CN107452064A - A kind of three-dimensional building entity space levelling implementation method, device and storage device - Google Patents
A kind of three-dimensional building entity space levelling implementation method, device and storage device Download PDFInfo
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Abstract
The invention discloses a kind of three-dimensional building entity space levelling implementation method, device and storage device, method includes：The cloud data of interior of building is obtained by laser point cloud 3-D scanning automation equipment；According to having ready conditions, adjustment Algorithm carries out noise processed to cloud data, filters the excess observation component in cloud data, obtains cloud data after first noise reduction；Included in cloud data after first noise reduction 1 points are chosen, plane is fitted according to least square method to obtain point-cloud fitting plane；Optimal face fitting is carried out according to point-cloud fitting plane, forms reference plane；Face or minimum point fitting face are fitted according to the peak of reference plane to obtain and be most worth fitting face data, and levelling volume is calculated according to most value fitting face data.The present invention realize the design phase complete levelling, accurate guiding construction, can accurate discharge, complete high quality finishing；Precision data can also be obtained, existing drawing data is corrected, construction material needed for accurate calculation, shortens man-hour.
Description
Technical Field
The invention relates to the technical field of three-dimensional space data processing, in particular to a method, a device and storage equipment for realizing three-dimensional building entity space leveling.
Background
The existing decoration design process is basically designed according to a house-type diagram, even if measurement is carried out in the earlier stage, the measurement is carried out by a two-dimensional laser scanner, the existing decoration design process is basically handheld, the measurement distance is generally within 200 meters, the precision is about 2mm, the longer the distance, the worse the precision, the serious artificial influence is caused, and the error is more difficult to control. This also makes building decoration difficult to bim (building information modeling) because the actual building data are all wrong with the drawing, for example, the wall surface on the drawing is flat, such as a line, but in the actual building, the wall surface is not flat, and the distance of each point on the surface may be different. So that the current architectural decoration design drawing and the data in the construction design have errors.
In the traditional architectural decoration process, the part of leveling work is completed in the construction process, which further aggravates the artificial inexhaustibility. Firstly, the process and difficulty are increased for construction, and the construction time is prolonged; secondly, the construction quality is difficult to control. Firstly, workers contact the building for the first time, only building drawings are used instead of real data, the house needs to be measured again, line is paid out, carelessness and omission are avoided, the technology of each worker is different, leveling is a foundation, and even the whole building decoration effect can be influenced, so that unevenness is caused. Namely, the vertical can not be vertical, the straight line is not straight, the success rate of acceptance check is reduced, the reworking is easy, the delivery time is delayed, and the great waste of people, property and materials is brought.
The existing flow can only level the part of work and put the work into construction, so the BIM policy requirement can not be met.
The leveling work is delayed in the construction stage, and a lot of building materials, especially customized products, can only be measured and purchased after the construction leveling is finished, so that the decoration time is prolonged. It also makes the materials trader very passive, tired of coping with delivery time, unable to realize zero stock management, customized as required.
Accordingly, the prior art is yet to be improved and developed.
Disclosure of Invention
In view of the defects of the prior art, the invention aims to provide a method, a device and a storage device for realizing three-dimensional building entity space leveling, and aims to solve the defects that in the prior art, the leveling work of a building decoration process is finished in construction, so that the process and the difficulty are increased for the construction, the construction time is prolonged, and the construction quality is difficult to control.
The technical scheme of the invention is as follows:
a three-dimensional building entity space leveling realization method comprises the following steps:
A. acquiring point cloud data inside a building through laser point cloud three-dimensional scanning automation equipment;
B. carrying out noise processing on the point cloud data according to a conditional adjustment algorithm, and filtering redundant observed quantities in the point cloud data to obtain point cloud data subjected to primary noise reduction;
C. selecting at least three points included in the point cloud data subjected to primary noise reduction, and fitting the plane according to a least square method to obtain a point cloud fitting plane;
D. performing optimal surface fitting according to the point cloud fitting plane to form a reference surface;
E. and obtaining maximum fitting surface data according to the maximum point fitting surface or the minimum point fitting surface of the reference surface, and calculating to obtain the leveling volume according to the maximum fitting surface data.
The method for realizing the spatial leveling of the three-dimensional building entity comprises the following steps:
b1, establishing a function model AV + W ═ O and a random model D ═ O0 2Q＝0 2P-1(ii) a Wherein,0 2representing the unit weight variance, Q representing the observation covariance matrix, and P representing the observation weight;
b2, obtaining function VTAnd PV is the V value in min, and the point cloud data after the primary noise reduction is obtained according to the V value.
The method for realizing the spatial leveling of the three-dimensional building entity comprises the following steps:
c1, selecting at least three points (x) included in the point cloud data after the primary noise reductioni,yi,zi) Wherein i is 0,1, …, n-1, and n is not less than 3;
c2, according to (x)i,yi,zi) Obtaining a point cloud fitting plane by least square fitting
C3, obtaining a point cloud fitting planeA when S takes minimum value0,a1,a2Wherein z is a0x+a1y+a2。
And C, setting the optimal fitting surface offset parameter to be 1000mm when fitting the plane according to the least square method in the step C.
The method for realizing the spatial leveling of the three-dimensional building entity comprises the step of measuring the height of the three-dimensional building entity, wherein the leveling volume in the step E is the product of an individual surface and the height, and the height is the maximum distance from the projection to the normal direction.
The utility model provides a three-dimensional building entity space realization device that makes level, wherein, three-dimensional building entity space realization device includes: a processor adapted to implement instructions; a storage device adapted to store a plurality of instructions; the storage device and the processor are connected by a communication bus; the instructions are adapted to be loaded and executed by a processor to:
acquiring point cloud data inside a building through laser point cloud three-dimensional scanning automation equipment;
carrying out noise processing on the point cloud data according to a conditional adjustment algorithm, and filtering redundant observed quantities in the point cloud data to obtain point cloud data subjected to primary noise reduction;
selecting at least three points included in the point cloud data subjected to primary noise reduction, and fitting the plane according to a least square method to obtain a point cloud fitting plane;
performing optimal surface fitting according to the point cloud fitting plane to form a reference surface;
and obtaining maximum fitting surface data according to the maximum point fitting surface or the minimum point fitting surface of the reference surface, and calculating to obtain the leveling volume according to the maximum fitting surface data.
The device for realizing the spatial leveling of the three-dimensional building entity is characterized in that in the step of carrying out noise processing on the point cloud data according to a conditional adjustment algorithm, filtering redundant observed quantities in the point cloud data and obtaining point cloud data after primary noise reduction, the processor is further used for executing the instruction so as to realize the following steps:
establishing a function model AV + W ═ O and a random model D ═ O0 2Q＝0 2P-1(ii) a Wherein,0 2representing the unit weight variance, Q representing the observation covariance matrix, and P representing the observation weight;
obtaining a function VTAnd PV is the V value in min, and the point cloud data after the primary noise reduction is obtained according to the V value.
The device for realizing space leveling of the three-dimensional building entity is characterized in that at least three points included in the point cloud data after the primary noise reduction are selected, and in the step of fitting a plane according to a least square method to obtain a point cloud fitting plane, the processor is further used for executing the instruction to realize the following steps:
selecting at least three points (x) included in the point cloud data after primary noise reductioni,yi,zi) Wherein i is 0,1, …, n-1, and n is not less than 3;
according to (x)i,yi,zi) Obtaining a point cloud fitting plane by least square fitting
Obtaining a point cloud fitting planeA when S takes minimum value0,a1,a2Wherein z is a0x+a1y+a2。
The device for realizing the spatial leveling of the three-dimensional building entity is characterized in that at least three points included in the point cloud data after the primary noise reduction are selected, and the optimal fitting surface offset parameter is set to be 1000mm when the plane is fitted according to the least square method in the step of fitting the plane according to the least square method to obtain the point cloud fitting plane.
A storage device, wherein a plurality of instructions are stored, said instructions being adapted to be loaded by a processor and to perform the steps of said method for achieving spatial leveling of a three-dimensional construction entity.
The invention provides a method, a device and storage equipment for realizing three-dimensional building entity space leveling, wherein the method comprises the following steps: acquiring point cloud data inside a building through laser point cloud three-dimensional scanning automation equipment; carrying out noise processing on the point cloud data according to a conditional adjustment algorithm, and filtering redundant observed quantities in the point cloud data to obtain point cloud data subjected to primary noise reduction; selecting at least three points included in the point cloud data subjected to primary noise reduction, and fitting the plane according to a least square method to obtain a point cloud fitting plane; performing optimal surface fitting according to the point cloud fitting plane to form a reference surface; and obtaining maximum fitting surface data according to the maximum point fitting surface or the minimum point fitting surface of the reference surface, and calculating to obtain the leveling volume according to the maximum fitting surface data. The invention realizes the completion of leveling work in the design stage, on one hand, the construction is accurately guided, the blanking can be accurately carried out, and the high-quality decoration is completed; on the other hand acquires accurate data, corrects the existing drawing data, can calculate required building material accurately, shortens man-hour, accurate unloading.
Drawings
Fig. 1 is a flowchart of a preferred embodiment of the method for implementing spatial leveling of a three-dimensional building entity according to the present invention.
Fig. 2 is a room cloud of the three-dimensional building physical space of the present invention.
FIG. 3 is a diagram of the leveling volume of the three-dimensional building solid space according to the present invention.
Detailed Description
The invention provides a method, a device and storage equipment for realizing three-dimensional building entity space leveling, and the invention is further described in detail below in order to make the purpose, technical scheme and effect of the invention clearer and clearer. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Please refer to fig. 1, which is a flowchart illustrating a method for implementing spatial leveling of a three-dimensional building entity according to a preferred embodiment of the present invention. As shown in fig. 1, the method for implementing spatial leveling of the three-dimensional building entity comprises the following steps:
s100, acquiring point cloud data inside a building through laser point cloud three-dimensional scanning automation equipment;
s200, carrying out noise processing on the point cloud data according to a conditional adjustment algorithm, and filtering redundant observed quantities in the point cloud data to obtain point cloud data subjected to primary noise reduction;
s300, selecting at least three points included in the point cloud data subjected to primary noise reduction, and fitting a plane according to a least square method to obtain a point cloud fitting plane;
s400, performing optimal surface fitting according to the point cloud fitting plane to form a reference surface;
and S500, obtaining maximum fitting surface data according to the highest point fitting surface or the lowest point fitting surface of the reference surface, and calculating to obtain the leveling volume according to the maximum fitting surface data.
In the embodiment of the invention, point cloud data in a building are obtained through laser point cloud three-dimensional scanning automation equipment; then applying a conditional adjustment algorithm to filter redundant observed quantities, and carrying out noise processing to resist the influence of noise points; then, the least square method is applied to plane fitting to the point cloud data to resist the influence of noise points, three points are applied to determine a plane, and the method comprises the steps of establishing a space grid to filter point clouds, reserving point cloud data in a specified range and the like; performing optimal surface fitting on the point cloud fitting plane to form a reference surface, wherein the optimal point is based on the fitting surface, has a surface, and finds out the point with the farthest opposite surface; the fitting plane passes through the highest point to form a highest point fitting surface; the fitting plane passes through the lowest point to form a lowest point fitting surface; and (4) according to different positions, taking the data of the most fitting surface and calculating the leveling volume. The individual surface is the fitting surface, the leveling volume can be obtained by using a conventional algorithm, namely, the volume is equal to the individual surface, the height is large (the maximum distance from the projection to the normal direction), the leveling error can be controlled within 0.5mm, the artificial influence is avoided, and the method is very accurate.
Preferably, in the method for implementing spatial leveling of a three-dimensional building entity, the step S200 specifically includes:
step S201, building a function model AV + W ═ O and a random model D ═ O0 2Q＝0 2P-1(ii) a Wherein,0 2
representing the unit weight variance, Q representing the observation covariance matrix, and P representing the observation weight;
step S202, acquiring function VTAnd PV is the V value in min, and the point cloud data after the primary noise reduction is obtained according to the V value.
Preferably, in the method for implementing spatial leveling of a three-dimensional building entity, the step S300 specifically includes:
s301, selecting at least three points (x) included in the point cloud data after primary noise reductioni,yi,zi) Wherein i is 0,1, …, n-1, and n is not less than 3;
step S302, according to (x)i,yi,zi) Obtaining a point cloud fitting plane by least square fitting
Step (ii) ofS303, obtaining a point cloud fitting planeA when S takes minimum value0,a1,a2Wherein z is a0x+a1y+a2。
Preferably, in the method for implementing spatial leveling of a three-dimensional building entity, the optimal fitting plane offset parameter is set to be 1000mm when the plane is fitted according to the least square method in step S300.
Preferably, in the method for implementing spatial leveling of a three-dimensional building entity, the leveling volume in step S500 is the product of an individual surface and a height, where the height is the maximum distance projected to the normal direction.
In order to more clearly understand the technical solution of the present invention, the following description is provided by a specific embodiment.
1. Importing certain room point cloud data acquired by a three-dimensional laser scanner into MP software, and manually deleting some noise point clouds (some point cloud data need manual deletion under manual judgment) by using a related filtering tool to obtain 4528754 pieces of related point cloud data, wherein the room point clouds are shown in FIG. 2;
2. the best fitting surface tool is utilized to realize the leveling function of the best fitting surface, and the maximum point distance of the leveling parameter is set to be 0.2mm to obtain the best fitting surface;
3. setting a maximum point distance parameter by using a tool for extracting the highest point fitting surface and the lowest point fitting surface to obtain a highest point fitting surface and a lowest point fitting surface;
4. the volume calculation tool selects one of the fitting surfaces and then sets the offset parameter of the fitting surface to obtain the volume, the optimal fitting surface is selected and the offset parameter is set to be 1000mm, and the obtained leveling volume is shown in fig. 3.
Therefore, the invention follows bim concept and finishes leveling work in the design stage. On one hand, the construction is accurately guided, the material can be accurately discharged, and the high-quality decoration is finished; on the one hand, accurate data are obtained, the existing drawing data are corrected, the required building materials can be accurately calculated, and home products are customized with manufacturers in advance. The working hours are shortened, the material is accurately discharged, and the visible and ready-to-use results of building decoration are really realized.
Based on the method embodiment, the invention also provides a device for realizing the spatial leveling of the three-dimensional building entity. The three-dimensional building entity space leveling realization device comprises: a processor adapted to implement instructions; a storage device adapted to store a plurality of instructions; the storage device and the processor are connected by a communication bus; the instructions are adapted to be loaded and executed by a processor to:
acquiring point cloud data inside a building through laser point cloud three-dimensional scanning automation equipment;
carrying out noise processing on the point cloud data according to a conditional adjustment algorithm, and filtering redundant observed quantities in the point cloud data to obtain point cloud data subjected to primary noise reduction;
selecting at least three points included in the point cloud data subjected to primary noise reduction, and fitting the plane according to a least square method to obtain a point cloud fitting plane;
performing optimal surface fitting according to the point cloud fitting plane to form a reference surface;
and obtaining maximum fitting surface data according to the maximum point fitting surface or the minimum point fitting surface of the reference surface, and calculating to obtain the leveling volume according to the maximum fitting surface data.
The device for realizing the spatial leveling of the three-dimensional building entity is characterized in that in the step of carrying out noise processing on the point cloud data according to a conditional adjustment algorithm, filtering redundant observed quantities in the point cloud data and obtaining point cloud data after primary noise reduction, the processor is further used for executing the instruction so as to realize the following steps:
establishing a function model AV + W ═ O and a random model D ═ O0 2Q＝0 2P-1(ii) a Wherein,0 2representing the unit weight variance, Q representing the observation covariance matrix, and P representing the observation weight;
obtaining a function VTAnd PV is the V value in min, and the point cloud data after the primary noise reduction is obtained according to the V value.
The device for realizing space leveling of the three-dimensional building entity is characterized in that at least three points included in the point cloud data after the primary noise reduction are selected, and in the step of fitting a plane according to a least square method to obtain a point cloud fitting plane, the processor is further used for executing the instruction to realize the following steps:
selecting at least three points (x) included in the point cloud data after primary noise reductioni,yi,zi) Wherein i is 0,1, …, n-1, and n is not less than 3;
according to (x)i,yi,zi) Obtaining a point cloud fitting plane by least square fitting
Obtaining a point cloud fitting planeA when S takes minimum value0,a1,a2Wherein z is a0x+a1y+a2。
The device for realizing the spatial leveling of the three-dimensional building entity is characterized in that at least three points included in the point cloud data after the primary noise reduction are selected, and the optimal fitting surface offset parameter is set to be 1000mm when the plane is fitted according to the least square method in the step of fitting the plane according to the least square method to obtain the point cloud fitting plane.
Based on the above method embodiment, the present invention further provides a storage device, wherein a plurality of instructions are stored in the storage device, and the instructions are suitable for being loaded by a processor and executing the steps of the three-dimensional building entity space leveling implementation method.
In summary, the method, the apparatus and the storage device for realizing the spatial leveling of the three-dimensional building entity provided by the present invention comprise: acquiring point cloud data inside a building through laser point cloud three-dimensional scanning automation equipment; carrying out noise processing on the point cloud data according to a conditional adjustment algorithm, and filtering redundant observed quantities in the point cloud data to obtain point cloud data subjected to primary noise reduction; selecting at least three points included in the point cloud data subjected to primary noise reduction, and fitting the plane according to a least square method to obtain a point cloud fitting plane; performing optimal surface fitting according to the point cloud fitting plane to form a reference surface; and obtaining maximum fitting surface data according to the maximum point fitting surface or the minimum point fitting surface of the reference surface, and calculating to obtain the leveling volume according to the maximum fitting surface data. The invention realizes the completion of leveling work in the design stage, on one hand, the construction is accurately guided, the blanking can be accurately carried out, and the high-quality decoration is completed; on the other hand acquires accurate data, corrects the existing drawing data, can calculate required building material accurately, shortens man-hour, accurate unloading.
It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.
Claims (10)
1. A three-dimensional building entity space leveling realization method is characterized by comprising the following steps:
A. acquiring point cloud data inside a building through laser point cloud three-dimensional scanning automation equipment;
B. carrying out noise processing on the point cloud data according to a conditional adjustment algorithm, and filtering redundant observed quantities in the point cloud data to obtain point cloud data subjected to primary noise reduction;
C. selecting at least three points included in the point cloud data subjected to primary noise reduction, and fitting the plane according to a least square method to obtain a point cloud fitting plane;
D. performing optimal surface fitting according to the point cloud fitting plane to form a reference surface;
E. and obtaining maximum fitting surface data according to the maximum point fitting surface or the minimum point fitting surface of the reference surface, and calculating to obtain the leveling volume according to the maximum fitting surface data.
2. The method for realizing the spatial leveling of the three-dimensional building entity according to claim 1, wherein the step B specifically comprises:
b1, establishing a function model AV + W ═ O and a random modelWherein,0 2the variance of the unit weight is represented,representing an observation value covariance matrix, wherein P represents an observation value weight;
b2, obtaining function VTAnd PV is the V value in min, and the point cloud data after the primary noise reduction is obtained according to the V value.
3. The method for realizing the spatial leveling of the three-dimensional building entity according to claim 1, wherein the step C specifically comprises:
c1, selecting at least three points (x) included in the point cloud data after the primary noise reductioni,yi,zi) Wherein i is 0,1, …, n-1, and n is not less than 3;
c2, according to (x)i,yi,zi) Obtaining a point cloud fitting plane by least square fitting
C3, obtaining a point cloud fitting planeMiddle S is minimumA at value0,a1,a2Wherein z is a0x+a1y+a2。
4. The method for realizing the spatial leveling of the three-dimensional building entity according to claim 1, wherein the optimal fitting plane offset parameter is set to be 1000mm when the plane is fitted according to the least square method in the step C.
5. The method for realizing the spatial leveling of the three-dimensional building entity according to claim 1, wherein the leveling volume in the step E is the product of an individual surface and a height, wherein the height is the maximum distance projected to the normal direction.
6. The utility model provides a three-dimensional building entity space realization device that makes level which characterized in that, three-dimensional building entity space realization device that makes level includes: a processor adapted to implement instructions; a storage device adapted to store a plurality of instructions; the storage device and the processor are connected by a communication bus; the instructions are adapted to be loaded and executed by a processor to:
acquiring point cloud data inside a building through laser point cloud three-dimensional scanning automation equipment;
carrying out noise processing on the point cloud data according to a conditional adjustment algorithm, and filtering redundant observed quantities in the point cloud data to obtain point cloud data subjected to primary noise reduction;
selecting at least three points included in the point cloud data subjected to primary noise reduction, and fitting the plane according to a least square method to obtain a point cloud fitting plane;
performing optimal surface fitting according to the point cloud fitting plane to form a reference surface;
and obtaining maximum fitting surface data according to the maximum point fitting surface or the minimum point fitting surface of the reference surface, and calculating to obtain the leveling volume according to the maximum fitting surface data.
7. The three-dimensional building entity space leveling implementation device of claim 6, wherein in the step of performing noise processing on the point cloud data according to a conditional adjustment algorithm, filtering redundant observed quantities in the point cloud data, and obtaining point cloud data after primary noise reduction, the processor is further configured to execute the instructions to implement the following steps:
establishing a function model AV + W ═ O and a random modelWherein,0 2the variance of the unit weight is represented,representing an observation value covariance matrix, wherein P represents an observation value weight;
obtaining a function VTAnd PV is the V value in min, and the point cloud data after the primary noise reduction is obtained according to the V value.
8. The three-dimensional building entity space leveling implementation device of claim 6, wherein in the step of selecting at least three points included in the point cloud data after the initial noise reduction and fitting a plane according to a least square method to obtain a point cloud fitting plane, the processor is further configured to execute the instructions to implement the following steps:
selecting at least three points (x) included in the point cloud data after primary noise reductioni,yi,zi) Wherein i is 0,1, …, n-1, and n is not less than 3;
according to (x)i,yi,zi) Obtaining a point cloud fitting plane by least square fitting
Obtaining a point cloud fitting planeA when S takes minimum value0,a1,a2Wherein z is a0x+a1y+a2。
9. The three-dimensional building entity space leveling realization device according to claim 6, wherein the selection of the at least three points included in the point cloud data after the initial noise reduction, the fitting of the plane according to the least square method to obtain the point cloud fitting plane, and the setting of the best fitting plane offset parameter to be 1000mm when the plane is fitted according to the least square method in the step of fitting the plane according to the least square method.
10. A storage device storing a plurality of instructions adapted to be loaded by a processor and to perform the steps of the method for achieving spatial leveling of a three-dimensional construction entity according to any one of claims 1 to 5.
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| CN116128886A (en) * | 2023-04-18 | 2023-05-16 | 深圳市其域创新科技有限公司 | Point cloud data segmentation method and device, electronic equipment and storage medium |
| CN116226951A (en) * | 2022-12-05 | 2023-06-06 | 中山市可讯科技有限公司 | Novel online plane measurement method and application thereof |
| CN117648750A (en) * | 2024-01-25 | 2024-03-05 | 上海盎维信息技术有限公司 | Automatic regulation method for space decoration finished surface size based on measured data |
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