Intelligent pay-off equipment based on visual stretching equipment

Abstract

The invention relates to intelligent paying-off equipment based on visual stretching equipment, which comprises a video visual monitoring platform, a stress remote monitoring platform and a stress sensing element, and is characterized in that the video visual monitoring platform and the stress sensing element are respectively in wireless communication connection with the stress remote monitoring platform through a data transmission module; the stress sensing element comprises a stress sensing module and a visual module; the video visual monitoring platform realizes effective visual global management and control; the stress sensing element is installed on a pole tower, a pulley or other paying-off key parts and used for collecting on-site stress data and can accurately measure the stress conditions of various different construction operation points and operation tools. The stress remote monitoring platform adopts simulink to carry out stress simulation analysis in the paying-off process, and gives an alarm in real time when the stress data collected on site exceeds or exceeds a limit value; the system has the advantages of being reasonable in structure, achieving global management and control, being easy to install and suspend and reducing risks.

Description

Technical Field

[0001] The invention belongs to the technical field of power transmission line construction, and in particular relates to intelligent line-laying equipment based on a visualized tensioning device. Background Art

[0002] During the construction of traditional transmission lines and during the tensioning and laying out process, the whole process tension is generally used to keep the conductor at a certain tension and away from the ground. The tensioning and laying out is generally about 8 kilometers. There are many construction machines and tools used in the tensioning and laying out process, and there are many risk points that need to be monitored. Important and critical parts require personnel on site, and the number of personnel and construction intensity are large. In addition, the on-site coordination is not strong, and the conditions for overall control are not met. At present, the construction of transmission lines adopts the traditional pole assembly and tensioning and laying out. In the traditional construction process, there are great safety hazards, and a lot of manpower and material resources are consumed, which urgently need to be solved and improved. Therefore, it is very necessary to provide an intelligent laying-out equipment based on visual tensioning equipment with a reasonable structure, overall control, easy installation and suspension, and risk reduction. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art and to provide an intelligent wire-laying equipment based on a visual tensioning device which has a reasonable structure, realizes global control, is easy to install and hang, and reduces risks.

[0004] The object of the present invention is achieved as follows: an intelligent wire-laying equipment based on a visualized tensioning device comprises a video visualization monitoring platform, a force remote monitoring platform and a force sensing element, wherein the video visualization monitoring platform and the force sensing element respectively establish a wireless communication connection with the force remote monitoring platform through a data transmission module, and the force sensing element comprises a force sensing module and a visualization module; the video visualization monitoring platform is equipped with a visualization and force analysis model module, and the video visualization monitoring platform cooperates with the force sensing module and the visualization module to realize remote viewing of the on-site conditions at various locations during the wire-laying process and the force conditions of poles, tools and materials, so as to realize effective visualized global control; the force sensing element is installed on poles, pulleys or other key parts of wire-laying, and is used to collect on-site force data, and can accurately measure the force conditions of various construction work points and work tools, and can use various connection methods such as hoisting, support and suspension; the force remote monitoring platform adopts simulink to perform force simulation analysis of the wire-laying process, and combines the force data collected on-site to exceed the limit value, and gives a real-time alarm.

[0005] The stress remote monitoring platform consists of two parts: the upper-layer monitoring center system and the lower-layer single-chip microcomputer subsystems of each visual tensioning device; the monitoring center completes the human-computer interaction work and provides users with a visual monitoring interface. It can monitor the working status of each single visual tensioning device at any time, analyze and diagnose the operating status of each single machine, and issue instructions to the on-site visual tensioning device operator to adjust and control the working status of the equipment in time; the lower layer meets the requirements of the on-site operator, monitors the operating status of each visual tensioning device in real time, sends an alarm signal to the operator when an abnormal situation occurs, and receives adjustment instructions or suggestions issued by the monitoring center; the communication connection between the upper and lower layers is realized by GPRS access to the Internet.

[0006] The stress remote monitoring platform adopts a single chip microcomputer installed on each traction machine and tension machine of the visual tensioning equipment, collects the working signals of the traction machine and tension machine in real time, and transmits the collected data to the base station BS in wireless form through the GPRS wireless network card. The GPRS sends the data from the base station to the service support node SGSN, and the SGSN communicates with the gateway support node GGSN. The GGSN processes the received packet data accordingly and then sends it to the destination network Internet; the IP packet marked with the mobile station address from the Internet is received by the GGSN, then forwarded to the SGSN, and then transmitted to the mobile station, thereby realizing the mutual communication between GPRS and the Internet; the monitoring center with a fixed IP address is directly connected to the Internet, thereby realizing the communication between the traction machine, tension machine stand-alone system and the monitoring center.

[0007] The visualization module of the force sensing element is installed above the force sensing module. The force sensing module includes a cylinder, a slide plate is arranged inside the left side of the cylinder, and movable plates are arranged on the upper and lower sides of the left side of the cylinder. The movable plates are all "L"-shaped structures and are symmetrically arranged up and down. The right end of the movable plate is slidably connected to the slide plate through a slide seat, and the movable plate is connected to the slide seat through a fixing bolt; a wireless data transceiver is arranged above the movable plate, and a suction nozzle is arranged inside the left end of the movable plate, and the suction nozzle is connected to the movable plate through a nozzle mounting shaft, and a hanging clamp is arranged on the inner side of the movable plate, and the hanging clamp is movably connected to the movable plate through a rotating disk.

[0008] A mounting plate is arranged on the right side of the cylinder, a force sensor element is arranged on the right side of the mounting plate, a mounting column with a "T"-shaped structure is arranged above the cylinder, and the visualization module is connected to the force sensor module through the mounting column.

[0009] The visualization module includes a stabilizing plate, a connecting plate is arranged on the outside of the stabilizing plate, an open clamp ring connected to the mounting column is arranged on the outside of the connecting plate, and a locking screw hole is arranged inside one side of the open clamp ring; a fixing plate is arranged above the connecting plate, and a visualization module device is arranged on the inside of the fixing plate.

[0010] The video visualization monitoring platform adopts a three-dimensional visualization platform for power transmission lines based on a spatial information model, which specifically includes the following steps:

[0011] Step 1: Construct the 3D visualization framework architecture of transmission lines;

[0012] Step 2: Coordinate transformation method based on genetic algorithm;

[0013] Step 3: Case analysis.

[0014] The construction of the three-dimensional visualization framework architecture of the transmission line in step 1 is specifically as follows: the data layer of the platform structure establishes two independent databases, a three-dimensional model library and a geographic information library, and through a unified information data model, realizes the sharing and interaction of spatial information data models and three-dimensional model data, and can complete communication between different systems.

[0015] The coordinate conversion method based on genetic algorithm in step 2 is specifically as follows: the actual GPS spatial coordinates of the tower are rendered in the unified world coordinate system defined by the three-dimensional engine and first converted into plane coordinates. However, the current coordinate conversion algorithm will lead to pathological problems in the conversion process, causing the defect of large conversion errors. Therefore, the coordinate conversion method based on genetic algorithm is adopted, which specifically includes the following steps:

[0016] Step 2.1: Ill-conditioned problem analysis: The Bursa model is used for coordinate transformation, and its expression is: In the process of coordinate transformation using the Bursa model, ΔX, ΔY, ΔZ, ε x , ε y , ε zThe choice of the seven parameter values ​​​​of k determines the conversion accuracy. Theoretically, using coordinate base conversion and coordinate system conversion, under the condition that the amount of data is large enough and accurate, the conversion of different coordinate forms between any two coordinate bases can be realized. However, due to the selection of model parameters, observation errors, and numerical processing problems, a small change in data will cause a huge change in the solution, resulting in very unstable values ​​after conversion, making it difficult for some towers to accurately locate in the terrain; errors are inevitable when converting GPS coordinates into local coordinates. First, the GPS coordinates received by the device are not real coordinates, but coordinates after deflection according to the encryption algorithm, and the map coordinate deflection value is nonlinear, and the offset values ​​in different regions are also different; secondly, the reference points used to solve the seven parameters are difficult to distribute in different areas of the conversion range. If the reference point distribution range is too small, the correlation between its rotation parameters and translation parameters is very large, which will inevitably lead to a relatively large condition number in formula (1), making the conversion parameter error obtained by the least squares method obviously large and unstable, and it is difficult to meet the requirements of system positioning accuracy;

[0017] Step 2.2: Genetic algorithm: Genetic algorithm GA is a method of searching for the optimal solution by simulating the natural evolution process by learning the biological evolution process of natural selection and genetics mechanism. Selecting crossover and mutation constitutes genetic operations. Genetic algorithm includes five basic elements: chromosome encoding, setting the initial population, designing fitness function, crossover and mutation operations, and setting control parameters. When using genetic algorithm to solve problems, it is necessary to transform the problem of solving a nonlinear equation group to find seven parameters into the form of finding the optimal solution. First, establish the following objective function: min f(x) = min||V2-ΔV+(1+k)V1+RV1||(2), where,

[0018] The genetic algorithm in step 2.2 specifically includes the following steps:

[0019] Step 2.21: Chromosome encoding: Determine the range of the solution space as [m,n] and perform binary encoding according to the following formula: In the formula, g k is the kth bit value of the binary digital string; the values ​​of m and n are determined by the specific coordinate position and the characteristics of the sampling data;

[0020] Step 2.22: Initial population setting: The distribution of the initial population should cover the entire solution space as much as possible to avoid the algorithm falling into a local optimum;

[0021] Step 2.23: Fitness evaluation: The objective function is directly mapped into the fitness function, and the fitness function is defined as F(v) = 1 / f(v). The larger the individual fitness value, the better the individual is, and thus has more opportunities to reproduce offspring;

[0022] Step 2.24: Individual selection: In the process of evolutionary selection, it is hoped that the constraints of early selection will be smaller so that some individuals with poor fitness have the opportunity to participate in genetic iteration; on the contrary, in the later period, the selection constraints will be increased to speed up the convergence of the algorithm. The formula for the probability of individual selection is:

[0023]

[0024] Step 2.25: Crossover operator: The two-point crossover method is used with a crossover probability P c The operation of selecting a pair of parent binary digital strings and crossing them to replace the partial structures of the two attached individuals to generate a new individual;

[0025] Step 2.26: Mutation operator: Assume that the offspring individuals are s = a1a2...a m , and set the appropriate individual mutation probability p m , perform mutation operation according to the following formula:

[0026] Step 2.27: Evolve and iterate according to the process to finally obtain the optimal solution to the optimization problem.

[0027] Beneficial effects of the present invention: the present invention is an intelligent wire-laying equipment based on a visualized tensioning device. During use, the video visualization monitoring platform of the present invention remotely views the stress condition of the pole tower through the built-in visualization and stress analysis model module, thereby achieving effective visualized global control, reducing the number of personnel used at various locations, and greatly saving labor costs, thereby effectively saving construction funds; the stress remote monitoring platform of the present invention adopts simulink to perform stress simulation analysis during the wire-laying process, and combines the stress data collected on-site. Through the platform or mobile phone, the on-site conditions at various locations during the pole tower assembly and wire-laying process and the stress conditions of tools and materials can be viewed in real time. When the limit value is exceeded, an alarm is issued to the person in charge of the work and the auditor, and the person in charge of the work and the auditor promptly stop the on-site violations. , avoiding safety accidents; the force sensing element of the present invention can accurately measure the force conditions of various construction work points and work tools and is easy to hang, and can be used with various connection methods such as hoisting, support, and suspension, effectively realizing the accurate measurement and remote transmission of the force of each component; on the basis of the visual tensioning machine, the present invention adds force sensing elements of key line-laying parts such as poles, pulleys, etc., remotely collects the force conditions of key line-laying parts at various locations, collects data, and carries out tension line-laying simulation analysis of the whole process, so as to realize the visualization of the whole process and all channels of line-laying; the present invention can reduce the personnel input in traditional tension line-laying construction, reduce the risks in traditional tension line-laying construction, and realize the control of the whole process of line-laying construction; the present invention has the advantages of reasonable structure, global control, easy installation and suspension, and reduced risks. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 The block diagram of the intelligent wire-paying equipment based on the visualized stretching device of the present invention.

[0029] Figure 2 It is a structural schematic diagram of the force remote monitoring platform of the intelligent wire-laying equipment based on the visualized stretching device of the present invention.

[0030] Figure 3 It is a structural schematic diagram of the force sensing element of the intelligent wire-paying equipment based on the visualized stretching device of the present invention.

[0031] Figure 4 It is a structural schematic diagram of the force sensing module of the intelligent wire-paying equipment based on the visualized stretching device of the present invention.

[0032] Figure 5 It is a structural schematic diagram of the visualization module of the intelligent wire-laying equipment based on the visualization stretching device of the present invention.

[0033] Figure 6 The present invention is a flowchart of generating a real geographical route by using an intelligent line-laying equipment based on a visualized stretching device.

[0034] Figure 7 This is a flow chart of the genetic algorithm of the intelligent wire-paying equipment based on the visualized stretching device of the present invention.

[0035] Figure 8 It is a statistical diagram of coordinate conversion errors of three laying methods of the intelligent wire-laying equipment based on the visualized stretching device of the present invention.

[0036] In the figure: 100, force sensing element 1, force sensing module 11, cylinder 12, mounting plate 13, force sensor element 14, mounting column 15, slide plate 16, moving plate 17, slide seat 18, fixing bolt 19, wireless data transceiver 101, nozzle mounting shaft 102, suction nozzle 103, rotating disk 104, hanging clamp 2, visualization module 21, stabilizing plate 22, connecting plate 23, open clamp ring 24, locking screw hole 25, fixing plate 26, visualization module device. DETAILED DESCRIPTION

[0037] The present invention will be further described below in conjunction with the accompanying drawings.

[0038] Example 1

[0039] like Figure 1-8As shown, the intelligent wire-laying equipment based on the visualization tensioning device includes a video visualization monitoring platform, a force remote monitoring platform and a force sensing element. The video visualization monitoring platform and the force sensing element respectively establish wireless communication connections with the force remote monitoring platform through a data transmission module, and the force sensing element includes a force sensing module and a visualization module; the video visualization monitoring platform is built with a visualization and force analysis model module, and the video visualization monitoring platform cooperates with the force sensing module and the visualization module to realize remote viewing of the on-site conditions and the force conditions of poles, tools and materials in the wire-laying process, so as to realize effective visualization global control; the force sensing element is installed on the poles, pulleys or other key parts of the wire-laying, and is used to collect on-site force data, and can accurately measure the force conditions of various construction work points and work tools, and can use various connection methods such as hoisting, support and suspension; the force remote monitoring platform adopts simulink to perform force simulation analysis of the wire-laying process, and combines the force data collected on-site to exceed the limit value, and gives a real-time alarm.

[0040] The stress remote monitoring platform is composed of two parts: the upper monitoring center system and the lower single-chip microcomputer subsystems of each visual tensioning device; the monitoring center completes the human-computer interaction work and provides users with a visual monitoring interface, which can monitor the working status of each single visual tensioning device at any time, analyze and diagnose the operating status of each single machine, and issue instructions to the on-site visual tensioning device operator to adjust and control the working status of the equipment in time; the lower layer meets the requirements of the on-site operator, monitors the operating status of each visual tensioning device in real time, issues an alarm signal to the operator when an abnormal situation occurs, and receives the adjustment instructions or suggestions issued by the monitoring center; the communication connection between the upper and lower layers is realized by GPRS access to the Internet, and the entire system structure is as follows Figure 2 shown.

[0041] The stress remote monitoring platform adopts a single chip microcomputer installed on each traction machine and tension machine of the visual tensioning equipment, collects the working signals of the traction machine and tension machine in real time, and transmits the collected data to the base station BS in wireless form through the GPRS wireless network card. The GPRS sends the data from the base station to the service support node SGSN, and the SGSN communicates with the gateway support node GGSN. The GGSN processes the received packet data accordingly and then sends it to the destination network Internet; the IP packet marked with the mobile station address from the Internet is received by the GGSN, then forwarded to the SGSN, and then transmitted to the mobile station, thereby realizing the mutual communication between GPRS and the Internet; the monitoring center with a fixed IP address is directly connected to the Internet, thereby realizing the communication between the traction machine, tension machine stand-alone system and the monitoring center.

[0042] The visualization module 2 of the force sensing element 100 is installed above the force sensing module 1. The force sensing module 1 includes a cylinder 11. A slide plate 15 is arranged inside the left side of the cylinder 11. A movable plate 16 is arranged on both the upper and lower sides of the left side of the cylinder 11. The movable plates 16 are all "L"-shaped structures and are symmetrically arranged up and down. The right end of the movable plate 16 is slidably connected to the slide plate 15 through a slide seat 17, and the movable plate 16 is connected to the slide seat 17 through a fixing bolt 18; a wireless data transceiver 19 is arranged above the movable plate 16, and a suction nozzle 102 is arranged inside the left end of the movable plate 16. The suction nozzle 102 is connected to the movable plate 16 through a nozzle mounting shaft 101, and a hanging clamp 104 is arranged on the inner side of the movable plate 16, and the hanging clamp 104 is movably connected to the movable plate 16 through a rotating disk 103.

[0043] A mounting plate 12 is arranged on the right side of the cylinder 11 , a force sensor element 13 is arranged on the right side of the mounting plate 12 , a mounting column 14 of a “T”-shaped structure is arranged above the cylinder 11 , and the visualization module 2 is connected to the force sensor module 1 via the mounting column 14 .

[0044] The visualization module 2 includes a stabilizing plate 21, a connecting plate 22 is arranged on the outside of the stabilizing plate 21, an open clamp ring 23 connected to the mounting column 14 is arranged on the outside of the connecting plate 22, and a locking screw hole 24 is arranged inside one side of the open clamp ring 23; a fixing plate 25 is arranged above the connecting plate 22, and a visualization module device 26 is arranged on the inside of the fixing plate 25.

[0045] The present invention is an intelligent wire-laying equipment based on a visualized tensioning device. During use, the video visualization monitoring platform of the present invention remotely views the stress condition of the pole tower through the built-in visualization and stress analysis model module, thereby realizing effective visualized global control, reducing the number of personnel used in various locations, and greatly saving labor costs, thereby effectively saving construction funds. The stress remote monitoring platform of the present invention adopts simulink to perform stress simulation analysis during the wire-laying process, and combines the stress data collected on site. Through the platform or mobile phone, the on-site conditions at various locations during the pole tower assembly and wire-laying process and the stress conditions of tools and materials can be viewed in real time. When the limit value is exceeded, an alarm is issued to the person in charge of the work and the auditor, and the person in charge of the work and the auditor promptly stop the on-site violations to avoid safety accidents. The accident occurred; the force sensing element of the present invention can accurately measure the force conditions of various construction work points and work tools and is easy to hang, and can be used with various connection methods such as lifting, supporting, and hanging, so as to effectively realize the accurate measurement and remote transmission of the force of each component; on the basis of the visual tensioning machine, the present invention adds force sensing elements of key line-laying parts such as poles, pulleys, etc., remotely collects the force conditions of key line-laying parts at various locations, collects data, and carries out tension line-laying simulation analysis of the whole process, so as to realize the visualization of the whole process and all channels of line-laying; the present invention can reduce the personnel input in traditional tension line-laying construction, reduce the risks in traditional tension line-laying construction, and realize the control of the whole process of line-laying construction; the present invention has the advantages of reasonable structure, global control, easy installation and suspension, and reduced risks.

[0046] Example 2

[0047] like Figure 1-8 As shown, the intelligent wire-laying equipment based on the visualization tensioning device includes a video visualization monitoring platform, a force remote monitoring platform and a force sensing element. The video visualization monitoring platform and the force sensing element respectively establish wireless communication connections with the force remote monitoring platform through a data transmission module, and the force sensing element includes a force sensing module and a visualization module; the video visualization monitoring platform is built with a visualization and force analysis model module, and the video visualization monitoring platform cooperates with the force sensing module and the visualization module to realize remote viewing of the on-site conditions and the force conditions of poles, tools and materials in the wire-laying process, so as to realize effective visualization global control; the force sensing element is installed on the poles, pulleys or other key parts of the wire-laying, and is used to collect on-site force data, and can accurately measure the force conditions of various construction work points and work tools, and can use various connection methods such as hoisting, support and suspension; the force remote monitoring platform adopts simulink to perform force simulation analysis of the wire-laying process, and combines the force data collected on-site to exceed the limit value, and gives a real-time alarm.

[0048] The video visualization monitoring platform adopts a three-dimensional visualization platform for power transmission lines based on a spatial information model, which specifically includes the following steps:

[0049] Step 1: Construct the 3D visualization framework architecture of transmission lines;

[0050] Step 2: Coordinate transformation method based on genetic algorithm;

[0051] Step 3: Case analysis.

[0052] The construction of the three-dimensional visualization framework architecture of the transmission line in step 1 is specifically as follows: the data layer of the platform structure establishes two independent databases, a three-dimensional model library and a geographic information library, and through a unified information data model, realizes the sharing and interaction of spatial information data models and three-dimensional model data, and can complete communication between different systems.

[0053] The coordinate conversion method based on genetic algorithm in step 2 is specifically as follows: the actual GPS spatial coordinates of the tower are rendered in the unified world coordinate system defined by the three-dimensional engine and first converted into plane coordinates. However, the current coordinate conversion algorithm will lead to pathological problems in the conversion process, causing the defect of large conversion errors. Therefore, the coordinate conversion method based on genetic algorithm is adopted, which specifically includes the following steps:

[0054] Step 2.1: Ill-conditioned problem analysis: The Bursa model is used for coordinate transformation, and its expression is: In the process of coordinate transformation using the Bursa model, ΔX, ΔY, ΔZ, ε x , ε y , ε z The choice of the seven parameter values ​​​​of k determines the conversion accuracy. Theoretically, using coordinate base conversion and coordinate system conversion, under the condition that the amount of data is large enough and accurate, the conversion of different coordinate forms between any two coordinate bases can be realized. However, due to the selection of model parameters, observation errors, and numerical processing problems, a small change in data will cause a huge change in the solution, resulting in very unstable values ​​after conversion, making it difficult for some towers to accurately locate in the terrain; errors are inevitable when converting GPS coordinates into local coordinates. First, the GPS coordinates received by the device are not real coordinates, but coordinates after deflection according to the encryption algorithm, and the map coordinate deflection value is nonlinear, and the offset values ​​in different regions are also different; secondly, the reference points used to solve the seven parameters are difficult to distribute in different areas of the conversion range. If the reference point distribution range is too small, the correlation between its rotation parameters and translation parameters is very large, which will inevitably lead to a relatively large condition number in formula (1), making the conversion parameter error obtained by the least squares method obviously large and unstable, and it is difficult to meet the requirements of system positioning accuracy;

[0055] Step 2.2: Genetic Algorithm: Genetic Algorithm GA is a method of searching for the optimal solution by simulating the natural evolution process by learning the biological evolution process of natural selection and genetics. Selecting crossover and mutation constitutes genetic operations. The genetic algorithm includes five basic elements: chromosome encoding, setting the initial population, designing the fitness function, crossover and mutation operations, and setting control parameters. The basic process is as follows: Figure 7 As shown, when using genetic algorithms to solve problems, it is necessary to transform the problem of solving a nonlinear system of equations to find seven parameters into the form of finding the optimal solution. First, the following objective function is established: min f(x) = min||V2-ΔV+(1+k)V1+RV1||(2), where

[0056] The genetic algorithm in step 2.2 specifically includes the following steps:

[0057] Step 2.21: Chromosome encoding: Determine the range of the solution space as [m,n] and perform binary encoding according to the following formula: In the formula, g k is the k-th bit value (gene value) of the binary digital string; the values ​​of m and n are determined by the specific coordinate position and the characteristics of the sampling data. According to engineering practice experience, accurate definition of the parameter value constraint range is very helpful to improve the optimization speed;

[0058] Step 2.22: Initial population setting: The distribution of the initial population should cover the entire solution space as much as possible to avoid the algorithm falling into a local optimum;

[0059] Step 2.23: Fitness evaluation: The objective function is directly mapped into the fitness function, and the fitness function is defined as F(v) = 1 / f(v). The larger the individual fitness value, the better the individual is, and thus has more opportunities to reproduce offspring;

[0060] Step 2.24: Individual selection: In the process of evolutionary selection, it is hoped that the constraints of early selection will be smaller so that some individuals with poor fitness have the opportunity to participate in genetic iteration; on the contrary, in the later period, the selection constraints will be increased to speed up the convergence of the algorithm. The formula for the probability of individual selection is:

[0061]

[0062] Step 2.25: Crossover operator: The two-point crossover method is used with a crossover probability P c The operation of selecting a pair of parent binary digital strings and crossing them to replace the partial structures of the two attached individuals to generate a new individual;

[0063] Step 2.26: Mutation operator: Assume that the offspring individuals are s = a1a2...a m, and set the appropriate individual mutation probability p m , perform mutation operation according to the following formula:

[0064] Step 2.27: Evolve and iterate according to the process to finally obtain the optimal solution to the optimization problem.

[0065] In this embodiment, example analysis: To verify the superiority of genetic algorithm in solving the ill-conditioned problem of coordinate transformation, the present invention uses 200 common points in a certain area to repeat the simulation 200 times, and records the error between the transformed coordinates and the known value. The error is calculated as: At the same time, in order to verify the effectiveness of the method of the present invention, the least square method, decoupling method and the method of the present invention are applied to coordinate transformation, and the transformation errors are statistically analyzed. The results are as follows: Figure 8 As shown;

[0066] From the comparison results, we can see that: ① The overall accuracy of the coordinate transformation obtained by the decoupling algorithm is higher than that of the least squares method, but if consistency distortion occurs, the accuracy will be greatly reduced; ② Due to the morbidity of the conversion coefficient, the influence of the error is magnified when the inversion is obtained, so the accuracy of the least squares method is relatively poor; ③ When using the genetic algorithm to solve the ill-conditioned equation, the genetic operation fitting method is directly performed on the objective function instead of inverting the transformation matrix, thus avoiding the morbid problems caused by matrix non-full rank, complex collinearity, etc., so the result is more accurate.

[0067] The present invention is an intelligent wire-laying equipment based on a visualized tensioning device. During use, the video visualization monitoring platform of the present invention remotely views the stress condition of the pole tower through the built-in visualization and stress analysis model module, thereby realizing effective visualized global control, reducing the number of personnel used in various locations, and greatly saving labor costs, thereby effectively saving construction funds. The stress remote monitoring platform of the present invention adopts simulink to perform stress simulation analysis during the wire-laying process, and combines the stress data collected on site. Through the platform or mobile phone, the on-site conditions at various locations during the pole tower assembly and wire-laying process and the stress conditions of tools and materials can be viewed in real time. When the limit value is exceeded, an alarm is issued to the person in charge of the work and the auditor, and the person in charge of the work and the auditor promptly stop the on-site violations to avoid safety accidents. The accident occurred; the force sensing element of the present invention can accurately measure the force conditions of various construction work points and work tools and is easy to hang, and can be used with various connection methods such as lifting, supporting, and hanging, so as to effectively realize the accurate measurement and remote transmission of the force of each component; on the basis of the visual tensioning machine, the present invention adds force sensing elements of key line-laying parts such as poles, pulleys, etc., remotely collects the force conditions of key line-laying parts at various locations, collects data, and carries out tension line-laying simulation analysis of the whole process, so as to realize the visualization of the whole process and all channels of line-laying; the present invention can reduce the personnel input in traditional tension line-laying construction, reduce the risks in traditional tension line-laying construction, and realize the control of the whole process of line-laying construction; the present invention has the advantages of reasonable structure, global control, easy installation and suspension, and reduced risks.

Claims

1. Intelligent wire-laying equipment based on visual stretching equipment, which includes a video visualization monitoring platform, a force remote monitoring platform and a force sensing element, and is characterized by: The video visualization monitoring platform and the force sensing element respectively establish wireless communication connections with the force remote monitoring platform through the data transmission module. The force sensing element includes a force sensing module and a visualization module. The video visualization monitoring platform is equipped with a visualization and force analysis model module. The video visualization monitoring platform cooperates with the force sensing module and the visualization module to realize remote viewing of the on-site conditions at various locations during the line-laying process and the stress conditions of poles, towers, tools and materials, thereby realizing effective visual global control. The force sensing element is installed on poles, pulleys or other key parts of line-laying to collect on-site force data, and can accurately measure the stress conditions of various construction work points and work tools, and can use various connection methods such as hoisting, supporting and hanging. The force remote monitoring platform adopts simulink to perform force simulation analysis of the line-laying process, and gives a real-time alarm when the force data collected on-site exceeds the limit value.

2. The intelligent wire-laying equipment based on the visual stretching device according to claim 1, characterized in that: The stress remote monitoring platform consists of two parts: Composition: the upper-layer monitoring center system and the lower-layer single-chip microcomputer subsystems of various visual stretching equipment; the monitoring center completes the human-computer interaction work and provides users with a visual monitoring interface. It can monitor the working status of each single visual stretching equipment at any time, analyze and diagnose the operating status of each single machine, and issue instructions to the on-site visual stretching equipment operator to adjust and control the working status of the equipment in time; the lower layer meets the requirements of the on-site operator, monitors the operating status of each visual stretching equipment in real time, sends an alarm signal to the operator when an abnormal situation occurs, and receives adjustment instructions or suggestions issued by the monitoring center; the communication connection between the upper and lower layers is realized by GPRS access to the Internet.

3. The intelligent wire-laying equipment based on the visual stretching device according to claim 2, characterized in that: The stress remote monitoring platform adopts a single chip microcomputer installed on each traction machine and tension machine of the visual tensioning equipment, collects the working signals of the traction machine and tension machine in real time, and transmits the collected data to the base station BS in wireless form through the GPRS wireless network card. The GPRS sends the data from the base station to the service support node SGSN, and the SGSN communicates with the gateway support node GGSN. The GGSN processes the received packet data accordingly and then sends it to the destination network Internet; the IP packet marked with the mobile station address from the Internet is received by the GGSN, then forwarded to the SGSN, and then transmitted to the mobile station, thereby realizing the mutual communication between GPRS and the Internet; The monitoring center with a fixed IP address is directly connected to the Internet, thus realizing the communication between the traction machine, tension machine stand-alone system and the monitoring center.

4. The intelligent wire-laying equipment based on the visual stretching device according to claim 1, characterized in that: The visualization module of the force sensing element is installed above the force sensing module. The force sensing module includes a cylinder, a slide plate is arranged inside the left side of the cylinder, and movable plates are arranged on the upper and lower sides of the left side of the cylinder. The movable plates are all "L"-shaped structures and are symmetrically arranged up and down. The right end of the movable plate is slidably connected to the slide plate through a slide seat, and the movable plate is connected to the slide seat through a fixing bolt; a wireless data transceiver is arranged above the movable plate, and a suction nozzle is arranged inside the left end of the movable plate, and the suction nozzle is connected to the movable plate through a nozzle mounting shaft, and a hanging clamp is arranged on the inner side of the movable plate, and the hanging clamp is movably connected to the movable plate through a rotating disk.

5. The intelligent wire-laying equipment based on the visual stretching device according to claim 4, characterized in that: A mounting plate is arranged on the right side of the cylinder, a force sensor element is arranged on the right side of the mounting plate, a mounting column with a "T"-shaped structure is arranged above the cylinder, and the visualization module is connected to the force sensor module through the mounting column.

6. The intelligent wire-laying equipment based on the visual stretching device according to claim 5, characterized in that: The visualization module includes a stabilizing plate, a connecting plate is arranged on the outside of the stabilizing plate, an open clamp ring connected to the mounting column is arranged on the outside of the connecting plate, and a locking screw hole is arranged inside one side of the open clamp ring; a fixing plate is arranged above the connecting plate, and a visualization module device is arranged on the inside of the fixing plate.

7. The intelligent wire-laying equipment based on the visual stretching device according to claim 1, characterized in that: The video visualization monitoring platform adopts a three-dimensional visualization platform for power transmission lines based on a spatial information model, which specifically includes the following steps: Step 1: Construct the 3D visualization framework architecture of transmission lines; Step 2: Coordinate transformation method based on genetic algorithm; Step 3: Case analysis.

8. The intelligent wire-laying equipment based on the visual stretching device according to claim 7, characterized in that: The construction of the three-dimensional visualization framework architecture of the transmission line in step 1 is specifically as follows: the data layer of the platform structure establishes two independent databases, a three-dimensional model library and a geographic information library, and through a unified information data model, realizes the sharing and interaction of spatial information data models and three-dimensional model data, and can complete communication between different systems.

9. The intelligent wire-laying equipment based on the visual stretching device according to claim 8, characterized in that: The coordinate conversion method based on genetic algorithm in step 2 is specifically as follows: the actual GPS spatial coordinates of the tower are rendered in the unified world coordinate system defined by the three-dimensional engine and first converted into plane coordinates. However, the current coordinate conversion algorithm will lead to pathological problems in the conversion process, causing the defect of large conversion errors. Therefore, the coordinate conversion method based on genetic algorithm is adopted, which specifically includes the following steps: Step 2.1: Ill-conditioned problem analysis: The Bursa model is used for coordinate transformation, and its expression is: In the process of coordinate transformation using the Bursa model, ΔX, ΔY, ΔZ, ε x , ε y , ε z The choice of the seven parameter values ​​​​of k determines the conversion accuracy. Theoretically, using coordinate base conversion and coordinate system conversion, under the condition that the data volume is large enough and accurate, the conversion of different coordinate forms between any two coordinate bases can be realized. However, due to the selection of model parameters, observation errors, and numerical processing problems, a small change in data will cause a huge change in the solution, resulting in very unstable values ​​after conversion, making it difficult for some towers to accurately locate in the terrain; errors are inevitable when converting GPS coordinates into local coordinates. First, the GPS coordinates received by the device are not real coordinates, but coordinates after deflection according to the encryption algorithm, and the map coordinate deflection value is nonlinear, and the offset values ​​in different regions are also different; secondly, the reference points used to solve the seven parameters are difficult to distribute in different areas of the conversion range. If the reference point distribution range is too small, the correlation between its rotation parameters and translation parameters is very large, which will inevitably lead to a relatively large condition number in formula (1), making the conversion parameter error obtained by the least squares method obviously large and unstable, and it is difficult to meet the requirements of system positioning accuracy; Step 2.2: Genetic algorithm: Genetic algorithm GA is a method of searching for the optimal solution by simulating the natural evolution process by learning the biological evolution process of natural selection and genetics mechanism. Selecting crossover and mutation constitutes genetic operations. Genetic algorithm includes five basic elements: chromosome encoding, setting the initial population, designing fitness function, crossover and mutation operations, and setting control parameters. When using genetic algorithm to solve problems, it is necessary to transform the problem of solving a nonlinear equation group to find seven parameters into the form of finding the optimal solution. First, establish the following objective function: minf(x)=min||V2-ΔV+(1+k)V1+RV1||(2), where, 10. The intelligent wire-laying equipment based on the visual stretching device according to claim 9, characterized in that: The genetic algorithm in step 2.2 specifically includes the following steps: Step 2.21: Chromosome encoding: Determine the range of the solution space as [m,n] and perform binary encoding according to the following formula: In the formula, g k is the kth bit value of the binary digital string; the values ​​of m and n are determined by the specific coordinate position and the characteristics of the sampling data; Step 2.22: Initial population setting: The distribution of the initial population should cover the entire solution space as much as possible to avoid the algorithm falling into a local optimum; Step 2.23: Fitness evaluation: The objective function is directly mapped into the fitness function, and the fitness function is defined as F(v) = 1 / f(v). The larger the individual fitness value, the better the individual is, and thus has more opportunities to reproduce offspring; Step 2.24: Individual selection: In the process of evolutionary selection, it is hoped that the constraints of early selection will be smaller so that some individuals with poor fitness have the opportunity to participate in genetic iteration; on the contrary, in the later period, the selection constraints will be increased to speed up the convergence of the algorithm. The formula for the probability of individual selection is: Step 2.25: Crossover operator: The two-point crossover method is used with a crossover probability P c The operation of selecting a pair of parent binary digital strings and crossing them to replace the partial structures of the two attached individuals to generate a new individual; Step 2.26: Mutation operator: Assume that the offspring individuals are s = a1a2...a m , and set the appropriate individual mutation probability p m , perform mutation operation according to the following formula: Step 2.27: Evolve and iterate according to the process to finally obtain the optimal solution to the optimization problem.

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