An intelligent database system for ancient building materials

Abstract

The invention relates to the field of image processing technology, in particular to an intelligent database system for ancient building materials, which comprises an acquisition processing unit, an analysis and calculation unit, and a prediction and replacement unit. The invention enhances the clarity of a blue brick image by Gaussian filtering, determines the damaged area of ​​the blue brick on the backlight side by using an edge detection algorithm, obtains the damage coefficient of the blue brick by calculating the area of ​​the damaged area, locates the damaged area of ​​the blue brick by a sensor, calculates the position of the damaged area of ​​the blue brick and the volume of the blue brick obtained from an intelligent database, obtains the hygroscopic expansion coefficient of the blue brick, obtains the influence coefficient of the blue brick on the overall structural stability of a bridge body by analyzing the damage coefficient and the hygroscopic expansion coefficient of the blue brick, finally, combines the influence coefficient of the blue brick on the overall structural stability of the ancient building bridge body with the bearing capacity of the blue brick in the intelligent database, calculates the predicted bearing capacity of the blue brick on the backlight side, and determines whether to replace the blue brick on the backlight side.

Description

Technical Field

[0001] The present invention relates to the technical field of image processing, and in particular to an intelligent database system for ancient building materials. Background Art

[0002] Image processing is an important technology. It can remove noise and enhance contrast of images to make them clearer, easier to observe and analyze. It can also reduce the storage space and transmission bandwidth of image data through effective compression algorithms. This is very important in image databases and network transmission. In recent years, with the continuous development of image processing technology, the intelligent database of ancient building materials has been widely used in the protection of ancient buildings. The intelligent database of ancient building materials is a system specially used to collect, organize, store and manage information related to ancient building materials. Its advantage is to provide accurate and detailed material information for the restoration, protection and reconstruction of ancient buildings, which helps to make scientific and reasonable decisions. Due to the long history of the ancient bridge, if the blue bricks on the backlight surface of the ancient bridge are not repaired and replaced in time, the ancient bridge structure will be unstable. In order to solve this technical problem, we provide an intelligent database system for ancient building materials. Summary of the invention

[0003] The purpose of the present invention is to provide an intelligent database system for ancient building materials to solve the problems raised in the above-mentioned background technology.

[0004] To achieve the above-mentioned purpose, an intelligent database system of ancient building materials is provided, which includes a collection and processing unit, an analysis and calculation unit, and a prediction and replacement unit;

[0005] The acquisition processing unit acquires images of the blue bricks on the backlight surface of the ancient building bridge body through a high-definition camera, and stores the acquired blue brick images in the intelligent database after image smoothing.

[0006] The analysis and calculation unit extracts the image of the backlit blue bricks of the ancient building bridge from the intelligent database, and obtains the area of ​​the damaged blue bricks on the backlit blue bricks of the ancient building bridge by analyzing the image of the backlit blue bricks, calculates the damage coefficient of the blue bricks according to the area of ​​the damaged blue bricks on the backlit blue bricks of the ancient building bridge, and then locates the position of the damaged blue bricks on the backlit blue bricks of the ancient building bridge, obtains the hygroscopic expansion coefficient of the blue bricks according to the position of the damaged blue bricks on the backlit blue bricks of the ancient building bridge and the volume of the blue bricks, calculates and analyzes the damage coefficient of the backlit blue bricks and the hygroscopic expansion coefficient of the blue bricks, and calculates the influence coefficient of the backlit blue bricks on the overall structural stability of the ancient building bridge;

[0007] The prediction replacement unit combines the influence coefficient of the backlit blue bricks on the overall structural stability of the ancient building bridge body with the bearing capacity of the blue bricks in the intelligent database, calculates the predicted bearing capacity of the backlit blue bricks, compares the predicted bearing capacity of the backlit blue bricks with the bearing capacity required for the ancient building bridge body in the intelligent database, and determines whether to replace the blue bricks on the backlit surface.

[0008] As a further improvement of the present technical solution, the high-definition camera in the acquisition and processing unit is installed at the vertex of the backlit surface of the ancient building bridge body, so as to clearly capture the entire blue brick image of the backlit surface of the ancient building bridge body. The image smoothing processing is to smooth the backlit surface blue brick image through Gaussian filtering, so as to reduce noise and enhance the clarity of the backlit surface blue brick image.

[0009] As a further improvement of the technical solution, the analysis and calculation unit includes an edge determination module, a coefficient calculation module, a positioning analysis module, and a combined calculation module:

[0010] The edge determination module determines the damaged blue brick image in the backlit blue brick image by setting a damage threshold, detects the edge of the damaged blue brick region in the damaged blue brick image by an algorithm, and calculates the damaged blue brick region area and the damaged blue brick depth according to the damaged blue brick edge;

[0011] The coefficient calculation module calculates the ratio of the damaged area of ​​the blue brick to the total area of ​​the backlight surface and the damaged depth of the blue brick to obtain the damage coefficient of the blue brick;

[0012] The positioning analysis module locates the position of the damaged area of ​​the blue brick through the position sensor, obtains the height of the damaged area of ​​the blue brick from the water surface, and then obtains the hygroscopic expansion coefficient of the blue brick according to the height of the damaged area of ​​the blue brick from the water surface and the volume of the blue brick;

[0013] The combined calculation module calculates and analyzes the damage coefficient of the backlit blue bricks and the hygroscopic expansion coefficient of the blue bricks, and calculates the influence coefficient of the backlit blue bricks on the overall structural stability of the ancient building bridge body.

[0014] As a further improvement of the technical solution, the edge determination module detects the edge of the damaged blue brick area in the damaged blue brick image through an algorithm, specifically including:

[0015] By using the Sobel operator in the damaged blue brick image, the gradient values ​​in the horizontal and vertical directions are calculated. These gradient values ​​represent the degree of change in the pixel intensity in the image. By combining the gradient values ​​in the horizontal and vertical directions, the gradient amplitude and direction of each pixel in the damaged blue brick image are calculated. The gradient amplitude represents the magnitude of the intensity change around the pixel, while the gradient direction represents the direction of the change. Non-maximum suppression is performed in the gradient direction. This step can help us find the pixel with the largest local gradient, so as to locate the edge more accurately, and set high and low thresholds. According to the high and low thresholds, the gradient amplitude is divided into two categories: strong edge and weak edge. The strong edge pixels are tracked, and the weak edge pixels adjacent to the strong edge pixels are divided into edge pixels, thereby forming a continuous edge line.

[0016] As a further improvement of the technical solution, the edge determination module calculates the area of ​​the damaged blue brick region and the damaged blue brick depth according to the damaged blue brick edge, specifically including:

[0017] Inside the edge line, a threshold is set according to the gray value of the pixel, and the damaged area of ​​the blue brick and the background are separated into two areas. For the segmented image, the number of pixels inside the damaged area is counted, and the actual area of ​​the damaged area is calculated according to the pixel size and the pixel size ratio of the image;

[0018] The threshold is set to T, and the pixel points whose pixel values ​​exceed the threshold are set as the pixels inside the damaged area, otherwise they are background pixels. The number of pixels inside the damaged area is counted by the formula, that is: Where I(i, j) represents the value of the pixel in the i-th row and j-th column, N represents the number of pixels inside the damaged area, and n represents the number of pixels inside the damaged area. If the pixel size ratio of the image is P, the area A of the damaged area of ​​the blue brick is calculated by the formula: A = N*P 2 ;

[0019] A depth estimation model is established according to the grayscale value of the damaged area of ​​the blue bricks. The expression of the depth estimation model is: B=a*β+b, wherein B represents the estimated value of the damaged depth of the blue bricks, β represents the grayscale value, and a and b represent model parameters.

[0020] As a further improvement of the technical solution, the coefficient calculation module calculates the ratio of the damaged area of ​​the blue brick to the total area of ​​the backlight surface and the damaged depth of the blue brick to obtain the damage coefficient of the blue brick, which specifically includes:

[0021] The total backlit area of ​​the ancient bridge is extracted from the intelligent database and recorded as S bg , the ratio of the area of ​​the damaged blue bricks on the backlight side to the total area of ​​the backlight side is calculated, denoted as α, then: By calculating α, the small damaged area of ​​blue bricks on the backlit surface of the bridge body is ignored to reduce the amount of calculation. The damage depth of blue bricks is substituted into the formula to calculate the damage coefficient γ of blue bricks, then:

[0022] γ=ω1*α+ω2*B;

[0023] Among them, ω1 and ω2 represent the influence weights of the damaged area of ​​blue bricks and the damaged depth of blue bricks on the damage coefficient of blue bricks, respectively.

[0024] As a further improvement of the technical solution, the positioning analysis module obtains the hygroscopic expansion coefficient of the blue brick according to the height of the blue brick damaged area from the water surface and the volume of the blue brick, specifically including:

[0025] The position of the damaged area of ​​the blue brick is located by the position sensor, and the vertical height of the damaged area of ​​the blue brick from the horizontal plane is obtained to be H, the damaged area of ​​the blue brick is A, and the depth of the damaged part of the blue brick is B. Then the initial volume of the blue brick is: V cs =A*H, the damaged volume of the blue brick is: V ps =A*B, then the volume of the green brick after moisture absorption and expansion is: V xs =V cs +V ps , then the hygroscopic expansion is V xs -V cs , the hygroscopic expansion coefficient is calculated as C through the formula, then:

[0026]

[0027] As a further improvement of the technical solution, the calculation of the influence coefficient of the overall structural stability of the ancient building bridge body by the combined calculation module specifically includes:

[0028] Since the ancient bridge is built with blue bricks, the damage coefficient and morphological changes of blue bricks will affect the structural stability of the ancient bridge. The morphological changes are reflected in the increase of the hygroscopic expansion coefficient of blue bricks due to the dark and damp backlight surface of the ancient bridge. The damage coefficient and hygroscopic expansion coefficient of blue bricks on the backlight surface of the ancient bridge are calculated by formula, and the influence coefficient on the structural stability of the ancient bridge is obtained, namely:

[0029] δ=γ*C.

[0030] As a further improvement of the present invention, the prediction replacement unit determines whether to replace the blue bricks on the backlight surface by calculating the predicted bearing capacity of the blue bricks on the backlight surface, specifically including:

[0031] The ancient bridge body is composed of blue bricks, so the bearing capacity of the ancient bridge body is the bearing capacity of the blue bricks. Now, by calculating the predicted bearing capacity of the blue bricks on the backlight side of the ancient bridge body, and comparing the predicted bearing capacity of the blue bricks on the backlight side with the bearing capacity required by the ancient bridge body in the intelligent database, it is determined whether the blue bricks on the backlight side should be replaced. The initial bearing capacity F0 of the blue bricks is extracted through the intelligent database. The calculation formula of the predicted bearing capacity is:

[0032] F yc =δ*F0;

[0033] Extract the minimum bearing capacity F of the blue bricks for normal use from the intelligent database min , the predicted bearing capacity of the green brick F yc and the minimum bearing capacity F min For comparison, if the predicted bearing capacity of the green brick is F yc Below the minimum load capacity F min , indicating that the blue bricks cannot bear the force exerted on them by the ancient building bridge and need to be replaced immediately.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] In the intelligent database system of ancient building materials, the analysis and calculation unit obtains the area of ​​the damaged blue bricks on the backlight surface of the ancient building bridge body by analyzing the image of the backlight blue bricks, excludes areas with small damaged blue brick areas, reduces the amount of calculation, and calculates the damage coefficient of the blue bricks based on the damaged area of ​​the blue bricks on the backlight surface of the ancient building bridge body, so that maintenance personnel can clearly understand the specific damage of the blue bricks and make the next plan in time. Then, the hygroscopic expansion coefficient of the blue bricks is analyzed by locating the damaged position, and the damaged area of ​​the blue bricks is further analyzed, making the calculation of the coefficient affecting the overall structural stability of the ancient building bridge body more intuitive. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 It is an overall block diagram of the present invention.

[0037] The meaning of each number in the figure is:

[0038] 1. Acquisition and processing unit; 2. Analysis and calculation unit; 21. Edge determination module; 22. Coefficient calculation module; 23. Positioning analysis module; 24. Combined calculation module; 3. Prediction and replacement unit. DETAILED DESCRIPTION

[0039] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0040] Example 1

[0041] The present invention provides an intelligent database system for ancient building materials. Figure 1 As shown, it includes a collection and processing unit 1, an analysis and calculation unit 2, and a prediction and replacement unit 3;

[0042] The acquisition and processing unit 1 acquires images of the blue bricks on the backlight surface of the ancient building bridge body through a high-definition camera, and stores the acquired blue brick images into the intelligent database after image smoothing;

[0043] The high-definition camera in the acquisition and processing unit 1 is installed at the vertex of the backlight surface of the ancient building bridge body, and the image smoothing process is to smooth the backlight surface blue brick image through Gaussian filtering;

[0044] The expression of Gaussian filtering is: Among them, x and y are the horizontal and vertical offsets of the pixel respectively, and σ is the standard deviation of the Gaussian kernel. The blue brick image is smoothed by Gaussian filtering to reduce the influence of noise and make the backlit blue brick image clearer.

[0045] The analysis and calculation unit 2 extracts the image of the backlit blue brick of the ancient building bridge from the intelligent database, and obtains the area of ​​the damaged area of ​​the backlit blue brick of the ancient building bridge by analyzing the image of the backlit blue brick, calculates the damage coefficient of the blue brick according to the area of ​​the damaged area of ​​the backlit blue brick of the ancient building bridge, and then locates the position of the damaged area of ​​the backlit blue brick of the ancient building bridge, obtains the hygroscopic expansion coefficient of the blue brick according to the position of the damaged area of ​​the backlit blue brick of the ancient building bridge and the volume of the blue brick, calculates and analyzes the damage coefficient of the backlit blue brick and the hygroscopic expansion coefficient of the blue brick, and calculates the influence coefficient of the backlit blue brick on the overall structural stability of the ancient building bridge;

[0046] The analysis and calculation unit 2 includes an edge determination module 21, a coefficient calculation module 22, a positioning analysis module 23, and a combination calculation module 24;

[0047] The edge determination module 21 determines the damaged blue brick image in the backlit blue brick image by setting a damage threshold, and detects the edge of the damaged blue brick region in the damaged blue brick image through an algorithm, and calculates the damaged blue brick region area and the damaged blue brick depth according to the damaged blue brick edge;

[0048] The edge determination module 21 detects the edge of the damaged brick area in the damaged brick image through an algorithm, specifically including:

[0049] By using the Sobel operator in the damaged brick image, the gradient values ​​in the horizontal and vertical directions are calculated. By combining the gradient values ​​in the horizontal and vertical directions, the gradient amplitude and direction of each pixel in the damaged brick image are calculated.

[0050] Calculation of gradient magnitude and direction, specifically including:

[0051] Horizontal gradient G x =(I*G x )*M x ; Vertical gradient G y =(I*G y )*M y ; Where I is the original brick image, M x and M y They are respectively represented as the horizontal and vertical convolution kernels of the Sobel operator;

[0052] The calculation formula of gradient amplitude is: The calculation formula for the gradient direction is: Non-maximum suppression is performed in the gradient direction to retain the pixel with the largest local gradient in order to locate the edge more accurately. High and low thresholds are set. According to the high and low thresholds, the gradient amplitude is divided into two categories: strong edge and weak edge. The strong edge pixels are tracked and the weak edge pixels adjacent to the strong edge pixels are classified as edge pixels, thus forming a continuous edge line, which is helpful for further image analysis.

[0053] The edge determination module 21 calculates the damaged area and damaged depth of the blue brick according to the damaged edge of the blue brick, specifically including:

[0054] Inside the edge line, a threshold is set according to the gray value of the pixel to separate the damaged area of ​​the blue brick from the background to form two areas. For the segmented image, the number of pixels inside the damaged area is counted, and the actual area of ​​the damaged area is calculated based on the pixel size and the pixel size ratio of the image.

[0055] The threshold is set to T. For pixels whose pixel values ​​exceed the threshold, they are set as pixels inside the damaged area, otherwise they are background pixels. The number of pixels inside the damaged area is counted using the formula: Where I(i,j) represents the value of the pixel in the i-th row and j-th column, N represents the number of pixels inside the damaged area, and n represents the number of pixels inside the damaged area. If the pixel size ratio of the image is P, the area A of the damaged area of ​​the blue brick is calculated by the formula: A = N*P 2 ;

[0056] A depth estimation model is established according to the grayscale value of the damaged area of ​​the blue brick. The expression of the depth estimation model is: B=a*β+b, where B represents the estimated value of the damaged depth of the blue brick, β represents the grayscale value, and a and b represent model parameters, which help users to understand the damage more comprehensively and lay the foundation for subsequent coefficient calculation.

[0057] The coefficient calculation module 22 calculates the ratio of the damaged area of ​​the blue brick to the total area of ​​the backlight surface and the damaged depth of the blue brick to obtain the damage coefficient of the blue brick;

[0058] The coefficient calculation module 22 calculates the ratio of the damaged area of ​​the blue brick to the total area of ​​the backlight surface and the damaged depth of the blue brick to obtain the damage coefficient of the blue brick, which specifically includes:

[0059] The total backlit area of ​​the ancient bridge is extracted from the intelligent database and recorded as S bg , the ratio of the area of ​​the damaged blue bricks on the backlight side to the total area of ​​the backlight side is calculated, denoted as α, then: Substituting the damage depth of the blue brick into the formula to calculate the damage coefficient γ of the blue brick, we can get:

[0060] γ=ω1*α+ω2*B;

[0061] Among them, ω1 and ω2 represent the influence weights of the damaged area of ​​blue bricks and the damaged depth of blue bricks on the damage coefficient of blue bricks, respectively.

[0062] The positioning analysis module 23 locates the position of the damaged area of ​​the blue brick through the position sensor, obtains the height of the damaged area of ​​the blue brick from the water surface, and then obtains the hygroscopic expansion coefficient of the blue brick according to the height of the damaged area of ​​the blue brick from the water surface and the volume of the blue brick;

[0063] The positioning analysis module 23 obtains the hygroscopic expansion coefficient of the brick according to the height of the damaged area of ​​the brick from the water surface and the volume of the brick, which specifically includes:

[0064] The position of the damaged area of ​​the blue brick is located by the position sensor, and the vertical height of the damaged area of ​​the blue brick from the horizontal plane is obtained to be H, the damaged area of ​​the blue brick is A, and the depth of the damaged part of the blue brick is B. Then the initial volume of the blue brick is: V cs =A*H, the damaged volume of the blue brick is: V ps =A*B, then the volume of the green brick after moisture absorption and expansion is: V xs =V cs +V ps , then the hygroscopic expansion is V xs -V cs , the hygroscopic expansion coefficient is calculated as C through the formula, then:

[0065]

[0066] Combined with the calculation module 24, the damage coefficient of the backlit blue brick and the hygroscopic expansion coefficient of the blue brick are calculated and analyzed to calculate the influence coefficient of the backlit blue brick on the overall structural stability of the ancient building bridge body;

[0067] The calculation module 24 is combined with the calculation of the overall structural stability influence coefficient of the ancient building bridge body, specifically including:

[0068] Since the ancient bridge is built with blue bricks, the damage coefficient and morphological changes of blue bricks will affect the structural stability of the ancient bridge. The morphological change is reflected in the increase of the hygroscopic expansion coefficient of blue bricks due to the dark and damp backlight surface of the ancient bridge. The damage coefficient and hygroscopic expansion coefficient of blue bricks on the backlight surface of the ancient bridge are calculated by the formula, and the influence coefficient on the structural stability of the ancient bridge is obtained, namely:

[0069] δ=γ*C.

[0070] The prediction replacement unit 3 combines the influence coefficient of the backlit blue bricks on the overall structural stability of the ancient building bridge body with the bearing capacity of the blue bricks in the intelligent database, calculates the predicted bearing capacity of the backlit blue bricks, compares the predicted bearing capacity of the backlit blue bricks with the bearing capacity required by the ancient building bridge body in the intelligent database, and determines whether to replace the blue bricks on the backlit surface;

[0071] The prediction replacement unit 3 determines whether to replace the blue bricks on the backlight surface by calculating the predicted bearing capacity of the blue bricks on the backlight surface, which specifically includes:

[0072] The ancient bridge body is composed of blue bricks, so the bearing capacity of the ancient bridge body is the bearing capacity of the blue bricks. Now, by calculating the predicted bearing capacity of the blue bricks on the backlight side of the ancient bridge body, and comparing the predicted bearing capacity of the blue bricks on the backlight side with the bearing capacity required by the ancient bridge body in the intelligent database, it is determined whether the blue bricks on the backlight side should be replaced. The initial bearing capacity F0 of the blue bricks is extracted through the intelligent database. The calculation formula for the predicted bearing capacity is:

[0073] F yc =δ*F0;

[0074] Extract the minimum bearing capacity F of the blue bricks for normal use from the intelligent database min , the predicted bearing capacity of the green brick F yc and the minimum bearing capacity F min For comparison, if the predicted bearing capacity of the green brick is F yc Below the minimum load capacity F min , indicating that the blue bricks cannot bear the force exerted on them by the ancient building bridge and need to be replaced immediately.

[0075] In the present invention, the clarity of the collected blue brick image is enhanced by Gaussian filtering, and the damaged area of ​​the blue brick on the backlight side is determined by using an edge detection algorithm. The damage coefficient of the blue brick is obtained by calculating the area of ​​the damaged area. The damaged area of ​​the blue brick is then located by a sensor, and the position of the damaged area of ​​the blue brick and the volume of the blue brick obtained from an intelligent database are calculated to obtain the hygroscopic expansion coefficient of the blue brick. The influence coefficient of the blue brick on the overall structural stability of the bridge body is obtained by analyzing the damage coefficient and the hygroscopic expansion coefficient of the blue brick. Finally, the influence coefficient of the blue brick on the overall structural stability of the ancient building bridge body is combined with the bearing capacity of the blue brick in the intelligent database to calculate the predicted bearing capacity of the blue brick on the backlight side, and it is determined whether the blue brick on the backlight side should be replaced.

[0076] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An intelligent database system for ancient building materials, characterized in that: It comprises a collection and processing unit (1), an analysis and calculation unit (2), and a prediction and replacement unit (3); The acquisition and processing unit (1) acquires images of the blue bricks on the backlight surface of the ancient building bridge body through a high-definition camera, and stores the acquired blue brick images in an intelligent database after image smoothing. The analysis and calculation unit (2) extracts the image of the backlit blue bricks of the ancient bridge from the intelligent database, and obtains the area of ​​the damaged blue bricks on the backlit blue bricks of the ancient bridge and the depth of the damaged blue bricks by analyzing the image of the backlit blue bricks. The analysis and calculation unit (2) comprises an edge determination module (21), a coefficient calculation module (22), a positioning analysis module (23), and a combination calculation module (24); The edge determination module (21) determines the damaged blue brick image in the backlit blue brick image by setting a damage threshold, detects the edge of the damaged blue brick region in the damaged blue brick image by an algorithm, and calculates the area of ​​the damaged blue brick region and the damaged blue brick depth according to the damaged blue brick edge; The coefficient calculation module (22) calculates the ratio of the area of ​​the damaged area of ​​the blue brick to the total area of ​​the backlight surface and the damage depth of the blue brick to obtain the damage coefficient of the blue brick. The coefficient calculation module (22) calculates the ratio of the area of ​​the damaged area of ​​the blue brick to the total area of ​​the backlight surface and the damage depth of the blue brick to obtain the damage coefficient of the blue brick, which specifically includes: The total backlit area of ​​the ancient bridge is extracted from the intelligent database and recorded as , the ratio of the area of ​​the damaged bricks on the backlight side to the total area of ​​the backlight side is calculated and recorded as ,but: , substitute the damage depth of the blue brick into the formula to calculate the damage coefficient of the blue brick ,but: ； in, and They are respectively represented by the influence weights of the damaged area of ​​the blue brick and the damaged depth of the blue brick on the damage coefficient of the blue brick The positioning analysis module (23) locates the position of the damaged area of ​​the blue brick by means of a position sensor, obtains the height of the damaged area of ​​the blue brick from the water surface, and then obtains the hygroscopic expansion coefficient of the blue brick according to the height of the damaged area of ​​the blue brick from the water surface and the volume of the blue brick; The combined calculation module (24) calculates and analyzes the damage coefficient of the back-lit blue bricks and the hygroscopic expansion coefficient of the blue bricks, calculates the influence coefficient of the back-lit blue bricks on the overall structural stability of the ancient building bridge body, then locates the position of the damaged area of ​​the back-lit blue bricks of the ancient building bridge body, and obtains the hygroscopic expansion coefficient of the blue bricks according to the position of the damaged area of ​​the back-lit blue bricks of the ancient building bridge body and the volume of the blue bricks, calculates and analyzes the damage coefficient of the back-lit blue bricks and the hygroscopic expansion coefficient of the blue bricks, and calculates the influence coefficient of the back-lit blue bricks on the overall structural stability of the ancient building bridge body; The prediction replacement unit (3) combines the influence coefficient of the backlit blue bricks on the overall structural stability of the ancient building bridge body with the bearing capacity of the blue bricks in the intelligent database, calculates the predicted bearing capacity of the backlit blue bricks, compares the predicted bearing capacity of the backlit blue bricks with the bearing capacity required by the ancient building bridge body in the intelligent database, and determines whether to replace the blue bricks on the backlit surface.

2. The ancient building material intelligent database system according to claim 1 is characterized in that: The high-definition camera in the acquisition and processing unit (1) is installed at the vertex of the backlight surface of the ancient building bridge body, and the image smoothing process is to smooth the backlight surface blue brick image through Gaussian filtering.

3. The ancient building material intelligent database system according to claim 2 is characterized in that: The edge determination module (21) detects the edge of the damaged blue brick area in the damaged blue brick image through an algorithm, specifically comprising: By using the Sobel operator in the damaged blue brick image, the gradient values ​​in the horizontal and vertical directions are calculated. By combining the gradient values ​​in the horizontal and vertical directions, the gradient amplitude and direction of each pixel in the damaged blue brick image are calculated. Non-maximum suppression is performed in the gradient direction, and high and low thresholds are set. According to the high and low thresholds, the gradient amplitude is divided into strong edge and weak edge categories, and the strong edge pixels are tracked. The weak edge pixels adjacent to the strong edge pixels are divided into edge pixels, thereby forming a continuous edge line.

4. The ancient building material intelligent database system according to claim 3 is characterized by: The edge determination module (21) calculates the area of ​​the damaged brick region and the damaged brick depth according to the damaged brick edge, specifically comprising: Inside the edge line, a threshold is set according to the gray value of the pixel, and the damaged area of ​​the blue brick and the background are separated into two areas. For the segmented image, the number of pixels inside the damaged area is counted, and the actual area of ​​the damaged area is calculated according to the pixel size and the pixel size ratio of the image; Set the threshold to , for pixels whose pixel values ​​exceed the threshold, they are set as pixels inside the damaged area, otherwise they are background pixels. The number of pixels inside the damaged area is counted by the formula, namely: ,in, Expressed as Row, No. The value of the column pixel, Expressed as the number of pixels inside the damaged area, Represented as the internal pixel of the damaged area, the pixel size ratio of the image is , then the area of ​​the damaged area of ​​the blue brick is Calculated by the formula: ; A depth estimation model is established according to the grayscale value of the damaged area of ​​the blue bricks. The expression of the depth estimation model is: ,in, It is the estimated value of the damaged depth of the blue brick. Represented as grayscale value, are represented as model parameters.

5. The ancient building material intelligent database system according to claim 4 is characterized in that: The positioning analysis module (23) obtains the hygroscopic expansion coefficient of the green brick based on the height of the damaged area of ​​the green brick from the water surface and the volume of the green brick, which specifically includes: The position of the damaged area of ​​the blue brick is located by the position sensor, and the vertical height of the damaged area of ​​the blue brick from the horizontal plane is The damaged area of ​​the blue brick is The depth of the damaged part of the blue brick is , then the initial volume of the blue brick is: , the damaged volume of the blue brick is: , then the volume of the green brick after moisture absorption and expansion is: , then the hygroscopic expansion is The hygroscopic expansion coefficient is calculated by the formula: ,but: 。 6. The ancient building material intelligent database system according to claim 5 is characterized by: The calculation of the overall structural stability influence coefficient of the ancient building bridge body by the combined calculation module (24) specifically includes: Since the ancient bridge is built with blue bricks, the damage coefficient and morphological changes of blue bricks will affect the structural stability of the ancient bridge. The morphological changes are reflected in the increase of the hygroscopic expansion coefficient of blue bricks due to the dark and damp backlight surface of the ancient bridge. The damage coefficient and hygroscopic expansion coefficient of blue bricks on the backlight surface of the ancient bridge are calculated by formula, and the influence coefficient on the structural stability of the ancient bridge is obtained, namely: 。 7. The ancient building material intelligent database system according to claim 6 is characterized by: The prediction replacement unit (3) determines whether to replace the blue bricks on the backlight surface by calculating the predicted bearing capacity of the blue bricks on the backlight surface, and specifically includes: The ancient bridge body is made of blue bricks, so the bearing capacity of the ancient bridge body is the bearing capacity of the blue bricks. Now, by calculating the predicted bearing capacity of the blue bricks on the backlight side of the ancient bridge body, and comparing the predicted bearing capacity of the blue bricks on the backlight side with the bearing capacity required by the ancient bridge body in the intelligent database, it is determined whether the blue bricks on the backlight side should be replaced, and the initial bearing capacity of the blue bricks is extracted through the intelligent database. , the calculation formula of the predicted bearing capacity is: ； Extract the minimum bearing capacity of the blue bricks for normal use from the intelligent database , the predicted bearing capacity of the blue brick and minimum load capacity For comparison, if the predicted bearing capacity of the green brick Below minimum load capacity , indicating that the blue bricks cannot bear the force exerted on them by the ancient building bridge and need to be replaced immediately.

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