CN116720302B - Implementation method for rapidly designing sewage pipeline scheme - Google Patents
Implementation method for rapidly designing sewage pipeline scheme Download PDFInfo
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- CN116720302B CN116720302B CN202311005921.2A CN202311005921A CN116720302B CN 116720302 B CN116720302 B CN 116720302B CN 202311005921 A CN202311005921 A CN 202311005921A CN 116720302 B CN116720302 B CN 116720302B
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- 238000000034 method Methods 0.000 title claims abstract description 22
- 239000010865 sewage Substances 0.000 title claims abstract description 14
- 238000013507 mapping Methods 0.000 claims abstract description 34
- 238000012545 processing Methods 0.000 claims abstract description 8
- 238000000605 extraction Methods 0.000 claims abstract description 6
- 230000011218 segmentation Effects 0.000 claims abstract description 5
- 238000013461 design Methods 0.000 claims description 13
- 238000010586 diagram Methods 0.000 claims description 7
- 238000001914 filtration Methods 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000010276 construction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000000059 patterning Methods 0.000 description 1
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- 238000012876 topography Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/18—Network design, e.g. design based on topological or interconnect aspects of utility systems, piping, heating ventilation air conditioning [HVAC] or cabling
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- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A10/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE at coastal zones; at river basins
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Abstract
The invention relates to the field of electric digital data processing, in particular to an implementation method for rapidly designing a sewage pipeline scheme. The method comprises the following steps: s1, acquiring aerial data of a target area, wherein the aerial data comprise a top view image of the target area; s2, constructing a model, namely constructing a primary model with elevation information of a target area according to aerial data; s3, skeleton extraction, namely carrying out segmentation treatment on the primary model according to different elevation information, and simplifying and abstracting treatment results to form a skeleton model; s4, regional mapping, namely extracting intersection information in the skeleton model, carrying out centering treatment on the parts except the skeleton model in the primary model, and mapping the result after the centering treatment into the skeleton model to form mapping information; the combination of the intersection point information and the mapping information forms a graphical model; s5, pipe network generation, combining intersection point information and mapping information, and calling a single-source shortest path algorithm to generate a directed line graph for communicating the intersection point information and the mapping information, so as to form a final pipe network scheme.
Description
Technical Field
The invention relates to the field of electric digital data processing, in particular to an implementation method for rapidly designing a sewage pipeline scheme.
Background
In recent years, with the development of unmanned aerial vehicle aerial photography technology, image data is formed by unmanned aerial vehicle aerial photography modeling, and multi-scene and multi-dimensional application becomes a mainstream technology and also gradually becomes an important tool and means for rural and urban construction. In sewage treatment pipeline design, considerable technical means and research experience are provided for urban pipeline analysis, but related pipeline design technology in rural areas still needs to be manually planned by a design institute unit according to graphic data at present, so that the design period is long, the cost is high, and time and labor are wasted.
Disclosure of Invention
The invention aims at: the implementation method for rapidly designing the sewage pipeline scheme is provided, so that the problems of long design period, high cost, time and labor waste of pipelines related to rural areas in the prior art are solved.
The technical scheme of the invention is as follows: an implementation method for rapidly designing a sewage pipeline scheme, comprising the following steps:
s1, acquiring aerial data of a target area, wherein the aerial data comprise a top view image of the target area;
s2, constructing a model, namely constructing a primary model with elevation information of a target area according to aerial data;
s3, skeleton extraction, namely carrying out segmentation treatment on the primary model according to different elevation information, and simplifying and abstracting treatment results to form a skeleton model;
s4, regional mapping, namely extracting intersection information in the skeleton model, carrying out centering treatment on the parts except the skeleton model in the primary model, and mapping the result after the centering treatment into the skeleton model to form mapping information; the combination of the intersection point information and the mapping information forms a graphical model;
s5, pipe network generation, combining intersection point information and mapping information, and calling a single-source shortest path algorithm to generate a directed line graph for communicating the intersection point information and the mapping information, so as to form a final pipe network scheme.
Preferably, the primary model is provided with a plurality of pixel groups including a first pixel group and a second pixel group and a third pixel group, and any of the pixel groups has the same or similar elevation information.
Preferably, the skeleton extraction includes the steps of:
s3.1, extracting a first pixel group, and performing binarization processing on the first pixel group;
s3.2, judging the neighborhood relation and geometric characteristics of any pixel in the first pixel group, and reserving or filtering the corresponding pixel according to the judging result; and the model formed by the retained pixels is set as a skeleton model.
Preferably, the region patterning includes the steps of:
s4.1, extracting a second pixel group, and carrying out centering treatment on the second pixel group to form a plurality of discrete center pixels;
s4.2, constructing a connecting line with the shortest distance between any central pixel and the skeleton model, wherein the intersection point of the connecting line and the skeleton model is set as a mapping point of the central pixel on the skeleton model;
s4.3, setting pixels with more than two adjacent pixels in the skeleton model as crossing points of the skeleton model;
and S4.4, reserving the mapping points and the crossing points, and deleting other pixels to form a graphical model.
Preferably, the pipe network generation includes the following steps:
s5.1, determining a third pixel group in the primary model, wherein the third pixel group comprises a round or rectangular area formed by closely arranging a certain number of pixels with the same elevation information, and setting the area as an area where a sewage treatment base station is located;
s5.2, taking the area as a starting point, and generating the shortest directed line leading to the adjacent mapping point or the cross point;
s5.3, forming a directional diagram passing through all the mapping points and the crossing points sequentially by adopting the same method to form a final pipe network scheme.
Preferably, in the step S5.1, the third pixel group has a lower elevation than the first pixel group and the second pixel group.
Compared with the prior art, the invention has the advantages that: according to the aerial photographing data of the unmanned aerial vehicle, a primary model, a skeleton model and a graphical model are sequentially built, so that a final pipe network design scheme is generated, rural sewage pipeline design is rapidly completed, and a large amount of time, manpower and material resources are saved.
Drawings
The invention is further described below with reference to the accompanying drawings and examples:
FIG. 1 is a flow chart of a method for implementing a rapid design sewer line scheme according to the present invention;
FIG. 2 is a schematic diagram of a primary model according to the present invention;
FIG. 3 is a schematic diagram illustrating the binarization of the first pixel group according to the present invention;
FIG. 4 is a schematic diagram of a skeletal model in accordance with the present invention;
FIG. 5 is a schematic diagram of a graphical model according to the present invention;
FIG. 6 is a schematic diagram of a piping network according to the present invention;
Detailed Description
The following describes the present invention in further detail with reference to specific examples:
as shown in fig. 1, a method for implementing a rapid design sewage pipeline scheme includes the following steps:
s1, acquiring aerial photographing data of a rural target area through an unmanned aerial vehicle or other high-altitude photographing equipment, wherein the aerial photographing data comprise overlooking images of the target area.
S2, as shown in FIG. 2, performing elevation analysis on the top view image, and establishing a primary model according to the elevation analysis, wherein the method comprises the following steps:
s2.1, carrying out pixel segmentation on the terrain, and judging the height of each pixel.
S2.2, judging whether the heights of the two adjacent pixels are the same, if so, judging the same terrain, and if not, judging the different terrains.
S2.3, determining the topography of each pixel.
S2.4, determining the prediction loss of each pixel.
S2.5, loss returns and parameter updating.
Wherein the primary model comprises a first group of pixels representing a road and a second group of pixels representing a building, and a third group of pixels.
S3, skeleton extraction, namely carrying out segmentation processing on the primary model according to different elevation information, and simplifying and abstracting a processing result to form a skeleton model. The method comprises the following steps:
s3.1, as shown in FIG. 3, extracting a first pixel group representing the road from the primary model, and performing binarization processing on the first pixel group.
S3.2, as shown in FIG. 4, judging the neighborhood relation and geometric characteristics of any pixel in the first pixel group according to the Hilditch algorithm, and reserving or filtering the corresponding pixel according to the judging result, so that redundant information is reduced as much as possible while the shape accuracy of the object is maintained. And the model formed by the pixels such as the axis\circle center and the like which are finally reserved by the primary model is set as a skeleton model.
Specifically, the pixel currently being processed is set to p0, and a matrix is constructed that includes eight neighbors p1-p8 of p0 centered on p 0.
Setting b [ i ] =1 (i=0 …) to represent the pixel values of eight neighborhoods, wherein if the pixel value is 255 in the algorithm process, b [ i ] =1; if the pixel value is 0, b [ i ] =0; the pixel value is 128, which indicates that the pixel point is marked as a pixel to be deleted in the last traversal, and b [ i ] = -1; each point of the image is traversed, and the current pixel is set as the pixel to be deleted when the following six conditions are simultaneously satisfied.
Condition one: the pixel value of p0 is 255 (b [0] =1), i.e., the current pixel is the foreground point.
Condition II: the pixel value of the p0 axial neighborhood is not all 255 (at least one of b1, b3, b 5, b 7 is equal to 0), i.e. the current pixel is the boundary point.
And (3) a third condition: at least two of the eight neighbors of p0 have pixel values of 255, i.e., the current pixel is neither an endpoint nor an outlier.
Condition four: at least one of the eight neighbors of p0 that are not marked as pixels to be removed and have a pixel value of 255, i.e., after deleting the pixel to be deleted, the current pixel becomes an outlier.
Condition five: the eight neighborhood connections of p0 are 1, i.e., nc (p) =1.
Condition six: if p1 and p3 have been marked as pixels to be deleted, the eight neighborhood join numbers are recalculated with values b1=0 and b3=0 and are to be equal to 1, respectively.
S4, regional mapping refers to converting the whole village into a graph consisting of points and edges. Wherein the top point in the figure represents the intersection of the road or the access point of the house and the road, the access point of the house and the road represents the intersection of the road and the connecting line between the house and the road nearest to the house, the node is used as the mapping of the house on the road, and the side between the points in the figure refers to the geographical curve distance between the two points. The method comprises the following steps:
s4.1, as shown in FIG. 5, any isolated unit in the second pixel group is subjected to centering processing to form a discrete center pixel corresponding to any house. And extracting intersection points in the skeleton model, namely intersection points of roads.
S4.2, constructing a connecting line with the shortest distance between any central pixel and the skeleton model, wherein the intersection point of the connecting line and the skeleton model is set as a mapping point of the central pixel on the skeleton model.
And S4.3, if any pixel in the skeleton model has two or more neighborhood pixels with the pixel value of 255, setting the pixel as an intersection of the skeleton model.
And S4.4, reserving the mapping points and the crossing points, and deleting other pixels to form a graphical model.
S5, pipe network generation, as shown in FIG. 6, combining intersection information and mapping information, and calling a single-source shortest path algorithm to generate a directed line graph for communicating the intersection information and the mapping information, so as to form a final pipe network scheme. The method specifically comprises the following steps:
s5.1, determining a third pixel group in the primary model, wherein the third pixel group comprises a circular or rectangular area formed by closely arranging a certain number of pixels with the same height information, and the area represents a flat open area, so that the area is set as an area where a sewage treatment base station is located; in addition, the area has a lower elevation than rivers and buildings, thereby facilitating the collection of sewage.
S5.2, taking the area where the sewage treatment base station is located as a starting point, adopting Dijkstra algorithm, recording the current shortest distance from the starting point to each vertex by using a distance array, and selecting the nearest vertex which is not visited in each step for expansion, and updating the distance array. By repeating this process until all vertices have been visited, the shortest path from the origin to each vertex is obtained. Thereby generating the shortest directed line to the adjacent mapped point or intersection.
S5.3, sequentially forming a directional line graph passing through all the mapping points and the crossing points by adopting the same method, wherein the direction from one vertex to the other vertex in the directional line graph is the same as the flow direction of the pipe network. Subsequently, the unit shortest algorithm is invoked to construct the final pipe network scheme.
The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement the same according to the content of the present invention, and are not intended to limit the scope of the present invention. It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof, and it is therefore desired that the present invention be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (4)
1. A method of implementing a rapid design sewer line scheme, comprising the steps of:
s1, acquiring aerial data of a target area, wherein the aerial data comprise a top view image of the target area;
s2, constructing a model, namely constructing a primary model with elevation information of a target area according to aerial data;
s3, skeleton extraction, namely carrying out segmentation treatment on the primary model according to different elevation information, and simplifying and abstracting treatment results to form a skeleton model;
s4, regional mapping, namely extracting intersection information in the skeleton model, carrying out centering treatment on the parts except the skeleton model in the primary model, and mapping the result after the centering treatment into the skeleton model to form mapping information; the combination of the intersection point information and the mapping information forms a graphical model;
s5, pipe network generation, combining intersection point information and mapping information, and calling a single-source shortest path algorithm to generate a directed graph for communicating the intersection point information and the mapping information, so as to form a final pipe network scheme;
the primary model is provided with a plurality of pixel groups including a first pixel group, a second pixel group and a third pixel group, and any pixel groups have the same or similar elevation information;
the skeleton extraction comprises the following steps:
s3.1, extracting a first pixel group, and performing binarization processing on the first pixel group;
s3.2, judging the neighborhood relation and geometric characteristics of any pixel in the first pixel group, reserving or filtering the corresponding pixel according to the judging result, reducing redundant information as far as possible while maintaining the shape accuracy of the object, and setting a model formed by reserved axial line and/or circle center pixels as a skeleton model.
2. A method of implementing a rapid design sewer line according to claim 1, wherein said region mapping includes the steps of:
s4.1, extracting a second pixel group, and carrying out centering treatment on the second pixel group to form a plurality of discrete center pixels;
s4.2, constructing a connecting line with the shortest distance between any central pixel and the skeleton model, wherein the intersection point of the connecting line and the skeleton model is set as a mapping point of the central pixel on the skeleton model;
s4.3, setting pixels with more than two adjacent pixels in the skeleton model as crossing points of the skeleton model;
and S4.4, reserving the mapping points and the crossing points, and deleting other pixels to form a graphical model.
3. The method of implementing a rapid design sewer line according to claim 2, wherein said network of pipes is formed by the steps of:
s5.1, determining a third pixel group in the primary model, wherein the third pixel group comprises a round or rectangular area formed by closely arranging a certain number of pixels with the same elevation information, and setting the area as an area where a sewage treatment base station is located;
s5.2, taking the area as a starting point, and generating the shortest directed line leading to the adjacent mapping point or the cross point;
s5.3, forming a directional diagram passing through all the mapping points and the crossing points sequentially by adopting the same method to form a final pipe network scheme.
4. A method of implementing a rapid design sewer line according to claim 3, wherein in step S5.1, the third pixel group has a lower elevation than the first pixel group and the second pixel group.
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| CN112801075A (en) * | 2021-04-15 | 2021-05-14 | 速度时空信息科技股份有限公司 | Automatic rural road boundary line extraction method based on aerial image |
| CN113177244A (en) * | 2021-04-15 | 2021-07-27 | 南京业道数据科技有限公司 | BIM model-based urban pipeline arrangement method |
| CN113901558A (en) * | 2021-10-22 | 2022-01-07 | 深圳小库科技有限公司 | Automatic pipeline generation method and system based on AI decision tree and electronic equipment |
| CN115270364A (en) * | 2021-04-29 | 2022-11-01 | 久瓴(江苏)数字智能科技有限公司 | Pipeline cross processing method and device, storage medium and electronic equipment |
| JP2022182359A (en) * | 2021-05-28 | 2022-12-08 | 株式会社日立製作所 | Three-dimensional model generation support system, program, and recording medium |
| CN115587457A (en) * | 2022-10-29 | 2023-01-10 | 中国二十二冶集团有限公司 | Construction method for optimizing urban water supply pipeline based on unmanned aerial vehicle and BIM technology |
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- 2023-08-10 CN CN202311005921.2A patent/CN116720302B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112801075A (en) * | 2021-04-15 | 2021-05-14 | 速度时空信息科技股份有限公司 | Automatic rural road boundary line extraction method based on aerial image |
| CN113177244A (en) * | 2021-04-15 | 2021-07-27 | 南京业道数据科技有限公司 | BIM model-based urban pipeline arrangement method |
| CN115270364A (en) * | 2021-04-29 | 2022-11-01 | 久瓴(江苏)数字智能科技有限公司 | Pipeline cross processing method and device, storage medium and electronic equipment |
| JP2022182359A (en) * | 2021-05-28 | 2022-12-08 | 株式会社日立製作所 | Three-dimensional model generation support system, program, and recording medium |
| CN113901558A (en) * | 2021-10-22 | 2022-01-07 | 深圳小库科技有限公司 | Automatic pipeline generation method and system based on AI decision tree and electronic equipment |
| CN115587457A (en) * | 2022-10-29 | 2023-01-10 | 中国二十二冶集团有限公司 | Construction method for optimizing urban water supply pipeline based on unmanned aerial vehicle and BIM technology |
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