Detection method and device for preventing hollowing and falling of outer wall in full-digital life cycle

Abstract

The invention relates to the technical field of building outer wall hollowing monitoring, in particular to a detection method and device for preventing hollowing and falling of an outer wall in an all-digital life cycle. According to the detection method and device for preventing hollowing and falling of the outer wall in the full-digital life cycle, the technical problem that hollowing detection cannot be carried out on the outer wall of a building in the prior art is solved. Some embodiments adopted to solve the technical problem include: the detection method for preventing the hollowing and falling of the outer wall in the full-digital life cycle comprises the following steps: acquiring a picture after the construction of the outer wall is completed as a first reference picture; by obtaining the first reference picture after the construction of the outer wall is completed, continuously obtaining the outer wall pictures according to the timeline and comparing the outer wall pictures, the subtle changes of the outer wall at different time points can be accurately captured. When slight hollowing occurs on the outer wall, the coordinate data of the hollowing part can be changed, and the difference between the coordinate data of the hollowing part and the coordinate data of the reference picture can exceed a set value, so that the potential hollowing problem can be found in time.

Description

Technical Field

[0001] This invention relates to the field of building exterior wall hollowness monitoring technology, and in particular to a detection method and device for preventing exterior wall hollowness and detachment with a fully digital lifecycle. Background Technology

[0002] Currently, most building exterior walls are constructed using plastering and paint, insulation boards and paint, glass curtain walls, etc. In the past, exterior wall tiles and other exterior decorative surfaces were also used. Over time, these exterior walls are prone to hollowing and falling off, and glass curtain walls may also experience cracking and other problems.

[0003] However, current technology cannot monitor building exterior walls. When minor hollow areas appear, they go unnoticed until material falls off. For high-rise buildings, falling material from these hollow areas could injure people, posing a safety hazard.

[0004] Therefore, existing technologies have the technical problem of being unable to detect hollow areas in building exterior walls. Summary of the Invention

[0005] This invention provides a fully digital lifecycle detection method and device for preventing hollowing and detachment of exterior walls, which solves the technical problem that existing technologies cannot detect hollowing in building exterior walls.

[0006] Some implementation schemes for solving the above-mentioned technical problems include: Firstly, a fully digital lifecycle detection method for preventing external wall hollowing and detachment includes the following steps: Step 10: Obtain an image of the completed exterior wall construction as the first reference image; Step 20: Continuously acquire exterior wall images according to the timeline. The current image in two adjacent images is the comparison image, and the image preceding the current image in the timeline is the second reference image. Step 30: Compare the comparison image with the second reference image. When the difference between the coordinate data of the comparison image and the coordinate data of the second reference image exceeds the set value, proceed to the next step. When the difference between the coordinate data of the comparison image and the coordinate data of the second reference image does not exceed the set value, repeat steps 20 to 30 no more than 50 times and then proceed to the next step. Step 40: Compare the comparison image with the first reference image. When the difference between the coordinate data of the comparison image and the coordinate data of the first reference image exceeds the set value, proceed to the next step. When the difference between the coordinate data of the comparison image and the coordinate data of the first reference image does not exceed the set value, repeat steps 20 to 40. Step 50: Obtain sensor data embedded in the exterior wall. The sensors embedded in the exterior wall are used to detect whether the exterior wall is hollow. When the sensor detects a hollow area in the exterior wall, it issues a first alarm message. When the sensor does not detect a hollow area in the exterior wall, it issues a second alarm message.

[0007] Preferably, step 10: obtaining an image of the completed exterior wall construction as the first reference image includes the following steps: Take photos of the entire exterior wall within 24 hours of its completion. A first virtual coordinate system is generated on the obtained image to obtain the first reference image.

[0008] Preferably, step 20 involves continuously acquiring exterior wall images along a timeline, with the current image serving as a comparison image between two adjacent images and the image preceding the current image in the timeline serving as a second reference image. A second virtual coordinate system is generated on each acquired image, wherein the origins of the first and second virtual coordinate systems coincide.

[0009] Preferably, step 30: comparing the comparison image with the second reference image includes the following steps: The comparison image is divided into multiple comparison regions according to the second virtual coordinate system, and comparison coordinate values ​​are assigned to each comparison region. The second reference image is divided into multiple comparison regions according to the second virtual coordinate system, and each comparison region is assigned a second reference coordinate value; The difference between the coordinate data of the comparison image and the coordinate data of the second reference image is obtained by comparing the coordinate values ​​and the second reference coordinate values.

[0010] Preferably, step 40, comparing the comparison image with the first reference image, includes the following steps: The comparison image is divided into multiple comparison regions according to the second virtual coordinate system, and comparison coordinate values ​​are assigned to each comparison region. The first reference image is divided into multiple comparison regions according to the first virtual coordinate system, and each comparison region is assigned a first reference coordinate value; The difference between the coordinate data of the comparison image and the coordinate data of the first reference image is obtained by comparing the coordinate values ​​and the first reference coordinate values.

[0011] Secondly, a detection device for implementing the detection method for preventing hollowing and falling off of exterior walls with a full digital lifecycle as described in the first aspect includes a sensor, which is pre-embedded in the exterior wall of the building. An image sensor for acquiring images of the exterior walls of a building, wherein the image sensor acquires an image of the entire exterior wall; The central processing unit (CPU) is connected to both the image sensor and the sensor, and the CPU processes the image data acquired by the image sensor and the data acquired by the sensor. And an alarm, which is controlled by the central processing unit.

[0012] Preferably, the sensor is an optical fiber sensor.

[0013] Preferably, the sensors are evenly distributed on the exterior walls of the building.

[0014] Preferably, the image sensor includes a camera and a base for fixing the camera, the base being provided with a cleaning component for cleaning the camera.

[0015] Preferably, the cleaning assembly includes a cleaning cover rotatably connected to the base, and the base is provided with a driver to drive the cleaning cover to rotate relative to the camera, and a cleaning sponge is disposed between the cleaning cover and the camera.

[0016] Compared with the prior art, the present invention has the following advantages: By acquiring an initial reference image after the exterior wall construction is completed, and then continuously acquiring and comparing exterior wall images chronologically, subtle changes in the exterior wall at different points in time can be accurately captured. When slight hollow areas appear in the exterior wall, the coordinate data of the hollow area will change, and the difference between the coordinate data and the reference image will exceed a set value, thus allowing for the timely detection of potential hollow problems. Compared to traditional manual inspections, this precise detection method can identify abnormalities in the exterior wall much earlier, significantly improving detection sensitivity.

[0017] During the inspection, the comparison images are not only compared with the second reference image, but also with the first reference image. This multi-dimensional verification method effectively avoids image data errors caused by environmental factors, ensuring the accuracy of the inspection results. For example, comparing only with the second reference image might lead to misjudgment due to short-term environmental changes; however, comparing with the first reference image allows for a comprehensive understanding of the changes in the exterior wall, further confirming whether a hollowing problem truly exists.

[0018] When the difference between the coordinate data of the comparison image and the coordinate data of the reference image does not exceed a set value, steps 20 to 30 or 20 to 40 will be repeated a certain number of times before proceeding to the next step. This intelligent cyclic judgment mechanism can avoid misjudgments caused by accidental factors, while also avoiding excessive consumption of system resources, thus improving detection efficiency. For example, if a deviation occurs in a single image comparison due to shooting angle or lighting issues, cyclic judgment can eliminate the influence of such accidental factors, ensuring the reliability of the detection results. Alternatively, if there is only a slight hollow area without any safety hazard, no alarm signal will be issued, reducing the frequency of false alarms.

[0019] Sensors embedded in the exterior wall can detect hollow areas in the wall in real time and issue corresponding alarm messages. Sensor data is compared with image data for verification. When the sensor detects a hollow area, it issues a first alarm; when it does not detect a hollow area, it issues a second alarm. This further enhances the reliability of the detection results. For example, if image comparison suggests a possible hollow area in the exterior wall, but the sensor does not detect any abnormality, the comparison can be further investigated for potential errors. Conversely, if the sensor detects a hollow area, but the image comparison does not show a significant change, the sensor can be calibrated or inspected to ensure the accuracy of the detection system.

[0020] The image sensor can acquire images of the entire exterior wall, ensuring comprehensive monitoring of the building's exterior. Compared to traditional partial inspection methods, this comprehensive information acquisition approach avoids overlooking potential hollowing issues due to partial inspection, and can more accurately grasp the overall condition of the exterior wall. For example, for some large buildings, partial inspection may fail to detect potential hollowing issues in other areas, while the image sensor can acquire images of the entire exterior wall, providing comprehensive data support for subsequent analysis and judgment.

[0021] The central processing unit (CPU) is responsible for processing image data acquired by the camera and data acquired by the sensors, enabling it to analyze and process this data quickly and accurately. Through efficient algorithms and computing power, the CPU can determine whether there are hollow areas on the exterior wall in a short time and issue an alarm promptly. For example, when the camera acquires a large amount of exterior wall images and sensor data, the CPU can quickly process this data, avoiding the tediousness and errors of manual data processing and improving detection efficiency.

[0022] The alarm system is controlled by a central processing unit and can promptly issue an alarm when it detects hollow areas in the exterior wall. This timely alarm mechanism can remind relevant personnel to take appropriate measures, such as repairs or reinforcement, to prevent further detachment of the hollow parts, thereby ensuring the safety of people around the building. For example, in high-rise buildings, if hollow parts detach, they may injure pedestrians or cause other safety accidents; timely alarms can prevent such situations from occurring in advance.

[0023] The detection device integrates sensors, image capture devices, central processing units, and alarms into a complete detection system. This integrated design facilitates the management and maintenance of the detection device, while also improving the stability and reliability of the system. Attached Figure Description

[0024] For illustrative purposes, several embodiments of the invention are illustrated in the following figures. These figures are incorporated herein by reference and form part of the detailed description. In some instances, well-known structures and components are shown in block diagram form to avoid obscuring the concept of the subject matter of the invention.

[0025] Figure 1 A flowchart for a detection method to prevent hollowing and detachment of exterior walls throughout the entire digital lifecycle.

[0026] Figure 2 This is a schematic diagram showing the placement of the sensors and image capture devices on the building.

[0027] Figure 3 This is a structural block diagram of a detection device for preventing hollowing and detachment of exterior walls throughout the entire digital lifecycle.

[0028] Figure 4 This is a schematic diagram of the first angle of the image sensor.

[0029] Figure 5 This is a schematic diagram of the second angle of the image sensor.

[0030] Figure 6 This is a schematic diagram of a cleaning hood.

[0031] Figure 7 This is a schematic diagram showing the installation position of the image sensor on the base.

[0032] Explanation of reference numerals in the attached figures: 1. Sensors.

[0033] 2. Image sensor, 21. Base, 211. Mounting post, 22. Transparent cover.

[0034] 3. Central Processing Unit (CPU).

[0035] 4. Alarm device.

[0036] 5. Cleaning components, 51. Cleaning hood, 511. Ring body, 52. Driver, 53. Bracket, 54. Worm gear, 55. Worm wheel. Detailed Implementation

[0037] The specific embodiments shown below are intended to describe various configurations of the subject matter of the invention and are not intended to represent the only configuration in which the subject matter of the invention can be practiced. The specific embodiments include particular details intended to provide a thorough understanding of the subject matter of the invention. However, it will be clear and apparent to those skilled in the art that the subject matter of the invention is not limited to the specific details shown herein and can be practiced without these specific details.

[0038] Understandably, in this document, relational terms such as “first” and “second” are intended to distinguish one entity or operation from another, and are not intended to expressly or imply any actual relationship or order between these entities or operations.

[0039] The terms “comprising,” “including,” or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase “comprising one…” does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0040] Reference Figures 1 to 2 As shown, in the first aspect, a fully digital lifecycle detection method for preventing external wall hollowing and detachment includes the following steps: Step 10: Obtain an image of the completed exterior wall construction as the first reference image; Step 20: Continuously acquire exterior wall images according to the timeline. The current image in two adjacent images is the comparison image, and the image preceding the current image in the timeline is the second reference image. Step 30: Compare the comparison image with the second reference image. When the difference between the coordinate data of the comparison image and the coordinate data of the second reference image exceeds the set value, proceed to the next step. When the difference between the coordinate data of the comparison image and the coordinate data of the second reference image does not exceed the set value, repeat steps 20 to 30 no more than 50 times and then proceed to the next step. Step 40: Compare the comparison image with the first reference image. When the difference between the coordinate data of the comparison image and the coordinate data of the first reference image exceeds the set value, proceed to the next step. When the difference between the coordinate data of the comparison image and the coordinate data of the first reference image does not exceed the set value, repeat steps 20 to 40. Step 50: Obtain data from sensor 1 embedded in the exterior wall. Sensor 1 is used to detect whether the exterior wall is hollow. When sensor 1 detects a hollow area in the exterior wall, it issues a first alarm message. When sensor 1 does not detect a hollow area in the exterior wall, it issues a second alarm message.

[0041] Understandably, this solution integrates the data from Sensor 1 and the image comparison data. An alarm signal is only issued when both the Sensor 1 data and the image comparison data meet the alarm requirements. Specifically, the first alarm signal can indicate potential wall detachment, while the second alarm signal can indicate a system malfunction, such as a significant deviation in the image comparison data.

[0042] Specifically, image acquisition devices (such as high-definition cameras) are used to continuously acquire images of the exterior walls at set time intervals. The image acquisition device can be set to a resolution of 1920×1080 and a frame rate of one frame per minute. This ensures that the images have sufficient detail for subsequent analysis while avoiding excessive data volume.

[0043] The acquired images undergo preprocessing to improve the accuracy of subsequent analysis. Preprocessing steps include image denoising, contrast enhancement, and brightness adjustment. For example, Gaussian filtering can remove random noise from the image, making the outline and details of the exterior wall clearer; histogram equalization can adjust the brightness distribution of the image, improving the overall contrast and facilitating subsequent coordinate data extraction.

[0044] Extract coordinate data of key parts of the exterior wall from the image. Feature point detection algorithms, such as SIFT (Scale Invariant Feature Transform) or SURF (Accelerated Robust Feature Transform), can be used to identify feature points on the exterior wall and record their coordinates. For example, the SIFT algorithm can detect stable feature points at different scales and rotation angles. These feature points can serve as markers on the exterior wall for subsequent coordinate comparison.

[0045] The currently acquired comparison image is compared with the previous image (second reference image) in the timeline using coordinate data. The difference between the coordinates of feature points in the comparison image and the corresponding feature point coordinates in the second reference image is calculated. If the difference exceeds a set threshold, it is considered that the exterior wall may have changed, and the next step of judgment is performed; if the difference does not exceed the threshold, the image acquisition and comparison steps are repeated, but the number of iterations does not exceed 50. For example, if the threshold is set to 5 pixels, when the coordinate difference of a certain feature point exceeds 5 pixels, it indicates that the area may have experienced hollowing or other changes.

[0046] If no significant change is found when comparing with the second reference image, or if the maximum number of iterations is reached, the coordinate data of the comparison image is compared with the image after the exterior wall construction is completed (the first reference image). The coordinate difference is calculated again. If the difference exceeds the set threshold, the risk of hollowness in the exterior wall is further confirmed, and the sensor 1 data acquisition step is entered; if the difference does not exceed the threshold, the image acquisition and comparison steps are repeated.

[0047] Sensor 1, embedded in the exterior wall, collects relevant data about the exterior wall in real time. Sensor 1 converts the collected analog signals into digital signals and transmits the data to the central processing unit 3 via a communication interface.

[0048] After receiving data from sensor 1, the central processing unit 3 parses and processes it. Based on the type and data format of sensor 1, it extracts useful information. For example, for pressure sensor 1 data, it needs to be converted into actual pressure values ​​and compared with a preset normal pressure range.

[0049] Based on the analysis results of the data from sensor 1, it is determined whether the exterior wall is hollow. If the data detected by sensor 1 exceeds the normal range, it is considered that the exterior wall is hollow, and a first alarm message is issued; if the data is within the normal range, a second alarm message is issued. For example, the normal pressure range of pressure sensor 1 is set to 100N to 200N. When the detected pressure value is lower than 100N or higher than 200N, it is determined that the exterior wall may have hollowness.

[0050] When image comparison and sensor 1 detect potential hollow areas in the exterior wall, a corresponding alarm is generated. This alarm is then transmitted via a communication network (such as Wi-Fi or 4G) to the relevant management terminal or personnel's mobile phone. Transmission can be performed using message queues, email, or SMS. For example, the alarm can be sent to property management personnel via SMS so they can take timely action.

[0051] In some embodiments, step 10: obtaining an image of the completed exterior wall construction as the first reference image includes the following steps: Take photos of the entire exterior wall within 24 hours of its completion. A first virtual coordinate system is generated on the obtained image to obtain the first reference image.

[0052] Understandably, the shorter the time between acquiring the first reference image and the completion of the exterior wall construction, the better the accuracy of the first reference image. Specifically, after the exterior wall construction is completed, if there are no defects such as deformation or hollow areas, the data displayed in the image represents the exterior wall under normal conditions. Marking this image as the first reference image ensures higher accuracy of the data in the first reference image.

[0053] In some embodiments, step 20 involves continuously acquiring exterior wall images along a timeline, with the current image serving as a comparison image between two adjacent images and the previous image in the timeline serving as a second reference image. A second virtual coordinate system is generated on each acquired image, wherein the origins of the first and second virtual coordinate systems coincide.

[0054] In some embodiments, step 30: comparing the comparison image with the second reference image includes the following steps: The comparison image is divided into multiple comparison regions according to the second virtual coordinate system, and comparison coordinate values ​​are assigned to each comparison region. The second reference image is divided into multiple comparison regions according to the second virtual coordinate system, and each comparison region is assigned a second reference coordinate value; The difference between the coordinate data of the comparison image and the coordinate data of the second reference image is obtained by comparing the coordinate values ​​and the second reference coordinate values.

[0055] In some embodiments, step 40: comparing the comparison image with the first reference image includes the following steps: The comparison image is divided into multiple comparison regions according to the second virtual coordinate system, and comparison coordinate values ​​are assigned to each comparison region. The first reference image is divided into multiple comparison regions according to the first virtual coordinate system, and each comparison region is assigned a first reference coordinate value; The difference between the coordinate data of the comparison image and the coordinate data of the first reference image is obtained by comparing the coordinate values ​​and the first reference coordinate values.

[0056] Reference Figures 2 to 7 As shown, in the second aspect, a detection device for a detection method for preventing hollowing and falling off of exterior walls that implements the full digital lifecycle described in the first aspect includes a sensor 1, which is pre-embedded in the exterior wall of the building. Image sensor 2, which is used to acquire images of the exterior wall of a building, wherein the image sensor 2 acquires an image of the entire exterior wall; The central processing unit 3 is connected to both the image sensor 2 and the sensor 1, and the central processing unit 3 processes the image data acquired by the image sensor 2 and the data acquired by the sensor 1. And alarm 4, which is controlled by the central processing unit 3.

[0057] Understandably, the central processing unit 3 issues different alarm messages based on the data acquired by the image sensor 2 and the data acquired by the sensor 1. An alarm message for external wall hollowness is only issued when both the data acquired by the image sensor 2 and the data acquired by the sensor 1 indicate that the external wall is hollow.

[0058] In some embodiments, the sensor 1 is an optical fiber sensor 1.

[0059] In some embodiments, the sensors 1 are evenly distributed on the exterior walls of the building.

[0060] In some embodiments, the image sensor includes a camera and a base 21 for fixing the camera, the base 21 being provided with a cleaning assembly 5 for cleaning the camera.

[0061] In some embodiments, the cleaning assembly 5 includes a cleaning cover 51 rotatably connected to the base 21, and the base 21 is provided with a driver 52 for driving the cleaning cover 51 to rotate relative to the camera, and a cleaning sponge is disposed between the cleaning cover 51 and the camera.

[0062] In some embodiments, the camera includes a lens assembly and a transparent cover 22 disposed outside the lens assembly, with the lens assembly completely located within the transparent cover 22.

[0063] In some embodiments, the transparent cover 22 is spherical in shape, the cleaning cover 51 is hemispherical in shape, and the cleaning cover 51 is concentric with the transparent cover 22.

[0064] In some embodiments, the cleaning cover 51 is provided with a ring 511 rotatably connected to the base 21. The ring 511 and the cleaning cover 51 are integrally formed, and a rolling bearing is also provided between the ring 511 and the cleaning cover 51.

[0065] The outer ring of the rolling bearing is interference-fitted with the cleaning cover 51, and the inner ring of the rolling bearing is interference-fitted with the base 21.

[0066] In some embodiments, the base 21 is further provided with a mounting post 211 for mounting the transparent cover 22. The mounting post 211 and the base 21 are an integral structure, and the ring 511 is rotatably connected to the mounting post 211.

[0067] In some embodiments, the driver 52 includes a motor, and the drive actuator drives the cleaning cover 51 to rotate via a transmission mechanism. The transmission mechanism includes a bracket 53 mounted on the base 21, the bracket 53 being rotatably connected to a worm gear 54, and the ring body 511 being provided with a worm wheel 55 that cooperates with the worm gear 54. The worm wheel 55 and the ring body 511 are an integral structure, and the worm gear 54 is driven by a motor.

[0068] In some embodiments, the bracket 53 is fixed to the base 21 by screws. Alternatively, the bracket 53 may also be welded to the base 21.

[0069] In some embodiments, the number of image sensors 2 is not limited and can be determined based on the parameters of the image sensors 2 and the area of ​​the exterior wall. The image sensors 2 can be installed at the corners of the exterior wall. One or more image sensors 2 can also be installed on other buildings.

[0070] The technical solution of the present invention and its corresponding details have been described above. It is understood that the above description is only some implementation schemes of the technical solution of the present invention, and some details may be omitted in the specific implementation.

[0071] Furthermore, in some embodiments of the above invention, multiple embodiments may be combined; however, due to space limitations, all such combinations will not be listed here. Those skilled in the art can freely combine and implement the above embodiments according to their needs to obtain a better application experience.

[0072] When implementing the subject matter of this invention, those skilled in the art can obtain other detailed configurations or drawings based on the subject matter and drawings. Obviously, these details are still within the scope of the subject matter of this invention without departing from it.

Claims

1. A fully digital lifecycle detection method for preventing hollowing and detachment of exterior walls, characterized in that, The process includes the following steps: Step 10: Obtain an image of the completed exterior wall construction as the first reference image; Step 20: Continuously acquire exterior wall images according to the timeline, with the current image in two adjacent images serving as the comparison image, and the image preceding the current image in the timeline serving as the second reference image; Step 30: Compare the comparison image with the second reference image. When the difference between the coordinate data of the comparison image and the coordinate data of the second reference image exceeds a set value, proceed to the next step. When the difference between the coordinate data of the comparison image and the coordinate data of the second reference image does not exceed the set value, repeat steps 20 to 30 no more than 50 times before proceeding to the next step. Step 40: Compare the comparison image with the first reference image. When the difference between the coordinate data of the comparison image and the coordinate data of the first reference image exceeds the set value, proceed to the next step. When the difference between the coordinate data of the comparison image and the coordinate data of the first reference image does not exceed the set value, repeat steps 20 to 40. Step 50: Obtain the data of the sensor (1) embedded in the outer wall. The sensor (1) embedded in the outer wall is used to detect whether the outer wall is hollow. When the sensor (1) detects the outer wall is hollow, it issues the first alarm message. When the sensor (1) does not detect the outer wall is hollow, it issues the second alarm message.

2. The detection method for preventing hollowing and detachment of exterior walls based on the full digital lifecycle as described in claim 1, characterized in that: Step 10: Obtaining an image of the completed exterior wall construction as the first reference image includes the following steps: taking an image containing the entire exterior wall within 24 hours after the completion of the exterior wall construction; generating a first virtual coordinate system on the obtained image to obtain the first reference image.

3. The detection method for preventing hollowing and detachment of exterior walls based on a fully digital lifecycle as described in claim 2, characterized in that: Step 20: Continuously acquire exterior wall images according to the timeline. In two adjacent images, the current image is the comparison image, and the image preceding the current image in the timeline is the second reference image. Continuously acquire exterior wall images according to the timeline, and generate a second virtual coordinate system on each acquired image. The origins of the first virtual coordinate system and the second virtual coordinate system coincide.

4. The detection method for preventing hollowing and detachment of exterior walls based on a fully digital lifecycle as described in claim 3, characterized in that: Step 30: Comparing the comparison image with the second reference image includes the following steps: dividing the comparison image into multiple comparison regions according to the second virtual coordinate system, and assigning comparison coordinate values ​​to each comparison region; dividing the second reference image into multiple comparison regions according to the second virtual coordinate system, and assigning second reference coordinate values ​​to each comparison region; obtaining the difference between the coordinate data of the comparison image and the coordinate data of the second reference image based on the comparison coordinate values ​​and the second reference coordinate values.

5. The detection method for preventing hollowing and detachment of exterior walls based on a fully digital lifecycle as described in claim 4, characterized in that: Step 40: Comparing the comparison image with the first reference image includes the following steps: dividing the comparison image into multiple comparison regions according to the second virtual coordinate system, and assigning comparison coordinate values ​​to each comparison region; dividing the first reference image into multiple comparison regions according to the first virtual coordinate system, and assigning first reference coordinate values ​​to each comparison region; obtaining the difference between the coordinate data of the comparison image and the coordinate data of the first reference image based on the comparison coordinate values ​​and the first reference coordinate values.

6. A detection device for implementing the detection method for preventing hollowing and detachment of exterior walls according to claim 5, characterized in that: The system includes a sensor (1) embedded in the exterior wall of the building; an image sensor (2) for acquiring images of the exterior wall of the building, wherein the image sensor (2) acquires images of the entire exterior wall; a central processing unit (3) through which both the image sensor (2) and the sensor (1) communicate, and the central processing unit (3) processes the image data acquired by the image sensor (2) and the data acquired by the sensor (1); and an alarm (4) controlled by the central processing unit (3).

7. The detection device for preventing hollowing and detachment of exterior walls based on a fully digital lifecycle as described in claim 6, characterized in that: The sensor (1) is an optical fiber sensor (1).

8. The detection device for preventing hollowing and detachment of exterior walls based on a fully digital lifecycle as described in claim 7, characterized in that: The sensors (1) are evenly distributed on the exterior walls of the building.

9. The detection device for preventing hollowing and detachment of exterior walls based on a fully digital lifecycle as described in claim 6, characterized in that: The image sensor includes a camera and a base (21) for fixing the camera, the base (21) being provided with a cleaning component (5) for cleaning the camera.

10. The detection device for preventing hollowing and detachment of exterior walls based on a fully digital lifecycle as described in claim 9, characterized in that: The cleaning assembly (5) includes a cleaning cover (51) which is rotatably connected to the base (21). The base (21) is provided with a driver (52) for driving the cleaning cover (51) to rotate relative to the camera. A cleaning sponge is provided between the cleaning cover (51) and the camera.

Images