Piezoelectric smart aggregate-based system and method for monitoring defect in concrete structure

Abstract

The present invention provides a piezoelectric smart aggregate-based system and method for monitoring a defect in a concrete structure. Piezoelectric detection signals respectively generated by all piezoelectric smart aggregates embedded inside a concrete structure are analyzed to obtain information on stress distribution inside the concrete structure, so as to determine an abnormal stress distribution region inside the concrete structure, and define a region within the concrete structure where internal cracks may deepen and spread; then, on the basis of the piezoelectric detection signals within the range corresponding to the abnormal stress distribution region, information on the presence and state of internal cracks is obtained, so as to construct an internal crack distribution map of the concrete structure, and enable a three-dimensional characterization of the distribution location and morphology of the internal cracks; and further, visual recognition is performed on the outer surface of the concrete structure to obtain information on the presence and state of cracks on the outer surface of the concrete structure, and the information is compared with the crack distribution map to determine a corresponding crack-defect region present in the concrete structure, thereby improving the continuity and reliability of crack monitoring in concrete structures.

Description

A Defect Monitoring System and Method for Concrete Structures Based on Piezoelectric Smart Aggregates Technical Field

[0001] This invention relates to the field of concrete structure monitoring, and more particularly to a concrete structure defect monitoring system and method based on piezoelectric smart aggregates. Background Technology

[0002] Concrete, as an important building material, is easily affected by external environmental factors such as temperature and humidity during the pouring process. Excessively high or low temperatures and humidity can affect the rate and uniformity of shrinkage during the concrete's setting process. Excessive or uneven shrinkage leads to uneven stress distribution within the concrete, causing cracks to form both internally and on the surface under prolonged uneven stress. While surface cracks can be accurately identified visually, internal cracks cannot be identified using conventional methods. If internal cracks show a tendency to deepen and spread, irreversible damage to the concrete structure can occur. Although existing technologies such as X-ray scanning can detect the interior of concrete structures, these methods cannot provide long-term, continuous, directional monitoring or identify the evolution of cracks, thus reducing the continuity and reliability of crack monitoring. Summary of the Invention

[0003] The purpose of this invention is to provide a concrete structure defect monitoring system and method based on piezoelectric smart aggregates. It analyzes the piezoelectric detection signals generated by each of the piezoelectric smart aggregates embedded within the concrete structure to obtain stress distribution information within the concrete structure, thereby identifying abnormal stress distribution areas and limiting the areas where cracks may deepen and spread. Based on the piezoelectric detection signals within the corresponding range of the abnormal stress distribution areas, it obtains the state information of internal cracks, constructing a crack distribution map within the concrete structure and providing a three-dimensional representation of the distribution location and morphology of internal cracks. Furthermore, it performs visual recognition on the outer surface of the concrete structure to obtain the state information of cracks on the outer surface, comparing it with the crack distribution map to determine the corresponding crack defect areas in the concrete structure. This allows for the linked identification of crack evolution inside and outside the concrete structure, improving the continuity and reliability of crack monitoring in concrete structures.

[0004] This invention is achieved through the following technical solution:

[0005] A concrete structure defect monitoring system based on piezoelectric smart aggregate, wherein the defect is a crack, comprising:

[0006] The internal stress distribution determination module is used to acquire the piezoelectric detection signals generated by each of the piezoelectric smart aggregates embedded in the concrete structure, analyze all the piezoelectric detection signals, and determine the stress distribution information inside the concrete structure.

[0007] The stress distribution anomaly region determination module is used to determine the stress distribution anomaly region inside the concrete structure based on the stress distribution information.

[0008] The internal crack state determination module is used to estimate the crack existence state information inside the stress distribution abnormal region based on the piezoelectric detection signal within the range corresponding to the stress distribution abnormal region.

[0009] The crack distribution map generation module is used to construct a crack distribution map inside the concrete structure based on the crack existence status information corresponding to all areas of abnormal stress distribution.

[0010] A visual recognition module is used to visually recognize the outer surface of the concrete structure and obtain information on the presence of cracks on the outer surface of the concrete structure.

[0011] The crack defect area determination module is used to determine the corresponding crack defect areas of the concrete structure based on the crack distribution map and the crack presence status information on the outer surface.

[0012] Optionally, the internal stress distribution determination module is used to acquire the piezoelectric detection signals generated by each of the piezoelectric smart aggregates embedded in the concrete structure, analyze all the piezoelectric detection signals, and determine the stress distribution information inside the concrete structure, including:

[0013] The piezoelectric detection signals generated by each of the piezoelectric smart aggregates embedded in the concrete structure are acquired. Signal drift analysis is performed on each piezoelectric detection signal to obtain the signal drift rate of each piezoelectric detection signal. If the signal drift rate exceeds a preset drift rate threshold, Kalman filtering is performed on the corresponding piezoelectric detection signal.

[0014] All piezoelectric detection signals are analyzed to obtain the stress intensity information of each piezoelectric smart aggregate at its corresponding position in the concrete structure. Based on the distribution location information of each piezoelectric smart aggregate inside the concrete structure, the stress intensity information corresponding to each piezoelectric smart aggregate is subjected to three-dimensional fitting processing to determine the stress distribution information inside the concrete structure.

[0015] The stress distribution anomaly region determination module is used to determine the stress distribution anomaly region inside the concrete structure based on the stress distribution information, including:

[0016] Based on the stress distribution information, the stress gradient variation information corresponding to the three-dimensional direction inside the concrete structure is determined; based on the stress gradient variation information, the stress discontinuity region inside the concrete structure is determined, which is used as the stress distribution abnormal region inside the concrete structure.

[0017] Optionally, the corresponding piezoelectric detection signal is subjected to Kalman filtering, including:

[0018] Step S1: Using the formula (1) below, based on the numerical change of each piezoelectric detection signal per unit time, obtain the stable value of the piezoelectric detection signal for each piezoelectric smart aggregate.

[0019] In the above formula (1), U(k_a) represents the stable value of the piezoelectric detection signal of the k-th piezoelectric smart aggregate; U(k_a) represents the value of the a-th piezoelectric detection signal of the k-th piezoelectric smart aggregate within a unit time; n represents the total number of piezoelectric detection signals collected by the k-th piezoelectric smart aggregate within a unit time. This represents the mode of the piezoelectric detection signal collected by the k-th piezoelectric smart aggregate per unit time.

[0020] Step S2: Using the formula (2) below, based on the stable value of the piezoelectric detection signal of each piezoelectric smart aggregate, perform signal drift analysis on each piezoelectric detection signal to obtain the signal drift rate of each piezoelectric detection signal.

[0021] In the above formula (2), U p (k) represents the signal drift rate of the piezoelectric detection signal of the kth piezoelectric smart aggregate; || represents taking the absolute value; U max This represents the maximum value among all piezoelectric detection signals;

[0022] Step S3, using the following formula (3), extract the piezoelectric detection signals that need to be Kalman filtered according to the signal drift rate of each of the piezoelectric detection signals, K={k|(1≤k≤M)&&[U p (k)>u p (3)

[0023] In the above formula (3), K represents the set of piezoelectric detection signals that need to be Kalman filtered; M represents the total number of piezoelectric smart aggregates; u p This represents the preset drift rate threshold; {k|(1≤k≤M)&&[U p (k)>u p ]} indicates that 1≤k≤M and U p (k)>u pThe set consists of k values.

[0024] Optionally, the internal crack state determination module is used to estimate the crack existence state information inside the stress anomaly region based on the piezoelectric detection signal within the range corresponding to the stress anomaly region, including:

[0025] Based on the coverage area of ​​the stress distribution anomaly region within the concrete structure, all associated piezoelectric smart aggregates of the stress distribution anomaly region are determined; based on the piezoelectric detection signals corresponding to all associated piezoelectric smart aggregates, the shape and size information of each of the stress distribution non-uniform sub-regions within the stress distribution anomaly region is determined; then, based on the shape and size information of each of the stress distribution non-uniform sub-regions, the location and size information of cracks within the stress distribution anomaly region are estimated, which are used as the crack existence status information;

[0026] The crack distribution map generation module is used to construct a crack distribution map inside the concrete structure based on the crack presence status information corresponding to all areas of abnormal stress distribution, including:

[0027] Based on the location and size information of cracks corresponding to all areas of abnormal stress distribution, a three-dimensional modeling process of crack morphology is performed to construct a crack distribution map inside the concrete structure; wherein, the crack distribution map is used to characterize the distribution location information of all cracks inside the concrete structure that meet the preset crack width condition.

[0028] Optionally, the visual recognition module is used to perform visual recognition on the outer surface of the concrete structure to obtain information on the presence of cracks on the outer surface of the concrete structure, including:

[0029] The outer surface of the concrete structure is subjected to three-dimensional visual acquisition to obtain a three-dimensional image of the outer surface of the concrete structure; pixel contour recognition is performed on the three-dimensional outer surface image to obtain the location information of the cracks on the outer surface of the concrete structure.

[0030] The crack defect region determination module is used to determine the corresponding crack defect regions in the concrete structure based on the crack distribution map and the crack presence status information on the outer surface, including:

[0031] The location of the crack distribution map and the location of the cracks on the outer surface are compared to determine the overlapping area of ​​the internal cracks and the external surface cracks of the concrete structure. The minimum distance between the internal cracks and the external surface cracks in the overlapping area is compared with a preset distance threshold. If the minimum distance is less than the preset distance threshold, the overlapping area is determined as a crack defect area of ​​the concrete structure; otherwise, the overlapping area is not determined as a crack defect area of ​​the concrete structure.

[0032] A method for monitoring defects in concrete structures based on piezoelectric smart aggregates, comprising:

[0033] The piezoelectric detection signals generated by each of the piezoelectric smart aggregates embedded in the concrete structure are acquired, and all piezoelectric detection signals are analyzed to determine the stress distribution information inside the concrete structure; based on the stress distribution information, the abnormal stress distribution areas inside the concrete structure are determined.

[0034] Based on the piezoelectric detection signals within the range corresponding to the abnormal stress distribution area, the crack existence status information inside the abnormal stress distribution area is estimated; based on the crack existence status information corresponding to all abnormal stress distribution areas, a crack distribution map inside the concrete structure is constructed.

[0035] Visual recognition is performed on the outer surface of the concrete structure to obtain information on the presence of cracks on the outer surface of the concrete structure; based on the crack distribution map and the information on the presence of cracks on the outer surface, the corresponding crack defect areas of the concrete structure are determined.

[0036] Optionally, the piezoelectric detection signals generated by each of the piezoelectric smart aggregates embedded in the concrete structure are acquired, and all piezoelectric detection signals are analyzed to determine the stress distribution information inside the concrete structure; based on the stress distribution information, abnormal stress distribution areas inside the concrete structure are determined, including:

[0037] The piezoelectric detection signals generated by each of the piezoelectric smart aggregates embedded in the concrete structure are acquired. Signal drift analysis is performed on each piezoelectric detection signal to obtain the signal drift rate of each piezoelectric detection signal. If the signal drift rate exceeds a preset drift rate threshold, Kalman filtering is performed on the corresponding piezoelectric detection signal.

[0038] All piezoelectric detection signals are analyzed to obtain the stress intensity information of each piezoelectric smart aggregate at its corresponding position in the concrete structure. Based on the distribution location information of each piezoelectric smart aggregate inside the concrete structure, the stress intensity information corresponding to each piezoelectric smart aggregate is subjected to three-dimensional fitting processing to determine the stress distribution information inside the concrete structure.

[0039] Based on the stress distribution information, the stress gradient variation information corresponding to the three-dimensional direction inside the concrete structure is determined; based on the stress gradient variation information, the stress discontinuity region inside the concrete structure is determined, which is used as the stress distribution abnormal region inside the concrete structure.

[0040] Optionally, based on the piezoelectric detection signals within the range corresponding to the abnormal stress distribution area, the crack presence status information within the abnormal stress distribution area is estimated; based on the crack presence status information corresponding to all abnormal stress distribution areas, a crack distribution map inside the concrete structure is constructed, including:

[0041] Based on the coverage area of ​​the stress distribution anomaly region within the concrete structure, all associated piezoelectric smart aggregates of the stress distribution anomaly region are determined; based on the piezoelectric detection signals corresponding to all associated piezoelectric smart aggregates, the shape and size information of each of the stress distribution non-uniform sub-regions within the stress distribution anomaly region is determined; then, based on the shape and size information of each of the stress distribution non-uniform sub-regions, the location and size information of cracks within the stress distribution anomaly region are estimated, which are used as the crack existence status information;

[0042] Based on the location and size information of cracks corresponding to all areas of abnormal stress distribution, a three-dimensional modeling process of crack morphology is performed to construct a crack distribution map inside the concrete structure; wherein, the crack distribution map is used to characterize the distribution location information of all cracks inside the concrete structure that meet the preset crack width condition.

[0043] Optionally, visual recognition is performed on the outer surface of the concrete structure to obtain information on the presence of cracks on the outer surface of the concrete structure; based on the crack distribution map and the information on the presence of cracks on the outer surface, the corresponding crack defect areas in the concrete structure are determined, including:

[0044] The outer surface of the concrete structure is subjected to three-dimensional visual acquisition to obtain a three-dimensional image of the outer surface of the concrete structure; pixel contour recognition is performed on the three-dimensional outer surface image to obtain the location information of the cracks on the outer surface of the concrete structure.

[0045] The location of the crack distribution map and the location of the cracks on the outer surface are compared to determine the overlapping area of ​​the internal cracks and the external surface cracks of the concrete structure. The minimum distance between the internal cracks and the external surface cracks in the overlapping area is compared with a preset distance threshold. If the minimum distance is less than the preset distance threshold, the overlapping area is determined as a crack defect area of ​​the concrete structure; otherwise, the overlapping area is not determined as a crack defect area of ​​the concrete structure.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] This invention provides a concrete structure defect monitoring system and method based on piezoelectric smart aggregates. It analyzes the piezoelectric detection signals generated by all piezoelectric smart aggregates embedded within the concrete structure to obtain stress distribution information within the concrete structure. This identifies areas of abnormal stress distribution and limits the regions where cracks may deepen and spread. Based on the piezoelectric detection signals within the corresponding range of the abnormal stress distribution areas, it obtains the state information of internal cracks, constructing a crack distribution map within the concrete structure and providing a three-dimensional representation of the location and morphology of internal cracks. Furthermore, it performs visual recognition on the outer surface of the concrete structure to obtain the state information of cracks on the outer surface, comparing it with the crack distribution map to determine the corresponding crack defect areas. This system and method enable linked identification of crack evolution both inside and outside the concrete structure, improving the continuity and reliability of crack monitoring in concrete structures. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0049] Figure 1 is a schematic diagram of a concrete structure defect monitoring system based on piezoelectric smart aggregate provided by the present invention.

[0050] Figure 2 is a flowchart illustrating a method for monitoring defects in concrete structures based on piezoelectric smart aggregates provided by the present invention. Detailed Implementation

[0051] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for explaining the present invention and not for limiting the present invention. Furthermore, it should be noted that, for ease of description, only the parts related to the present invention are shown in the accompanying drawings, not all structures. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of the present invention.

[0052] The terms "comprising" and "having," and any variations thereof, used in this invention are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0053] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0054] Please refer to Figure 1. An embodiment of the present invention provides a concrete structure defect monitoring system based on piezoelectric smart aggregates. This concrete structure crack monitoring system based on piezoelectric smart aggregates includes:

[0055] The internal stress distribution determination module is used to acquire the piezoelectric detection signals generated by all piezoelectric smart aggregates embedded in the concrete structure, analyze all piezoelectric detection signals, and determine the stress distribution information inside the concrete structure.

[0056] The stress distribution anomaly region determination module is used to determine the stress distribution anomaly region inside the concrete structure based on the stress distribution information.

[0057] The internal crack state determination module is used to estimate the crack existence state information inside the stress abnormality area based on the piezoelectric detection signal within the corresponding range of the stress abnormality area.

[0058] The crack distribution map generation module is used to construct a crack distribution map inside the concrete structure based on the crack existence status information corresponding to all areas of abnormal stress distribution.

[0059] The visual recognition module is used to visually recognize the outer surface of the concrete structure and obtain information on the presence of cracks on the outer surface of the concrete structure.

[0060] The crack defect area determination module is used to determine the corresponding crack defect area of ​​the concrete structure based on the crack distribution map and the crack presence status information on the outer surface.

[0061] The beneficial effects of the above embodiments are that the concrete structure defect monitoring system based on piezoelectric smart aggregates analyzes the piezoelectric detection signals generated by all piezoelectric smart aggregates embedded in the concrete structure to obtain stress distribution information inside the concrete structure, thereby identifying abnormal stress distribution areas and limiting the areas where cracks inside the concrete structure may deepen and spread; then, based on the piezoelectric detection signals within the corresponding range of the abnormal stress distribution areas, it obtains the state information of internal cracks, thereby constructing a crack distribution map inside the concrete structure and performing three-dimensional characterization of the distribution location and morphology of internal cracks; it also performs visual recognition on the outer surface of the concrete structure to obtain the state information of cracks on the outer surface of the concrete structure, and compares it with the crack distribution map to determine the corresponding crack defect areas in the concrete structure, and performs linkage recognition of the evolution of cracks inside and outside the concrete structure, thereby improving the continuity and reliability of crack monitoring of concrete structures.

[0062] In another embodiment, the internal stress distribution determination module is used to acquire the piezoelectric detection signals generated by each of the piezoelectric smart aggregates embedded in the concrete structure, analyze all the piezoelectric detection signals, and determine the stress distribution information inside the concrete structure, including:

[0063] The piezoelectric detection signals generated by each of the piezoelectric smart aggregates embedded in the concrete structure are acquired. Signal drift analysis is performed on each piezoelectric detection signal to obtain the signal drift rate of each piezoelectric detection signal. If the signal drift rate exceeds the preset drift rate threshold, Kalman filtering is performed on the corresponding piezoelectric detection signal.

[0064] All piezoelectric detection signals are analyzed to obtain the stress intensity information of each piezoelectric smart aggregate at its corresponding position in the concrete structure. Based on the distribution information of each piezoelectric smart aggregate inside the concrete structure, the stress intensity information corresponding to each piezoelectric smart aggregate is subjected to three-dimensional fitting to determine the stress distribution information inside the concrete structure.

[0065] The stress distribution anomaly region determination module is used to determine the stress distribution anomaly regions inside the concrete structure based on the stress distribution information, including:

[0066] Based on this stress distribution information, the stress gradient variation information corresponding to the three-dimensional direction inside the concrete structure is determined; based on this stress gradient variation information, the stress discontinuity region inside the concrete structure is determined, which is used as the stress distribution abnormal region inside the concrete structure.

[0067] The beneficial effects of the above embodiments are that piezoelectric smart aggregates are pre-embedded at different locations within the concrete during the concrete pouring process. These piezoelectric smart aggregates can be, but are not limited to, piezoelectric sensors. During and after the concrete solidifies, the piezoelectric smart aggregates within the concrete generate corresponding electrical signals under the influence of internal stress, which are transmitted outward through the signal lines inherent in the piezoelectric smart aggregates. All the piezoelectric smart aggregates within the concrete can be evenly distributed in a regular array (e.g., at equal intervals) across the entire three-dimensional space within the concrete, thereby achieving global monitoring of the internal stress. The more piezoelectric smart aggregates within the concrete and the smaller the spacing between adjacent piezoelectric smart aggregates, the more accurately the collected piezoelectric detection signals reflect the stress state within the concrete. Generally, the piezoelectric detection signals generated by the piezoelectric smart aggregates are positively correlated with the stress exerted on the piezoelectric smart aggregates by the internal concrete. In the actual processing of piezoelectric detection signals, the piezoelectric smart aggregate itself may have certain measurement errors, causing drift and oscillation in the generated piezoelectric detection signals. To ensure the accuracy of the piezoelectric detection signals, signal drift analysis is first performed on all piezoelectric detection signals to obtain the signal drift rate of each signal. If the signal drift rate exceeds a preset drift rate threshold, it indicates that the corresponding piezoelectric detection signal has a large signal interference component. In this case, Kalman filtering is performed on the corresponding piezoelectric detection signal to reduce noise interference and avoid affecting the accuracy of subsequent concrete structure crack detection. Then, all piezoelectric detection signals are analyzed to obtain the stress intensity information of each piezoelectric smart aggregate at its corresponding location in the concrete structure. Combined with the distribution information of each piezoelectric smart aggregate within the concrete structure, a three-dimensional spatial correlation fitting is performed on all stress intensity information to obtain the stress distribution information within the concrete structure. This allows for a global characterization of the stress magnitude distribution throughout the entire three-dimensional space within the concrete structure. Furthermore, based on this stress distribution information, the stress gradient variation information corresponding to the three-dimensional directions within the concrete structure can be determined. For example, the stress gradient variation information corresponding to the X, Y, and Z axes (i.e., the stress variation per unit distance in the corresponding directions) can be determined. If cracks exist within the concrete, the stress in the cracked area will not be continuously transmitted, resulting in a sudden decrease in stress in the cracked area. Thus, based on this stress gradient variation information, regions of discontinuity in stress variation within the concrete structure can be identified, serving as abnormal stress distribution areas within the concrete structure. This allows for comprehensive location and identification of abnormal stress distribution areas within the concrete structure.

[0068] In another embodiment, the corresponding piezoelectric detection signal is subjected to Kalman filtering, including:

[0069] Step S1: Using the formula (1) below, based on the numerical change of each piezoelectric detection signal per unit time, obtain the stable value of the piezoelectric detection signal for each piezoelectric smart aggregate.

[0070] In the above formula (1), U(k_a) represents the stable value of the piezoelectric detection signal of the k-th piezoelectric smart aggregate; U(k_a) represents the value of the a-th piezoelectric detection signal of the k-th piezoelectric smart aggregate within a unit time; n represents the total number of piezoelectric detection signals collected by the k-th piezoelectric smart aggregate within a unit time. This represents the mode of the piezoelectric detection signal collected by the k-th piezoelectric smart aggregate per unit time.

[0071] Step S2: Using the formula (2) below, based on the stable value of the piezoelectric detection signal of each piezoelectric smart aggregate, perform signal drift analysis on each piezoelectric detection signal to obtain the signal drift rate of each piezoelectric detection signal.

[0072] In the above formula (2), U p (k) represents the signal drift rate of the piezoelectric detection signal of the kth piezoelectric smart aggregate; || represents taking the absolute value; U max This represents the maximum value among all piezoelectric detection signals;

[0073] Step S3: Using the following formula (3), extract the piezoelectric detection signals that need to be Kalman filtered according to the signal drift rate of each of the piezoelectric detection signals, K={k|(1≤k≤M)&&[Up(k)>u p ]} (3)

[0074] In the above formula (3), K represents the set of piezoelectric detection signals that need to be Kalman filtered; M represents the total number of piezoelectric smart aggregates; u p This represents the preset drift rate threshold; {k|(1≤k≤M)&&[U p (k)>u p ]} indicates that 1≤k≤M and U p (k)>u p The set consists of k values.

[0075] The beneficial effects of the above embodiments are as follows: using the above formula (1), based on the numerical change of each piezoelectric detection signal in a unit time, the stable value of the piezoelectric detection signal of each piezoelectric smart aggregate is obtained, thus laying the foundation for subsequent drift state determination; then using the above formula (2), based on the stable value of the piezoelectric detection signal of each piezoelectric smart aggregate, signal drift analysis is performed on each piezoelectric detection signal to obtain the signal drift rate of each piezoelectric detection signal, thus knowing the state of each signal facilitates timely control processing and ensures the timeliness of the system; then using the above formula (3), based on the signal drift rate of each piezoelectric detection signal, the piezoelectric detection signals that need to be processed by Kalman filtering are extracted, thus all extracted and processed and then subjected to centralized Kalman filtering can improve the working efficiency of the system.

[0076] In another embodiment, the internal crack state determination module is used to estimate the crack presence state information within the stress anomaly region based on the piezoelectric detection signal within the range corresponding to the stress anomaly region, including:

[0077] Based on the coverage area of ​​the abnormal stress distribution region within the concrete structure, all associated piezoelectric smart aggregates within the abnormal stress distribution region are determined; based on the piezoelectric detection signals corresponding to all associated piezoelectric smart aggregates, the shape and size information of each of the non-uniform stress distribution sub-regions within the abnormal stress distribution region is determined; and based on the shape and size information of each of the non-uniform stress distribution sub-regions, the location and size information of cracks within the abnormal stress distribution region are estimated, which are used as the crack existence status information.

[0078] This crack distribution map generation module is used to construct a crack distribution map inside the concrete structure based on the crack presence status information corresponding to all areas of abnormal stress distribution, including:

[0079] Based on the location and size information of cracks corresponding to all areas of abnormal stress distribution, a three-dimensional modeling process of crack morphology is performed to construct a crack distribution map inside the concrete structure. The crack distribution map is used to characterize the distribution location information of all cracks inside the concrete structure that meet the preset crack width condition.

[0080] The beneficial effects of the above embodiments are that areas with abnormal stress distribution inside the concrete structure have a relatively high probability of generating cracks and a tendency for crack deepening and propagation. To accurately identify the crack distribution inside the concrete structure, based on the coverage area of ​​the abnormal stress distribution area within the concrete structure, all associated piezoelectric smart aggregates of the abnormal stress distribution area are determined. The piezoelectric detection signals corresponding to all associated piezoelectric smart aggregates are then screened and analyzed to determine the shape and size information of each of the non-uniform stress distribution sub-regions within the abnormal stress distribution area. This allows for the limitation of the crack-prone areas within the concrete structure. Furthermore, based on the shape and size information of each of the non-uniform stress distribution sub-regions, the location and size of cracks within the abnormal stress distribution area are estimated, serving as the crack presence status information. Generally, the size and shape of the non-uniform stress distribution sub-regions within the concrete structure are directly proportional to the size of the cracks within the concrete structure. This allows for the determination of the location and size of all cracks within the concrete structure.

[0081] In another embodiment, the visual recognition module is used to perform visual recognition on the outer surface of the concrete structure to obtain information on the presence of cracks on the outer surface of the concrete structure, including:

[0082] A three-dimensional visual acquisition was performed on the outer surface of the concrete structure to obtain a three-dimensional image of the outer surface of the concrete structure; pixel contour recognition was performed on the three-dimensional image of the outer surface to obtain the location information of the cracks on the outer surface of the concrete structure.

[0083] The crack defect area determination module is used to determine the corresponding crack defect areas in the concrete structure based on the crack distribution map and the crack presence status information on the outer surface, including:

[0084] The location of the crack distribution map and the location information of the external surface crack are compared to determine the overlapping area of ​​the internal crack and the external surface crack of the concrete structure. The minimum distance between the internal crack and the external surface crack in the overlapping area is compared with a preset distance threshold. If the minimum distance is less than the preset distance threshold, the overlapping area is determined as a crack defect area of ​​the concrete structure; otherwise, the overlapping area is not determined as a crack defect area of ​​the concrete structure.

[0085] The beneficial effects of the above embodiments are that by performing three-dimensional visual acquisition and pixel contour recognition on the outer surface of the concrete structure, the location information of cracks on the outer surface of the concrete structure can be obtained, thus enabling quantitative determination of the crack state on the outer surface of the concrete structure. Furthermore, by comparing the crack distribution map with the location information of the cracks on the outer surface, the overlapping area of ​​internal and external surface cracks in the concrete structure can be determined. This overlapping area is affected by both internal and external surface cracks, making the concrete structure in this area more susceptible to damage and cracking. The minimum distance between the internal and external surface cracks in the overlapping area is then compared with a preset distance threshold. If the minimum distance is less than the preset distance threshold, it indicates that the corresponding internal and external surface cracks will connect during further deepening and expansion, thus creating a structural defect in the overlapping area. This overlapping area is then identified as the crack defect area of ​​the concrete structure, providing a reliable basis for subsequent repair of the concrete structure.

[0086] Please refer to Figure 2, which illustrates an embodiment of the present invention providing a method for monitoring cracks in concrete structures based on piezoelectric smart aggregates. This method for monitoring cracks in concrete structures based on piezoelectric smart aggregates...

[0087] The piezoelectric detection signals generated by each of the piezoelectric smart aggregates embedded in the concrete structure are acquired, and all piezoelectric detection signals are analyzed to determine the stress distribution information inside the concrete structure. Based on the stress distribution information, the abnormal stress distribution areas inside the concrete structure are identified.

[0088] Based on the piezoelectric detection signals within the corresponding range of the abnormal stress distribution area, the crack existence status information inside the abnormal stress distribution area is estimated; based on the crack existence status information corresponding to all abnormal stress distribution areas, a crack distribution map inside the concrete structure is constructed.

[0089] Visual recognition is performed on the outer surface of the concrete structure to obtain information on the presence and state of cracks on the outer surface of the concrete structure; based on the crack distribution map and the information on the presence and state of cracks on the outer surface, the corresponding crack defect areas in the concrete structure are determined.

[0090] The beneficial effects of the above embodiments are as follows: This method for monitoring cracks in concrete structures based on piezoelectric smart aggregates analyzes the piezoelectric detection signals generated by all piezoelectric smart aggregates embedded in the concrete structure to obtain stress distribution information inside the concrete structure, thereby identifying abnormal stress distribution areas and limiting the areas where cracks inside the concrete structure may deepen and spread; based on the piezoelectric detection signals within the corresponding range of the abnormal stress distribution areas, the existence status information of internal cracks is obtained, thereby constructing a crack distribution map inside the concrete structure and performing three-dimensional characterization of the distribution location and morphology of internal cracks; furthermore, visual recognition is performed on the outer surface of the concrete structure to obtain the existence status information of cracks on the outer surface of the concrete structure, and compared with the crack distribution map to determine the corresponding crack defect areas in the concrete structure, thereby linking the identification of crack evolution inside and outside the concrete structure and improving the continuity and reliability of crack monitoring in concrete structures.

[0091] In another embodiment, the piezoelectric detection signals generated by each of the piezoelectric smart aggregates embedded in the concrete structure are acquired, and all piezoelectric detection signals are analyzed to determine the stress distribution information inside the concrete structure. Based on this stress distribution information, abnormal stress distribution areas inside the concrete structure are determined, including:

[0092] The piezoelectric detection signals generated by each of the piezoelectric smart aggregates embedded in the concrete structure are acquired. Signal drift analysis is performed on each piezoelectric detection signal to obtain the signal drift rate of each piezoelectric detection signal. If the signal drift rate exceeds the preset drift rate threshold, Kalman filtering is performed on the corresponding piezoelectric detection signal.

[0093] All piezoelectric detection signals are analyzed to obtain the stress intensity information of each piezoelectric smart aggregate at its corresponding position in the concrete structure. Based on the distribution information of each piezoelectric smart aggregate inside the concrete structure, the stress intensity information corresponding to each piezoelectric smart aggregate is subjected to three-dimensional fitting to determine the stress distribution information inside the concrete structure.

[0094] Based on this stress distribution information, the stress gradient variation information corresponding to the three-dimensional direction inside the concrete structure is determined; based on this stress gradient variation information, the stress discontinuity region inside the concrete structure is determined, which is used as the stress distribution abnormal region inside the concrete structure.

[0095] The beneficial effects of the above embodiments are that piezoelectric smart aggregates are pre-embedded at different locations within the concrete during the concrete pouring process. These piezoelectric smart aggregates can be, but are not limited to, piezoelectric sensors. During and after the concrete solidifies, the piezoelectric smart aggregates within the concrete generate corresponding electrical signals under the influence of internal stress, which are transmitted outward through the signal lines inherent in the piezoelectric smart aggregates. All the piezoelectric smart aggregates within the concrete can be evenly distributed in a regular array (e.g., at equal intervals) across the entire three-dimensional space within the concrete, thereby achieving global monitoring of the internal stress. The more piezoelectric smart aggregates within the concrete and the smaller the spacing between adjacent piezoelectric smart aggregates, the more accurately the collected piezoelectric detection signals reflect the stress state within the concrete. Generally, the piezoelectric detection signals generated by the piezoelectric smart aggregates are positively correlated with the stress exerted on the piezoelectric smart aggregates by the internal concrete. In the actual processing of piezoelectric detection signals, the piezoelectric smart aggregate itself may have certain measurement errors, causing drift and oscillation in the generated piezoelectric detection signals. To ensure the accuracy of the piezoelectric detection signals, signal drift analysis is first performed on all piezoelectric detection signals to obtain the signal drift rate of each signal. If the signal drift rate exceeds a preset drift rate threshold, it indicates that the corresponding piezoelectric detection signal has a large signal interference component. In this case, Kalman filtering is performed on the corresponding piezoelectric detection signal to reduce noise interference and avoid affecting the accuracy of subsequent concrete structure crack detection. Then, all piezoelectric detection signals are analyzed to obtain the stress intensity information of each piezoelectric smart aggregate at its corresponding location in the concrete structure. Combined with the distribution information of each piezoelectric smart aggregate within the concrete structure, a three-dimensional spatial correlation fitting is performed on all stress intensity information to obtain the stress distribution information within the concrete structure. This allows for a global characterization of the stress magnitude distribution throughout the entire three-dimensional space within the concrete structure. Furthermore, based on this stress distribution information, the stress gradient variation information corresponding to the three-dimensional directions within the concrete structure can be determined. For example, the stress gradient variation information corresponding to the X, Y, and Z axes (i.e., the stress variation per unit distance in the corresponding directions) can be determined. If cracks exist within the concrete, the stress in the cracked area will not be continuously transmitted, resulting in a sudden decrease in stress in the cracked area. Thus, based on this stress gradient variation information, regions of discontinuity in stress variation within the concrete structure can be identified, serving as abnormal stress distribution areas within the concrete structure. This allows for comprehensive location and identification of abnormal stress distribution areas within the concrete structure.

[0096] In another embodiment, based on the piezoelectric detection signal within the range corresponding to the abnormal stress distribution region, the crack presence status information within the abnormal stress distribution region is estimated; based on the crack presence status information corresponding to all abnormal stress distribution regions, a crack distribution map inside the concrete structure is constructed, including:

[0097] Based on the coverage area of ​​the abnormal stress distribution region within the concrete structure, all associated piezoelectric smart aggregates within the abnormal stress distribution region are determined; based on the piezoelectric detection signals corresponding to all associated piezoelectric smart aggregates, the shape and size information of each of the non-uniform stress distribution sub-regions within the abnormal stress distribution region is determined; and based on the shape and size information of each of the non-uniform stress distribution sub-regions, the location and size information of cracks within the abnormal stress distribution region are estimated, which are used as the crack existence status information.

[0098] Based on the location and size information of cracks corresponding to all areas of abnormal stress distribution, a three-dimensional modeling process of crack morphology is performed to construct a crack distribution map inside the concrete structure. The crack distribution map is used to characterize the distribution location information of all cracks inside the concrete structure that meet the preset crack width condition.

[0099] The beneficial effects of the above embodiments are that areas with abnormal stress distribution inside the concrete structure have a relatively high probability of generating cracks and a tendency for crack deepening and propagation. To accurately identify the crack distribution inside the concrete structure, based on the coverage area of ​​the abnormal stress distribution area within the concrete structure, all associated piezoelectric smart aggregates of the abnormal stress distribution area are determined. The piezoelectric detection signals corresponding to all associated piezoelectric smart aggregates are then screened and analyzed to determine the shape and size information of each of the non-uniform stress distribution sub-regions within the abnormal stress distribution area. This allows for the limitation of the crack-prone areas within the concrete structure. Furthermore, based on the shape and size information of each of the non-uniform stress distribution sub-regions, the location and size of cracks within the abnormal stress distribution area are estimated, serving as the crack presence status information. Generally, the size and shape of the non-uniform stress distribution sub-regions within the concrete structure are directly proportional to the size of the cracks within the concrete structure. This allows for the determination of the location and size of all cracks within the concrete structure.

[0100] In another embodiment, visual recognition is performed on the outer surface of the concrete structure to obtain information on the presence of cracks on the outer surface of the concrete structure; based on the crack distribution map and the information on the presence of cracks on the outer surface, the corresponding crack defect areas of the concrete structure are determined, including:

[0101] A three-dimensional visual acquisition was performed on the outer surface of the concrete structure to obtain a three-dimensional image of the outer surface of the concrete structure; pixel contour recognition was performed on the three-dimensional image of the outer surface to obtain the location information of the cracks on the outer surface of the concrete structure.

[0102] The location of the crack distribution map and the location information of the external surface crack are compared to determine the overlapping area of ​​the internal crack and the external surface crack of the concrete structure. The minimum distance between the internal crack and the external surface crack in the overlapping area is compared with a preset distance threshold. If the minimum distance is less than the preset distance threshold, the overlapping area is determined as a crack defect area of ​​the concrete structure; otherwise, the overlapping area is not determined as a crack defect area of ​​the concrete structure.

[0103] The beneficial effects of the above embodiments are that by performing three-dimensional visual acquisition and pixel contour recognition on the outer surface of the concrete structure, the location information of cracks on the outer surface of the concrete structure can be obtained, thus enabling quantitative determination of the crack state on the outer surface of the concrete structure. Furthermore, by comparing the crack distribution map with the location information of the cracks on the outer surface, the overlapping area of ​​internal and external surface cracks in the concrete structure can be determined. This overlapping area is affected by both internal and external surface cracks, making the concrete structure in this area more susceptible to damage and cracking. The minimum distance between the internal and external surface cracks in the overlapping area is then compared with a preset distance threshold. If the minimum distance is less than the preset distance threshold, it indicates that the corresponding internal and external surface cracks will connect during further deepening and expansion, thus creating a structural defect in the overlapping area. This overlapping area is then identified as the crack defect area of ​​the concrete structure, providing a reliable basis for subsequent repair of the concrete structure.

[0104] In summary, this concrete structure crack monitoring system and method based on piezoelectric smart aggregates analyzes the piezoelectric detection signals generated by all piezoelectric smart aggregates embedded in the concrete structure to obtain stress distribution information within the concrete structure. This identifies areas of abnormal stress distribution and limits the areas where cracks may deepen and spread. Based on the piezoelectric detection signals within the corresponding range of abnormal stress distribution areas, the system obtains the state information of internal cracks, constructing a crack distribution map of the concrete structure and providing a three-dimensional representation of the location and morphology of internal cracks. Furthermore, the system performs visual recognition on the outer surface of the concrete structure to obtain the state information of cracks on the outer surface. This information is compared with the crack distribution map to determine the corresponding crack defect areas in the concrete structure. This collaborative identification of crack evolution both inside and outside the concrete structure improves the continuity and reliability of crack monitoring in concrete structures.

[0105] The above is only one specific embodiment of the present invention, and any improvements made based on the concept of the present invention shall be considered within the scope of protection of the present invention.

Claims

1. A concrete structure defect monitoring system based on piezoelectric smart aggregate, the defect being a crack, characterized in that, The system comprises: an internal stress distribution determination module configured to acquire piezoelectric detection signals generated by all piezoelectric smart aggregates embedded in a concrete structure, analyze the piezoelectric detection signals, and determine stress distribution information of the concrete structure; a stress distribution abnormal area determination module configured to determine stress distribution abnormal areas in the concrete structure based on the stress distribution information; an internal crack state determination module configured to estimate crack existence state information in the stress distribution abnormal areas based on piezoelectric detection signals in a corresponding range of the stress distribution abnormal areas; a crack distribution map generation module configured to construct a crack distribution map of the concrete structure based on crack existence state information corresponding to all stress distribution abnormal areas; a visual recognition module configured to visually recognize an outer surface of the concrete structure to obtain outer surface crack existence state information of the concrete structure; a crack defect area determination module configured to determine crack defect areas corresponding to the concrete structure based on the crack distribution map and the outer surface crack existence state information.

2. The piezoelectric smart aggregate-based concrete structure defect monitoring system of claim 1, wherein: the internal stress distribution determination module is configured to acquire piezoelectric detection signals generated by all piezoelectric smart aggregates embedded in a concrete structure, analyze the piezoelectric detection signals, and determine stress distribution information of the concrete structure, including: acquiring piezoelectric detection signals generated by all piezoelectric smart aggregates embedded in a concrete structure, respectively performing signal drift analysis on all piezoelectric detection signals, and obtaining signal drift rates of all piezoelectric detection signals; if the signal drift rate exceeds a preset drift rate threshold, performing Kalman filter processing on the corresponding piezoelectric detection signal; analyzing all piezoelectric detection signals to obtain stress intensity information of all piezoelectric smart aggregates at corresponding positions of the concrete structure; based on distribution position information of all piezoelectric smart aggregates in the concrete structure, performing three-dimensional fitting processing on stress intensity information corresponding to all piezoelectric smart aggregates to determine stress distribution information of the concrete structure; the stress distribution abnormal area determination module is configured to determine stress distribution abnormal areas in the concrete structure based on the stress distribution information, including: based on the stress distribution information, determining stress gradient change information corresponding to three-dimensional directions in the concrete structure; based on the stress gradient change information, determining stress change discontinuous areas in the concrete structure as stress distribution abnormal areas in the concrete structure.

3. The piezoelectric smart aggregate-based concrete structure defect monitoring system of claim 2, wherein: performing Kalman filter processing on the corresponding piezoelectric detection signal includes: Step S1, according to the numerical change of each piezoelectric detection signal in unit time, the stable value of each piezoelectric smart aggregate is obtained by using the following formula (1), In the above formula (1), represents the stable value of the piezoelectric detection signal of the kth piezoelectric intelligent aggregate, respectively; U(k_a) represents the value of the a th piezoelectric detection signal of the kth piezoelectric intelligent aggregate in a unit time; n represents the total number of piezoelectric detection signals collected by the kth piezoelectric intelligent aggregate in a unit time; representing a mode in piezoelectric detection signals collected by the kth piezoelectric smart aggregate in a unit of time. Step S2, according to the stable value of each piezoelectric smart aggregate's respective piezoelectric detection signal, the signal drift of each piezoelectric detection signal is analyzed by using the following formula (2), and the signal drift rate of all piezoelectric detection signals is obtained, In the above equation (2), U p (k) represents the signal drift rate of the piezoelectric detection signal of the kth piezoelectric smart aggregate; || represents taking the absolute value; U max represents the maximum value in all piezoelectric detection signals; Step S3, according to the signal drift rate of each piezoelectric detection signal, the piezoelectric detection signal needing Kalman filtering processing is extracted by using formula (3) as follows, K = {k | (1 < k < M) && [U p (k) > u p ]} (3) In the above formula (3), K represents a set of numbers of piezoelectric detection signals that need to be subjected to Kalman filtering processing; M represents a total number of piezoelectric intelligent aggregates; u p represents a preset drift rate threshold;{k|(1≤k≤M)&&[U p (k)>u p ]represents a set of k values that satisfy 1≤k≤M and U p (k)>u p . 4.The piezoelectric intelligent aggregate based concrete structure defect monitoring system of claim 1, wherein: The internal crack state determination module is configured to estimate the crack existence state information inside the stress distribution abnormal area based on the piezoelectric detection signals in the corresponding range of the stress distribution abnormal area, including: Based on the coverage range of the stress distribution abnormal area in the concrete structure, all associated piezoelectric intelligent aggregates of the stress distribution abnormal area are determined; based on the piezoelectric detection signals corresponding to all associated piezoelectric intelligent aggregates, the shape size information of each stress distribution uneven sub-area inside the stress distribution abnormal area is determined; and based on the shape size information of all stress distribution uneven sub-areas, the crack position and size information inside the stress distribution abnormal area are estimated as the crack existence state information. The crack distribution map generation module is configured to construct the crack distribution map inside the concrete structure based on the crack existence state information corresponding to all stress distribution abnormal areas, including: Based on the crack position and size information corresponding to all stress distribution abnormal areas, crack morphology three-dimensional modeling processing is performed to construct the crack distribution map inside the concrete structure; wherein the crack distribution map is used to represent the distribution position information of all cracks inside the concrete structure that meet the preset crack width condition. 5.The piezoelectric intelligent aggregate based concrete structure defect monitoring system of claim 1, wherein: The visual recognition module is configured to perform visual recognition on the outer surface of the concrete structure to obtain the outer surface crack existence state information of the concrete structure, including: performing three-dimensional visual collection on the outer surface of the concrete structure to obtain three-dimensional outer surface images of the concrete structure; and performing pixel contour recognition on the three-dimensional outer surface images to obtain the outer surface crack existence position information of the concrete structure. The crack defect area determination module is configured to determine the crack defect area corresponding to the concrete structure based on the crack distribution map and the outer surface crack existence state information, including: comparing the positions of the crack distribution map and the outer surface crack existence position information to determine the overlapping area of the internal crack and the outer surface crack of the concrete structure; comparing the minimum distance between the internal crack and the outer surface crack in the overlapping area with a preset distance threshold value, if the minimum distance is less than the preset distance threshold value, the overlapping area is determined as the crack defect area of the concrete structure; otherwise, the overlapping area is not determined as the crack defect area of the concrete structure.

6. A method for monitoring the defects of a concrete structure based on piezoelectric smart aggregate, characterized by, including: acquiring the piezoelectric detection signals generated by all piezoelectric intelligent aggregates embedded in the concrete structure, analyzing all piezoelectric detection signals, and determining the stress distribution information inside the concrete structure; based on the stress distribution information, determining the stress distribution abnormal area inside the concrete structure; estimate crack existence state information inside the stress distribution abnormal area based on the piezoelectric detection signal in the corresponding range of the stress distribution abnormal area; and construct a crack distribution map inside the concrete structure based on crack existence state information corresponding to all stress distribution abnormal areas. perform visual identification on the outer surface of the concrete structure to obtain outer surface crack existence state information of the concrete structure; and determine a crack defect area corresponding to the concrete structure based on the crack distribution map and the outer surface crack existence state information.

7. The method according to claim 6, wherein: stress distribution information inside the concrete structure is determined by analyzing all piezoelectric detection signals generated by all piezoelectric smart aggregates embedded inside the concrete structure; stress distribution abnormal areas inside the concrete structure are determined based on the stress distribution information, including: signal drift rates of all piezoelectric detection signals are obtained by respectively performing signal drift analysis on all piezoelectric detection signals generated by all piezoelectric smart aggregates embedded inside the concrete structure; if the signal drift rate exceeds a preset drift rate threshold, Kalman filtering processing is performed on the corresponding piezoelectric detection signal; stress intensity information of all piezoelectric smart aggregates at corresponding positions of the concrete structure is obtained by analyzing all piezoelectric detection signals; and stress distribution information inside the concrete structure is determined by performing three-dimensional fitting processing on stress intensity information corresponding to all piezoelectric smart aggregates based on distribution position information of all piezoelectric smart aggregates inside the concrete structure; stress gradient change information corresponding to three-dimensional directions inside the concrete structure is determined based on the stress distribution information; and stress change discontinuous areas inside the concrete structure are determined based on the stress gradient change information, which are used as stress distribution abnormal areas inside the concrete structure.

8. The method according to claim 6, wherein: crack existence state information inside the stress distribution abnormal area is estimated based on the piezoelectric detection signal in the corresponding range of the stress distribution abnormal area; and a crack distribution map inside the concrete structure is constructed based on crack existence state information corresponding to all stress distribution abnormal areas, including: all associated piezoelectric smart aggregates of the stress distribution abnormal area are determined based on the coverage range of the stress distribution abnormal area inside the concrete structure; shape and size information of all stress distribution uneven sub-areas inside the stress distribution abnormal area are determined based on piezoelectric detection signals corresponding to all associated piezoelectric smart aggregates; and crack position and size information inside the stress distribution abnormal area are estimated based on shape and size information of all stress distribution uneven sub-areas, which are used as the crack existence state information. ​ ​ ​ ​ ​ ​ ​ ​ Based on the crack position and size information corresponding to all stress distribution abnormal areas, a crack morphology three-dimensional modeling process is performed to construct a crack distribution map inside the concrete structure; wherein the crack distribution map is used to represent the distribution position information of all cracks inside the concrete structure that meet the preset crack width condition. 9.The piezoelectric smart aggregate based concrete structure defect monitoring method of claim 6, characterized in that: visual recognition is performed on the outer surface of the concrete structure to obtain outer surface crack existence state information of the concrete structure; based on the crack distribution map and the outer surface crack existence state information, a crack defect area corresponding to the concrete structure is determined, including: three-dimensional visual collection is performed on the outer surface of the concrete structure to obtain a three-dimensional outer surface image of the concrete structure; pixel contour recognition is performed on the three-dimensional outer surface image to obtain outer surface crack existence position information of the concrete structure; position comparison is performed between the crack distribution map and the outer surface crack existence position information to determine an overlapping area of the internal cracks and the outer surface cracks of the concrete structure; comparison is performed between a minimum distance between the internal cracks and the outer surface cracks in the overlapping area and a preset distance threshold value; if the minimum distance is less than the preset distance threshold value, the overlapping area is determined as a crack defect area of the concrete structure; otherwise, the overlapping area is not determined as the crack defect area of the concrete structure.

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