Power transmission line working condition simulation power line model compression method and system

Abstract

The invention relates to the technical field of power line model compression, and discloses a power transmission line working condition simulation power line model compression method and system, and the method comprises the steps: carrying out spatial line simulation, and determining a catenary equation and parameters; constructing a space line compression model; and calculating the nearest distance based on a spatial line compression model. According to the method, regional line segments are adopted to replace discrete point sets in tree obstacle detection under the limiting working condition, and the defect that dense spatial line discrete point sets are needed in a traditional method is overcome; secondly, adopting a vertical distance from a point to a regional line segment as a filtering constraint condition, and realizing compression of a power line model on the basis of ensuring tree obstacle detection calculation precision requirements; the compressed power line model constructed by the method can greatly reduce the number of working condition simulation power line model points, optimize the calculation speed of subsequent tree obstacle hidden danger detection and reduce the overhead of power line model display and storage calculation resources on the basis of ensuring tree obstacle detection precision under the extreme working condition, and has relatively high use value.

Description

Technical Field

[0001] The present invention relates to the technical field of power line model compression, and in particular to a method and system for compressing a power line model for simulating transmission line working conditions. Background Art

[0002] The power line condition simulation of transmission lines is an important part of the airborne LiDAR power inspection data processing, providing basic data support for the subsequent tree obstacle detection under extreme conditions of transmission lines. In the existing technology, since the catenary curve equation used in the condition simulation cannot be directly applied to the distance compliance verification, it is often necessary to convert the power line curve model into a dense discrete point set to calculate the shortest distance from the tree point to the power line. This dense point set model has a large amount of data, which causes a computational burden on the model display and storage of the subsequent extreme condition power line model, greatly reducing the efficiency of tree obstacle hidden danger detection under extreme conditions. Summary of the invention

[0003] In view of the above-mentioned problems, the present invention is proposed.

[0004] Therefore, the technical problem solved by the present invention is that the data level of the working condition simulation power line model constructed by the prior art is large, which causes a computational burden on the model display and storage of the subsequent extreme working condition power line model.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: a method for compressing a power line model for simulating transmission line operating conditions, comprising: performing spatial line simulation to determine catenary equations and parameters; constructing a spatial line compression model; and calculating the shortest distance based on the spatial line compression model.

[0006] As a preferred solution of the power line model compression method for simulating the working condition of a transmission line described in the present invention, before determining the catenary equation and parameters, it also includes collecting point cloud data of the space line and determining the three-dimensional coordinates of the space line hanging point.

[0007] As a preferred solution of the power line model compression method for simulating transmission line operating conditions described in the present invention, the construction of the spatial line compression model includes treating the power lines between sampling points as line segment distributions and determining the spatial line compression model bundle conditions based on the chord height difference.

[0008] As a preferred scheme of the power line model compression method for simulating the working condition of a transmission line described in the present invention, the calculation of the shortest distance includes, based on the retrieval of the nearest point from the detection point to the discrete point set of the spatial line, calculating the shortest distance from the detection point to the line segment in the area where the nearest point of the discrete point set of the spatial line is located.

[0009] As a preferred solution of the power line model compression method for simulating the working condition of a transmission line described in the present invention, wherein: the spatial line includes but is not limited to the transmission line; the determination of the catenary equation and parameters includes calculating the height difference angle from the three-dimensional coordinates of the hanging point, and the vertical load, horizontal load and stress value of the power line at the lowest point of the power line are determined by the design parameters of the power line, the meteorological parameters under extreme working conditions and the measured power line distribution through state equation calculation.

[0010] As a preferred solution of the power line model compression method for simulating the working condition of the transmission line described in the present invention, wherein: the determination of the space line compression model bundle condition based on the chord height difference includes: step 1, constructing an initial area line segment with hanging points A and B as endpoints; step 2, calculating the horizontal projection length l from the middle point of the area line segment to the hanging point A AP , calculate the corresponding sag and windage values ​​of the middle point of the regional line segment based on the catenary equation, and obtain the three-dimensional coordinates of the power line point corresponding to the middle point of the regional line segment; step 3, calculate the vertical distance from the power line point corresponding to the middle point of the regional line segment to the regional line segment, when the vertical distance is greater than the maximum chord height difference threshold, split the regional line segment to obtain a new regional line segment; step 4, repeat steps 2-3 for the newly generated regional line segment until the vertical distance is less than the maximum chord height difference threshold.

[0011] As a preferred scheme of the power line model compression method for simulating the operating conditions of a transmission line described in the present invention, wherein: the detection points include but are not limited to tree points, key points of buildings and terrain obstacle points; the spatial line discrete point set includes but is not limited to the extreme operating condition spatial line point set, the normal operating condition spatial line point set and the spatial line dynamic deformation point set.

[0012] A power line model compression system for simulating the working condition of a power transmission line using any of the methods described in the present invention, wherein: a line simulation module performs power line simulation, determines a catenary equation, and determines the parameters of the catenary equation based on point cloud data of the power line; a model construction module regards the power lines between sampling points as line segment distributions, uses regional line segments instead of discrete point sets to express the power lines, and realizes the construction of a working condition simulation power line compression model by controlling the chord height difference from the power line point corresponding to the middle point of the regional line segment to the regional line segment; and a calculation module calculates the closest distance from a detection point to the regional line segment where the nearest point of the discrete point set of the power line is located based on the power line compression model.

[0013] A computer device comprises: a memory and a processor; the memory stores a computer program, comprising: the steps of implementing any one of the methods of the present invention when the processor executes the computer program.

[0014] A computer-readable storage medium stores a computer program, comprising: when the computer program is executed by a processor, the steps of implementing any one of the methods of the present invention are implemented.

[0015] Beneficial effects of the present invention: The method of the present invention uses regional line segments instead of discrete point sets in tree obstacle detection under extreme working conditions, which solves the drawback that traditional methods require dense spatial line discrete point sets; secondly, the vertical distance from the point to the regional line segment is used as a filtering constraint to achieve compression of the power line model on the basis of ensuring the accuracy of tree obstacle detection calculations. The compressed power line model constructed by this method can greatly reduce the number of points in the working condition simulation power line model on the basis of ensuring the accuracy of tree obstacle detection under extreme working conditions, optimize the calculation speed of subsequent tree obstacle hidden danger detection, and reduce the power line model display and storage calculation resource overhead, and has a strong use value. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0017] Figure 1 An overall flow chart of a method for compressing a power line model for simulating power transmission line conditions provided by one embodiment of the present invention;

[0018] Figure 2 A schematic diagram of an initial area line segment of a power line model compression method for simulating power line conditions of a power transmission line provided by an embodiment of the present invention;

[0019] Figure 3 A schematic diagram of regional line segment splitting of a power line model compression method for simulating power line conditions of a power transmission line provided by an embodiment of the present invention;

[0020] Figure 4 A schematic diagram of the nearest point 1 of a power line model compression method for simulating power line conditions provided by a second embodiment of the present invention;

[0021] Figure 5 A schematic diagram of the nearest point 2 of a power line model compression method for simulating power line conditions provided by a second embodiment of the present invention;

[0022] Figure 6 A schematic diagram of the nearest point 3 of a method for compressing a power line model for simulating transmission line operating conditions provided by the second embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0024] Example 1, reference Figure 1 , as an embodiment of the present invention, provides a method for compressing a power line model for simulating transmission line working conditions, comprising:

[0025] S1: Perform space line simulation to determine the catenary equation and parameters.

[0026] Further, the space line is various linear or strip infrastructures erected in space, including but not limited to overhead lines, traffic lines, bridge cables, and air transportation facilities. In one embodiment of the present invention, the space line is a power transmission line under extreme working conditions.

[0027] Specifically, the power line simulation under the extreme working conditions of the transmission line is carried out to determine the parameters in the catenary equation and realize the three-dimensional coordinate calculation of any point on the power line under the extreme working conditions. The catenary equation is expressed as:

[0028]

[0029] Where A and B represent the points at both ends of the power line; f vP represents the sag value corresponding to point P; f hP Indicates the wind deviation value corresponding to point P; l AB Indicates the projection distance between hanging point A and hanging point B on the horizontal plane; l AP represents the projection distance between the hanging point A and point P on the horizontal plane; β represents the altitude angle; γ v represents the vertical load on the power line under specified meteorological conditions; γ h represents the horizontal load on the power line under specified meteorological conditions; σ0 represents the stress value at the lowest point of the power line under specified extreme conditions.

[0030] Through the sag value f vP , wind deviation value f hP And the position of the corresponding point on line AB can be used to calculate the three-dimensional coordinates of point P.

[0031] It should be noted that power line simulation under extreme conditions of transmission lines refers to simulating the power line morphology of transmission lines under specific extreme environmental conditions (such as extreme weather, loads, etc.), and calculating the force and morphological changes of power lines under these conditions. The maximum sag, wind deflection and other deformation parameters of power lines under extreme conditions are determined through simulation to evaluate the safety and reliability of the lines.

[0032] Furthermore, based on the transmission line point cloud data collected by airborne LiDAR, the three-dimensional coordinates of the hanging points A and B can be determined manually or by the hanging point advance algorithm. The height difference angle β can be directly calculated from the three-dimensional coordinates of the hanging points A and B, and γ v , γ h and σ0 are determined by the design parameters of the power lines, the meteorological parameters under extreme conditions and the power line distribution measured by airborne LiDAR through state equation calculation.

[0033] In another embodiment of the present invention, the space line may also be an aerial transportation facility, such as a cable car, a ropeway or an aerial hanging rail, etc. The cables stretched in the air provide a path for the transportation vehicles.

[0034] For aerial transportation facilities (taking cable cars as an example), the extreme working conditions include strong winds, loads and temperature stresses. The hanging points are fixed supporting structures at both ends (such as cable car stations). The positioning of the hanging points needs to consider the changes in the height, span and fixed positions of the facilities at both ends. For cable cars with longer distances, the middle support point can be used as the hanging point and modeled in sections.

[0035] S2: Construct a spatial line compression model.

[0036] Furthermore, since the catenary equation cannot directly calculate the shortest distance from a point to a spatial curve, in order to subsequently calculate the distance from the tree point to the power line under extreme working conditions and realize the detection of tree hidden danger points, the traditional method needs to convert the power line curve into a discrete point set based on the catenary equation for representation, and take the shortest distance from the tree point to the discrete point set of the power line as the distance between the tree point and the power line.

[0037] In order to ensure the distance calculation accuracy of the traditional method, the distance between adjacent sampling points in the power line discrete point set needs to be set within a small range, resulting in a huge number of points in the power line discrete point set, which creates a computational burden on subsequent model display, storage, and proximity calculations. Therefore, this method regards the power lines between the sampling points as line segment distributions, uses regional line segments instead of discrete point sets to express the power lines, and controls the chord height difference from the corresponding power line point to the regional line segment at the middle point of the regional line segment to achieve the construction of a power line compression model for working condition simulation.

[0038] Among them, the chord height difference specifically refers to the vertical distance from a point to a straight line.

[0039] The specific process of constructing the working condition simulation power line compression model is as follows:

[0040] Step 1, as shown in the attached Figure 2 As shown, the initial area segment is constructed with hanging points A and B as endpoints;

[0041] Step 2: Calculate the horizontal projection length l from the midpoint of the area segment to the hanging point A AP , based on the catenary equation, the corresponding sag and windage values ​​of the midpoint of the regional line segment are calculated to obtain the three-dimensional coordinates of the power line point corresponding to the midpoint of the regional line segment;

[0042] Step 3: Calculate the vertical distance D from the power line point corresponding to the midpoint of the regional line segment to the regional line segment. When the vertical distance D is greater than the maximum chord height difference threshold (the value in this embodiment is 5 mm), split the regional line segment (as shown in the attached figure). Figure 3 ) obtain a new area segment;

[0043] Step 4: Repeat steps 2-3 for the newly generated area segment until the vertical distance D is less than the maximum chord height difference threshold.

[0044] S3: Calculate the shortest distance based on the spatial line compression model.

[0045] Furthermore, based on the retrieval of the nearest point from the detection point to the discrete point set of the spatial line, the shortest distance from the detection point to the line segment of the area where the nearest point of the discrete point set of the spatial line is located is calculated.

[0046] The detection points are key position points in space for distance calculation with spatial linear facilities, and the detection points include but are not limited to tree points, building key points, and terrain obstacle points.

[0047] The space line discrete point set refers to a set of discrete points used to represent space linear facilities, through which the curve shape of the facilities is simplified and approximated. The space line discrete point set includes but is not limited to the transmission line discrete point set, the communication line discrete point set, the railway contact network discrete point set and the cableway discrete point set.

[0048] In one embodiment of the present invention, the detection point may be a tree point, and the space line discrete point set may be a power line discrete point set. Specifically, since the power line is expressed using regional line segments instead of discrete point sets, when calculating the distance from the tree point to the power line, it is necessary to further calculate the closest distance from the detection point to the regional line segment where the nearest point of the point set is located on the basis of searching the nearest point to the point set.

[0049] Furthermore, there are three cases for the method of calculating the closest distance.

[0050] Specifically, case 1: the nearest point from the detection point to the power line discrete point set is a point on the current line segment, and the vertical projection point of the detection point is within the range of the line segment. At this time, the closest distance from the detection point to the power line is the vertical distance (perpendicular distance) from the vertical projection point to the detection point, because the vertical point is on the regional line segment.

[0051] Case 2: The closest point from the detection point to the power line discrete point set is on the previous discrete point of the current line segment, and the vertical projection point of the detection point is located on the area line segment where the previous discrete point is located. In this case, the closest distance from the detection point to the power line is the perpendicular distance from the detection point to the line segment where the previous discrete point is located.

[0052] Case 3: The closest point from the detection point to the power line discrete point set is on the next discrete point of the current line segment, and the vertical projection point of the detection point is on the line segment of the region where the next discrete point is located. In this case, the closest distance from the detection point to the power line is the perpendicular distance from the detection point to the line segment where the next discrete point is located.

[0053] In another embodiment of the present invention, the detection point can also be a cable car cabin position point, and the shortest distance from the detection point to the cable car suspension cable is calculated. In this case, the cable car cabin position point represents the actual position of the cable car in space, and the cable car suspension cable simplifies the spatial representation of its actual path through a series of discrete point sets. To ensure the safety of the cable car during operation, we need to calculate the shortest distance from the cabin position point to the cable to determine whether the cable car cabin remains within a safe range to avoid collision or close contact with the cable.

[0054] Example 2, reference Figure 4-6 , as an embodiment of the present invention, provides a method for compressing a power line model for simulating transmission line operating conditions.

[0055] like Figure 4-6 As shown, where P is any detection point, P i is the nearest point in the P electric line discrete point set, P i-1 , P i+1 are the first and last points of P in the discrete point set, P″ i-1 , P″ i+1 P and P i-1 , P i+1 The perpendicular point on the line segment.

[0056] According to the theorem that the hypotenuse of a right triangle is greater than the right side, when the vertical point is located on the line segment of the power line area, the vertical line distance is less than the shortest distance from the detection point to the discrete point set of the power line. Therefore, Figure 4 Middle P″ i-1 For the nearest point, Figure 5 Middle P″ i+1 For the nearest point, Figure 6 Medium i is the nearest point.

[0057] Embodiment 3: In an exemplary embodiment, a power line model compression system for simulating transmission line conditions is also provided, including a line simulation module, a model building module and a calculation module.

[0058] Among them, the line simulation module performs power line simulation, determines the catenary equation, and determines the parameters of the catenary equation based on the point cloud data of the power line.

[0059] The model construction module regards the power lines between sampling points as line segment distribution, uses regional line segments instead of discrete point sets to express the power lines, and realizes the construction of the power line compression model for working condition simulation by controlling the chord height difference from the power line point corresponding to the middle point of the regional line segment to the regional line segment.

[0060] The calculation module calculates the shortest distance from the detection point to the line segment in the area where the nearest point of the power line discrete point set is located based on the power line compression model.

[0061] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program code.

[0062] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0063] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0064] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0065] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for compressing a power line model for simulating transmission line conditions, characterized in that: include: Perform space line simulation to determine the catenary equation and parameters; Construct a spatial line compression model; Calculate the shortest distance based on the spatial line compression model.

2. The method for compressing a power line model for simulating power line conditions according to claim 1, characterized in that: Before determining the catenary equation and parameters, the method further includes: Collect the point cloud data of the space line and determine the three-dimensional coordinates of the space line hanging points.

3. The method for compressing a power line model for simulating power line conditions according to claim 2, characterized in that: The construction of the spatial line compression model includes considering the electric lines between the sampling points as line segment distribution and determining the bundle conditions of the spatial line compression model based on the chord height difference.

4. The method for compressing a power line model for simulating power transmission line operating conditions according to claim 3, characterized in that: The calculating of the shortest distance includes, based on the retrieval of the nearest point from the detection point to the discrete point set of the space line, calculating the shortest distance from the detection point to the line segment of the area where the nearest point of the discrete point set of the space line is located.

5. The method for compressing a power line model for simulating power line conditions according to claim 2, characterized in that: The space lines are not limited to transmission lines; The determination of the catenary equation and parameters includes calculating the height difference angle from the three-dimensional coordinates of the hanging point, and the vertical load, horizontal load and stress value of the lowest point of the power line are determined by the design parameters of the power line, meteorological parameters under extreme working conditions and measured power line distribution through state equation calculation.

6. The method for compressing a power line model for simulating power transmission line operating conditions according to claim 3, characterized in that: The determining of the bundle condition of the spatial line compression model based on the chord height difference includes: Step 1, construct the initial area segment with hanging points A and B as endpoints; Step 2: Calculate the horizontal projection length l from the midpoint of the area segment to the hanging point A AP , based on the catenary equation, the corresponding sag and windage values ​​of the midpoint of the regional line segment are calculated to obtain the three-dimensional coordinates of the power line point corresponding to the midpoint of the regional line segment; Step 3, calculating the vertical distance from the power line point corresponding to the middle point of the regional line segment to the regional line segment, when the vertical distance is greater than the maximum chord height difference threshold, split the regional line segment to obtain a new regional line segment; Step 4: Repeat steps 2-3 for the newly generated area segment until the vertical distance is less than the maximum chord height difference threshold.

7. The method for compressing a power line model for simulating power transmission line operating conditions according to claim 4, characterized in that: The detection points include but are not limited to tree points, building key points and terrain obstacle points; The space line discrete point set includes but is not limited to an extreme working condition space line point set, a normal working condition space line point set and a space line dynamic deformation point set.

8. A power line model compression system for simulating transmission line conditions using the method according to any one of claims 1 to 7, characterized in that: include, The line simulation module performs power line simulation, determines the catenary equation, and determines the parameters of the catenary equation based on the point cloud data of the power line; The model building module regards the power lines between sampling points as line segment distribution, uses regional line segments instead of discrete point sets to express the power lines, and controls the chord height difference from the power line point corresponding to the middle point of the regional line segment to the regional line segment to achieve the construction of the power line compression model for working condition simulation; The calculation module calculates the shortest distance from the detection point to the line segment in the area where the nearest point of the power line discrete point set is located based on the power line compression model.

9. A computer device comprising: Memory and processor; The memory stores a computer program, characterized in that: when the processor executes the computer program, the steps of the power line model compression method for simulating the working condition of a transmission line are implemented as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the power line model compression method for simulating the working condition of a transmission line are implemented as described in any one of claims 1-7.

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