A housing deformation monitoring method and system

Abstract

The present invention relates to the field of housing monitoring technology, and discloses a housing deformation monitoring method, the method comprising: S1, collecting real-life images of each wall of a house, and importing the real-life images into a trained image recognition model, outputting a result indicating whether the wall has cracks; S2, marking the wall with cracks as a target wall, and recording the original characteristic parameters of the corresponding cracks; S3, installing a crack detector at the crack of the target wall, and collecting real-time change data of the crack width; S4, presetting a plurality of first monitoring points on the target wall, and presetting a plurality of second monitoring points on the floor slab connected to the target wall; S5, obtaining position information data of the first monitoring point and the second monitoring point through monitoring, and performing a comprehensive analysis on the position information data of the first monitoring point and the second monitoring point. The present invention not only improves the timeliness of capturing housing monitoring information, but also reduces the safety hazards generated by the housing deformation monitoring process.

Description

Technical Field

[0001] The present invention relates to the technical field of house monitoring, and in particular to a house deformation monitoring method and system. Background Art

[0002] With the aging of my country's large urban infrastructure, such as buildings and bridges, structural health monitoring is becoming increasingly important. There is an urgent need to develop automated structural health monitoring systems based on new technologies. The existing process for building deformation monitoring typically involves regular visits to the building to be monitored, conducting on-site surveys using various measuring instruments, and then analyzing the survey data to determine the building's deformation status.

[0003] Due to the emergence of various advanced measuring instruments and the continuous improvement of the professionalism of relevant personnel, the accuracy of house deformation monitoring has been significantly improved. However, the problems with existing house deformation monitoring methods are that regular measurement and analysis of houses still cannot achieve the effect of real-time monitoring. In addition, in special cases such as deformation monitoring of dangerous buildings, regular manual field surveys still have certain safety risks. Summary of the Invention

[0004] The purpose of the present invention is to provide a building deformation monitoring method and system to solve the above technical problems:

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A method for monitoring house deformation, comprising:

[0007] S1. Collect real-life images of each wall of a house, import the real-life images into a trained image recognition model, and output results indicating whether there are cracks on the wall;

[0008] S2. Mark the wall with cracks as the target wall and record the original characteristic parameters of the corresponding cracks;

[0009] S3. Install a crack detector at the crack of the target wall to collect real-time crack width change data;

[0010] S4. Preset a number of first monitoring points on the target wall and a number of second monitoring points on the floor slab connected to the target wall;

[0011] S5. Acquire location information data of the first monitoring point and the second monitoring point through monitoring, and perform comprehensive analysis on the location information data of the first monitoring point and the second monitoring point;

[0012] S6. Establish a housing deformation early warning strategy based on the results of the comprehensive analysis.

[0013] Through the above technical solution, a house deformation monitoring method is provided. When performing deformation monitoring on a house, the target wall with cracks is first located through image acquisition and recognition, and then monitoring points are set on the target wall and the floor slab connected to the target wall. Combined with the monitoring of changes in crack width and the monitoring of displacement changes at each monitoring point, the monitoring result data is comprehensively analyzed to determine the deformation of the house. The monitoring process provided above only requires manual intervention when arranging measuring equipment (such as a crack meter). After that, the house can be automatically monitored and analyzed in real time. Therefore, the above monitoring method not only improves the timeliness of capturing monitoring information data, but also reduces the safety hazards caused by the house deformation monitoring process.

[0014] As a further technical solution, before step S3, the following is further included:

[0015] S21. Preliminary analysis of original characteristic parameters of cracks on the target wall;

[0016] S22. Perform a safety evaluation on the tested house based on the results of the pre-analysis, where the result of the safety evaluation indicates whether the house meets the safety monitoring standards;

[0017] S23. If the tested house does not meet the safety monitoring standards, steps S3 to S6 are not executed, and a danger warning signal for the corresponding house is generated. Otherwise, steps S3 to S6 are continued to be executed.

[0018] As a further technical solution, the original characteristic parameters of the cracks include: initial length and initial width of the cracks and the total number of cracks on the same target wall.

[0019] As a further technical solution, the process of pre-analyzing the original characteristic parameters of the cracks on the target wall includes:

[0020] By formula Calculate the risk assessment coefficient R of the house;

[0021] Among them, k i is the preset correlation coefficient, and k i >0; N is the number of cracks on the target wall; l i and are the length and average width of the i-th crack on the target wall respectively; S is the total area of ​​the target wall;

[0022] The risk assessment coefficient R is compared with the preset safety standard value R st To compare:

[0023] If R>R st , then it is judged that the house does not meet the safety monitoring standards;

[0024] If R≤R st, then it is judged that the house meets the safety monitoring standards.

[0025] As a further technical solution, the process of presetting the first monitoring point and the second monitoring point includes:

[0026] A number of first monitoring points are evenly distributed in rows and columns around the cracks of the target wall;

[0027] Install a laser rangefinder at a preset position on the floor slab connected to the target wall;

[0028] Taking the position of the laser rangefinder as the reference point, several measuring points are selected at the intersection of the floor slab and the target wall, and a static level is installed. The measuring points and the reference points are marked as the second monitoring points.

[0029] The distance from each monitoring point on the target wall to the reference point is obtained by a laser rangefinder, and the vertical displacement data of each measuring point is obtained by a static level.

[0030] As a further technical solution, the process of comprehensively analyzing the location information data of the first monitoring point and the second monitoring point includes:

[0031] By formula Calculate and obtain the settlement variation coefficient D1 of the corresponding floor;

[0032] Among them, ε1 and ε2 are the preset first weight coefficients; ω i is the preset second weight coefficient, Δh i is the height difference between each measuring point and the reference point; is the average height difference; n is the number of measuring points;

[0033] The settlement variation coefficient D1 of the corresponding floor is compared with the first preset threshold D θ，1 Conduct comparative analysis:

[0034] If D1>D θ，1 , then a corresponding warning signal about excessive deformation of the building floor is generated;

[0035] If D1≤D θ，1 , no danger warning signal for floor deformation is generated.

[0036] As a further technical solution, the process of comprehensively analyzing the location information data of the first monitoring point and the second monitoring point further includes:

[0037]

[0038] The wall deformation coefficient D2 of the target wall is calculated by formula (3) to (4);

[0039] Where dj is the measured distance between the jth first monitoring point and the reference point; h j is the initial height from the jth first monitoring point to the intersection of the target wall and the floor; αj is the laser elevation angle when the laser measures the position of the jth monitoring point; Δw is the maximum change in the crack width on the target wall; w0 is the preset standard proportional coefficient; m is the number of first monitoring points; μj is the preset third weight coefficient;

[0040] The wall deformation coefficient D2 is compared with the second preset threshold D θ，2 Conduct comparative analysis:

[0041] If D2>D θ，2 , then a corresponding warning signal about excessive deformation of the house wall is generated;

[0042] If D2≤D θ，2 , no danger warning signal for wall deformation is generated.

[0043] A method and system for monitoring housing deformation, the system comprising:

[0044] Image acquisition module, used to collect image information of the house wall;

[0045] Image recognition module, which identifies cracks in wall images based on convolutional neural networks and records the original characteristic parameters of the cracks;

[0046] The pre-analysis module is used to pre-analyze the original characteristic parameters and conduct a safety evaluation of the tested house based on the results of the pre-analysis;

[0047] A data acquisition module is used to collect position information data of a first monitoring point and a second monitoring point on the wall and the floor;

[0048] A data processing module is used to comprehensively analyze the location information data of the first monitoring point and the second monitoring point, and establish a house deformation early warning strategy based on the comprehensive analysis;

[0049] Human-computer interaction module, used to implement house deformation early warning strategy.

[0050] Beneficial effects of the present invention:

[0051] When monitoring deformation of a house, the present invention first locates the target wall with cracks through image acquisition and recognition, then sets monitoring points on the target wall and the floor slab connected to the target wall, combines the monitoring of crack width changes and the monitoring of displacement changes of each monitoring point, and comprehensively analyzes the monitoring result data to judge the deformation of the house. The above monitoring process only requires manual intervention when arranging the measuring equipment, after which the house can be automatically monitored and analyzed in real time, thereby improving the timeliness of capturing house monitoring information and reducing the safety hazards caused by the house deformation monitoring process. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The present invention will be further described below with reference to the accompanying drawings.

[0053] Figure 1 This is a flow chart of the housing deformation monitoring method of the present invention;

[0054] Figure 2 This is a block diagram of the contents of the house deformation monitoring system in the present invention. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making any creative efforts shall fall within the scope of protection of the present invention.

[0056] See also Figure 1 As shown, a housing deformation monitoring method includes:

[0057] S1. Collect real-world images of each wall surface of the house. This can be captured by a staff member at the house to be tested, or other methods can be used depending on the specific environment of the house. For example, for a dangerous building that has been uninhabited for a long time, drones can be used to capture images of the interior and exterior of the house. These real-world images are then fed into a trained image recognition model, and the output indicates whether cracks exist in the wall surface. For example, a convolutional neural network recognition model is used to identify wall cracks in the image.

[0058] S2. Mark the wall with cracks as a target wall, and record the original characteristic parameters of the corresponding cracks. The original characteristic parameters are specifically the initial length and initial width of the cracks and the total number of cracks on the same target wall.

[0059] S3. Install a crack detector at the crack of the target wall to collect real-time data on crack width changes. This data indicates the development trend of the wall crack and is also a factor that drives wall deformation. The trend of crack width changes can reflect whether the stability and safety of the wall structure are gradually deteriorating. If the crack continues to expand, it may mean that structural problems are worsening.

[0060] S4. Preset a number of first monitoring points on the target wall and a number of second monitoring points on the floor slab connected to the target wall;

[0061] S5. Acquire position information data of the first monitoring point and the second monitoring point through monitoring. Specifically, during the monitoring process, obtain distance change data from the first monitoring point to a specific reference point using a laser rangefinder, obtain settlement change data of the second monitoring point using a static level, and perform a comprehensive analysis on the position information data of the first monitoring point and the second monitoring point;

[0062] S6. Establish a housing deformation early warning strategy based on the results of the comprehensive analysis.

[0063] Through the above technical solution, this embodiment provides a house deformation monitoring method. When performing deformation monitoring on a house, the target wall with cracks is first located through image acquisition and recognition, and then monitoring points are set on the target wall and the floor slab connected to the target wall. Combined with the monitoring of the crack width change and the monitoring of the displacement change of each monitoring point, the monitoring result data is comprehensively analyzed to judge the deformation of the house. The above monitoring process only requires manual intervention when arranging the measuring equipment. After that, the house can be automatically monitored and analyzed in real time. Therefore, it not only improves the timeliness of capturing monitoring information, but also reduces the safety hazards caused by the house deformation monitoring process.

[0064] Before step S3, the method further includes:

[0065] S21. Preliminary analysis of original characteristic parameters of cracks on the target wall;

[0066] S22. Perform a safety evaluation on the tested house based on the results of the pre-analysis, where the result of the safety evaluation indicates whether the house meets the safety monitoring standards;

[0067] S23. If the tested house does not meet the safety monitoring standards, steps S3 to S6 are not executed, and a danger warning signal for the corresponding house is generated. Otherwise, steps S3 to S6 are continued to be executed.

[0068] Through the above technical solution, this embodiment provides the preparatory work content before step S3. Specifically, the original characteristic parameters of the cracks on the target wall are first pre-analyzed. The purpose of the pre-analysis is to determine whether there are major safety hazards in the house to be tested. If so, step S3 and other subsequent steps cannot be executed. At the same time, a corresponding danger warning signal needs to be generated, which can be sent to people near the house.

[0069] The original characteristic parameters of the cracks include: initial length and initial width of the cracks and the total number of cracks on the same target wall.

[0070] Through the above technical solution, this embodiment provides the specific content of the original characteristic parameters of the crack. The above-mentioned parameters can reflect the danger of the house, especially for the deformation monitoring of dangerous buildings.

[0071] The process of pre-analyzing the original characteristic parameters of cracks on the target wall includes:

[0072] By formula Calculate the risk assessment coefficient R of the house;

[0073] Among them, k i is the preset correlation coefficient, which is related to the shape and direction of the crack, and k i >0; N is the number of cracks on the target wall; l i and are the length and average width of the i-th crack on the target wall respectively; S is the total area of ​​the target wall;

[0074] The risk assessment coefficient R is compared with the preset safety standard value R st To compare:

[0075] If R>R st , then it is judged that the house does not meet the safety monitoring standards;

[0076] If R≤R st , then it is judged that the house meets the safety monitoring standards.

[0077] Through the above technical solution, this embodiment provides a process for pre-analyzing the original characteristic parameters of the cracks on the target wall. Specifically, first, the formula Calculate the risk assessment coefficient R of the house. The larger the risk assessment coefficient, the more dangerous the house is, and the less suitable it is for the layout of monitoring equipment.

[0078] The process of presetting the first monitoring point and the second monitoring point includes:

[0079] Several first monitoring points are evenly distributed in rows and columns around the cracks of the target wall, and a laser rangefinder is installed at a preset position on the floor connected to the target wall. The first monitoring points are marked with highly reflective materials to improve the measurement accuracy of the laser rangefinder. The laser rangefinder is installed on the floor through an automatically adjustable multi-axis bracket (such as a robotic arm), which facilitates the collection of position information of multiple first monitoring points.

[0080] Taking the position of the laser rangefinder as the reference point, several measuring points are selected at the intersection of the floor slab and the target wall, and a static level is installed. The measuring points and the reference points are marked as the second monitoring points.

[0081] The distance from each monitoring point on the target wall to the reference point is obtained by a laser rangefinder, and the vertical displacement data of each measuring point is obtained by a static level.

[0082] Through the above technical solution, this embodiment provides a process for presetting the first monitoring point and the second monitoring point. When presetting the first monitoring point, since the wall surface around the crack is prone to more obvious deformation, a number of first monitoring points are set around the crack of the target wall in rows and columns. When presetting the second monitoring point, the position of the laser rangefinder is used as the reference point, and a number of measuring points are selected at the intersection of the floor slab and the target wall, and a static level is installed. The measuring points and the reference points are both marked as second monitoring points.

[0083] The process of comprehensively analyzing the location information data of the first monitoring point and the second monitoring point includes:

[0084] By formula Calculate and obtain the settlement variation coefficient D1 of the corresponding floor;

[0085] Among them, ε1 and ε2 are the preset first weight coefficients; ω i is the preset second weight coefficient, Δh i is the height difference between each measuring point and the reference point; is the average height difference; n is the number of measuring points;

[0086] The settlement variation coefficient D1 of the corresponding floor is compared with the first preset threshold D θ，1 Conduct comparative analysis:

[0087] If D1>D θ，1 , then a corresponding warning signal about excessive deformation of the building floor is generated;

[0088] If D1≤D θ，1 , no danger warning signal for floor deformation is generated.

[0089] Through the above technical solution, this embodiment provides a process for comprehensively analyzing the location information data of the first monitoring point and the second monitoring point. Specifically, first, the formula Calculate and obtain the settlement variation coefficient D1 of the corresponding floor, and then compare the settlement variation coefficient D1 of the corresponding floor with the first preset threshold D θ，1 Perform comparative analysis. If D1>D θ，1 , indicating that a significant settlement change has occurred at the intersection of the floor slab and the target wall, so a corresponding danger warning signal about excessive deformation of the house floor slab is generated. If D1≤D θ，1 , then no danger warning signal for floor deformation is generated. It should be noted that ε1 and ε2 are the preset first weight coefficients, ω i is a preset second weight coefficient, which can be obtained by fitting empirical data or experimental data and will not be described in detail here.

[0090] The process of comprehensively analyzing the location information data of the first monitoring point and the second monitoring point also includes:

[0091]

[0092] The wall deformation coefficient D2 of the target wall is calculated by formula (3) to (4);

[0093] Where dj is the measured distance between the jth first monitoring point and the reference point; h j is the initial height from the jth first monitoring point to the intersection line of the target wall and floor; α j is the laser elevation angle when the laser measures the position of the jth monitoring point; Δw is the maximum change in the crack width on the target wall; w0 is the preset standard proportional coefficient; m is the number of the first monitoring points; μ is the preset third weight coefficient;

[0094] The wall deformation coefficient D2 is compared with the second preset threshold D θ，2 Conduct comparative analysis:

[0095] If D2>D θ，2 , then a corresponding warning signal about excessive deformation of the house wall is generated;

[0096] If D2≤D θ，2 , no danger warning signal for wall deformation is generated.

[0097] Through the above technical solution, this embodiment first calculates the wall deformation coefficient D2 of the target wall through formulas (3) to (4), where The distance from the reference point to the first monitoring point in the ideal state (the wall is flat and the wall is perpendicular to the floor), the wall deformation coefficient D2 is compared with the second preset threshold D θ，2 Perform comparative analysis: If D2>Dθ，2 , indicating that the wall has a large deformation, so a corresponding warning signal about excessive deformation of the house wall is generated. If D2≤D θ，2 , no danger warning signal for wall deformation is generated. w0 is the preset standard proportional coefficient, μ j It is a preset third weight coefficient, which is obtained based on empirical data.

[0098] See also Figure 2 As shown, a housing deformation monitoring method and system, the system comprising:

[0099] The image acquisition module is used to collect image information of the house wall, specifically including a camera and a drone with a camera function.

[0100] Image recognition module, which identifies cracks in wall images based on convolutional neural networks and records the original characteristic parameters of the cracks;

[0101] The pre-analysis module is used to pre-analyze the original characteristic parameters and conduct a safety evaluation of the tested house based on the results of the pre-analysis;

[0102] A data acquisition module, including a laser rangefinder and a static level, for collecting position information data of a first monitoring point and a second monitoring point on the wall and the floor;

[0103] A data processing module is used to comprehensively analyze the location information data of the first monitoring point and the second monitoring point, and establish a house deformation early warning strategy based on the comprehensive analysis;

[0104] The human-computer interaction module specifically includes the staff's handheld terminal or other display device, which is used to implement the house deformation early warning strategy.

[0105] Through the above technical solution, this embodiment provides a house deformation monitoring system. When monitoring house deformation, the system first locates the target wall with cracks through the cooperation of the image acquisition module and the image recognition module. The data acquisition module collects displacement change data at each monitoring point. The data processing module comprehensively analyzes the monitoring results and determines the house deformation. The monitoring system can automatically monitor and analyze the house in real time, improving monitoring efficiency and making the monitoring process safer.

[0106] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A housing deformation monitoring method, characterized in that: The method comprises: S1. Collect real-life images of each wall of a house, import the real-life images into a trained image recognition model, and output results indicating whether there are cracks on the wall; S2. Mark the wall with cracks as the target wall and record the original characteristic parameters of the corresponding cracks; S3. Install a crack detector at the crack of the target wall to collect real-time crack width change data; S4. Preset a number of first monitoring points on the target wall and a number of second monitoring points on the floor slab connected to the target wall; S5. Acquire location information data of the first monitoring point and the second monitoring point through monitoring, and perform comprehensive analysis on the location information data of the first monitoring point and the second monitoring point; S6. Establish a housing deformation early warning strategy based on the results of the comprehensive analysis; The process of comprehensively analyzing the location information data of the first monitoring point and the second monitoring point includes: By formula Calculate the settlement variation coefficient of the corresponding floor ; in, 、 is the preset first weight coefficient; is the preset second weight coefficient, is the height difference between each measuring point and the reference point; is the average height difference; is the number of measuring points; The corresponding floor settlement variation coefficient and the first preset threshold Conduct comparative analysis: like , then a corresponding warning signal about excessive deformation of the building floor is generated; like , then no danger warning signal for floor deformation is generated; The process of comprehensively analyzing the location information data of the first monitoring point and the second monitoring point also includes: ； ； By formula ~ Calculate the wall deformation coefficient of the target wall ; in, is the measured distance between the jth first monitoring point and the reference point; is the initial height from the jth first monitoring point to the intersection line of the target wall and floor; is the laser elevation angle when the laser measures the position of the j-th monitoring point; is the maximum change in crack width on the target wall; is the preset standard scale factor; is the number of the first monitoring points; is the preset third weight coefficient; The wall deformation coefficient and the second preset threshold Conduct comparative analysis: like , then a corresponding warning signal about excessive deformation of the house wall is generated; like , no danger warning signal for wall deformation is generated.

2. A housing deformation monitoring method according to claim 1, characterized in that: Before step S3, the method further includes: S21. Preliminary analysis of original characteristic parameters of cracks on the target wall; S22. Perform a safety evaluation on the tested house based on the results of the pre-analysis, where the result of the safety evaluation indicates whether the house meets the safety monitoring standards; S23. If the tested house does not meet the safety monitoring standards, steps S3 to S6 are not executed, and a danger warning signal for the corresponding house is generated. Otherwise, steps S3 to S6 are continued.

3. A housing deformation monitoring method according to claim 2, characterized in that: The original characteristic parameters of the cracks include: initial length and initial width of the cracks and the total number of cracks on the same target wall.

4. A building deformation monitoring method according to claim 3, characterized in that: The process of pre-analyzing the original characteristic parameters of cracks on the target wall includes: By formula Calculate the risk assessment coefficient of the house ; in, is the preset correlation coefficient, and ; is the number of cracks on the target wall; and are the length and average width of the i-th crack on the target wall respectively; is the total wall area of ​​the target wall; The risk assessment factor Compared with the preset safety standard value To compare: like , then it is judged that the house does not meet the safety monitoring standards; like , then it is judged that the house meets the safety monitoring standards.

5. A housing deformation monitoring method according to claim 4, characterized in that: The process of presetting the first monitoring point and the second monitoring point includes: A number of first monitoring points are evenly distributed in rows and columns around the cracks of the target wall; Install a laser rangefinder at a preset position on the floor slab connected to the target wall; Taking the location of the laser rangefinder as the reference point, select several measuring points at the intersection of the floor slab and the target wall, and install a static level. Both the measuring points and the reference points are marked as the second monitoring points; The distance from each monitoring point on the target wall to the reference point is obtained by a laser rangefinder, and the vertical displacement data of each measuring point is obtained by a static level.

6. A house deformation monitoring system, characterized in that: The system is used to perform the housing deformation monitoring method according to any one of claims 1 to 5, and the system includes: Image acquisition module, used to collect image information of the house wall; Image recognition module, which identifies cracks in wall images based on convolutional neural networks and records the original characteristic parameters of the cracks; The pre-analysis module is used to pre-analyze the original characteristic parameters and conduct a safety evaluation of the tested house based on the results of the pre-analysis; A data acquisition module is used to collect position information data of a first monitoring point and a second monitoring point on the wall and the floor; A data processing module is used to comprehensively analyze the location information data of the first monitoring point and the second monitoring point, and establish a house deformation early warning strategy based on the comprehensive analysis; Human-computer interaction module, used to implement house deformation early warning strategy.

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