A method for identifying bulges of external wall bricks of a building facade

Abstract

The application discloses a building outer facade outer wall brick bulge identification method, belongs to the building outer facade inspection technical field, and the identification method depends on a unmanned aerial vehicle, a camera and a controller are installed on the unmanned aerial vehicle, and the controller is used for identifying images shot by the camera; the identification method comprises the following steps: controlling the unmanned aerial vehicle to fly according to a preset path, adjusting a horizontal shooting angle of the camera, making the camera shoot images of outer wall bricks of a building outer facade at a fixed angle of view at regular time intervals and sending the images to the controller; when the unmanned aerial vehicle is at a reference detection height, the controller constructs a theoretical two-dimensional grid template according to the identified vertical gaps and horizontal gaps; the problems that in the prior art, the visual angle deviation of manual inspection is large, the efficiency is low, the danger is high, and it is difficult to highlight three-dimensional features in the front view of the shot images, so that the bulge identification and severity evaluation are inaccurate are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of building facade inspection and repair, and in particular to a method for identifying bulges on exterior wall bricks of a building facade. Background Art

[0002] Among existing methods for detecting bulges on building exterior wall tiles, traditional manual inspection requires workers to climb up close or stand on the ground to observe upwards. This is not only inefficient and dangerous, but also limited by perspective deviation. When standing on the ground and observing upwards, the tilted line of sight causes visual perspective distortion of the exterior wall tiles, making it difficult to accurately identify the actual position of the brick joints and the three-dimensional raised features of the bulge area. This can easily cause visual confusion between the bulge edge and normal wall tiles, leading to missed detections, misjudgments, or miscalculation of the severity of the bulge. Although image recognition technology based on frontal photography has attempted to assist in detection through drones, the difference in wall flatness under the frontal perspective is difficult to effectively present in two-dimensional images, the shadow effect of the bulge area is insufficient, and there are still problems such as blurred edge features and difficulty in quantifying deviations. In addition, the establishment of theoretical grid templates in existing technologies lacks flexibility and is difficult to adapt to the arrangement patterns of exterior wall tiles of different buildings. In addition, the detection path planning does not fully take into account detection efficiency and image acquisition stability, resulting in a long detection process or large image deviations. Summary of the Invention

[0003] The purpose of the present invention is to solve the above-mentioned problem and provide a method for identifying bulges of exterior wall bricks on a building facade.

[0004] The technical solution of the present invention is achieved as follows:

[0005] The present invention provides a method for identifying bulges in exterior wall bricks of a building facade, the method relying on a drone equipped with a camera and a controller for identifying images captured by the camera;

[0006] The identification method comprises: controlling the drone to fly along a preset path, adjusting the lateral shooting angle of the camera so that it faces the exterior wall bricks of the building facade at an acute angle, and regularly capturing images of the exterior wall bricks at a fixed viewing angle and sending the images to a controller;

[0007] When the drone is at the reference detection height, the controller constructs a theoretical two-dimensional grid template for the identified vertical and horizontal gaps. The theoretical two-dimensional grid template is generated based on the arrangement pattern of standard exterior wall tiles.

[0008] During subsequent flights, the controller will identify the actual gap grid in the image and compare it with the theoretical grid template. If the deviation exceeds the threshold, the severity of the bulge will be assessed based on the degree of gap deviation.

[0009] The reference detection height corresponds to the height of the first floor or the second floor of the building.

[0010] The advantages or beneficial effects of the above technical solution include at least:

[0011] 1. By controlling the drone to shoot exterior wall tile images at an oblique angle, the shadow effect of the bulge area is enhanced, the three-dimensional characteristics of the surface are highlighted, and the confusion between the bulge edge and normal wall tiles when shooting from the front is avoided, significantly improving the accuracy of bulge identification.

[0012] 2. The theoretical two-dimensional grid template supports both automatic generation and manual selection modes. It can be automatically constructed based on standard arrangement rules through image processing algorithms, or manually drawn by staff in designated normal areas, improving the template's adaptability to the arrangement characteristics of different building exterior wall tiles.

[0013] 3. The preset path adopts a design that combines a vertical main section with a horizontal turning section, mainly covering the facade in the vertical direction. Combined with steering speed optimization, it shortens the turning time while ensuring comprehensive detection, thereby improving overall detection efficiency.

[0014] 4. By comprehensively considering multiple factors such as the gap deviation value, area size, and deviation change gradient of the bulge area, the bulge type and severity are graded and assessed to form a more comprehensive and scientific basis for risk assessment.

[0015] 5. During flight, the system monitors the overlap between the theoretical grid and the actual gap in real time, automatically adjusting the template horizontally to match the actual gap, reducing detection errors caused by position offset or image distortion, and ensuring the stability of detection results.

[0016] 6. After a bulge is detected, the position and height are automatically recorded and the image is uploaded to the terminal for manual review, realizing an organic combination of automated detection and manual intervention, and improving the convenience and reliability of the detection process. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings illustrate exemplary embodiments of the invention and together with the description serve to explain the principles of the invention. These drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification.

[0018] Figure 1 A schematic diagram showing the rotation angle of a drone camera according to an embodiment of the present invention;

[0019] Figure 2 A schematic diagram showing an image captured by a camera when a drone according to an embodiment of the present invention flies to a reference detection altitude;

[0020] Figure 3A schematic diagram showing a controller according to an embodiment of the present invention generating a theoretical two-dimensional grid template from an image;

[0021] Figure 4 A schematic diagram showing an image captured by a camera when a drone according to an embodiment of the present invention flies to a detection area, wherein the camera captures a bulge;

[0022] Figure 5 A schematic diagram showing a controller according to an embodiment of the present invention generating an actual gap grid from an image;

[0023] Figure 6 A schematic diagram showing the overlap and comparison of an actual gap grid and a theoretical two-dimensional grid template according to an embodiment of the present invention is shown;

[0024] Figure 7 shows a schematic diagram after overlapping and comparing the embodiments of the present invention;

[0025] Figure 8 A schematic diagram showing a preset flight path according to an embodiment of the present invention is shown;

[0026] Figure 9 A schematic diagram of front view shooting according to an embodiment of the present invention is shown; DETAILED DESCRIPTION

[0027] Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments described herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0028] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0029] It should be understood that the term "including" and its variations used in this document are open inclusions, that is, "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one other embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description. It should be noted that the concepts of "first", "second", etc. mentioned in the present invention are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0030] It should be noted that the modifications of "one" and "multiple" mentioned in the present invention are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0031] The names of the messages or information exchanged between multiple devices in the embodiments of the present invention are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0032] A method for identifying bulges in exterior wall bricks on a building facade, the method relying on a drone equipped with a camera and a controller configured to identify images captured by the camera;

[0033] The identification method includes: controlling the drone to fly along a preset path, adjusting the horizontal shooting angle of the camera, and regularly capturing images of exterior wall tiles at a fixed viewing angle and sending the images to a controller so that the drone faces the exterior wall tiles on the building's facade at an acute angle; when the drone is at a reference detection height, the controller constructs a theoretical two-dimensional grid template for the identified vertical and horizontal gaps, wherein the theoretical two-dimensional grid template is generated based on the arrangement pattern of standard exterior wall tiles; during subsequent flight, the controller identifies the actual gap grid in the image, compares the actual gap grid with the theoretical grid template, and if the deviation exceeds a threshold, evaluates the severity of the bulge based on the degree of gap deviation; wherein the reference detection height corresponds to the height of the first or second floor of the building.

[0034] Specifically, such as Figure 1 As shown, the acute angle is 30° to 60°, and the preferred acute angle is 45°. Figure 2 The enlarged part is the image captured by the drone, including Figure 4 This is also an image captured by a drone. If the image is taken from the front, the edges of the bulging bricks in the image will easily be confused with the edges of the surrounding non-bulging bricks, making it difficult to judge the bulge and the severity of the bulge. Therefore, it is necessary to shoot at an oblique angle, such as Figure 9 As shown, it can better highlight the three-dimensional characteristics of the exterior wall brick surface and enhance the shadow effect of the bulging area.

[0035] Furthermore, the preset path includes a vertical main segment and a horizontal turning segment, such as Figure 8 As shown; the vertical main segment extends in the vertical direction of the building facade, and the extension directions of adjacent vertical main segments are opposite; the horizontal turning segment connects the same-side endpoints of adjacent vertical main segments; the preset path can be used to inspect the wall bricks of the building facade mainly in the vertical direction, and there is a fixed interval between the preset path and the building facade, and the preferred fixed interval is 1.5~2m.

[0036] Among them, the flight speed of the vertical main segment is v1, the flight speed of the horizontal turning segment is v2, 2*v2≥v1, so as to shorten the time of turning from the vertical main segment to the adjacent vertical main segment.

[0037] In the control method, the exterior wall brick part based on the theoretical two-dimensional grid template in the image can also be selected manually. The staff can control the drone to fly to the specified location outside the building. The controller sends the image taken by the camera to the manual control terminal. The staff can use the control terminal to first control the drone to establish the theoretical two-dimensional grid template on the part of the normal exterior wall brick without bulges. The control terminal can even hand-draw the theoretical two-dimensional template based on the arrangement of the exterior wall bricks at the benchmark detection height, such as Figure 3 As shown, the red line grid in the figure is the theoretical two-dimensional grid template.

[0038] Under the automatically generated theoretical two-dimensional network template, the controller identifies vertical and horizontal gaps in the following ways: pre-processing the captured image, including grayscale conversion, filtering and denoising, and edge enhancement; applying the Canny edge detection algorithm to extract edge information in the image, and setting a double threshold (low threshold 30, high threshold 90) for Canny edge detection to extract edges, retaining continuous and clear brick joint contours; identifying straight edges through Hough transform, and screening out vertical and horizontal gaps based on the arrangement characteristics of the exterior wall bricks; after identifying all vertical and horizontal gaps, calculating the spacing between each gap to obtain the size of the wall bricks in the image; constructing a probability distribution model of the gap spacing through statistical analysis methods, and screening the spacing value with the highest frequency as the preliminary standard brick joint size; the controller identifies the complete cross brick joint intersection in the pre-processed image as a candidate origin; using the selected origin as the reference point, generating equidistant grid lines in the horizontal and vertical directions according to the standard brick joint size; Figure 3 As shown, Figure 3 The red line grid in the figure is the theoretical two-dimensional grid template.

[0039] The controller generates the actual gap mesh in the following ways:

[0040] Probabilistic Hough transform is applied to extract edge information of straight line segments in the image, and the slope, starting point coordinates and end point coordinates of each straight line segment are recorded; Figures 4 to 5 The method for generating the actual gap grid includes: extracting vertical gap edge lines and horizontal gap edge lines actually existing in the image to construct the actual gap grid.

[0041] The controller compares the actual identified gap grid with the theoretical grid template in a method including: aligning the horizontal lines in the theoretical two-dimensional grid template with the horizontal lines and vertical lines of the actual gap grid, and comparing whether there are gaps between the vertical lines in the actual gap grid and the vertical lines in the theoretical two-dimensional template, such as Figures 6 and 7 As shown in the figure, by comparing the same position points in adjacent image frames, the origin positioning error is ensured to be less than 0.5 times the standard brick joint size. If the gap exceeds the threshold, it is judged that a bulge occurs. The intersection point in the center of the image is preferentially selected as the grid origin to reduce the impact of edge distortion on grid generation.

[0042] After detecting a bulge, the controller will evaluate the type and severity of the bulge. The severity is evaluated based on the following factors:

[0043] The maximum gap deviation value of the bulging area is quantitatively evaluated by comparing the maximum offset between the actual detected gap position and the corresponding position in the theoretical grid template. The maximum gap deviation value is calculated based on the side length of a standard exterior wall tile. The maximum gap deviation value is divided into three levels: when the deviation value is less than 0.1 times the side length of the standard tile, it is mild bulging; when it is between 0.1 and 0.3 times, it is moderate bulging; and when it is greater than 0.3 times, it is severe bulging;

[0044] The size of the bulge area is assessed by calculating the number of intact wall tiles contained within the closed area enclosed by continuous excessive gaps. The area is measured in units of standard exterior wall tiles. Based on the exterior wall tile fall risk assessment standard, the bulge area is categorized into three levels: less than three bricks is considered mild bulging, 3-10 bricks is considered moderate bulging, and more than 10 bricks is considered severe bulging.

[0045] The gradient of the gap deviation value within the bulge area is evaluated by calculating the rate of change of the gap deviation value between adjacent grid nodes. The gradient is calculated based on the side length of a standard exterior wall tile. Based on the analysis of the bulge morphological characteristics, the gradient is divided into three levels: a gentle bulge when the gradient value is less than 0.05 times the brick side length, a transitional bulge when the gradient value is between 0.05 and 0.1 times the brick side length, and a sharp bulge when the gradient value is greater than 0.1 times the brick side length.

[0046] When the theoretical two-dimensional grid template is established, the standard brick side length unit of a single standard exterior wall brick has been obtained. By using the side length of a single standard brick as the unit of measurement, the error between the picture ratio and the actual size can be reduced.

[0047] It should be noted that when the drone flies along the preset flight path, it needs to adjust its position so that the vertical lines of the theoretical two-dimensional grid template in the image coincide with the vertical lines of the actual gap grid, and then fly up or down along the vertical main segment. Of course, during the flight, the vertical lines also need to be guaranteed to coincide. If a deviation occurs, the controller will make a horizontal adaptive adjustment to the theoretical two-dimensional grid template in the picture based on the actual gap grid until the two coincide.

[0048] When bulges appear, the vertical lines of the actual gap grid can obviously deviate from the vertical lines of the theoretical two-dimensional grid template, such as Figure 6 As shown, after the controller detects the deviation, it stabilizes the altitude and attitude of the UAV, stabilizes the image, performs recognition, records the altitude and position, and takes a photo and uploads it to the terminal for manual inspection, and then continues cruise recognition.

[0049] In the description of the present invention, it should be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, they cannot be understood as limiting the present invention.

[0050] It should be understood by those skilled in the art that the above embodiments are merely for the purpose of illustrating the present invention clearly, and are not intended to limit the scope of the present invention. For those skilled in the art, other changes or modifications may be made based on the above disclosure, and these changes or modifications are still within the scope of the present invention.

Claims

1. A method for identifying bulges on exterior wall bricks of a building facade, characterized by: The recognition method relies on a drone equipped with a camera and a controller for identifying images captured by the camera; The identification method comprises: controlling the drone to fly along a preset path, adjusting the lateral shooting angle of the camera so that it faces the exterior wall bricks of the building facade at an acute angle, and regularly capturing images of the exterior wall bricks at a fixed viewing angle and sending the images to a controller; When the drone is at the reference detection height, the controller constructs a theoretical two-dimensional grid template for the identified vertical and horizontal gaps. The theoretical two-dimensional grid template is generated based on the arrangement pattern of standard exterior wall tiles. During subsequent flights, the controller will identify the actual gap grid in the image and compare it with the theoretical grid template. If the deviation exceeds the threshold, the severity of the bulge will be assessed based on the degree of gap deviation. Wherein, the reference detection height corresponds to the height of the first floor or the second floor of the building; The controller identifies vertical gaps and horizontal gaps in the following manner: Preprocess the captured images, including grayscale conversion, filtering, denoising, and edge enhancement; Apply the Canny edge detection algorithm to extract edge information in the image; Hough transform is used to identify straight edges, and vertical and horizontal gaps are screened out based on the arrangement characteristics of the exterior wall tiles. The generation method of the theoretical two-dimensional grid template includes: After identifying all vertical and horizontal gaps, calculate the spacing between each gap; construct a probability distribution model of gap spacing through statistical analysis methods, and select the spacing value with the highest frequency as the preliminary standard brick joint size; The controller identifies a complete cross-shaped brick joint intersection in the pre-processed image as a candidate origin; using the selected origin as a reference point, generates equidistant grid lines in the horizontal and vertical directions according to the standard brick joint size; The controller generates the actual gap grid in the following manner: Probabilistic Hough transform is applied to extract edge information of straight line segments in the image, and the slope, starting point coordinates and end point coordinates of each straight line segment are recorded; The method for generating the actual gap grid includes: Extract the vertical and horizontal gap edge lines that actually exist in the image and construct the actual gap grid; The method in which the controller compares the actually identified gap grid with the theoretical grid template includes: The horizontal lines in the theoretical two-dimensional grid template are aligned with the horizontal and vertical lines of the actual gap grid. The controller compares whether there is a gap between the vertical lines in the actual gap grid and the vertical lines in the theoretical two-dimensional template. If the gap exceeds the threshold, it is determined that a bulge has occurred.

2. The method for identifying bulges on exterior wall bricks of a building facade according to claim 1, characterized in that: The severity level is assessed based on a combination of the following factors: The maximum gap deviation value of the bulging area is quantitatively evaluated by comparing the maximum offset between the actual detected gap position and the corresponding position in the theoretical grid template. The maximum gap deviation value is calculated based on the side length of a standard exterior wall tile. The maximum gap deviation value is divided into three levels: when the deviation value is less than 0.1 times the side length of the standard tile, it is mild bulging; when it is between 0.1 and 0.3 times, it is moderate bulging; and when it is greater than 0.3 times, it is severe bulging; The size of the bulge area is assessed by calculating the number of intact wall tiles contained within the closed area enclosed by continuous excessive gaps. The area is measured in units of standard exterior wall tiles. Based on the exterior wall tile fall risk assessment standard, the bulge area is categorized into three levels: less than three bricks is considered mild bulging, 3-10 bricks is considered moderate bulging, and more than 10 bricks is considered severe bulging. The gradient of the gap deviation value within the bulge area is calculated by calculating the rate of change of the gap deviation value between adjacent grid nodes to evaluate the bulge development trend. The gradient is calculated based on the side length of a standard exterior wall tile. According to the analysis of the morphological characteristics of the bulge, the change gradient is divided into three level intervals: when the gradient value is less than 0.05 times the length of the brick side, it is a gentle bulge; when it is 0.05-0.1 times the length of the brick side, it is a transitional bulge; when it is greater than 0.1 times the length of the brick side, it is a sharp bulge.

3. The method for identifying bulges on exterior wall bricks of a building facade according to claim 1, characterized in that: The preset path includes: A vertical main flight section extends in the vertical direction of the building facade, with adjacent vertical main flight sections extending in opposite directions; A horizontal turning segment connects the same-side endpoints of adjacent vertical main segments; Among them, the flight speed of the vertical main segment is v1, the flight speed of the horizontal turning segment is v2, 2*v2≥v1; Moreover, the detection ranges of the UAVs in adjacent vertical main flight segments have overlapping parts; Furthermore, there is a fixed interval between the preset path and the building facade.

4. The method for identifying bulges on exterior wall bricks of a building facade according to claim 1, wherein: The acute angle is 30°~60°.

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