Digital model of engineering structure crack and storage method thereof

Abstract

The invention provides a digital model of an engineering structure crack and a storage method thereof. The digital model of the engineering structure crack comprises a plurality of independent cracks. Each crack comprises an end node and a crack main body, position coordinates of two ends of the crack are recorded in the end node, crack information is recorded in the crack main body, and all cracks are connected through a common end node to form a crack net; the crack information comprises crack position parameters, crack basic geometric parameters and crack shapes. According to the method, digital expression and physical storage of the complex crack network can be realized, an accurate mathematical expression model and efficient storage are provided for performance evaluation of a downstream crack structure, and the method is low in research and development difficulty, easy to popularize and apply and good in market prospect.

Description

Technical Field

[0001] The invention relates to the field of engineering structure cracks and digital technology, and in particular to a digital model of engineering structure cracks and a storage method thereof. Background Art

[0002] In concrete structures, the formation of cracks may be induced by a variety of factors, including temperature fluctuations, drying shrinkage, uneven foundation settlement, and the effects of mechanical loads. The presence of these cracks not only exacerbates the corrosion process of the steel bars, but also significantly reduces the overall safety of the structure, adversely affecting its applicability and durability. In addition, the appearance of cracks not only damages the appearance of the building, but also provides a channel for moisture and harmful substances to penetrate into the concrete, thereby causing steel corrosion, weakening the bearing capacity and durability of the structure, and threatening the safety and stability of the building. Therefore, structural operation and maintenance engineers need to pay close attention to the crack problem of concrete structures and take timely and effective measures to repair them to ensure the long-term safety and stability of the building.

[0003] Traditionally, visual inspection is used as a basic method to identify obvious cracks on the concrete surface through direct visual observation. Ultrasonic testing technology transmits and receives ultrasonic waves, and infers the existence of cracks based on waveform changes. The radiographic detection method relies on the refraction phenomenon when the rays penetrate concrete to detect cracks. In addition, the core sampling method drills core samples from the concrete surface to visually check the condition of the cracks in the core samples.

[0004] However, these traditional crack detection technologies have obvious limitations, such as high reliance on manual operation, low detection quality and efficiency, and greater risks to the safety of operators in the operation and maintenance environment. In this context, with the rapid development of artificial intelligence technologies such as deep learning, engineers have begun to apply these advanced technologies to the field of crack detection. At present, crack detection methods based on deep learning technology mainly include convolutional neural networks (CNN), deeplab series, fully convolutional networks (FCN), U-Net networks, and YOLO algorithms.

[0005] Although artificial intelligence technology has made significant progress in crack identification, the representation of cracks still mainly relies on the traditional discrete line segment positioning method. The disadvantage of this method is the lack of crack representation data structure for intelligent algorithms, which limits the efficient application of artificial intelligence algorithms in crack-based structural performance assessment. Summary of the invention

[0006] The purpose of the present invention is to provide a digital model of engineering structure cracks and a storage method thereof, which is used to solve the problem that the prior art lacks a crack representation data structure for intelligent algorithms, thereby limiting the efficient application of artificial intelligence algorithms in crack-based structural performance assessment, and can realize the digital expression and physical storage of complex crack networks.

[0007] In order to achieve the above-mentioned object, in a first aspect, the present invention provides a digital model of cracks in an engineering structure, comprising a plurality of independent cracks; each crack comprises an end node and a crack body, the end node records the position coordinates of the two ends of the crack, the crack body records the crack information, and all the cracks are connected through a common end node to form a crack network; Crack information includes crack location parameters, crack basic geometric parameters and crack shape.

[0008] According to a digital model of an engineering structure crack provided by the present invention, crack position parameters include crack axis intersection endpoint numbers and crack actual endpoint numbers.

[0009] According to a digital model of an engineering structure crack provided by the present invention, the crack shape refers to the curve shapes of the upper side, the lower side and the middle axis of the crack respectively described by three mathematical expressions.

[0010] According to a digital model of engineering structure cracks provided by the present invention, the three mathematical expressions specifically include: constructing a global coordinate system based on the crack grid image, and using polynomial fitting to generate mathematical expressions of the upper side, lower side and central axis of the crack.

[0011] According to a digital model of an engineering structure crack provided by the present invention, basic geometric parameters of the crack include an average crack width, a maximum crack width, a minimum crack width, and a crack length.

[0012] According to a digital model of engineering structure cracks provided by the present invention, the average crack width, the maximum crack width, and the minimum crack width are obtained by calculating the shortest distance between the upper side and the lower side of the crack through mathematical expressions, and the crack length is calculated through the mathematical expression of the crack center axis.

[0013] In a second aspect, the present invention further provides a method for storing a digital model of a crack in an engineering structure, which is applied to the digital model of a crack in an engineering structure in the first aspect, and the method comprises: Step 1: Use an imaging device to capture images of cracks in the engineering structure to obtain a crack grid image; Step 2: Identify and digitally locate the crack grid image, and determine the position coordinates of each end node of the crack network in the crack grid image in the global coordinate system; Step 3: Cut the crack network into multiple image units with a single crack, and obtain the crack information in each image unit; Step 4: Assemble all cracks through common end nodes according to the crack information to form a crack network map; Step 5: Store the crack network map using an adjacency matrix or a linked list.

[0014] According to a method for storing a digital model of cracks in an engineering structure provided by the present invention, crack information is stored via JSON or an array.

[0015] According to a method for storing a digital model of cracks in an engineering structure provided by the present invention, the method also includes: step 6, traversing and acquiring all crack information in a crack network map through a recursive search algorithm, selecting a structural performance evaluation algorithm, and performing performance degradation evaluation on the cracks.

[0016] The present invention provides a digital model of engineering structure cracks and a storage method thereof, wherein the digital model of engineering structure cracks includes multiple independent cracks; each crack includes an end node and a crack body, the end node records the position coordinates of the two ends of the crack, the crack body records the crack information, and all cracks are connected through a common end node to form a crack network; the crack information includes crack position parameters, crack basic geometric parameters and crack shape. The present invention can realize the digital expression and physical storage of complex crack networks, provide an accurate mathematical expression model and efficient storage for the performance evaluation of downstream cracked structures, and has low research and development difficulty, is easy to promote and apply, and has a good market prospect. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] In the attached picture: Figure 1 This is a physical picture of a crack network of a concrete structure according to an embodiment of the present invention; Figure 2 is a schematic diagram of a crack network according to an embodiment of the present invention; Figure 3 A schematic diagram of a crack network map according to an embodiment of the present invention; Figure 4 A schematic diagram of a digital crack model according to an embodiment of the present invention; Figure 5 This is a schematic diagram of crack geometry fitting according to an embodiment of the present invention; Figure 6A schematic diagram of a fracture network map stored in an adjacency matrix in an embodiment of the present invention; Figure 7 This is a flow chart of a method for storing a digital model of cracks in an engineering structure according to another embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Some embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0021] To promote the in-depth application of intelligent technology in the field of concrete structure health monitoring and damage assessment, please refer to Figures 1 to 4 The embodiment of the present invention provides a digital model of engineering structure cracks, including multiple independent cracks; each crack includes an end node and a crack body, that is, the engineering structure cracks are represented as a knowledge graph consisting of "end node - crack body - end node". The position coordinates of the two ends of the crack are recorded in the end node, the crack body is located by the position coordinates of the two ends, the crack body records the crack information, and all cracks are connected through the common end node to form a crack network, then the crack network can be represented as a crack network graph consisting of "end node - crack body - end node".

[0022] Specifically, the crack information includes crack location parameters, basic crack geometric parameters, crack shape, etc., which can be stored through data structures such as JSON and arrays, and parsed through corresponding parsing algorithms.

[0023] Among them, the crack position parameters include the intersection endpoint number of the crack axis and the actual endpoint number of the crack. The basic geometric parameters of the crack include information such as the average width of the crack, the maximum width of the crack, the minimum width of the crack, and the length of the crack, which can be obtained by calculating the mathematical expression of the crack shape. The width of the crack (average width, maximum width, minimum width) is obtained by the shortest distance between the upper side and the lower side of the crack. The length of the crack refers to the length calculated by the mathematical expression of the crack center axis. The crack shape refers to the shape of the crack described by a mathematical expression, including three mathematical expressions for the upper side, lower side and center axis of the crack, specifically including: constructing a global coordinate system based on the image pixel grid map of the crack (crack grid image), using polynomial fitting to generate the mathematical expression of the crack, and storing the coefficients of the mathematical expression in order of the power size of the variable, generally an array or linked list data structure can be selected.

[0024] It should be noted that Figure 1 This is a physical picture of the crack network of a concrete structure. Figure 2 is a schematic diagram of the crack network. Figure 2 There are three cracks in the figure, marked as crack 1, crack 2, and crack 3. The intersection of the axes of crack 1 and crack 2 is point A. Crack 1 and crack 3 do not intersect, but the intersection of their axes is point B, that is, one of the end nodes of crack 3 is at a distance from the starting point of crack 1. Accordingly, Figure 3 In the figure, the two end nodes of crack 1 are numbered as node[1] and node[5]; the two end nodes of crack 2 are numbered as node[2] and node[4]; the two end nodes of crack 3 are actually numbered as node[3,1] and node[6,1], and the axis intersection endpoints are numbered as node[3] and node[6]; there are five crack bodies formed between the three cracks: edge[1,2], edge[2,3], edge[3,5], edge[2,4], and edge[3,6]. Figure 4 This is a schematic diagram of the digital crack model, showing the crack body edge[i,j] between the end nodes node[i] and node[j]. The mathematical expression is: Y=a0+a1x+a2x 2 +a3x 3 +……, the corresponding end node coordinates, the variable coefficients of the mathematical expression constitute the geometric expression, geometric characteristics and the crack body. Figure 5 The three mathematical expressions of the upper side, lower side and middle axis of the crack are Y u =f(x1),Y c =a0+a1x+a2x 2 +a3x 3 +……、Y b = f(x2), and the maximum crack width, average width and length are shown. Figure 6 Schematic diagram of the storage of the fracture network map using the adjacency matrix method.

[0025] Another embodiment of the present invention provides a method for storing a digital model of cracks in an engineering structure, which can realize digital storage of cracks. It is very important for structural damage rating based on digital image vision technology. Digital storage can not only improve the accuracy and efficiency of crack detection, but also provide richer and more structured data for artificial intelligence algorithms, thereby helping to achieve efficient and accurate structural performance evaluation. Figure 7 As shown, the method includes: Step 1: Use an imaging device to capture images of cracks in the engineering structure to obtain a crack grid image; Specifically, the target crack structure can be selected first, and then the cracks can be photographed or recorded with a digital camera manually or by an unmanned aerial vehicle to obtain a crack grid image, or the video frame can be converted into a crack grid image to form a crack image library. Step 2: Identify and digitally locate the crack grid image, and determine the position coordinates of each end node of the crack network in the crack grid image in the global coordinate system; Specifically, pre-trained deep learning algorithms such as YOLO and UNET with crack recognition function can be used to identify cracks in the crack grid image and perform digital positioning to determine the position coordinates of each end node in the crack network in the global coordinate system.

[0026] Step 3: Cut the crack network into multiple image units with a single crack, and obtain the crack information in each image unit; Specifically, the crack network can be positioned and cropped through the OpenCV library to form an image unit with a single crack, and then the background noise of the single crack can be removed through filtering algorithms such as candy and Gaussian, and the skeleton of the single crack can be stripped out. Based on each image unit with a single crack, the geometric shapes of the upper side, lower side and central axis of the crack are polynomially fitted to form a mathematical expression. According to the proportional relationship between the crack length and the pixel point, mathematical calculations are performed based on the above three mathematical expressions to obtain the crack length, average crack width, maximum crack width, minimum crack width and crack position parameters. The traversal loop performs the above processing on all image units with a single crack to obtain the crack information of all cracks.

[0027] Step 4: Assemble all cracks through common end nodes according to the crack information to form a crack network map; Step 5: Store the crack network map in the form of an adjacency matrix or a linked list.

[0028] Specifically, the fracture network map may be stored in a physical hard disk in the form of an adjacency matrix or a linked list. In some embodiments, the method may further include: step 6, traversing and acquiring all crack information in the crack network map through recursive search algorithms such as depth-first and breadth-first, selecting a structural performance evaluation algorithm, and evaluating the performance degradation of the crack structure. Thus, scientific decisions can be made on measures such as reinforcement, repair and maintenance of the crack structure in combination with the structural performance degradation index.

[0029] In summary, the digital model of engineering structure cracks and its storage method provided by the present invention represent engineering structure cracks as a crack network map composed of "end node - crack body - end node", obtain characteristic parameters such as crack length and width by fitting the crack shape with polynomials, and perform physical storage through adjacency matrix, linked list, etc., to achieve digital expression and physical storage of complex crack networks, and provide accurate mathematical expression models and efficient storage for performance evaluation of downstream cracked structures. The related knowledge graph technology and crack feature recognition technology are mature existing technologies with low research and development difficulty, easy to promote and apply, and have good market prospects.

[0030] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the embodiments disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A digital model of engineering structure cracks, characterized in that: It includes multiple independent cracks; each crack includes an end node and a crack body, the end node records the position coordinates of the two ends of the crack, the crack body records the crack information, and all the cracks are connected through a common end node to form a crack network; The crack information includes crack position parameters, crack basic geometric parameters and crack shape.

2. The digital model of engineering structure cracks according to claim 1, characterized in that: The crack position parameters include the crack axis intersection endpoint number and the crack actual endpoint number.

3. The digital model of engineering structure cracks according to claim 1, characterized in that: The crack shape refers to the curve shapes of the upper side, lower side and middle axis of the crack described by three mathematical expressions respectively.

4. The digital model of engineering structure cracks according to claim 3, characterized in that: The three mathematical expressions specifically include: constructing a global coordinate system based on the crack grid image, and generating mathematical expressions of the upper side, lower side and middle axis of the crack by using a polynomial fitting method.

5. The digital model of engineering structure cracks according to claim 3, characterized in that: The basic geometric parameters of the crack include the average crack width, the maximum crack width, the minimum crack width, and the crack length.

6. The digital model of engineering structure cracks according to claim 5, characterized in that: The average width, maximum width and minimum width of the crack are obtained by calculating the shortest distance between the upper side and the lower side of the crack through a mathematical expression, and the length of the crack is calculated through a mathematical expression of the center axis of the crack.

7. A method for storing a digital model of cracks in an engineering structure, characterized in that: The method applied to the digital model of the engineering structure crack according to any one of claims 1 to 6 comprises: Step 1: Use an imaging device to capture images of cracks in the engineering structure to obtain a crack grid image; Step 2: Identify and digitally locate the crack grid image to determine the position coordinates of each end node of the crack network in the crack grid image in the global coordinate system; Step 3: cutting the crack network into a plurality of image units having a single crack, and obtaining crack information in each image unit; Step 4: assemble all the cracks through common end nodes according to the crack information to form a crack network map; Step 5: storing the crack network map using an adjacency matrix or a linked list.

8. The method for storing a digital model of a crack in an engineering structure according to claim 7, characterized in that: The crack information is stored via JSON or an array.

9. The method for storing a digital model of a crack in an engineering structure according to claim 7, characterized in that: The method further includes: step 6, traversing and acquiring all crack information in the crack network map through a recursive search algorithm, selecting a structural performance evaluation algorithm, and performing performance degradation evaluation on the cracks.

Images