Tunnel disease information visualization method and system

Abstract

The invention discloses a tunnel disease information visualization method and system, and relates to the technical field of tunnel disease detection, and the method comprises the steps: obtaining the form information and position information of a tunnel disease according to tunnel disease detection data, generating a tunnel matrix, determining the type of the tunnel disease according to the form information of the tunnel disease, and carrying out the detection of the tunnel disease. According to the type and the position information of the tunnel disease, the position and the size of the tunnel disease in the tunnel matrix are obtained through return operation of a round function and rounding operation of a fix function, an all-one matrix with the same position and the size as the tunnel disease is generated accordingly, the corresponding position of the tunnel matrix is filled with the all-one matrix, color filling is conducted on the tunnel matrix through an imagesc function, and the tunnel disease is obtained. And obtaining a display result of the tunnel disease. According to the method, the content and the position information of the tunnel diseases are stored in a matrix form and arranged into a matrix, each matrix element stores the information related to the corresponding positions and the diseases, and the method can more conveniently analyze, process and visually present the disease data.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel disease detection, and in particular to a method and system for visualizing tunnel disease information. Background Art

[0002] A tunnel is an engineering structure buried in the ground. It is a form of human utilization of underground space. In a broad sense, it refers to a cavern with a cross-sectional area greater than 2 that is built underground by any method in a specified shape and size for some purpose. During the operation of the tunnel, water damage, lining cracks, tunnel frost damage, lining corrosion, earthquake damage, and air pollution in the tunnel may occur. Tunnel diseases have an impact on the normal operation and safety of the tunnel, and sometimes the impact is very serious. Moreover, there is a prominent contradiction between disease control and maintaining operation. Disease control interferes with normal operation and causes operational losses. Disease control is carried out under conditions where space, time and construction conditions are limited, and there are many difficulties. Therefore, prevention should be the priority. Preventive measures must be taken in the design stage to prevent the occurrence of diseases. On the other hand, the causes of the diseases must be identified and reasonable measures must be taken to control them, so as to improve the engineering quality and economic benefits of tunnel disease control.

[0003] Tunnel disease visualization technology is a method of displaying tunnel disease conditions in a graphical manner, which is extremely important for tunnel maintenance and management; this technology may include data collection, specifically the use of various devices to collect tunnel disease data, data processing, specifically converting raw data into a format suitable for visualization, and data visualization, specifically using tools to display data in two-dimensional or three-dimensional space; some common tunnel disease visualization technologies include: video measurement technology, laser scanning technology, infrared imaging technology, ultrasonic detection technology, microwave imaging technology, and video measurement technology.

[0004] However, when these technologies process large-scale, multi-dimensional tunnel disease data, due to their singleness and limitations, after identifying the deep structure inside the tunnel, they can only display the shallow texture information, hole information or structural information of the tunnel disease information, making it difficult to clearly display the disease information inside the tunnel in all directions. Summary of the invention

[0005] The embodiments of the present invention provide a method and system for visualizing tunnel disease information, which can solve the problem in the prior art that it is difficult to clearly display the disease information inside the tunnel in an all-round manner.

[0006] The embodiment of the present invention provides a method for visualizing tunnel disease information, comprising the following steps:

[0007] According to the tunnel disease detection data, the morphological information and location information of the tunnel disease are obtained;

[0008] According to the morphological information of tunnel diseases, the crack information in the morphological information is retrieved by using the conditional judgment method, and the crack information is matched with the tunnel disease type by using the matching technology to determine the tunnel disease type;

[0009] Expand the tunnel into a rectangle determined by its length and width, divide the rectangle into a rectangular array with fixed square areas, fill each area in the array with zeros to form an all-zero tunnel matrix; determine the size of the tunnel disease in the rectangle and rectangular array according to the tunnel disease type and location information, round the decimal part of the tunnel disease size to a decimal place containing only one decimal place, combine the decimal place of the tunnel disease size with the integer place, and obtain the position and size of the tunnel disease in the all-zero tunnel matrix;

[0010] According to the position and size of the tunnel disease in the all-zero tunnel matrix, an all-1 matrix with the same position and size as the tunnel disease is generated, and it is filled into the corresponding position of the tunnel disease in the all-zero tunnel matrix. The imagesc function is used in Matlab to convert the element values ​​in the tunnel matrix into different colors according to their sizes, and the color map filling method is used to fill the colors to obtain the display results of the tunnel disease.

[0011] Preferably, the step of obtaining the morphological information of tunnel damage comprises the following steps:

[0012] According to the tunnel disease detection data, the digital information in the detection data is extracted using regular expressions;

[0013] The digital information is converted into numerical data to obtain the morphological information of tunnel diseases.

[0014] Preferably, obtaining the location information of tunnel damage comprises the following steps:

[0015] Based on the tunnel disease detection data, the location description is obtained using text processing technology;

[0016] The location descriptions are classified, and the digital expression information of the locations is extracted to obtain the location information of tunnel diseases.

[0017] Preferably, forming an all-zero tunnel matrix comprises the following steps:

[0018] Extract the tunnel width, length, height and curvature data based on tunnel disease detection data;

[0019] Expand the tunnel into a matrix determined by the length and width, divide the rectangle into fixed square areas to obtain a rectangular array, and fill each area in the rectangular array with zeros to form an all-zero tunnel matrix.

[0020] Preferably, the determining of the tunnel damage type comprises the following steps:

[0021] According to the morphological information of tunnel diseases, the if function and for function of the conditional judgment method are used to loop and check the crack information in the morphological information;

[0022] Matching technology is used to match the crack information with the tunnel disease type to determine the tunnel disease type.

[0023] Preferably, the tunnel damage types include:

[0024] Longitudinal cracks, circumferential cracks, oblique cracks, and network cracks.

[0025] Preferably, obtaining the position and size of the tunnel defect in the all-zero tunnel matrix comprises the following steps:

[0026] Determine the size of tunnel defects in rectangular and rectangular arrays based on the tunnel defect type and location information;

[0027] The decimal part of the tunnel defect size is rounded off step by step to form a decimal place containing only one decimal place;

[0028] Extract the integer part of the tunnel disease size into integer bits;

[0029] By combining the decimal value and the integer value, the position and size of the tunnel disease in the all-zero tunnel matrix are obtained.

[0030] Preferably, obtaining the display result of tunnel damage comprises the following steps:

[0031] According to the position and size of the tunnel disease in the all-zero tunnel matrix, generate an all-1 matrix with the same position and size as the tunnel disease;

[0032] Fill the all-1 matrix to the corresponding position of the tunnel disease in the all-zero tunnel matrix, and use the imagesc function in Matlab to convert the element values ​​in the tunnel matrix into different colors according to their size to obtain the shallow display result;

[0033] The colormap function and jet function in Matlab are used to set the color mapping for the shallow display results, and the colorbar function in Matlab is used to add a color bar to the shallow display results to obtain the two-dimensional display results of the tunnel disease.

[0034] The three-dimensional function is used to represent the entire tunnel, and the position of the tunnel disease in three dimensions is obtained according to the cross-sectional function. Combined with the two-dimensional display results of the tunnel disease, the three-dimensional display results of the tunnel disease are obtained.

[0035] Preferably, each number in the matrix represents a fixed square area of ​​0.1 m×0.1 m in practice.

[0036] The present invention also provides a tunnel disease information visualization system, comprising:

[0037] Data acquisition and processing module, used to collect tunnel disease detection data;

[0038] Feature extraction module, used to obtain the morphological and location information of tunnel defects;

[0039] A data structure initialization module is used to expand the tunnel into a rectangle determined by the length and width, divide the rectangle into a rectangular array with fixed square areas, and fill each area in the array with zeros to form an all-zero tunnel matrix;

[0040] The feature recognition module uses the conditional judgment method to retrieve the crack information in the morphological information according to the morphological information of the tunnel disease, and uses the matching technology to match the crack information with the tunnel disease type to determine the tunnel disease type;

[0041] The disease classification module is used to determine the size of the tunnel disease in the rectangular and rectangular arrays according to the tunnel disease type and location information, round the decimal part of the tunnel disease size to a decimal place containing only one decimal place, combine the decimal place of the tunnel disease size with the integer place, and obtain the position and size of the tunnel disease in the all-zero tunnel matrix;

[0042] The data processing module generates an all-1 matrix with the same position and size as the tunnel disease according to the position and size of the tunnel disease in the all-zero tunnel matrix;

[0043] A size mapping module is used to fill it into the corresponding position of the tunnel disease in the all-zero tunnel matrix;

[0044] The visualization module is used to convert the element values ​​in the tunnel matrix into different colors according to their sizes using the imagesc function in Matlab, and fill them with colors using the color map filling method to obtain the display results of tunnel diseases.

[0045] The embodiment of the present invention provides a method and system for visualizing tunnel disease information. Compared with the prior art, the beneficial effects thereof are as follows:

[0046] By acquiring the detection data of tunnel diseases, the morphological information and position information of the tunnel diseases are obtained, and accordingly an all-zero matrix with the same size as the tunnel is generated. The tunnel disease type is determined according to the morphological information of the tunnel diseases. The position and size of the tunnel diseases in the tunnel are calculated by combining the position information of the tunnel and using the return operation of the round function and the integer operation of the fix function. Then, an all-1 matrix with the same position and size as the tunnel disease is generated and filled into the corresponding position of the tunnel matrix. The tunnel diseases are displayed after coloring by various means. The present invention organizes the tunnel into a huge all-zero matrix, fills the tunnel diseases into the corresponding positions of the all-zero matrix in the form of an all-1 matrix, and compares the tunnels without diseases and the tunnels with diseases from the perspective of the matrix with zero and one. Overall, the presentation of tunnel diseases is clearer, making it more convenient for staff to view and manage tunnels. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A schematic diagram of the overall process of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0048] Figure 2 A schematic diagram of tunnel disease information of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0049] Figure 3 A schematic diagram of two-dimensional display of tunnel disease information of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0050] Figure 4 A schematic diagram of three-dimensional display of tunnel disease information of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0051] Figure 5 A visualization effect diagram of longitudinal cracks of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0052] Figure 6 A grid coordinate effect diagram of longitudinal cracks of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0053] Figure 7 A matrix processing effect diagram of longitudinal cracks of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0054] Figure 8 A visualization effect diagram of circumferential cracks of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0055] Fig. 9A grid coordinate effect diagram of circumferential cracks of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0056] Fig.10 A matrix effect diagram of circumferential cracks of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0057] Fig.11 A visualization effect diagram of oblique cracks of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0058] Fig.12 A grid coordinate effect diagram of oblique cracks of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0059] Fig.13 A matrix effect diagram of oblique cracks of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0060] Fig.14 A visualization effect diagram of network cracks of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0061] Fig.15 A grid coordinate effect diagram of mesh cracks of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0062] Fig.16 A matrix processing effect diagram of mesh cracks of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0063] Fig.17 A visualization effect diagram of a mountain tunnel of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0064] Fig.18 A visualization effect diagram of a plateau tunnel of a tunnel disease information visualization method and system provided by an embodiment of the present invention;

[0065] Fig.19 A visualization effect diagram of a plain tunnel of a tunnel disease information visualization method and system provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0066] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present invention, so the present invention is not limited by the specific embodiments disclosed below.

[0067] See also Figures 1 to 19 The embodiment of the present invention provides a method for visualizing tunnel disease information, comprising the following steps:

[0068] Step one: text extraction and number recognition.

[0069] Read the data in the Excel file and store it in a new matrix; first use the readtable function to read the Excel file named "test.xlsx" and store the data in the variable tableData; then use the size function to get the number of rows and columns of tableData, and then create a new all-zero matrix a, whose number of rows and columns are the number of rows and 5 of tableData respectively; finally, assign the data in the 6th and 7th columns of tableData to the 4th and 5th columns of the new matrix a respectively, completing the data reading and processing process.

[0070] Step 2: Extract location information.

[0071] Extract numbers from tableData.Var2 and find the maximum value and its index, and use the extracted numbers as the first column of matrix a; first, create an empty cell array numbers of the same size as tableData.Var2, then, through a loop that iterates over each element in tableData.Var2, use the regexp function to extract numbers from each element, and convert them into double-precision numbers and store them in numbers{i}. In each loop, only the second element in the number array extracted by the regular expression is retained. After the loop ends, convert the cell array numbers into a matrix, and then use the max function to find the maximum value of the first column and its index. Finally, use the extracted numbers as the first column of matrix a.

[0072] Step 3: Matching disease types.

[0073] According to the crack information in tableData.Var4 and tableData.Var5, assign appropriate values ​​to the second column of matrix a. Then create an empty cell array ttp with a size of the number of rows multiplied by 2, and assign the data of tableData.Var4 and tableData.Var5 to the first and second columns of ttp respectively. Then, through a nested for loop and multiple if statements, check the crack information in ttp{i,1} and ttp{i,2}, and assign appropriate values ​​to the second column of matrix a. In each if statement, generate a random number and multiply it by part of the tunnel width to obtain a suitable value, which will be stored in a(i,2).

[0074] Step 4: Generate tunnel matrix.

[0075] Get the tunnel width from the detection report, and then create an all-zero matrix fla determined by the tunnel length and tunnel width.

[0076] Step 5: Determine the location of the disease.

[0077] Create the corresponding crack pattern in the FLA matrix according to the specified crack type information and display it. First, start a loop to traverse all the rows. Inside this loop, a nested if statement is used to check the crack type of each row, which may include circumferential cracks, longitudinal cracks, oblique cracks and mesh cracks. For each crack type, use the round and fix functions to determine the location and size of the crack.

[0078] Step 6: Generate disease matrix.

[0079] Once this information is determined, a matrix small is created that is filled with all 1s and the size matches the cracks, and is filled into the corresponding positions of the matrix fla. The matrix fla is then visualized using the imagesc function, the colormap and jet(256) colormap are used to set the color map, and the colorbar function is used to add a color bar to improve the visualization effect.

[0080] Step 7: Visualization.

[0081] The imagesc function is used to visualize the tunnel disease matrix, achieving a two-dimensional visualization effect of tunnel diseases. The tunnel section is expressed using a function. The three-dimensional function is first used to express the entire tunnel. According to the location of the tunnel disease and the matrix disease, the position of the disease point at each location is calculated in three dimensions according to the section function. Finally, the two are combined to form a three-dimensional visualization of the tunnel disease.

[0082] like Figure 2As shown, a tunnel disease information display diagram of a tunnel disease information visualization method is provided in an embodiment of the present invention, and the status, characteristics, size and form of the tunnel disease information are specifically displayed in a table; specifically, the initial data set is first collected and annotated, and then the mileage pile number and disease information are extracted, followed by identifying and classifying the disease type and location, and finally a structured matrix is ​​constructed, in which the number of columns is set according to the actual situation.

[0083] like Figure 3 FIG. 1 is a schematic diagram of a two-dimensional display of tunnel disease information of a method for visualizing tunnel disease information provided by an embodiment of the present invention, specifically, Figure 2 The tunnel disease information shown in the information perfectly presents the crack distribution of the tunnel. By unfolding the tunnel structure plane, the cracks exist in line shape, and the length and position of the cracks are clearly depicted on the two-dimensional plane. Cracks of different widths are distinguished by the thickness of the lines. Wider cracks are represented by thicker lines, which provides convenience for observers to intuitively perceive the crack width. In this way, the spatial distribution and size of tunnel cracks are presented in a simple and clear manner, providing an intuitive reference for subsequent disease analysis and repair.

[0084] like Figure 4 As shown, a schematic diagram of three-dimensional display of tunnel disease information of a tunnel disease information visualization method provided by an embodiment of the present invention is shown. To further enhance the visualization effect, a three-dimensional space coordinate system is generated according to the physical size and structural characteristics of the tunnel, and a three-dimensional tunnel model is established based on this. The location of the disease is integrated into the three-dimensional model, replacing 1 in the disease matrix. The data are visualized through three-dimensional display technology to present a three-dimensional view of the tunnel disease.

[0085] like Figures 5 to 16 As shown, the matrix processing effect and visualization effect diagram of the longitudinal cracks, annular cracks, mesh cracks and oblique cracks of the present invention are shown. These matrices are based on 0 and are filled in the corresponding positions according to the shape characteristics of the cracks, so as to perform a visualization display, which can accurately reflect the shape and characteristics of the disease and simplify the data processing process. In the form of a matrix, complex disease data can be effectively classified, analyzed and stored, thereby improving the efficiency and accuracy of damage diagnosis.

[0086] For the extraction of text in the document, there are also the following methods:

[0087] Bag of Words model: This is a common text data conversion method that converts text into a vector (which can be imagined as a one-dimensional matrix), in which each element represents the frequency or weight of a word in the text.

[0088] TF-IDF: This is an evolution of the bag-of-words model that considers not only the frequency of words but also the importance of words (i.e., the frequency of occurrence of words in all texts). This method can generate a matrix in which each row represents a text and each column represents a word.

[0089] Document vectors (Doc2Vec): This is a method that converts entire documents into vectors, which can produce a richer representation of text than bag-of-words and TF-IDF.

[0090] Word Embedding: This is a method that uses a neural network model to convert words into high-dimensional vectors, such as Word2Vec, GloVe, etc. The word embeddings of all words in a document can be averaged or otherwise operated to obtain a vector representation of the document.

[0091] Image encoding: Matrix data can be regarded as images and encoded using convolutional neural networks (CNNs) to obtain dense representations of images, which is common in the field of computer vision.

[0092] The present invention represents and stores the disease data in the form of a matrix. The disease data includes disease content and location information. These data are organized into a matrix, wherein the rows and columns of the matrix correspond to different diseases and their locations, and each matrix element can store information related to the corresponding location and disease, such as the severity, type, size, etc. of the disease. Through this matrixization method, the disease data can be more conveniently analyzed, processed and visualized, helping engineers and researchers to better understand and manage the disease conditions in tunnels or other structures. This method helps to improve the operability of the data and the efficiency of analysis.

[0093] Extracting tunnel disease reports for three-dimensional reconstruction of tunnels is to create a two-dimensional model or image of the tunnel by using the information in the disease report, such as the location, type, size, etc. of the disease, and then realize the three-dimensional model of the tunnel disease through three-dimensional display technology.

[0094] A method of storing data in the form of a matrix. In computer science and data processing, matrices usually organize data in the form of rows and columns. The core idea of ​​matrix storage is to store data in a row and column structure for more efficient retrieval, analysis, and processing.

[0095] The embodiment of the present invention further provides a tunnel disease information visualization system, including:

[0096] The data acquisition and processing module is used to convert the raw detection data into a format more suitable for subsequent analysis and visualization.

[0097] The feature extraction module belongs to feature extraction and classification and is a deep-level application of data preprocessing.

[0098] The data structure initialization module is used to create a data structure based on the extracted size information for subsequent processing and analysis.

[0099] The feature recognition module is used to accurately identify the type and characteristics of the disease in the detection data.

[0100] Disease classification module, these classifications and descriptions can be represented by graphics, symbols or color coding.

[0101] The data processing module processes the raw data obtained after tunnel disease detection for further analysis and visualization.

[0102] The visualization module converts the tunnel disease detection data into visual information.

[0103] The size mapping module converts the detected tunnel defect sizes into corresponding units in the matrix.

[0104] like Figures 17 to 19 As shown, it is the effect diagram after the visualization of different tunnel diseases according to the embodiment of the present invention, based on which the tunnel can be reconstructed, the degree of tunnel disease can be evaluated, and the tunnel can be repaired.

[0105] The above-mentioned embodiments only express several implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A method for visualizing tunnel disease information, characterized in that: The following steps are involved: According to the tunnel disease detection data, the morphological information and location information of the tunnel disease are obtained; According to the morphological information of tunnel diseases, the crack information in the morphological information is retrieved by using the conditional judgment method, and the crack information is matched with the tunnel disease type by using the matching technology to determine the tunnel disease type; Expand the tunnel into a rectangle determined by its length and width, divide the rectangle into a rectangular array with fixed square areas, fill each area in the array with zeros to form an all-zero tunnel matrix; determine the size of the tunnel disease in the rectangle and rectangular array according to the tunnel disease type and location information, round the decimal part of the tunnel disease size to a decimal place containing only one decimal place, combine the decimal place of the tunnel disease size with the integer place, and obtain the position and size of the tunnel disease in the all-zero tunnel matrix; According to the position and size of the tunnel disease in the all-zero tunnel matrix, an all-1 matrix with the same position and size as the tunnel disease is generated, and it is filled into the corresponding position of the tunnel disease in the all-zero tunnel matrix. The imagesc function is used in Matlab to convert the element values ​​in the tunnel matrix into different colors according to their sizes, and the color map filling method is used to fill the colors to obtain the display results of the tunnel disease.

2. A tunnel disease information visualization method according to claim 1, characterized in that: The step of obtaining the morphological information of tunnel damage comprises the following steps: According to the tunnel disease detection data, the digital information in the detection data is extracted using regular expressions; The digital information is converted into numerical data to obtain the morphological information of tunnel diseases.

3. A method for visualizing tunnel disease information according to claim 1, characterized in that: The step of obtaining the location information of tunnel defects comprises the following steps: Based on the tunnel disease detection data, the location description is obtained using text processing technology; The location descriptions are classified, and the digital expression information of the locations is extracted to obtain the location information of tunnel diseases.

4. A tunnel disease information visualization method according to claim 1, characterized in that: The forming of an all-zero tunnel matrix comprises the following steps: Extract the tunnel width, length, height and curvature data based on tunnel disease detection data; Expand the tunnel into a matrix determined by the length and width, divide the rectangle into fixed square areas to obtain a rectangular array, and fill each area in the rectangular array with zeros to form an all-zero tunnel matrix.

5. The method for visualizing tunnel disease information according to claim 1, characterized in that: Determining the tunnel disease type comprises the following steps: According to the morphological information of tunnel diseases, the if function and for function of the conditional judgment method are used to loop and check the crack information in the morphological information; Matching technology is used to match the crack information with the tunnel disease type to determine the tunnel disease type.

6. A tunnel disease information visualization method according to claim 1, characterized in that: The tunnel disease types include: Longitudinal cracks, circumferential cracks, oblique cracks, and network cracks.

7. The method for visualizing tunnel disease information according to claim 1, characterized in that: The method of obtaining the position and size of the tunnel defect in the all-zero tunnel matrix comprises the following steps: Determine the size of tunnel defects in rectangular and rectangular arrays based on the tunnel defect type and location information; The decimal part of the tunnel defect size is rounded off step by step to form a decimal place containing only one decimal place; Extract the integer part of the tunnel disease size into integer bits; By combining the decimal value and the integer value, the position and size of the tunnel disease in the all-zero tunnel matrix are obtained.

8. The method for visualizing tunnel disease information according to claim 1, characterized in that: The method of obtaining the display result of tunnel disease comprises the following steps: According to the position and size of the tunnel disease in the all-zero tunnel matrix, generate an all-1 matrix with the same position and size as the tunnel disease; Fill the all-1 matrix to the corresponding position of the tunnel disease in the all-zero tunnel matrix, and use the imagesc function in Matlab to convert the element values ​​in the tunnel matrix into different colors according to their size to obtain the shallow display result; The colormap function and jet function in Matlab are used to set the color mapping for the shallow display results, and the colorbar function in Matlab is used to add a color bar to the shallow display results to obtain the two-dimensional display results of the tunnel disease. The three-dimensional function is used to represent the entire tunnel, and the position of the tunnel disease in three dimensions is obtained according to the cross-sectional function. Combined with the two-dimensional display results of the tunnel disease, the three-dimensional display results of the tunnel disease are obtained.

9. The method for visualizing tunnel disease information according to claim 1, characterized in that: Each number in the matrix represents a fixed square area of ​​0.1 m×0.1 m in practice.

10. A tunnel disease information visualization system, characterized in that: include: Data acquisition and processing module, used to collect tunnel disease detection data; Feature extraction module, used to obtain the morphological and location information of tunnel defects; A data structure initialization module is used to expand the tunnel into a rectangle determined by the length and width, divide the rectangle into a rectangular array with fixed square areas, and fill each area in the array with zeros to form an all-zero tunnel matrix; The feature recognition module uses the conditional judgment method to retrieve the crack information in the morphological information according to the morphological information of the tunnel disease, and uses the matching technology to match the crack information with the tunnel disease type to determine the tunnel disease type; The disease classification module is used to determine the size of the tunnel disease in the rectangular and rectangular arrays according to the tunnel disease type and location information, round the decimal part of the tunnel disease size to a decimal place containing only one decimal place, combine the decimal place of the tunnel disease size with the integer place, and obtain the position and size of the tunnel disease in the all-zero tunnel matrix; The data processing module generates an all-1 matrix with the same position and size as the tunnel disease according to the position and size of the tunnel disease in the all-zero tunnel matrix; A size mapping module is used to fill it into the corresponding position of the tunnel disease in the all-zero tunnel matrix; The visualization module is used to convert the element values ​​in the tunnel matrix into different colors according to their sizes using the imagesc function in Matlab, and fill them with colors using the color map filling method to obtain the display results of tunnel diseases.

Images