagram showing the overall system configuration according to an embodiment of the present invention. FIG. 2 is a flowchart showing a data processing flow according to an embodiment of the present invention. FIG. 3 is a control diagram showing a carbonation depth calculation algorithm according to an embodiment of the present invention. Specific details for implementing the invention

[0048] Further objects, features, and advantages of the present invention can be more clearly understood from the following detailed description and the accompanying drawings.

[0049] Before providing a detailed description of the present invention, it should be understood that the present invention is capable of various modifications and may have various embodiments, and that the examples described below and illustrated in the drawings are not intended to limit the present invention to specific embodiments, but rather include all modifications, equivalents, and substitutions that fall within the spirit and scope of the present invention.

[0050] When it is stated that one component is "connected" or "connected" to another component, it should be understood that while it may be directly connected or connected to that other component, there may also be other components in between. On the other hand, when it is stated that one component is "directly connected" or "directly connected" to another component, it should be understood that there are no other components in between.

[0051] The terms used in this specification are used merely to describe specific embodiments and are not intended to limit the invention. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, terms such as "comprising" or "having" are intended to indicate the existence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0052] Furthermore, in the description referring to the attached drawings, identical components are assigned the same reference numeral regardless of drawing symbols, and redundant descriptions thereof are omitted. In describing the present invention, if it is determined that a detailed description of related prior art could unnecessarily obscure the essence of the present invention, such detailed description is omitted.

[0054] A hybrid QR marker (100) is attached to the surface of the concrete structure.

[0055] The image acquisition unit (200) captures the QR marker using a drone or a smartphone.

[0056] The color analysis unit (300) normalizes the color and brightness of the captured image using a reference color area (130).

[0057] The pH calculation unit (400) calculates the pH value using a sigmoid model based on normalized color values.

[0058] The depth estimation unit (500) calculates the carbonation depth by applying a diffusion model based on the calculated pH.

[0059] The depth estimation unit (500) can calculate the depth of carbonation penetration inside the concrete using the pH value of the concrete surface calculated by the pH calculation unit (400) as a boundary condition.

[0060] The data management department (600) stores the data and analyzes changes over time.

[0061] The data management unit (600) can store the measured pH value and carbonation depth data in a database in conjunction with the identification information of the QR marker, and can accumulate and manage data from multiple points in time for the same location as a time series.

[0062] In addition, the remaining lifespan or repair time of a concrete structure can be calculated using the above prediction results, and the time when it is expected to reach a certain critical depth can be determined in advance.

[0064] FIG. 1 is a block diagram showing the overall configuration of a concrete carbonation depth monitoring system using a pH-sensitive hybrid QR marker according to one embodiment of the present invention.

[0065] The system of the present invention may include a hybrid QR marker (100), an image acquisition unit (200, Camera), a color analysis unit (300), a pH calculation unit (400), a depth estimation unit (500), and a data management unit (600, Database).

[0066] The hybrid QR marker (100) may include an identification information area (110), a pH-sensitive area (120), and a reference color area (130). The hybrid QR marker (100) is formed on a single plane, and the marker may have a structure in which a plurality of functional areas are partitioned within an outer frame.

[0067] Specifically, the identification information area (110) may be placed on one side or the center of the marker in the form of a QR code to provide structural identification information, and the pH-sensitive area (120) may be placed adjacent to or surrounding the identification information area (110) and configured to change color according to changes in the pH of the concrete surface.

[0068] Additionally, the reference color area (130) may be configured to be placed around the pH-sensitive area (120) or in a separate section to provide a reference value for color correction during shooting.

[0069] In this way, each region (110, 120, 130) may be divided and arranged on the same plane or formed as a stacked structure, and is configured to be recognized simultaneously within a single image when captured.

[0070] The image acquisition unit (200) can acquire image data by photographing the hybrid QR marker (100), and the color analysis unit (300) can normalize the color and brightness using the reference color area (130) in the image data and then extract the color value of the pH-sensitive area (120).

[0071] The pH calculation unit (400) calculates the pH using the color value, and the depth estimation unit (500) can calculate the carbonation depth based on the pH. In one embodiment, the correspondence between the color value and the actual measured pH value can be experimentally secured in advance as shown in Table 1, and as a result of color analysis of multiple concrete specimens, a characteristic in which the pH value changes non-linearly according to the change in color value can be confirmed.

[0072] Such experimental data can be utilized as reference data to model the correspondence between color values ​​and pH, and through this, pH values ​​can be quantitatively calculated using color values ​​extracted from captured images.

[0074]

[0076] As an example, the depth estimation unit (500) can calculate the carbonation depth (d) using the following mathematical formula 1 by using a diffusion model based on Fick's second law of diffusion.

[0078]

[0079] Here, d is the carbonation penetration depth (mm), t is the exposure time of the structure (year), and K is the carbonation rate coefficient (mm / It represents.

[0080] The above carbonation rate coefficient (K) can be defined as Equation 2 by reflecting the diffusion characteristics of concrete and external environmental conditions.

[0082]

[0083] Here, D represents the carbonation diffusion coefficient of concrete, CO2 concentration, and Cca represents the concentration of carbonable substances within the concrete.

[0084] The above diffusion coefficient (D) can be set by considering the water-cement ratio, density of concrete, humidity, type of cement and aggregate characteristics, etc., and can be determined by referring to design data or standard specifications.

[0085] The data management unit (600) can store and manage the above results. In one embodiment, the data management unit (600) can store and manage the rate of change over time based on the accumulated carbonation depth data. It is possible to calculate ) or predict future carbonation trends by applying a linear regression model or a non-linear regression model.

[0087] Referring to FIG. 2, the carbonation depth monitoring method of the present invention can have each step performed by a functional part constituting the system.

[0088] First, the image acquisition step (S210) can be performed by the image acquisition unit (200). The image acquisition unit (200) acquires an image of the hybrid QR marker (100) attached to the surface of the structure using a drone, a smartphone, or other shooting device.

[0089] Next, the color normalization step (S220) can be performed by the color analysis unit (300). The color analysis unit (300) uses reference color information from the captured image to correct the color and brightness of the entire image and converts it into analyzable color data. The image data processed in the color normalization step (S220) may include information on the identification information area (110), pH-sensitive area (120), and reference color area (130) included in the hybrid QR marker (100).

[0090] Next, the pH calculation step (S230) can be performed by the pH calculation unit (400). The pH calculation unit (400) calculates a corresponding pH value using the color value transmitted from the color analysis unit (300).

[0091] The above pH calculation step (S230) can convert the color value (x) into a pH value using the sigmoid regression equation of the following mathematical formula 3.

[0093]

[0094] Here, A1 and A2 are the minimum and maximum pH limits that the color values ​​can have, x is the color value extracted from the QR marker, x0 is the color value at the inflection point where the discoloration occurs most actively, and p is a factor determining the slope of the curve and represents the reaction sensitivity of the indicator.

[0095] Next, Carbonation depth calculation step (S240) This can be performed by a depth estimation unit (500). The depth estimation unit (500) calculates the carbonation depth inside the concrete using the pH value as input.

[0096] finally, Data storage step (S250) This can be performed by the data management unit (600). The data management unit (600) stores the calculated pH value and carbonation depth value, and manages time series data for the same location.

[0097] That is, each step of FIG. 2 is performed in a distributed manner by an image acquisition unit (200), a color analysis unit (300), a pH calculation unit (400), a depth estimation unit (500), and a data management unit (600), and each functional unit is sequentially linked to generate final carbonation depth information.

[0099] FIG. 3 is a control diagram showing the internal processing structure of a carbonation depth calculation algorithm according to one embodiment of the present invention.

[0100] Referring to FIG. 3, the algorithm processing structure can be implemented as detailed functional blocks performed within each functional part constituting the system of FIG. 1.

[0101] first, Color conversion unit (310) The color conversion unit (310) can be implemented by being included within the color analysis unit (300). The color conversion unit (310) converts the color information of the image data acquired by the image acquisition unit (200) into an analyzable form, and as an example, can convert RGB color data into LAB color data to separate the illuminance component and the chromaticity component.

[0102] Next, Color value calculation unit (320) This can be implemented by being included in the color analysis unit (300). The color value calculation unit (320) calculates an effective color value corresponding to the pH-sensitive region based on the data converted by the color conversion unit (310).

[0103] Next, pH estimation unit (330) The pH estimation unit (330) can be implemented by being included within the pH calculation unit (400). The pH estimation unit (330) receives a color value transmitted from the color value calculation unit (320) and calculates a pH value, and as an example, can reflect a non-linear relationship between color and pH using a sigmoid regression model.

[0104] Next, Depth of the mountain (340)This can be implemented by being included in the depth estimation unit (500). The depth estimation unit (340) calculates the carbonation depth inside the concrete by applying a diffusion model using the pH value calculated by the pH estimation unit (330) as input.

[0105] finally, Result output unit (350) It can be implemented by being included in the data management unit (600). The result output unit (350) outputs the carbonation depth and pH information calculated by the depth calculation unit (340) to the user or records it in a storage device so that it can be managed as time-series data.

[0106] That is, the color conversion unit (310) and color value calculation unit (320) of FIG. 3 are included in the color analysis unit (300), the pH estimation unit (330) is included in the pH calculation unit (400), the depth calculation unit (340) is included in the depth estimation unit (500), and the result output unit (350) is included in the data management unit (600) to form an algorithm processing structure that is linked to the entire system.

[0107] Meanwhile, the model path indicated by the dotted line in Fig. 3 represents a data processing flow that sequentially connects the color conversion unit (310), the color value calculation unit (320), the pH estimation unit (330), and the depth calculation unit (340).

[0108] The above model path represents a series of calculation paths in which color data extracted from an input image is converted into an analyzable form through a color conversion unit (310), quantified in a color value calculation unit (320), converted into a pH value in a pH estimation unit (330), and finally converted into a carbonation depth value in a depth calculation unit (340).

[0109] In other words, the above model path refers to a continuous data processing structure leading from "color value -> pH -> carbonation depth," and each step forms a dependent operation structure that uses the output value of the previous step as input.

[0110] The embodiments described in this specification and the accompanying drawings are merely illustrative of a part of the technical concept included in the present invention. Accordingly, since the embodiments disclosed in this specification are intended to explain, not limit, the technical concept of the present invention, it is obvious that the scope of the technical concept of the present invention is not limited by these embodiments. All variations and specific embodiments that can be easily deduced by a person skilled in the art within the scope of the technical concept included in the specification and drawings of the present invention should be interpreted as being included within the scope of the rights of the present invention. Explanation of the symbols

[0112] 100: Hybrid QR Marker 110: Identification Information Area 120: pH sensitivity range 130 : Standard color gamut 200 : Image acquisition unit 300 : Color Analysis Unit 310 : Color conversion unit 320 : Color value calculation unit 330 : pH estimation section 340 : Depth calculation section 350 : Result output section 400 : pH calculation section 500 : Depth estimation section 600 : Data Management Department S210: Image acquisition step S220: Color Normalization Step S230: pH calculation step S240: Carbonation depth calculation step S250: Data storage stage

Claims

Claim 1 A carbonation depth monitoring system for estimating the carbonation depth of a concrete structure in a non-destructive manner comprises: a single planar hybrid QR marker (100) attached to the surface of the structure; an image acquisition unit (200) that acquires a single image data by photographing the hybrid QR marker (100) in a non-contact manner; a color analysis unit (300) that analyzes color information from the image data; a pH calculation unit (400) that calculates the hydrogen ion concentration (pH) of the concrete surface using the color information processed by the color analysis unit (300); and a depth estimation unit (500) that calculates the carbonation penetration depth inside the concrete using the pH value calculated by the pH calculation unit (400) as a boundary condition.The system includes a data management unit (600) that stores the pH value and the carbonation penetration depth and manages data from multiple points in time for the same location in a time series, and the hybrid QR marker (100) includes an identification information area (110) that stores identification information of the structure or provides it to be readable by an external device, a pH-sensitive area (120) that is arranged in a manner surrounding the identification information area (110) and whose color changes according to the pH change of the concrete surface, and a reference color area (130) that is arranged around the pH-sensitive area (120) or in a separate section and provides a reference value for color correction during shooting, wherein the pH-sensitive area (120) is configured to change color in response to the pH change of the concrete surface, and the identification information area (110), the pH-sensitive area (120), and the reference color area (130) are arranged in sections on the single plane so as to be recognized simultaneously within a single captured image, and the color analysis unit (300) uses the reference color value of the reference color area (130) in the image data to determine the color of the image data and A carbonation depth monitoring system characterized by normalizing brightness, extracting color values ​​of the pH-sensitive region (120) from the normalized image data, the pH calculation unit (400) calculating the pH value using a correspondence relationship between the color value of the pH-sensitive region (120) and pH or a sigmoid regression equation, the depth estimation unit (500) calculating the carbonation penetration depth according to a continuous data processing structure in which the color value, pH value, and carbonation penetration depth value are sequentially calculated using the pH value as input, and the data management unit (600) storing the structure identification information read from the identification information region (110) in conjunction with the pH value and the carbonation penetration depth. Claim 2 delete Claim 3 delete Claim 4 delete Claim 5 delete Claim 6 delete Claim 7 A carbonation depth measurement method for estimating the carbonation depth of a concrete structure in a non-destructive manner, comprising: an image acquisition unit (200) that acquires one image data by photographing a hybrid QR marker (100) on a single plane attached to the surface of the structure in a non-contact manner (S210); a color analysis unit (300) that analyzes color information from the image data (S220); a pH calculation unit (400) that calculates the hydrogen ion concentration (pH) of the concrete surface using the color information processed by the color analysis unit (300) (S230); and a carbonation penetration depth calculation unit (500) that calculates the carbonation penetration depth inside the concrete using the pH value calculated by the pH calculation unit (400) as a boundary condition (S240).The data management unit (600) includes a data management step (S250) that stores the pH value and the carbonation penetration depth and accumulates and manages data from multiple points in time for the same location in a time series, and the hybrid QR marker (100) includes an identification information area (110) that stores identification information of the structure or provides it to be readable by an external device, a pH-sensitive area (120) that is arranged in a manner surrounding the identification information area (110) and changes color according to the pH change of the concrete surface, and a reference color area (130) that is arranged around the pH-sensitive area (120) or in a separate section and provides a reference value for color correction during shooting, wherein the pH-sensitive area (120) is configured to change color in response to the pH change of the concrete surface, and the identification information area (110), the pH-sensitive area (120), and the reference color area (130) are arranged in sections on the single plane so as to be recognized simultaneously within a single captured image, and the color analysis step (S220) includes the reference color in the image data A method for measuring carbonation depth, characterized by including a step of normalizing the color and brightness of the image data using a reference color value of the region (130) and then extracting the color value of the pH-sensitive region (120) from the normalized image data; the pH calculation step (S230) includes a step of calculating the pH value using a correspondence relationship between the color value of the pH-sensitive region (120) and the pH or a sigmoid regression equation; the carbonation penetration depth calculation step (S240) includes a step of calculating the carbonation penetration depth according to a continuous data processing structure in which the color value, the pH value, and the carbonation penetration depth value are sequentially calculated using the pH value as input; and the data management step (S250) includes a step of storing the structure identification information read from the identification information region (110) in conjunction with the pH value and the carbonation penetration depth. Claim 8 delete Claim 9 delete Claim 10 delete

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