A deformation detection method and system for engineering building wall

Abstract

The present invention relates to the field of building deformation detection technology, and specifically to a deformation detection method and system for engineering building walls. The present invention first divides the point cloud data model to obtain each block area included in each layer model; according to the difference between the point cloud data model corresponding to the block area and the BIM model, the regional error of the block area is obtained; according to the regional error of the block area included in each layer model, the abnormal degree of wall deformation of the engineering building wall is obtained; according to the abnormal degree of wall deformation of the engineering building wall, the deformation detection of the engineering building wall is performed. The present invention improves the accuracy of the deformation detection results of the engineering building wall by deeply analyzing the mutual influence of the wall deformation of the building layer.

Description

Technical Field

[0001] The present invention relates to the technical field of building deformation detection, and in particular to a deformation detection method and system for an engineering building wall. Background Art

[0002] The walls of engineering buildings are an important part of buildings. They need to have sufficient strength and stability to ensure the safety of the buildings. As the main load-bearing and enclosure structure of the building, the stability of the wall is directly related to the safety of the building. In order to ensure the safety and functionality of the wall, deformation detection is required to detect deformation problems in the wall in time to avoid safety accidents.

[0003] The existing technology uses the difference between point cloud data and BIM models to perform shape detection on engineering building walls. In the process of the existing technology for the shape detection of engineering building walls, it is ignored that as the building height increases, the deformation of the wall of the building layer will affect each other, resulting in inaccurate shape detection results of the engineering building wall, which is difficult to effectively reduce the risk of the construction process. Summary of the invention

[0004] In order to solve the technical problem that the deformation detection results of engineering building walls in the prior art are inaccurate, the purpose of the present invention is to provide a deformation detection method and system for engineering building walls. The technical solution adopted is as follows:

[0005] A deformation detection method for a wall of an engineering building, the method comprising:

[0006] Obtain point cloud data model and BIM model of engineering building walls;

[0007] The point cloud data model is divided to obtain each block area included in each layer model; according to the difference between the block area and the point cloud data model and the BIM model, the regional error of the block area is obtained; according to the regional error of the block area included in each layer model, the abnormal degree of wall deformation of the engineering building wall is obtained;

[0008] According to the abnormal degree of the wall deformation of the engineering building wall, deformation detection is performed on the engineering building wall.

[0009] Furthermore, the layer model acquisition method includes:

[0010] The point cloud data model and the BIM model of the engineering building wall are mapped to a three-dimensional space coordinate system to construct a minimum circumscribed cuboid including the point cloud data model and the BIM model; the minimum circumscribed cuboid is equally divided into sub-cubes; the sub-cubes are used as block areas, and all the block areas included in each layer in the Z-axis direction of the three-dimensional space coordinate system are used as layer models.

[0011] Furthermore, the method for obtaining the regional error degree includes:

[0012] Mapping all data points of the point cloud data model to the BIM model, and obtaining a mapped data point corresponding to each data point;

[0013] In each block area, the average of the absolute values ​​of the differences between the curvature values ​​of all data points and the mapped data points is calculated to obtain the regional error degree of the block area.

[0014] Furthermore, the method for obtaining the abnormal degree of wall deformation includes:

[0015] Obtaining a first deformation measurement of the wall of the engineering building according to the relevant conditions of the regional error degrees of the block regions included in the layer model;

[0016] Obtaining a second deformation measurement of the wall of the engineering building according to the distribution of the regional error degree of the block area included in the layer model and the layer model adjacent to it in spatial distribution;

[0017] The regional error of all the block areas is integrated to obtain the third deformation measurement of the wall of the engineering building;

[0018] The first wall deformation measurement, the second wall deformation measurement and the third wall deformation measurement of the engineering building wall are forwardly integrated to obtain the abnormal degree of wall deformation.

[0019] Furthermore, the method for obtaining the first deformation measurement of the wall includes:

[0020] For each layer model, the regional error degrees corresponding to all the block areas in the layer model are counted in sequence according to the preset sorting order to obtain the regional error degree sequence of each layer model;

[0021] According to the preset height direction, the layer models are sorted in turn to obtain the serial numbers of the layer models; according to the serial number order of the layer models, the first layer model is used as the basic model, and all layer models except the basic model are used as models to be analyzed;

[0022] According to the order of the layer models, the Pearson coefficient of each model to be analyzed and the basic model is calculated and normalized to obtain the association metric of each model to be analyzed; the mean of the association metrics of all models to be analyzed is calculated to obtain the overall association metric of the base layer;

[0023] According to the order of the layer models, the difference value of the association metric of each model to be analyzed is calculated and normalized to obtain the local enhancement metric of each model to be analyzed; the mean of the local enhancement metrics of all models to be analyzed is calculated to obtain the base-level association enhancement metric;

[0024] The mean of the base overall association metric and the base association enhancement metric is calculated to obtain a first wall deformation metric of the engineering building wall.

[0025] Furthermore, the method for obtaining the second deformation measurement of the wall includes:

[0026] According to the regional error degree of the block area, the block area is divided into a deformation area and a stable area; any layer model is taken as the current layer model, and in the current layer model and its adjacent layer model in spatial distribution, the total number of the deformation areas adjacent to the current layer model in the adjacent layer model is taken and normalized as the coincidence measure of the layer model; the mean of the coincidence measures of all layer models is calculated to obtain the second deformation measure of the wall of the engineering building.

[0027] Furthermore, the method of forward fusion of the first wall deformation measurement, the second wall deformation measurement and the third wall deformation measurement of the engineering building wall to obtain the abnormal degree of wall deformation includes:

[0028] The product of the first deformation measurement of the wall, the second deformation measurement of the wall and the third deformation measurement of the wall of the engineering building is calculated and normalized to obtain the abnormal degree of wall deformation.

[0029] Furthermore, the method for detecting deformation of a wall of an engineering building comprises:

[0030] If the abnormal degree of the wall deformation of the engineering building wall is greater than a preset abnormal threshold, deformation detection is performed on the engineering building wall.

[0031] Furthermore, the preset abnormal threshold is set to 0.4.

[0032] The present invention provides a deformation detection system for an engineering building wall, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the deformation detection method for the engineering building wall are implemented.

[0033] The present invention has the following beneficial effects:

[0034] In order to analyze the deformation of the wall more carefully, we need to divide the point cloud data model into smaller units, namely block areas, and further organize these block areas into layer models according to the height of the building. The regional error degree is obtained by comparing the differences between the point cloud data model corresponding to the block area and the BIM model. The regional error degree reflects the degree of deformation of the wall corresponding to the block area. The degree of abnormal deformation of the entire engineering building wall is evaluated according to the regional error degree of the block area contained in each layer model. The degree of abnormal deformation of the wall reflects the degree of deformation of the engineering building wall. The degree of abnormal deformation of the wall not only takes into account the differences between the point cloud data model and the BIM model, but also fully considers the mutual influence of the wall deformation of the building layer, comprehensively reflects the deformation degree of the engineering building wall, and improves the accuracy of the surface detection results of the engineering building wall. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0036] Figure 1 A flow chart of a deformation detection method for a construction wall provided by an embodiment of the present invention;

[0037] Figure 2 A schematic diagram of a three-dimensional space coordinate system provided by an embodiment of the present invention;

[0038] Figure 3 A flow chart of a method for obtaining the abnormal degree of wall deformation provided by an embodiment of the present invention;

[0039] Figure 4 A structural diagram of a deformation detection system for a construction wall provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of a deformation detection method and system for a construction wall according to the present invention, its specific implementation method, structure, features and effects, in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics in one or more embodiments may be combined in any suitable form.

[0041] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0042] The following is a detailed description of a deformation detection method and system for a construction wall provided by the present invention in conjunction with the accompanying drawings.

[0043] The embodiment of the present invention provides a deformation detection method and system for a construction wall. Figure 1 , which shows a flow chart of a deformation detection method for a construction wall provided by an embodiment of the present invention, the method comprising the following steps:

[0044] Step S1: Obtain the point cloud data model and BIM model of the engineering building wall.

[0045] In order to perform deformation detection on the walls of engineering buildings, it is first necessary to obtain the point cloud data model and BIM model of the walls of the engineering buildings.

[0046] The point cloud data model of the engineering building wall is obtained from the monitoring system of the engineering building wall. The specific steps include: using a laser radar device to collect the initial point cloud data of the engineering building wall. Since the application environment of the engineering building wall is often more complex, the initial point cloud data of the engineering building wall contains noise, and the noise will cause inaccurate measurement of the engineering building wall. Therefore, it is necessary to denoise the initial point cloud data of the engineering building wall to obtain the point cloud data model of the engineering building wall. The embodiment of the present invention uses Gaussian filtering for noise reduction, and other filtering methods, such as bilateral filtering, can also be used. The implementer can set it according to the actual situation.

[0047] The BIM model of the engineering building wall is obtained from the monitoring system of the engineering building wall. The specific steps include: combining CAD drawings and geographic information system data, where the CAD drawings provide the geometric information of the building wall, and the geographic information system data provides the geographical location information of the building wall, generating an initial model through professional BIM software, and the engineer optimizes the initial model to obtain the BIM model of the engineering building wall. Among them, the BIM model is a digital model that integrates various relevant information of the construction project, which can provide a reference for the construction stage.

[0048] It should be noted that, in order to facilitate calculation, all indicator data involved in the calculation in the embodiment of the present invention are preprocessed to eliminate the dimension effect. The specific means of eliminating the dimension effect are technical means well known to those skilled in the art and are not limited here.

[0049] Step S2: Divide the point cloud data model to obtain the block areas included in each layer model; obtain the regional error of the block area according to the difference between the point cloud data model corresponding to the block area and the BIM model; obtain the abnormal degree of wall deformation of the engineering building wall according to the regional error of the block area included in each layer model.

[0050] In order to analyze the deformation of the wall more carefully, we need to divide the point cloud data model into smaller units, namely block areas, and further organize these block areas into layer models according to the height of the building. The regional error degree is obtained by comparing the differences between the point cloud data model corresponding to the block area and the BIM model. The regional error degree reflects the degree of deformation of the wall corresponding to the block area. The degree of abnormal deformation of the entire engineering building wall is evaluated according to the regional error degree of the block area contained in each layer model. The abnormal degree of wall deformation more accurately reflects the degree of deformation of the engineering building wall.

[0051] In order to analyze the engineering building wall in detail, it is necessary to divide the point cloud data model to obtain each block area included in each layer model. Preferably, in one embodiment of the present invention, the layer model acquisition method includes:

[0052] The point cloud data model and BIM model of the engineering building wall are mapped to the three-dimensional space coordinate system, and the minimum circumscribed cuboid including the point cloud data model and the BIM model is constructed; the minimum circumscribed cuboid is equally divided into various sub-cubes; each sub-cube is used as a block area, and all the block areas included in each layer in the Z-axis direction of the three-dimensional space coordinate system are used as layer models.

[0053] Specifically, in one embodiment of the present invention, the XY plane of the three-dimensional space coordinate is parallel to the ground, and the Z axis is perpendicular to the ground. Figure 2 , Figure 2 A schematic diagram of a three-dimensional space coordinate system provided by an embodiment of the present invention, wherein the three axes of the three-dimensional space coordinate system correspond to the X-axis, the Y-axis and the Z-axis respectively. Figure 2It is only a schematic diagram to help understand the three-dimensional space coordinate system. The point cloud data model and BIM model of the engineering building wall are mapped to the three-dimensional space coordinate system, and the minimum circumscribed cuboid including the point cloud data model and the BIM model is constructed; wherein the minimum circumscribed cuboid is equally divided into each sub-cube; the length of the sub-cube is the ratio of the length of the minimum circumscribed cuboid to the number of preset length segments; the width of the sub-cube is the ratio of the width of the minimum circumscribed cuboid to the number of preset width segments; the height of the sub-cube is the ratio of the height of the minimum circumscribed cuboid to the number of preset height segments; each sub-cube is taken as a block area, and all the block areas included in each layer in the Z-axis direction of the three-dimensional space coordinate system are taken as layer models. The number of layer models is the number of preset height segments. In one embodiment of the present invention, the preset length segment number, the preset width segment number and the preset height segment number are used to equally divide the minimum circumscribed cuboid, the preset length segment number is set to 15, the preset width segment number is set to 7, and the preset height segment number is set to 21, which can be set by the implementer according to the implementation scenario. It should be noted that the positive direction of the Z axis indicates the upward direction from the horizontal ground.

[0054] For the above steps, in order to ensure the consistency of the Z-axis direction of the three-dimensional space coordinate system and the wall of the engineering building, and to facilitate subsequent analysis, first construct the XY plane of the three-dimensional space coordinate system parallel to the ground and the Z-axis perpendicular to the ground; in order to analyze the wall of the engineering building in detail, it is necessary to divide the point cloud data model and obtain each block area; the layer model represents all the block areas of the engineering building wall in a specific height range in the vertical direction, so as to analyze the mutual influence between the wall deformations of the building layers in the subsequent analysis.

[0055] In order to analyze the deformation degree of the wall corresponding to the block area, preferably, in one embodiment of the present invention, the method for obtaining the regional error degree includes:

[0056] Map all data points of the point cloud data model to the BIM model, and obtain the mapped data points corresponding to each data point;

[0057] In each block area, the average of the absolute values ​​of the differences between the curvature values ​​of all data points and the data points after their mapping is calculated to obtain the regional error degree of the block area. It should be noted that the method for obtaining the curvature value is a prior art well known to those skilled in the art and can be obtained by the least squares method, which will not be described in detail here.

[0058] For the above steps, all data points in the point cloud data model are mapped to the BIM model one by one to find the corresponding position of each data point in the point cloud data model in the BIM model. The mapped data points represent the points in the BIM model corresponding to the data points of the point cloud data model. Then the difference in curvature value between all data points and their mapped data points is calculated. This difference is measured by calculating the absolute value of the difference between the curvature value of the data point and its mapped data point. Then the mean of all the absolute values ​​of the difference in each block area is calculated, and this mean is defined as the regional error degree of the block area. The regional error degree reflects the degree of difference between the actual wall corresponding to the block area and the ideal situation. The larger the regional error degree, the greater the difference between the wall corresponding to the block area and the ideal situation, and the more likely the wall corresponding to the block area is to have a greater degree of deformation.

[0059] Considering that the error of the wall in the construction stage of the engineering building is difficult to avoid due to manual operation, only considering the difference between the point cloud data model and the BIM model, the deformation of the engineering building wall is not comprehensive enough, ignoring that with the increase of the building height, the correlation between the upper wall and the lower wall may indeed increase, because the stability of the high-rise wall is more dependent on the stability of the lower wall. The correlation between the upper wall and the lower wall is an important deformation feature. In addition, considering the impact of deformation defects on the surrounding area is also an important deformation feature. By analyzing the regional error of the block area contained in each layer model, a more comprehensive analysis of the deformation degree of the engineering building wall is constructed. Please refer to Figure 3 , which shows a flow chart of a method for obtaining the abnormal degree of wall deformation in one embodiment of the present invention. The method for obtaining the abnormal degree of wall deformation includes:

[0060] Step S201: obtaining a first deformation measurement of a wall of a construction building according to the relevant conditions of the regional error of the block regions included in the layer model.

[0061] As the building height increases, the stability of the high-rise walls is indeed more dependent on the stability of the bottom walls. If the bottom wall is deformed or damaged, then this effect may be transmitted to the upper wall, causing the stability of the entire building structure to be affected. Therefore, when performing deformation analysis, it is necessary to take into account the correlation between such walls and construct the first deformation metric of the engineering building wall to reflect the influence of the upper wall on the bottom wall. The larger the first deformation metric of the wall, the greater the influence of the upper wall on the bottom wall, and the more serious the deformation defect of the engineering building wall.

[0062] Preferably, in one embodiment of the present invention, the method for obtaining the first deformation measurement of the wall includes:

[0063] For each layer model, the regional error degrees corresponding to all the block areas in the layer model are counted in sequence according to the preset sorting order to obtain the regional error degree sequence of each layer model;

[0064] According to the preset height direction, the layer models are sorted in turn to obtain the serial numbers of the layer models; according to the serial number order of the layer models, the first layer model is used as the basic model, and all layer models except the basic model are used as models to be analyzed;

[0065] According to the order of the layer models, the Pearson coefficient of each model to be analyzed and the basic model is calculated and normalized to obtain the correlation measure of each model to be analyzed; the mean of the correlation measures of all models to be analyzed is calculated to obtain the overall correlation measure of the base layer;

[0066] According to the order of the layer models, the difference value of the association metric of each model to be analyzed is calculated and normalized to obtain the local enhancement metric of each model to be analyzed; the mean of the local enhancement metrics of all models to be analyzed is calculated to obtain the base-level association enhancement metric;

[0067] Calculate the mean of the overall association metric of the base layer and the association enhancement metric of the base layer to obtain the first deformation metric of the wall of the engineering building. In one embodiment of the present invention, the preset height direction is the positive direction of the Z axis of the three-dimensional space coordinate system, and the preset height direction represents the direction of the height increase of the engineering building; the preset sorting order of the layer model is: map the layer model to the XY plane, take the block area closest to the upper left corner in the layer model as the starting point, and label each block area in the layer model in sequence from left to right and from top to bottom. The labeling order is the preset sorting order of the layer model. It should be noted that the present invention is a regular engineering building that is a rectangular parallelepiped. The characteristics of this type of building are that the layout and size between different layers are roughly the same, that is, the block areas with the same label in different layer models reflect the position of the same column of walls in the engineering building. It should be noted that the Pearson coefficient is a well-known prior art in the art and will not be described here. It should be noted that the normalization method is: normalization is performed using the norm normalization function to limit the value range to between 0 and 1. Normalization is a technical means well known to those skilled in the art, and the normalization function may be linear normalization or standard normalization, etc. The specific normalization method is not limited here.

[0068] According to the above steps, in order to analyze the correlation between the bottom wall and the upper wall, the regional error sequence of each layer model is first constructed to reflect the deformation of the block area in the layer model. All layer models are sorted according to the height direction of the building, and the first layer model is determined as the basic model, and the remaining layer models are regarded as the models to be analyzed. The correlation between the model to be analyzed and the basic model is quantified by the correlation metric of the model to be analyzed. The base layer correlation enhancement metric reflects the degree to which the upper wall is affected by the bottom wall from an overall perspective. The base layer correlation enhancement metric is constructed to reflect the increasing trend of the correlation between walls as the floor height increases. Combining the base layer overall correlation metric and the base layer correlation enhancement metric, the first deformation metric of the wall of the engineering building wall is obtained. The first deformation metric of the wall comprehensively evaluates the possibility of deformation of the entire building wall under the influence of the bottom wall. The larger the first deformation metric of the wall, the greater the influence of the upper wall on the bottom wall, and the greater the possibility of deformation of the engineering building wall.

[0069] Step S202: obtaining a second deformation measurement of the wall of the engineering building according to the distribution of the regional error of the block area included in the layer model and its adjacent layer model in spatial distribution.

[0070] Considering that the influence of deformation defects on the surrounding area is also an important deformation feature, that is, the greater the influence of the layer model on the deformation degree of its adjacent layer model in spatial distribution, the more serious the deformation defects of the engineering building wall are, and the second deformation measurement of the engineering building wall is obtained. The larger the second deformation measurement of the wall, the more serious the influence of the defects of the layer model of the engineering building on the surrounding area is, and the more serious the deformation defects of the engineering building wall are.

[0071] Preferably, in one embodiment of the present invention, the method for obtaining the second deformation measurement of the wall includes:

[0072] According to the regional error degree of the block area, the block area is divided into a deformation area and a stable area; any layer model is taken as the current layer model, and in the current layer model and its adjacent layer model in spatial distribution, the total number of deformation areas adjacent to the current layer model in the adjacent layer model is normalized and used as the coincidence measure of the layer model; the mean of the coincidence measures of all layer models is calculated to obtain the second deformation measure of the wall of the engineering building wall. Among them, the specific steps of dividing the block area into deformation areas and stable areas are: the block area with a regional error degree greater than the preset error division threshold is marked as a deformation area; the block area with a regional error degree not greater than the preset error division threshold is marked as a stable area. It should be noted that the preset error division threshold is 0.23, and the implementer can set it according to the implementation scenario. It should be noted that normalization processing is a technical means well known to those skilled in the art, and normalization processing can adopt linear normalization, etc., which is not limited here.

[0073] According to the above steps, in order to distinguish the area with deformation defects and the relatively stable area, the block area is divided into deformation area and stable area according to the regional error degree of the block area. The deformation area reflects the wall corresponding to the deformation defect; while the stable area reflects the relatively stable building wall with a small deformation degree. For any layer model, check its adjacent layer model in spatial distribution, that is, in the positive direction of the Z axis of the three-dimensional space coordinate system, take the previous layer model and the next layer model of the current layer model as the layer model adjacent to the current layer model in spatial distribution, and in the current layer model and its adjacent layer model in spatial distribution, take the total number of deformation areas adjacent to the current layer model in the adjacent layer model as the overlap measure of the layer model. The overlap measure reflects the possibility of deformation defect propagation between layer models. The larger the overlap measure, the easier it is for the defects of the layer model to propagate. The mean of the overlap measures of all layer models is calculated to obtain the second deformation measure of the wall of the engineering building wall. The second deformation measure of the wall reflects the average degree of mutual influence of deformation defects between layer models in the entire building wall. The larger the second deformation measure of the wall, the more serious the impact of the defects in the middle-level model of the engineering building on the surrounding area, and the greater the possibility of deformation defects in the walls of the engineering building.

[0074] Step S203: The regional error degrees of all the block regions are integrated to obtain the third deformation measure of the wall of the engineering building.

[0075] Considering that the larger the regional error, the greater the difference between the wall corresponding to the block area and the ideal situation, the more likely the deformation of the wall corresponding to the block area is, the regional error of all block areas is combined to obtain the third deformation measure of the wall of the engineering building. The larger the third deformation measure of the wall, the more serious the deformation defect of the engineering building wall.

[0076] The mean of the regional error of all block areas is calculated to obtain the third deformation measure of the wall of the engineering building.

[0077] In view of the above steps, the third deformation metric of the wall integrates the deformation information of all block areas and provides an overall evaluation of the deformation of the entire wall.

[0078] Step S204: forwardly fuse the first wall deformation metric, the second wall deformation metric and the third wall deformation metric of the engineering building wall to obtain the abnormal degree of wall deformation.

[0079] The abnormal degree of wall deformation not only takes into account the differences between the point cloud data model and the BIM model, but also fully considers the mutual influence of the wall deformation of the building layer, and comprehensively reflects the deformation degree of the engineering building wall.

[0080] It should be noted that forward fusion is an existing technology well known to those skilled in the art, and forward fusion can adopt simple product, arithmetic mean or other suitable fusion methods. In one embodiment of the present invention, the product of the first deformation metric of the wall, the second deformation metric of the wall and the third deformation metric of the wall of the engineering building is calculated and normalized to obtain the abnormal degree of wall deformation. It should be noted that normalization processing is a technical means well known to those skilled in the art, and normalization processing can adopt linear normalization, etc., which is not limited here.

[0081] Step S3: performing deformation detection on the engineering building wall according to the abnormal degree of wall deformation of the engineering building wall.

[0082] The abnormal degree of wall deformation not only takes into account the differences between the point cloud data model and the BIM model, but also fully considers the mutual influence of the wall deformation of the building layer, comprehensively reflects the deformation degree of the engineering building wall, and improves the accuracy of the surface detection results of the engineering building wall.

[0083] In order to perform more accurate deformation detection, preferably, in one embodiment of the present invention, the method for performing deformation detection on a wall of an engineering building includes:

[0084] If the abnormal deformation degree of the wall of the engineering building is greater than the preset abnormal threshold, deformation detection is performed on the wall of the engineering building and reinforcement is performed. In one embodiment of the present invention, the preset abnormal threshold is set to 0.4, and the implementer can set it according to the implementation scenario.

[0085] For the above steps, the degree of abnormal deformation of the wall not only takes into account the differences between the point cloud data model and the BIM model, but also fully considers the mutual influence of the wall deformation of the building layer, and comprehensively reflects the deformation degree of the wall of the engineering building. If the abnormal deformation degree of the wall is greater than the preset abnormal threshold, it means that the wall of the engineering building has a more obvious deformation, and the inspection personnel need to conduct further deformation detection. Deformation detection includes more detailed measurement, monitoring and analysis to determine the specific cause, scope and degree of deformation. According to the results of deformation detection, formulate and implement reinforcement treatment plans to ensure the safety and stability of the building. Reinforcement treatment may include adding support structures, repairing cracks, adjusting wall structures, etc.

[0086] The present invention also proposes a deformation detection system for engineering building walls, see Figure 4 , which shows a structural diagram of a deformation detection system for a construction wall provided by an embodiment of the present invention. The system includes: a data acquisition module 101, a deformation anomaly analysis module 102, and a deformation detection module 103.

[0087] The data acquisition module 101 is used to acquire the point cloud data model and BIM model of the engineering building wall.

[0088] The deformation anomaly analysis module 102 is used to divide the point cloud data model to obtain the various block areas included in each layer model; obtain the regional error of the block area according to the difference between the point cloud data model corresponding to the block area and the BIM model; obtain the degree of abnormal wall deformation of the engineering building wall according to the regional error of the block area included in each layer model.

[0089] The deformation detection module 103 is used to perform deformation detection on the engineering building wall according to the abnormal degree of wall deformation of the engineering building wall.

[0090] It should be noted that: the system provided in the above embodiment is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the computer device is divided into different functional modules to complete all or part of the functions described above. In addition, the deformation detection system for a construction wall provided in the above embodiment and the deformation detection method embodiment for a construction wall belong to the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0091] In summary, the embodiment of the present invention provides a deformation detection method and system for engineering building walls. First, the point cloud data model is divided to obtain each block area included in each layer model; according to the difference between the point cloud data model corresponding to the block area and the BIM model, the regional error of the block area is obtained; according to the regional error of the block area included in each layer model, the abnormal degree of wall deformation of the engineering building wall is obtained; according to the abnormal degree of wall deformation of the engineering building wall, the deformation of the engineering building wall is detected. The present invention improves the accuracy of the deformation detection results of the engineering building wall by deeply analyzing the wall deformation of the building layer and the mutual influence.

[0092] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0093] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A deformation detection method for a construction wall, characterized in that: The method comprises: Obtain point cloud data model and BIM model of engineering building walls; The point cloud data model is divided to obtain each block area included in each layer model; according to the difference between the block area and the point cloud data model and the BIM model, the regional error of the block area is obtained; according to the regional error of the block area included in each layer model, the abnormal degree of wall deformation of the engineering building wall is obtained; Performing deformation detection on the engineering building wall according to the abnormal degree of deformation of the wall of the engineering building wall; The method for obtaining the abnormal degree of wall deformation includes: Obtaining a first deformation measurement of the wall of the engineering building according to the relevant conditions of the regional error degrees of the block regions included in the layer model; Obtaining a second deformation measurement of the wall of the engineering building according to the distribution of the regional error degree of the block area included in the layer model and the layer model adjacent to it in spatial distribution; The regional error of all the block areas is integrated to obtain the third deformation measurement of the wall of the engineering building; Forward fusion of the first wall deformation measurement, the second wall deformation measurement and the third wall deformation measurement of the engineering building wall to obtain the abnormal degree of wall deformation; The method for obtaining the first deformation measurement of the wall includes: For each layer model, the regional error degrees corresponding to all the block areas in the layer model are counted in sequence according to the preset sorting order to obtain the regional error degree sequence of each layer model; According to the preset height direction, the layer models are sorted in turn to obtain the serial numbers of the layer models; according to the serial number order of the layer models, the first layer model is used as the basic model, and all layer models except the basic model are used as models to be analyzed; According to the order of the layer models, the Pearson coefficient of each model to be analyzed and the basic model is calculated and normalized to obtain the association metric of each model to be analyzed; the mean of the association metrics of all models to be analyzed is calculated to obtain the overall association metric of the base layer; According to the order of the layer models, the difference value of the association metric of each model to be analyzed is calculated and normalized to obtain the local enhancement metric of each model to be analyzed; the mean of the local enhancement metrics of all models to be analyzed is calculated to obtain the base-level association enhancement metric; The mean of the base overall association metric and the base association enhancement metric is calculated to obtain a first wall deformation metric of the engineering building wall.

2. A deformation detection method for a construction wall according to claim 1, characterized in that: The method for obtaining the layer model includes: The point cloud data model and the BIM model of the engineering building wall are mapped to a three-dimensional space coordinate system to construct a minimum circumscribed cuboid including the point cloud data model and the BIM model; the minimum circumscribed cuboid is equally divided into sub-cubes; the sub-cubes are used as block areas, and all the block areas included in each layer in the Z-axis direction of the three-dimensional space coordinate system are used as layer models.

3. The deformation detection method of a construction wall according to claim 1, characterized in that: The method for obtaining the regional error degree includes: Mapping all data points of the point cloud data model to the BIM model, and obtaining a mapped data point corresponding to each data point; In each block area, the average of the absolute values ​​of the differences between the curvature values ​​of all data points and the mapped data points is calculated to obtain the regional error degree of the block area.

4. The deformation detection method of a construction wall according to claim 1, characterized in that: The method for obtaining the second deformation measurement of the wall includes: According to the regional error degree of the block area, the block area is divided into a deformation area and a stable area; any layer model is taken as the current layer model, and in the current layer model and its adjacent layer model in spatial distribution, the total number of the deformation areas adjacent to the current layer model in the adjacent layer model is taken and normalized as the coincidence measure of the layer model; the mean of the coincidence measures of all layer models is calculated to obtain the second deformation measure of the wall of the engineering building.

5. The deformation detection method of a construction wall according to claim 1, characterized in that: The method of forward fusing the first deformation measurement of the wall, the second deformation measurement of the wall and the third deformation measurement of the wall of the engineering building to obtain the abnormal degree of wall deformation includes: The product of the first deformation measurement of the wall, the second deformation measurement of the wall and the third deformation measurement of the wall of the engineering building is calculated and normalized to obtain the abnormal degree of wall deformation.

6. The deformation detection method of a construction wall according to claim 1, characterized in that: The method for detecting deformation of a wall of an engineering building comprises: If the abnormal degree of the wall deformation of the engineering building wall is greater than a preset abnormal threshold, deformation detection is performed on the engineering building wall.

7. A deformation detection method for a construction wall according to claim 6, characterized in that: The preset abnormal threshold is set to 0.

4.

8. A deformation detection system for a construction wall, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the deformation detection method of an engineering building wall as described in any one of claims 1 to 7 are implemented.

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