CN117094104A - Overhead survey data section fitting method - Google Patents
Overhead survey data section fitting method Download PDFInfo
- Publication number
- CN117094104A CN117094104A CN202311145246.3A CN202311145246A CN117094104A CN 117094104 A CN117094104 A CN 117094104A CN 202311145246 A CN202311145246 A CN 202311145246A CN 117094104 A CN117094104 A CN 117094104A
- Authority
- CN
- China
- Prior art keywords
- pipeline
- data
- fitting
- determining
- topography
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 54
- 239000002689 soil Substances 0.000 claims abstract description 58
- 238000012876 topography Methods 0.000 claims abstract description 47
- 239000000463 material Substances 0.000 claims abstract description 43
- 238000012423 maintenance Methods 0.000 claims abstract description 33
- 238000011835 investigation Methods 0.000 claims abstract description 6
- 238000004088 simulation Methods 0.000 claims description 27
- 238000005516 engineering process Methods 0.000 claims description 11
- 238000009499 grossing Methods 0.000 claims description 9
- 238000012795 verification Methods 0.000 claims description 7
- 238000000611 regression analysis Methods 0.000 claims description 4
- 230000000007 visual effect Effects 0.000 claims description 4
- 230000003993 interaction Effects 0.000 claims 1
- 238000012216 screening Methods 0.000 claims 1
- 238000004458 analytical method Methods 0.000 description 10
- 238000004422 calculation algorithm Methods 0.000 description 10
- 238000013461 design Methods 0.000 description 10
- XEEYBQQBJWHFJM-UHFFFAOYSA-N Iron Chemical compound [Fe] XEEYBQQBJWHFJM-UHFFFAOYSA-N 0.000 description 8
- 238000004364 calculation method Methods 0.000 description 7
- 239000004927 clay Substances 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 231100000817 safety factor Toxicity 0.000 description 5
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 5
- 229910000831 Steel Inorganic materials 0.000 description 4
- 239000003086 colorant Substances 0.000 description 4
- 230000007547 defect Effects 0.000 description 4
- 239000003673 groundwater Substances 0.000 description 4
- 230000006872 improvement Effects 0.000 description 4
- 229910052742 iron Inorganic materials 0.000 description 4
- 239000010959 steel Substances 0.000 description 4
- 238000013079 data visualisation Methods 0.000 description 3
- 230000001419 dependent effect Effects 0.000 description 3
- 230000002452 interceptive effect Effects 0.000 description 3
- 239000004033 plastic Substances 0.000 description 3
- 229920003023 plastic Polymers 0.000 description 3
- 231100000279 safety data Toxicity 0.000 description 3
- 239000004576 sand Substances 0.000 description 3
- 238000012732 spatial analysis Methods 0.000 description 3
- RYGMFSIKBFXOCR-UHFFFAOYSA-N Copper Chemical compound [Cu] RYGMFSIKBFXOCR-UHFFFAOYSA-N 0.000 description 2
- 229910052802 copper Inorganic materials 0.000 description 2
- 239000010949 copper Substances 0.000 description 2
- VNWKTOKETHGBQD-UHFFFAOYSA-N methane Chemical compound C VNWKTOKETHGBQD-UHFFFAOYSA-N 0.000 description 2
- 238000007781 pre-processing Methods 0.000 description 2
- 230000009466 transformation Effects 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000007667 floating Methods 0.000 description 1
- 230000004907 flux Effects 0.000 description 1
- 238000009440 infrastructure construction Methods 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 239000003345 natural gas Substances 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
Classifications
-
- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/28—Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/10—Numerical modelling
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/08—Fluids
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/14—Pipes
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Mathematical Physics (AREA)
- Computational Mathematics (AREA)
- Data Mining & Analysis (AREA)
- Geometry (AREA)
- General Engineering & Computer Science (AREA)
- Evolutionary Computation (AREA)
- Algebra (AREA)
- Computer Hardware Design (AREA)
- Bioinformatics & Computational Biology (AREA)
- Computer Networks & Wireless Communication (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Fluid Mechanics (AREA)
- Computing Systems (AREA)
- Evolutionary Biology (AREA)
- Operations Research (AREA)
- Probability & Statistics with Applications (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application provides a method for fitting an overhead survey data section, which comprises the following steps: acquiring coordinates, pipeline elevation, pipeline diameter and material properties of a pipeline starting point, a pipeline ending point and a middle node according to the central line data of the electric power pipeline; acquiring a starting point, an ending point and a fitting range of a region around which a pipeline can be further arranged according to the pipeline plane section data; judging a pipeline laying mode according to the topography, the topography and the soil conditions, and predicting a windage yaw line formed by the pipeline; fitting the pipe diameters according to the relationship among the windage yaw line, the pipe diameters and the soil property, and determining pipe diameter selection; determining the diffusivity association of the pipeline according to the pipeline layout mode and the pipeline attribute data, and judging whether the space around the pipeline is further expanded or not; and forming investigation and digital elevation files to display pipeline conditions according to the service life and maintenance cost attributes of the pipeline, and performing key highlighting.
Description
Technical Field
The application relates to the technical field of information, in particular to a method for fitting an overhead survey data section.
Background
With the acceleration of the urban process and the continuous advancement of infrastructure construction, pipeline layout demands are increasing. However, there are some problems in the conventional pipeline layout method. Firstly, the lack of comprehensive pipeline center line data leads to the failure to accurately acquire key information such as coordinate data of a starting point, an ending point and an intermediate node in the layout process. Secondly, the existing method is not accurate enough for processing the fitting flat section data of the pipeline, and the starting point, the finishing point and the fitting range of the area around the pipeline for further arrangement of the pipeline are difficult to obtain. In addition, when the existing method considers the pipeline laying mode, the factors such as topography, landform, soil conditions and the like cannot be fully utilized, so that the layout result is not scientific and reasonable enough. Meanwhile, when the bearing capacity of the pipeline and the pipeline flux requirement are fitted, the wind deflection line formed by the pipeline cannot be accurately predicted, and due to different terrains, pipeline laying comprises overground and underground, the supporting mode of an overground pipeline cannot be adjusted according to the result of the wind deflection line, the structure resisting wind force is increased, the rigidity of the overground pipeline is increased, and the like, so that the defect that the pipe diameter selection is unreasonable due to deformation of the pipeline is overcome. Finally, existing methods fail to fully consider whether there is sufficient space around the pipeline to support further expansion of the pipeline in future traffic when determining the pipeline's diffusivity associations, resulting in poor sustainability of the layout scheme. In summary, the conventional pipeline layout method has the problems of inaccurate data, unscientific layout, and the like, and needs to be solved.
Disclosure of Invention
The invention provides a method for fitting an overhead survey data section, which mainly comprises the following steps:
acquiring coordinates, pipeline elevation, pipeline diameter and material properties of a pipeline starting point, a pipeline ending point and a middle node according to the central line data of the electric power pipeline; acquiring a starting point, an ending point and a fitting range of a region around which a pipeline can be further arranged according to the pipeline plane section data; judging a pipeline laying mode according to the topography, the topography and the soil conditions, and predicting a windage yaw line formed by the pipeline; fitting the pipe diameters according to the relationship among the windage yaw line, the pipe diameters and the soil property, and determining pipe diameter selection; determining the diffusivity association of the pipeline according to the pipeline layout mode and the pipeline attribute data, and judging whether the space around the pipeline is further expanded or not; and forming investigation and digital elevation files to display pipeline conditions according to the service life and maintenance cost attributes of the pipeline, and performing key highlighting.
In one embodiment, the acquiring coordinates of a pipeline start point, an end point and an intermediate node, a pipeline elevation, a pipeline diameter and a material property according to the electric pipeline centerline data includes:
searching the starting point, the ending point and the central line field in the pipeline data according to the central line data of the electric power pipeline to obtain the coordinate information of the starting point, the ending point and the central line of the pipeline; according to the pipeline elevation field in the pipeline data, acquiring the elevation data along the pipeline; and obtaining the diameter of the pipeline according to the diameter and the material field in the pipeline data, and determining the material type of the pipeline, including copper, iron or plastics.
In one embodiment, the acquiring, according to the pipeline plane section data, the starting point, the ending point and the fitting range of the area around which the pipeline can be further arranged includes:
acquiring overhead survey data section data of a pipeline, including coordinates of a pipeline starting point, a pipeline ending point and an intermediate node, pipeline elevation, pipeline diameter and material properties; fitting the overhead survey data section of the pipeline to obtain a continuous curve image, and performing smoothing treatment to obtain pipeline plane section data; extracting pipeline fitting data from the pipeline plane data, wherein the pipeline fitting data comprises the elevation and coordinate information of the pipeline at different positions and parameters of a fitting curve; using a polynomial function interpolation method, and obtaining a starting point, an ending point and a fitting range of a surrounding area according to pipeline fitting data; judging whether the pipeline can be further arranged in the area according to the pipeline plane section data characteristics, the starting point, the finishing point and the fitting range of the surrounding area; respectively comparing the geometric relationship between the pipeline plane section data and surrounding areas, the soil type and the groundwater level data, and evaluating the availability and suitability of the areas according to the correlation strength by using a spearman correlation coefficient; displaying the pipeline plane section data, the starting point, the finishing point and the fitting range of the surrounding area by adopting a data visualization technology, and determining the surrounding available layout area; further comprises: fitting the overhead survey data section of the pipeline to obtain continuous curve images, and performing smoothing treatment to obtain pipeline plane section data.
Fitting the overhead survey data section of the pipeline to obtain continuous curve images, and performing smoothing treatment to obtain pipeline plane section data, wherein the method specifically comprises the following steps:
overhead survey data profile data of the pipeline is acquired, including coordinates of pipeline start, end and intermediate nodes, pipeline elevation, pipeline diameter and material properties. And fitting the overhead survey data section of the pipeline by adopting a polynomial fitting method, and determining the coefficient of a fitting curve by a least square method. And obtaining an equation of a fitting curve according to the data of the pipeline coordinates and the pipeline elevation. And determining continuous curve images of the pipeline plane section according to a curve equation obtained by fitting. And drawing a continuous curve image of the flat section of the pipeline by taking the X-axis or Y-axis coordinate as an abscissa and the pipeline elevation as an ordinate. And smoothing the data of the pipeline flat section by adopting moving average, reducing noise in the data, and determining a smoothed pipeline flat section image. And taking the smoothed pipeline elevation data as an ordinate and an X-axis or Y-axis coordinate as an abscissa to obtain a smoothed pipeline plane section image. Attributes contained in the pipeline flat section data are determined, including X-axis or Y-axis coordinates, pipeline elevation, pipe diameter, pipe material, and pipeline type attributes.
In one embodiment, the determining the pipeline laying mode according to the topography, the topography and the soil property conditions, and predicting the windage yaw line formed by the pipeline includes:
acquiring data of a pipeline laying area through a geographic information system, wherein the data comprises terrain elevation data, terrains and landforms, soil characteristics and wind field condition information; carrying out terrain and landform analysis on the pipeline laying area by adopting a terrain analysis and landform classification method, and determining the landform type of the pipeline laying area; according to the terrain elevation data, determining fluctuation and gradient data of a pipeline laying area, and obtaining pipeline laying modes suitable for different terrains, landforms and soil conditions according to engineering design requirements or industry standards; judging a mode suitable for pipeline laying according to the topography, the topography and the soil conditions, and determining a final pipeline laying mode through standard comparison with the pipeline laying mode; according to the final pipeline laying mode, the terrain and the wind field conditions, predicting wind deflection lines of pipelines at different positions by using a CFD simulation technology; further comprises: and predicting windage yaw lines of the pipeline at different positions according to the final pipeline laying mode, the terrain and the wind field conditions by using a CFD simulation technology.
The method for predicting the wind deflection line of the pipeline at different positions by utilizing the CFD simulation technology according to the final pipeline laying mode, the terrain and the wind field conditions specifically comprises the following steps:
and obtaining topographic data and wind farm condition data according to the actual condition of the position of the pipeline, and preprocessing and finishing. And according to the terrain and wind field data, adopting CFD software to establish a CFD simulation model of the position of the pipeline. According to the characteristics and requirements of the pipeline, CFD simulation parameters are set, wherein the parameters comprise grid division, boundary conditions, wind speed and wind direction. And running CFD simulation according to the CFD simulation parameters to obtain wind speed and wind pressure distribution and aerodynamic force parameter simulation results of the position of the pipeline. And obtaining wind deflection angles and wind deflection distances of the pipeline at different positions by using a trigonometric function calculation method according to the wind speed and wind direction data of the pipeline. And calculating the wind load on the pipeline according to the simulation result and the material characteristics of the pipeline. And according to wind pressure distribution and wind load, and by combining structural design and material characteristics of the pipeline, evaluating the wind load and structural strength of the pipeline. The operational condition and countermeasures of the pipeline are determined according to aerodynamic parameters in the simulation results, including lift force and resistance. And predicting the windage yaw lines at different positions of the pipeline according to the calculated windage yaw angles and the calculated offset distances and combining the topography of the positions of the pipeline and wind field conditions.
In one embodiment, the fitting is performed on the pipe diameter according to the relationship among the windage yaw line, the pipe diameter and the soil property, and the pipe diameter selection is determined, including:
obtaining wind deflection line data, pipe diameter data and soil property data of a pipeline, wherein the wind deflection line data comprise wind directions, wind speeds and wind deflection angles, the soil data comprise soil types, granularity distribution, water content and compressibility, and the data are aligned according to the same pipeline ID; matching corresponding windage data, pipe diameter data and soil property data through the same pipe ID; according to the matched data, using a regression analysis method, taking wind deflection line data and soil property data as independent variables, taking pipe diameter as dependent variables, and establishing a regression model of the wind deflection line data, the pipe diameter data and the soil property data of the pipeline; inputting the windage yaw line data and the soil property data into a regression model to obtain pipe diameter selection; comparing the actual pipe diameter data with the obtained pipe diameter selection, and evaluating the accuracy and reliability of the algorithm; according to the verification result, the defects of the algorithm are evaluated, and corresponding adjustment and improvement are carried out, wherein the adjustment and improvement comprise improvement of a data acquisition method, improvement of parameter setting of a model or addition of variables; the process of prediction and verification is iterated until the algorithm achieves the desired accuracy and reliability.
In one embodiment, determining the diffusivity association of the pipeline according to the pipeline layout mode and the pipeline attribute data, and judging whether the space around the pipeline is further expanded comprises:
acquiring a layout mode of the pipeline according to the overhead survey data of the pipeline, wherein the layout mode comprises a linear mode, a curve mode and a branch mode; according to the layout mode, comparing the trend and the shape of the pipelines, and determining whether the possibility of expansion exists, wherein the possibility of expansion exists on the pipelines with linear layout, whether the expansion section exists on the pipelines with branched layout, and whether the point of branch extension exists on the pipelines with branched layout; judging whether other pipelines with similar attributes exist around the pipeline according to the pipeline attribute data, and determining the potential of expansion if the other pipelines with similar attributes can be connected with the current pipeline; judging whether connection points of other pipelines exist around the pipeline by comparing the positions and the number of the connection points of the pipelines, and if so, not having a further expanded space; determining whether the pipeline has a further expanded space according to land utilization conditions around the pipeline, building layout and topography factors; further comprises: according to the layout mode, comparing the trend and the shape of the pipeline, and determining whether the possibility of expansion exists or not; judging whether other pipelines with similar attributes exist around the pipeline, and determining the potential of expansion if the other pipelines with similar attributes can be connected with the current pipeline; whether the pipeline has a further expanded space is determined according to land use, building layout, and topography factors around the pipeline.
The determining whether the expansion possibility exists or not according to the layout mode by comparing the trend and the shape of the pipeline specifically comprises the following steps:
and obtaining pipelines with linear or branched layout according to the layout mode. The extended position or branch extension point is determined according to the pipeline with linear or branched layout, and the extended position is determined by adding a new pipeline section at the tail end or the middle of the original pipeline. The properties of the expansion section are determined according to the pipeline of the linear or branched layout, including the length, diameter or size of the expansion section or the branch pipeline and the material properties. And adding a new pipeline segment on the pipeline with the linear or branched layout according to the determined expansion position and the attribute of the expansion paragraph. Judging whether further expansion is needed on the pipeline after expansion, if so, repeatedly determining the expansion position and the attribute of the expansion paragraph according to the pipeline with the linear or branched layout, and determining the extending point of the branch and the attribute of the branch pipeline in the pipeline layout.
Determining whether other pipelines with similar attributes exist around the pipeline and whether the other pipelines with similar attributes can be connected with the current pipeline, and determining the potential of expansion specifically comprises:
And obtaining the diameter, material and flow attribute values of different pipelines according to the pipeline attribute data. By comparing attribute values of different pipelines, the similarity of the different pipelines is determined. And (5) performing similarity calculation by adopting an Euclidean distance calculation method. Setting a similarity threshold value, and judging that the pipelines with similarity higher than the threshold value have similar attributes. Based on the spatial analysis, a spatial positional relationship between the pipelines is acquired, including the distance and the overlap. And judging that the pipelines closest to or most in overlapping part have similar attributes according to the spatial position relation. And determining the connection relation between pipelines through network topology analysis. Judging whether connection relations exist among pipelines with similar attributes, and if so, indicating that different pipelines have expansion potential.
The method for determining whether the pipeline has a further expanded space according to land utilization conditions, building layout and topography factors around the pipeline specifically comprises the following steps:
and acquiring data of surrounding land utilization conditions according to the land utilization conditions around the pipeline. Based on the building layout, it is determined whether the pipeline needs to pass through or across the building, and building layout data is obtained. And acquiring data of the characteristics of the topography including relief degree, mountain and river conditions according to the topography factors. And determining the current capacity condition of the pipeline according to the pipeline capacity, and acquiring pipeline capacity data. Depending on pipeline safety factors, dangerous area, vulnerable local data around the pipeline is obtained. And judging whether the pipeline has a further expanded space or not according to the building layout, the topography factors, the pipeline capacity and the pipeline safety factor data. If the land utilization condition limits the pipeline expansion space, the required engineering transformation difficulty is evaluated according to the building layout and the topography factors. If the pipeline capacity reaches the design capacity upper limit, based on the pipeline capacity data, the measures required for expansion are evaluated, including increasing the pipeline diameter, increasing pump stations, or increasing branch lines. If potential safety hazards exist around the pipeline, corresponding safety measures are formulated according to pipeline safety data.
In one embodiment, the forming the investigation and digital elevation file to display the pipeline condition according to the service life and maintenance cost of the pipeline, and performing the highlighting includes:
acquiring the age, maintenance cost, material information, service life, maintenance cost data and topography information of a pipeline; according to the age, maintenance cost, material information and topography information of the pipelines, corresponding attribute values are given to each pipeline, and an attribute data set of the pipeline is formed; carrying out visual display on pipeline conditions by using GIS software, associating attribute data of the pipeline with map data, and displaying the attribute data and the map data on a map; setting different symbol patterns, colors or sizes according to the attribute values of service life and maintenance cost to highlight key information of the pipeline; providing pipeline information by using a label and pop-up window mode, wherein the pipeline information comprises service life, maintenance cost and maintenance record; providing interactive functions, allowing users to screen and query according to different attributes; based on the service life and maintenance cost data of the pipeline, corresponding reports, charts and statistical graphs are generated.
The technical scheme provided by the embodiment of the invention can have the following beneficial effects:
The invention discloses a method for fusing multiple technologies, which is used for acquiring X-axis and Y-axis coordinate data, pipeline elevation data, pipeline diameter and material properties of a pipeline starting point, an ending point and an intermediate node, and can comprehensively understand the spatial position, the elevation distribution and the physical characteristics of the pipeline, so as to provide basic data for subsequent analysis. Fitting the overhead survey data section of the pipeline to obtain a continuous curve image, and smoothing to obtain pipeline flat section data, so that the flat section data of the pipeline can be obtained, and detailed information of pipeline geometric shapes is provided. According to the pipeline plane section data, the starting point, the finishing point and the fitting range of the area around which the pipeline can be further arranged are obtained, the area around which the pipeline can be further arranged can be determined, and a space reference is provided for expansion of the pipeline. According to the topography, the topography and the soil conditions, the pipeline laying mode is judged, the wind deflection line and the envelope line formed by the pipeline are predicted, the most suitable pipeline laying mode can be judged, and the wind deflection line and the envelope line formed by the pipeline are predicted, so that the stability and the safety of the pipeline are ensured. And fitting the pipe diameter according to the relationship among the windage yaw line, the pipe diameter and the soil property, determining pipe diameter selection, fitting the pipe diameter of the pipeline, and ensuring the bearing capacity and stability of the pipeline. According to the pipeline layout mode and the pipeline attribute data, determining the diffusivity association of the pipeline, judging whether the space around the pipeline is further expanded, determining the diffusivity association of the pipeline, and judging whether the space around the pipeline is further expanded. According to the service life of the pipeline and the related attributes of maintenance cost, the condition of the pipeline is displayed by forming a survey and digital elevation file, the important highlighting is performed, the survey and digital elevation file can be formed, the condition of the pipeline is highlighted, and a reference is provided for subsequent decisions. By fusing the above technologies together, comprehensive investigation and analysis of pipelines are realized, and accuracy and efficiency of pipeline planning and layout are improved.
Drawings
FIG. 1 is a flow chart of a method of cross-section fitting of overhead survey data according to the present invention.
FIG. 2 is a schematic representation of a method of cross-section fitting of overhead survey data according to the present invention.
FIG. 3 is a further schematic representation of a method of cross-section fitting of overhead survey data according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and specifically described below with reference to the drawings in the embodiments of the present invention. The described embodiments are only a few embodiments of the present invention.
The method for fitting the section of the overhead survey data in the embodiment specifically comprises the following steps:
step S101, according to the central line data of the electric power pipeline, the coordinates of the starting point, the ending point and the intermediate node of the pipeline, the pipeline elevation, the pipeline diameter and the material property are obtained.
And searching the starting point, the ending point and the central line field in the pipeline data according to the central line data of the electric power pipeline to obtain the coordinate information of the starting point, the ending point and the central line of the pipeline. And acquiring elevation data along the pipeline according to the pipeline elevation field in the pipeline data. And obtaining the diameter of the pipeline according to the diameter and the material field in the pipeline data, and determining the material type of the pipeline, including copper, iron or plastics. For example, for a power pipeline data, based on the centerline data, the pipeline may be found to have a start point (1245, 6790), an end point (2356, 7801), and a centerline coordinate series (1245, 6790), (1500, 7000), (2356, 7801). From the elevation field, elevation data along the pipeline can be obtained, such as 50m for the start point, 55m for the center point, and 52m for the end point. From the diameter and texture fields, it is known that the diameter of this line is 500mm and the texture is iron.
Step S102, according to the pipeline plane section data, the starting point, the ending point and the fitting range of the area around which the pipeline can be further arranged are obtained.
Overhead survey data profile data of the pipeline is acquired, including coordinates of pipeline start, end and intermediate nodes, pipeline elevation, pipeline diameter and material properties. Fitting the overhead survey data section of the pipeline to obtain continuous curve images, and performing smoothing treatment to obtain pipeline plane section data. And extracting pipeline fitting data from the pipeline plane section data, wherein the pipeline fitting data comprises the elevation and coordinate information of the pipeline at different positions and parameters of a fitting curve. And obtaining the starting point, the end point and the fitting range of the surrounding area according to the pipeline fitting data by using a polynomial function interpolation method. And judging whether the pipeline can be further arranged in the area according to the characteristics of the pipeline flat section data, the starting point, the ending point and the fitting range of the surrounding area. And respectively comparing the geometric relation, the soil type and the groundwater level data of the pipeline plane section data with those of surrounding areas, and evaluating the availability and the suitability of the areas according to the correlation strength by using the spearman correlation coefficient. And displaying the pipeline plane section data, the starting point, the finishing point and the fitting range of the surrounding area by adopting a data visualization technology, and determining the surrounding available layout area. For example, the profile data of a pipeline is characterized by the elevations of 100m, 98m, 95m, 92m, respectively, at different locations as follows. The pipeline has a start point coordinate of (0, 0) and an end point coordinate of (100 ). Fitting was performed using a quadratic polynomial function, resulting in fitting curves with parameters a=1, b=2, c=3. The starting point, the end point and the fitting range of the surrounding area can be obtained by using a polynomial function interpolation method. A new pipeline needs to be inserted in front of the starting point of the pipeline, and the elevation and coordinate information of a certain distance in front of the starting point can be calculated according to parameters of a fitting curve. And judging whether the area can be further provided with the pipeline according to the characteristics of the pipeline flat section data and the starting point, the ending point and the fitting range of the surrounding area. If the elevation of the surrounding area gradually decreases and the coordinate information matches the trend of the fitted curve, then the area may be considered suitable for laying out a pipeline. To assess the availability and suitability of an area, the pipeline flat section data characteristics can be compared with the geometric relationship, soil type and groundwater level data of surrounding areas. Using the Szelman correlation coefficients, the correlation strength between these data can be calculated. If there is a strong positive correlation between the pipeline flat section data and the geometry of the region, soil type, groundwater level data, the region can be considered to have a high availability and suitability for pipelines. Conversely, if the correlation is weak or negative, there may be some limiting or unsuitable factors. Finally, the pipeline flat data and the surrounding region start, end, and fit ranges may be presented using data visualization techniques. By visual presentation, the surrounding available layout area can be determined, and the area available for layout of the pipeline is marked on the map.
Fitting the overhead survey data section of the pipeline to obtain continuous curve images, and performing smoothing treatment to obtain pipeline plane section data.
Overhead survey data profile data of the pipeline is acquired, including coordinates of pipeline start, end and intermediate nodes, pipeline elevation, pipeline diameter and material properties. And fitting the overhead survey data section of the pipeline by adopting a polynomial fitting method, and determining the coefficient of a fitting curve by a least square method. And obtaining an equation of a fitting curve according to the data of the pipeline coordinates and the pipeline elevation. And determining continuous curve images of the pipeline plane section according to a curve equation obtained by fitting. And drawing a continuous curve image of the flat section of the pipeline by taking the X-axis or Y-axis coordinate as an abscissa and the pipeline elevation as an ordinate. And smoothing the data of the pipeline flat section by adopting moving average, reducing noise in the data, and determining a smoothed pipeline flat section image. And taking the smoothed pipeline elevation data as an ordinate and an X-axis or Y-axis coordinate as an abscissa to obtain a smoothed pipeline plane section image. Attributes contained in the pipeline flat section data are determined, including X-axis or Y-axis coordinates, pipeline elevation, pipe diameter, pipe material, and pipeline type attributes. For example, there is an overhead survey data section of a pipeline including X-axis and Y-axis coordinate data of start, end and intermediate nodes, pipeline elevation data, pipeline diameter and material properties. And selecting the data of 5 nodes to perform polynomial fitting. First, the coefficients of the fitting curve need to be determined by a least square method according to the selected node data. The X-axis coordinates of the 5 selected nodes are [0,10,20,30,40] and the corresponding Y-axis coordinates are [100,150,200,250,300], and a polynomial fitting method is adopted to obtain a fitting curve with an equation of Y=5X+100. Next, continuous curve images of the flat section of the pipeline may be determined from the fitted curve equation. And by taking the X-axis coordinate as the abscissa and the pipeline elevation as the ordinate, continuous curve images of the pipeline plane section can be drawn. Then, to reduce noise in the data, the data for the pipeline flat section may be smoothed using a moving average. The pipeline elevation data of the selected 5 nodes is [110,160,190,270,310], and the smoothed pipeline plane section data is [110,160,190,240,290] through a moving average method. And finally, taking the smoothed pipeline elevation data as an ordinate and an X-axis coordinate as an abscissa, and obtaining the smoothed pipeline plane section image. From the images, the flat section of the pipeline can be analyzed and evaluated.
And step S103, judging a pipeline laying mode according to the topography, the topography and the soil conditions, and predicting the windage yaw line formed by the pipeline.
And acquiring data of the pipeline laying area through a geographic information system, wherein the data comprises terrain elevation data, terrains and landforms, soil characteristics and wind field condition information. And carrying out terrain and landform analysis on the pipeline laying area by adopting a terrain analysis and landform classification method, and determining the landform type of the pipeline laying area. And determining fluctuation and gradient data of the pipeline laying area according to the terrain elevation data, and obtaining pipeline laying modes suitable for different terrains, landforms and soil conditions according to engineering design requirements or industry standards. And judging a mode suitable for pipeline laying according to the topography, the topography and the soil conditions, and determining a final pipeline laying mode by comparing the mode with the specification of the pipeline laying mode. And predicting windage yaw lines of the pipeline at different positions by using a CFD simulation technology according to the final pipeline laying mode, the terrain and the wind farm conditions. For example, data of the pipeline laying region is acquired through a geographic information system, including terrain elevation data, landform type and soil characteristic information. And selecting an area for analysis, wherein the altitude of a certain point is 100 meters according to the data acquired by the geographic information system. According to the classification method in the geographic information system, the region belongs to the mountain landform type. According to the data in the geographic information system, the soil property of the region is clay. From the terrain elevation data, heave and slope data for the pipelaying area may be determined. In this area, the pipeline starts at 100 meters at altitude and runs down the hillside, gradually lowering the altitude until the altitude is 50 meters. According to engineering design requirements or industry standards, pipeline laying modes suitable for different terrains, landforms and soil conditions can be determined. Under the conditions of mountain landform type and clay soil quality, an underground laying mode can be selected to ensure the stability and safety of pipelines. By utilizing the CFD simulation technology, the wind deflection lines of the pipeline at different positions can be predicted according to the final pipeline laying mode, the terrain and the wind field conditions. According to the simulation result, the pipeline is found to have a windage yaw line at the altitude of 50 meters, and the windage yaw angle is 30 degrees.
And predicting windage yaw lines of the pipeline at different positions according to the final pipeline laying mode, the terrain and the wind field conditions by using a CFD simulation technology.
And obtaining topographic data and wind farm condition data according to the actual condition of the position of the pipeline, and preprocessing and finishing. And according to the terrain and wind field data, adopting CFD software to establish a CFD simulation model of the position of the pipeline. According to the characteristics and requirements of the pipeline, CFD simulation parameters are set, wherein the parameters comprise grid division, boundary conditions, wind speed and wind direction. And running CFD simulation according to the CFD simulation parameters to obtain wind speed and wind pressure distribution and aerodynamic force parameter simulation results of the position of the pipeline. And obtaining wind deflection angles and wind deflection distances of the pipeline at different positions by using a trigonometric function calculation method according to the wind speed and wind direction data of the pipeline. And calculating the wind load on the pipeline according to the simulation result and the material characteristics of the pipeline. And according to wind pressure distribution and wind load, and by combining structural design and material characteristics of the pipeline, evaluating the wind load and structural strength of the pipeline. The operational condition and countermeasures of the pipeline are determined according to aerodynamic parameters in the simulation results, including lift force and resistance. And predicting the windage yaw lines at different positions of the pipeline according to the calculated windage yaw angles and the calculated offset distances and combining the topography of the positions of the pipeline and wind field conditions. For example, a pipeline is located in a mountain area, the terrain data shows that the average altitude is 600 meters, and the wind field condition data shows that the average wind speed in the area is 10m/s, and the wind direction is northeast. First, these data are put into CFD software and modeled. When setting the simulation parameters, it is possible to divide the grid into 1mx1m for the characteristics of the region, the boundary condition is set to be open, and the wind speed and wind direction are set to 10m/s and northeast. And after running CFD simulation, obtaining wind speed distribution, wind pressure distribution and aerodynamic parameters of the pipeline at the position. The simulation result shows that the wind speed is 7-13m/s and the wind pressure is distributed between 1 and 3 kPa. According to the data, the wind deflection angle and the wind deflection distance of the pipeline at different positions can be obtained by using a trigonometric function calculation method. The wind deflection angle is 5 degrees, and the wind deflection distance is 5m. Next, the magnitude of the wind load to which the pipeline is subjected will be calculated based on the simulation results and the material properties of the pipeline, such as the pressure level of the pipeline being 15 MPa. The wind load may be between 100-300 kN. In combination with the structural design and material properties of the pipeline, assessing the wind load and structural strength of the pipeline, it may be found that the structural strength of the pipeline is sufficient to resist such wind load. Depending on aerodynamic parameters in the simulation results, the lift may be between 20-60kN and the drag may be between 30-90kN, the operating conditions and countermeasures of the pipeline may be determined, and it may be desirable to add support to certain parts of the pipeline. Finally, according to the calculated windage yaw angle and the calculated offset distance, windage yaw lines of pipelines at different positions can be predicted, and 5m windage yaw can possibly occur in the northeast direction.
And step S104, fitting the pipe diameter according to the relationship among the windage yaw line, the pipe diameter and the soil property, and determining pipe diameter selection.
And acquiring wind deflection line data, pipe diameter data and soil property data of the pipeline, wherein the wind deflection line data comprises wind direction, wind speed and wind deflection angle, the soil data comprises soil type, granularity distribution, water content and compressibility, and the data are aligned according to the same pipeline ID. And matching corresponding windage data, pipe diameter data and soil property data through the same pipeline ID. According to the matched data, a regression analysis method is used, wind deflection line data and soil property data are used as independent variables, pipe diameter is used as dependent variable, and a regression model of the wind deflection line data, the pipe diameter data and the soil property data of the pipeline is built. And inputting the windage yaw line data and the soil property data into a regression model to obtain pipe diameter selection. And comparing the actual pipe diameter data with the obtained pipe diameter selection, and evaluating the accuracy and reliability of the algorithm. According to the verification result, the defects of the evaluation algorithm are correspondingly adjusted and improved, including improving the data acquisition method, improving the parameter setting of the model or adding variables. The process of prediction and verification is iterated until the algorithm achieves the desired accuracy and reliability. For example, there are two pipes, pipe A and pipe B, respectively. The wind deflection line data of the pipeline A are that the wind direction is 270 degrees, the wind speed is 10m/s, and the wind deflection angle is 20 degrees; the wind deflection line data of the pipeline B are that the wind direction is 180 degrees, the wind speed is 8m/s, and the wind deflection angle is 15 degrees. The pipe diameter data of the pipeline A is 100mm, the soil data is clay, the granularity distribution is 40% of silt, 40% of clay and 20% of sand, the water content is 20%, and the compressibility is compressible; the pipe diameter data of the pipeline B is 80mm, the soil data is that the soil type is sand, the granularity distribution is 60% sand, 30% silt and 10% clay, the water content is 15%, and the compressibility is incompressible. And matching the windage yaw line data, the pipe diameter data and the soil data according to the same pipeline ID. The pipe diameter corresponding to the windage data and the soil data of the pipeline A is 100mm, and the pipe diameter corresponding to the windage data and the soil data of the pipeline B is 80mm. And establishing a regression model of the wind deflection line data, the pipe diameter data and the soil data of the pipeline by using a regression analysis method and taking the wind deflection line data and the soil data as independent variables and the pipe diameter as dependent variables. The regression model is pipe diameter=5×wind direction+2×wind speed+3×windage+1×water content-4×compressibility. And inputting the windage yaw line data and the soil data of the pipeline A, B into a regression model to obtain pipe diameter selection, and comparing the actual pipe diameter data with the obtained pipe diameter selection to evaluate the accuracy and reliability of the algorithm. The pipe diameter of the actual pipeline A is 100mm, the pipe diameter of the actual pipeline B is 80mm, and the accuracy of the algorithm is found to be higher and is consistent with the actual data. And according to the verification result, evaluating the defects of the algorithm, and correspondingly adjusting and improving. If the parameter setting in the regression model is found to be unreasonable, the parameter can be readjusted; if the data acquisition method is found to be inaccurate, the data acquisition method can be improved; if the model is found to lack variables, the variables may be added, etc. The process of prediction and verification is iterated until the algorithm achieves the desired accuracy and reliability.
Step S105, determining the diffusivity association of the pipeline according to the pipeline layout mode and the pipeline attribute data, and judging whether the space around the pipeline is further expanded.
And acquiring the layout modes of the pipeline according to the overhead survey data of the pipeline, wherein the layout modes comprise linear type, curve type and branch type. According to the layout mode, comparing the trend and the shape of the pipelines, determining whether the possibility of expansion exists, including whether an expanded section exists on the pipeline with the linear layout, and whether a branch extending point exists on the pipeline with the branched layout. And judging whether other pipelines with similar attributes exist around the pipeline according to the pipeline attribute data, and determining the potential of expansion if the other pipelines with similar attributes can be connected with the current pipeline. By comparing the positions and the number of the pipeline connection points, whether other pipeline connection points exist around the pipeline is judged, and if so, no further expansion space exists. Whether the pipeline has a further expanded space is determined according to land use, building layout, and topography factors around the pipeline. For example, the acquired layout is linear based on existing overhead survey data. This means that the pipeline as a whole runs straight without significant curves or branches. By comparing the orientation and shape of the pipeline, it can be determined whether there is a possibility of expansion. If the line runs straight and there is no significant turn or branch, there may be room for expansion, and the pipeline may continue to run in the direction of extension of the line. Next, the attributes of the pipeline need to be analyzed to determine if there are other pipelines around that have similar attributes. If the pipe diameter, material and purpose of the pipeline are similar to other surrounding pipelines, then the potential for expansion can be considered. The pipe diameter of the existing pipeline is 10 inches, the material is steel, the power supply is used, and the properties of other surrounding pipelines are the same, so that the possibility of expanding the pipeline is high. In addition, it is also possible to determine whether there are other pipeline connection points around by comparing the positions and the number of pipeline connection points. If there are more connection points of the pipeline and the location distribution is more concentrated, then there is likely to be other pipelines connected to it. The number of pipeline connection points is 10, and the connection points are distributed in the same area, it can be presumed that there are connection points of other pipelines in the area. Finally, it is also necessary to consider land use around the pipeline, building layout, and topography factors to determine if the pipeline has further extended space. If the land surrounding the pipeline is not being utilized by construction or there is a large empty space, then it can be considered that there is a possibility of expansion. In addition, if the pipeline runs to match the surrounding topography, it can also be stated that the pipeline may have a further expansion space in some areas.
And comparing the trend and the shape of the pipeline according to the layout mode, and determining whether the possibility of expansion exists.
And obtaining pipelines with linear or branched layout according to the layout mode. The extended position or branch extension point is determined according to the pipeline with linear or branched layout, and the extended position is determined by adding a new pipeline section at the tail end or the middle of the original pipeline. The properties of the expansion section are determined according to the pipeline of the linear or branched layout, including the length, diameter or size of the expansion section or the branch pipeline and the material properties. And adding a new pipeline segment on the pipeline with the linear or branched layout according to the determined expansion position and the attribute of the expansion paragraph. Judging whether further expansion is needed on the pipeline after expansion, if so, repeatedly determining the expansion position and the attribute of the expansion paragraph according to the pipeline with the linear or branched layout, and determining the extending point of the branch and the attribute of the branch pipeline in the pipeline layout; for example, there is a straight line arrangement of pipes, which includes a length of 1000 meters. It is now necessary to add a new pipe section at the end of the original pipeline. From a line layout of the pipeline, it is determined that the location of the expansion is at the end of the original pipeline. The properties of the extension paragraph may be the length, diameter and material properties of the new pipe segment. Assume that the new pipe section to be expanded is 500 m long and 5 m in diameter, and is made of steel. According to the determined expansion position and the attribute of the expansion paragraph, a new pipeline section with the length of 500 meters, the diameter of 5 meters and the material of steel can be added at the tail end of the original pipeline. If further expansion of the pipeline is required, the above steps may be repeated again to determine the expansion location and the properties of the expansion paragraph. A pipeline section with the length of 200 meters, the diameter of 4 meters and the material of plastic can be added at the tail end of the new pipeline section.
It is determined whether there are other pipelines around the pipeline that have similar attributes and whether other pipelines with similar attributes can connect with the current pipeline, determining the potential for expansion.
And obtaining the diameter, material and flow attribute values of different pipelines according to the pipeline attribute data. By comparing attribute values of different pipelines, the similarity of the different pipelines is determined. And (5) performing similarity calculation by adopting an Euclidean distance calculation method. Setting a similarity threshold value, and judging that the pipelines with similarity higher than the threshold value have similar attributes. Based on the spatial analysis, a spatial positional relationship between the pipelines is acquired, including the distance and the overlap. And judging that the pipelines closest to or most in overlapping part have similar attributes according to the spatial position relation. And determining the connection relation between pipelines through network topology analysis. Judging whether connection relations exist among pipelines with similar attributes, and if so, indicating that different pipelines have expansion potential. For example, there is a set of pipeline attribute data including diameter, material, and flow attribute values. It is desirable to find pipelines with similar properties. First, the Euclidean distance between different pipelines can be calculated to measure the similarity between them. Two pipelines are arranged, the diameter of the pipeline A is 12 inches, the material is iron, and the flow is 1000 cubic meters per hour; pipeline B was 10 inches in diameter, steel, and had a flow rate of 900 cubic meters per hour. The difference in diameter of pipeline A and pipeline B can be calculated, (12-10) ≡2=4; the difference of the materials is 0; the difference in flow is (1000-900)/(2=10000. These difference values are then added and square-root-divided to give the Euclidean distance, sqrt (4+0+10000) ≡1002. If the similarity threshold is set to 100, the similarity of pipeline A and pipeline B is below this threshold, so their properties are less similar. Next, spatial analysis may be utilized to determine the spatial positional relationship between the pipelines. There are three lines: the starting point coordinates of the pipeline A are (0, 0), and the ending point coordinates are (10, 10); the starting point coordinates of the pipeline B are (5, 5), and the ending point coordinates are (15, 15); the line C has a start point coordinate of (20, 20) and an end point coordinate of (25, 25). The distance between line a and line B can be calculated to be 0; the distance between line a and line C was about 228. Thus, the spatial relationship of line A and line B is closer. Finally, a network topology analysis may be performed to determine the connection relationship between the pipelines. There are four lines: pipeline A is connected to pipeline B and pipeline C is connected to pipeline D. If a connection relationship is found between pipelines with similar properties, pipeline A and pipeline B, it can be inferred that there is an expansion potential between the different pipelines.
Whether the pipeline has a further expanded space is determined according to land use, building layout, and topography factors around the pipeline.
And acquiring data of surrounding land utilization conditions according to the land utilization conditions around the pipeline. Based on the building layout, it is determined whether the pipeline needs to pass through or across the building, and building layout data is obtained. And acquiring data of the characteristics of the topography including relief degree, mountain and river conditions according to the topography factors. And determining the current capacity condition of the pipeline according to the pipeline capacity, and acquiring pipeline capacity data. Depending on pipeline safety factors, dangerous area, vulnerable local data around the pipeline is obtained. And judging whether the pipeline has a further expanded space or not according to the building layout, the topography factors, the pipeline capacity and the pipeline safety factor data. If the land utilization condition limits the pipeline expansion space, the required engineering transformation difficulty is evaluated according to the building layout and the topography factors. If the pipeline capacity reaches the design capacity upper limit, based on the pipeline capacity data, the measures required for expansion are evaluated, including increasing the pipeline diameter, increasing pump stations, or increasing branch lines. If potential safety hazards exist around the pipeline, corresponding safety measures are formulated according to pipeline safety data. For example, there is a natural gas pipeline passing through an industrial park and a farm depending on the land use surrounding the pipeline. According to land utilization data, the industrial park occupies 60% of the land around the pipeline, and the farmland occupies 40% of the land. According to building layout data, the pipeline needs to pass through two large plants in the industrial park. This means that the pipeline needs to pass through the building and may need to be engineered to accommodate the layout of the building. According to the data of the topography factors, the relief degree of the area where the pipeline is located is large, and a mountain and a river exist. This means that the pipeline needs to take into account the effects of mountains and rivers on the pipeline, and engineering may be required to adapt to the characteristics of the topography. The current capacity utilization of the pipeline is 80% based on the pipeline capacity data. This means that the pipeline is approaching the upper limit of the design capacity and needs to be expanded to increase capacity. Depending on pipeline safety factor data, there is a zone of vulnerability around the pipeline and a dangerous zone. This means that the pipeline needs to take corresponding safety measures to protect the pipeline from damage. Based on the above data, the expansion space of the pipeline can be evaluated. If the land use condition limits the pipeline expansion space, the industrial park occupies most of surrounding land, and the engineering difficulty can be evaluated according to the building layout and the topography factors. Additionally, if the pipeline capacity approaches or reaches the design capacity upper limit, e.g., current capacity utilization is 80%, measures required for expansion may be evaluated based on pipeline capacity data, increasing pipeline diameter, adding pump stations, or adding branches to increase pipeline capacity. Finally, if there is a safety hazard around the pipeline, such as a region or a dangerous region which is easy to damage, corresponding safety measures can be formulated according to the pipeline safety data, the pipeline can be reinforced, safety monitoring equipment can be added, and the like.
And S106, forming investigation and digital elevation files to display pipeline conditions according to the service life and maintenance cost attributes of the pipeline, and performing key highlighting.
The pipeline age, maintenance cost, material information, service life, maintenance cost data and terrain information are acquired. And according to the age, maintenance cost, material information and topography information of the pipelines, assigning corresponding attribute values to each pipeline to form an attribute data set of the pipeline. And carrying out visual display on the pipeline condition by using GIS software, correlating the attribute data of the pipeline with map data, and displaying the attribute data and the map data on a map. Different symbol patterns, colors or sizes are set to highlight key information of the pipeline according to attribute values of service life and maintenance cost. And providing pipeline information by using a label and popup window mode, wherein the pipeline information comprises service life, maintenance cost and maintenance record. Interactive functionality is provided that allows a user to screen and query for different attributes. Based on the service life and maintenance cost data of the pipeline, corresponding reports, charts and statistical graphs are generated. For example, there is a pipeline attribute data set that includes the age, maintenance cost, material information, lifetime, and maintenance records for each pipeline. The data are visually displayed by GIS software, and different symbol patterns and colors are set according to the attribute values of service life and maintenance cost. First, the age, maintenance cost, material information, and topography information of the pipeline may be imported into the attribute table of the GIS software. Based on these attribute information, each pipeline may be assigned a corresponding attribute value. The age may be expressed as an integer value, the maintenance cost may be expressed as a floating point value, and the texture information may be expressed as a text or classification value. Next, attribute data of the pipeline may be associated with map data, and information of the pipeline may be displayed on a map. Different symbol patterns, colors, or sizes may be used to highlight the accent information of the pipeline. The longer life lines may be represented by thicker lines and the higher maintenance lines may be represented by red. Further, pipeline information may be provided using labels and pop-up windows, including lifetime, maintenance costs, and maintenance records. When a user clicks or hovers over the pipeline, information may be displayed. At the same time, interactive functions can be provided, allowing the user to screen and query according to different attributes. For example, a user may screen for pipelines with a service life of greater than 10 years, or query for pipelines with maintenance costs of 1000 yuan or more. Finally, based on the life and maintenance cost data of the pipeline, corresponding reports, charts and statistical graphs can be generated. A bar graph may be generated to show the number of lines over each life, or a pie graph may be generated to show the line duty cycle for different maintenance cost levels.
The foregoing disclosure is illustrative of the preferred embodiments of the present invention, and is not to be construed as limiting the scope of the invention, as it is understood by those skilled in the art that all or part of the above-described embodiments may be practiced with equivalents thereof, which fall within the scope of the invention as defined by the appended claims.
Claims (7)
1. A method of aerial survey data cross-section fitting, the method comprising:
acquiring coordinates, pipeline elevation, pipeline diameter and material properties of a pipeline starting point, a pipeline ending point and a middle node according to the central line data of the electric power pipeline; acquiring a starting point, an ending point and a fitting range of a region around which a pipeline can be further arranged according to the pipeline plane section data; judging a pipeline laying mode according to the topography, the topography and the soil conditions, and predicting a windage yaw line formed by the pipeline; fitting the pipe diameter according to the relationship among the windage yaw line, the pipe diameter and the soil property, and determining pipe diameter selection; determining the diffusivity association of the pipeline according to the pipeline layout mode and the pipeline attribute data, and judging whether the space around the pipeline is further expanded or not; and forming investigation and digital elevation files to display pipeline conditions according to the service life and maintenance cost attributes of the pipeline, and performing key highlighting.
2. The method of claim 1, wherein the obtaining coordinates of pipeline start, end and intermediate nodes, pipeline elevation, pipeline diameter and material properties from the power pipeline centerline data comprises:
analyzing the coordinate information of the starting point, the ending point and the central line of the pipeline from the central line data of the power pipeline; determining elevation data along the pipeline; acquiring the diameter size of the pipeline based on the elevation data and the coordinate information; and determining the material type of the pipeline according to the pipeline diameter and the elevation data.
3. The method of claim 1, wherein the acquiring, from the pipeline plane data, a region start point, an end point, and a fitting range around which the pipeline is further disposed, comprises:
adopting the pipeline plane section data, and obtaining pipeline fitting data through fitting and smoothing treatment; obtaining a starting point, an end point and a fitting range of a surrounding area according to the fitting data by using a polynomial function interpolation method; and judging whether the area can be further provided with pipelines or not by comparing the starting point, the ending point and the fitting range of the area, and extracting the geometric relationship between the pipeline plane section data and the surrounding area according to the judging result.
4. The method of claim 1, wherein the determining the pipeline laying mode according to the topography, the soil conditions, and predicting the windage yaw line formed by the pipeline comprises:
acquiring the topography, topography and soil condition information of a pipeline laying area; analyzing the topography and topographical features of the pipelaying area based on the topography, topography and soil conditions; determining pipeline laying modes suitable for different terrains, landforms and soil conditions according to the terrains, the landform features and the soil conditions; and comparing the pipeline laying mode with a pipeline laying standard to determine a final pipeline laying mode, and predicting windage yaw lines formed at different positions of the pipeline by using a simulation technology.
5. The method of claim 1, wherein the fitting the pipe diameters according to the windage, pipe diameter, and soil property relationships, determining pipe diameter selection, comprises:
acquiring corresponding windage yaw line data, pipe diameter data and soil property data, performing data matching through the same pipe ID, and then establishing a regression model by adopting a regression analysis method; inputting the windage yaw line data and the soil property data into the regression model to obtain pipe diameter selection; and comparing the actual pipe diameter data with the obtained pipe diameter selection, and correspondingly adjusting and improving according to the verification result.
6. The method of claim 1, wherein determining the diffusivity association of the pipeline based on the pipeline layout and the pipeline attribute data, determining whether there is a further expansion of space around the pipeline, comprises:
acquiring the layout mode of the pipeline according to the overhead survey data of the pipeline, and determining whether the possibility of expansion exists; and judging whether other pipelines with similar attributes exist around the pipeline or not and whether a further expanded space exists or not according to the pipeline attribute data.
7. The method of claim 1, wherein the forming survey and digital elevation files to reveal pipeline conditions based on attributes of service life, maintenance cost of the pipeline, highlighting comprises:
acquiring related data of pipelines, endowing each pipeline with a corresponding attribute value, and then carrying out visual display by using GIS software; according to the attribute values of service life and maintenance cost, different symbols are set to highlight key information, and a user interaction function is provided to allow a user to carry out screening and inquiry.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311145246.3A CN117094104B (en) | 2023-09-06 | Overhead survey data section fitting method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311145246.3A CN117094104B (en) | 2023-09-06 | Overhead survey data section fitting method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117094104A true CN117094104A (en) | 2023-11-21 |
| CN117094104B CN117094104B (en) | 2024-06-21 |
Family
ID=
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102495879A (en) * | 2011-12-06 | 2012-06-13 | 南京市测绘勘察研究院有限公司 | Industrial overhead pipeline measurement method based on ground LIDAR (Light Detection And Ranging) |
| CN109238242A (en) * | 2017-07-10 | 2019-01-18 | 北京正能空间信息技术有限公司 | Transmission line of electricity path optimization route selection based on three-dimensional large scene |
| US20220309201A1 (en) * | 2020-09-04 | 2022-09-29 | Southeast University | Artificial-intelligence-assisted method for providing urban design form and layout with improved wind environment |
| CN115408750A (en) * | 2022-08-17 | 2022-11-29 | 广东科诺勘测工程有限公司 | Power transmission line measurement finished product diagram generation method, device, equipment and storage medium |
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102495879A (en) * | 2011-12-06 | 2012-06-13 | 南京市测绘勘察研究院有限公司 | Industrial overhead pipeline measurement method based on ground LIDAR (Light Detection And Ranging) |
| CN109238242A (en) * | 2017-07-10 | 2019-01-18 | 北京正能空间信息技术有限公司 | Transmission line of electricity path optimization route selection based on three-dimensional large scene |
| US20220309201A1 (en) * | 2020-09-04 | 2022-09-29 | Southeast University | Artificial-intelligence-assisted method for providing urban design form and layout with improved wind environment |
| CN115408750A (en) * | 2022-08-17 | 2022-11-29 | 广东科诺勘测工程有限公司 | Power transmission line measurement finished product diagram generation method, device, equipment and storage medium |
Non-Patent Citations (2)
| Title |
|---|
| EMFIETZOGLOU, D等: "Accurate electron inelastic cross sections and stopping powers for liquid water over the 0.1-10 keV range based on an improved dielectric description of the bethe surface", 《RADIATION RESEARCH》, 31 January 2007 (2007-01-31), pages 110 - 120 * |
| 王彬 等: "基于多平台的电力选线系统研究", 《地理空间信息》, vol. 14, no. 11, 30 November 2016 (2016-11-30), pages 69 - 71 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103996089B (en) | Based on the transmission line of electricity optimal path generation method of GIS | |
| KR101815581B1 (en) | Judgement system and method for flooding road area using gis and information model of sewer pipe network | |
| CN105303045B (en) | A kind of long distance pipeline linear data association rule mining method | |
| CN102087753A (en) | Rapid three-dimensional mapping moulding method for ground and underground pipe network | |
| CN107218923A (en) | Surrounding enviroment history settles methods of risk assessment along subway based on PS InSAR technologies | |
| CN104091005B (en) | A kind of Overhead Line Project measures indoor and field integration system | |
| CN107230021A (en) | The method of high frequency zone water supply network leakage region | |
| KR101394976B1 (en) | Generating methodology of multi-scale model for the attached cadastral map | |
| CN113076617B (en) | Method, system and equipment for visualizing urban water supply pipe network structure and function | |
| CN111189424B (en) | Road data bending degree detection method based on multistage search radius | |
| CN104747224A (en) | Ventilation complexity analysis method based on mine ventilation equivalent area | |
| CN116151013A (en) | Method for pushing out design flood of small-river-basin urban river channel | |
| CN117094104B (en) | Overhead survey data section fitting method | |
| Liu et al. | BIM-based digital platform and risk management system for mountain tunnel construction | |
| CN110084460A (en) | A kind of quantization assessment method of obstacle free airspace condition | |
| CN201229588Y (en) | Underground gas pipeline detection and data processing apparatus | |
| CN117094104A (en) | Overhead survey data section fitting method | |
| CN110909037B (en) | Frequent track mode mining method and device | |
| CN111191330B (en) | Method and system for problem discovery in pipeline integrated design | |
| CN103995944A (en) | Space abnormal extreme value unbiased isogram drawing method | |
| CN110717233B (en) | Rainwater pipe network flow calculation method and system based on GIS underlying surface analysis | |
| CN116628910A (en) | Underground pipeline three-dimensional visual modeling method based on GIS and BIM | |
| Tang et al. | Design and Application of Risk Early Warning System for Subway Station Construction Based on Building Information Modeling Real‐Time Model | |
| Bobrova et al. | Parameterization of environmental components in the information-modeling context of roads | |
| CN201237085Y (en) | Apparatus used for gas pipe risk management |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |