Safe distance early warning method and device based on heavy-load line

Abstract

The invention discloses a safety distance early warning method and device based on a heavy-load line, and relates to the technical field of safety distance early warning. The method comprises the following steps of collecting and analyzing related data of a heavy-load line, environment related data of the heavy-load line and dynamic scene related data, comparing a corrected safe distance evaluation coefficient of the heavy-load line with a dynamic scene early warning distance evaluation coefficient, transmitting an instruction to a safe distance early warning device, and performing early warning on the heavy-load line. And sending an early warning signal to the dynamic scene. According to the invention, the early warning processing scheme is provided according to the early warning signal, and the early warning signal and the early warning processing scheme are divided into three grades according to the comparison result. Therefore, the corresponding early warning signal and the early warning processing scheme are matched according to the comparison difference between the corrected safety distance evaluation coefficient of the heavy-load line and the dynamic scene early warning distance evaluation coefficient, the effect of improving the early warning accuracy of the early warning system is achieved, and the problem that the early warning accuracy of the early warning system is insufficient in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of safety distance warning, and particularly to a safety distance warning method and device based on a heavy-load line. Background Art

[0002] With the continuous growth of power demand and the continuous expansion of the power grid scale, heavy-load lines play an increasingly important role in the power system. However, the safe operation of heavy-load lines faces many challenges, such as the approach of obstacles and the influence of environmental factors. In order to ensure the safe operation of heavy-load lines, effective warning measures need to be taken.

[0003] In the prior art, heavy-load lines generally refer to transmission lines that carry a relatively high current load in the power system. Therefore, the safety distance warning for heavy-load lines is usually calculated based on the load of the line, environmental conditions, and safety standards to obtain the safety distance of the line, that is, the minimum safety distance between the line and the obstacle. Then, the real-time monitored distance is compared with the safety distance to determine whether to trigger a warning. After the warning is issued, necessary measures are taken to ensure safety.

[0004] For example, a power grid line hidden danger warning method and system disclosed in the invention patent with the publication number of CN118941088A includes: performing hidden danger analysis on a two-dimensional image of the line environment captured in real time based on a knowledge graph algorithm and a preset hidden danger analysis database to obtain a hidden danger analysis result; obtaining three-dimensional point cloud data of the line environment based on the hidden danger analysis result; calculating the distance between the hidden danger and the line based on the three-dimensional point cloud data of the line environment; and performing a warning judgment on the distance between the hidden danger and the line based on a safety threshold of a preset hidden danger to issue a line hidden danger warning.

[0005] For example, a lightning strike trip warning method for a distribution network line disclosed in the invention patent with the publication number of CN117436581A includes: step S1, calculating the lightning strike trip situation of the whole line according to the average height of the conductor, the span, the terrain and landform where the line is located, the average height of the lightning protection line, the grounding resistance, the lightning current amplitude, the adjacent lightning strike distance, and the lightning strike density through a pre-trained lightning strike trip warning model for a distribution network line based on a GA-BP neural network; step S2, performing hierarchical warning on the lightning strike trip of the distribution line according to the lightning strike trip situation of the whole line and a preset trip warning classification standard. The embodiments of the present invention efficiently and quickly realize the lightning strike trip warning of the distribution line.

[0006] However, in the process of implementing the technical solutions of the embodiments of the present application, it is found that the above technologies have at least the following technical problems:

[0007] In the prior art, dynamic scenarios require more frequent monitoring and maintenance of lines to cope with the impacts brought about by load changes. Only combining the data of large-load lines and the environmental data of large-load lines to give early warnings for dynamic obstacles close to large-load lines has the problem of insufficient accuracy of the early warning system. Summary of the Invention

[0008] By providing a safety distance early warning method and device based on large-load lines in the embodiments of the present application, the problem of insufficient accuracy of the early warning system in the prior art is solved, and the effect of improving the accuracy of the early warning system is achieved.

[0009] The embodiments of the present application provide a safety distance early warning method based on large-load lines, including the following steps: collecting relevant data of large-load lines, environmental relevant data of large-load lines, and dynamic scenario relevant data, analyzing the relevant data of large-load lines to obtain an initial safety distance evaluation coefficient of large-load lines, correcting the initial safety distance evaluation coefficient of large-load lines according to the environmental relevant data of large-load lines to obtain a corrected safety distance evaluation coefficient of large-load lines, analyzing the dynamic scenario relevant data to obtain a dynamic scenario early warning distance evaluation coefficient; comparing the corrected safety distance evaluation coefficient of large-load lines with the dynamic scenario early warning distance evaluation coefficient, transmitting an instruction to a safety distance early warning device according to the comparison result to send an early warning signal for the dynamic scenario; providing an early warning processing plan according to the early warning signal, dividing the early warning signal and the early warning processing plan into three levels according to the comparison result, and matching corresponding early warning signals and early warning processing plans according to the comparison difference between the corrected safety distance evaluation coefficient of large-load lines and the dynamic scenario early warning distance evaluation coefficient.

[0010] Further, the specific steps of collecting relevant data of large-load lines, environmental relevant data of large-load lines, and dynamic scenario relevant data are as follows: the relevant data of large-load lines include the load rate of large-load lines, the spacing of large-load lines, and the cross-sectional area of large-load lines; the environmental relevant data of large-load lines include environmental humidity, environmental wind speed, and environmental temperature; the dynamic scenario relevant data include the distance between the dynamic obstacle and the line, the moving speed of the dynamic obstacle, and the wind speed near the large-load line.

[0011] Further, the specific analysis process for analyzing the relevant data of high-load lines is as follows: The current of high-load lines is monitored in real time through a power monitoring system. The load factor of high-load lines is calculated based on the current of high-load lines. The spacing and cross-sectional area of high-load lines are obtained from the design drawings of high-load lines. The weight factors of the load factor of high-load lines, the spacing of high-load lines, and the cross-sectional area of high-load lines are obtained from the database. The load factor, spacing, and cross-sectional area of high-load lines are arranged in sequence according to the number of high-load lines. The load factor, spacing, and cross-sectional area of high-load lines are corrected using the corresponding weight factors, and the results of each correction process are coupled and averaged to obtain the initial safety distance evaluation coefficient of high-load lines.

[0012] Further, the specific steps for correcting the initial safety distance evaluation coefficient of high-load lines according to the environmental relevant data of high-load lines are as follows: Environmental monitoring devices including temperature and humidity sensors and anemometers are installed along high-load lines to monitor the environmental relevant data of high-load lines in real time. The environmental relevant data of high-load lines are transmitted to the warning system. A mathematical model of the relationship between environmental factors and safety distance is established, including the influence of environmental humidity on insulation performance, the influence of environmental wind speed on line vibration, and the influence of environmental temperature on line resistance and heat loss. The initial safety distance evaluation coefficient calculated from the load factor, spacing, and cross-sectional area is input into the warning system. The environmental relevant data of high-load lines are input into the mathematical model of the relationship between environmental factors and safety distance for calculation to obtain the environmental correction factor of the initial safety distance evaluation coefficient of high-load lines. The environmental correction factor of the initial safety distance evaluation coefficient of high-load lines is combined with the initial safety distance evaluation coefficient to obtain the corrected safety distance evaluation coefficient of high-load lines.

[0013] Further, the specific steps for analyzing the relevant data of the dynamic scenario are as follows: The distance between the dynamic obstacle and the line and the moving speed of the dynamic obstacle are monitored in real time through sensors in the dynamic scenario. The weight factors of the distance between the dynamic obstacle and the line, the moving speed of the dynamic obstacle, and the wind speed near the high-load line are obtained from the database. The distance between the dynamic obstacle and the line, the moving speed of the dynamic obstacle, and the wind speed near the high-load line are arranged in time series. The ratio of the real-time value to the standard value is processed for the distance between the dynamic obstacle and the line, the moving speed of the dynamic obstacle, and the wind speed near the high-load line respectively. The results of each ratio processing are corrected using the corresponding weight factors, and the results of each correction process are coupled and averaged to obtain the warning distance evaluation coefficient of the dynamic scenario.

[0014] Further, the specific comparison process of comparing the safety distance evaluation coefficient of the corrected large-load line with the dynamic scenario warning distance evaluation coefficient is as follows: Analyze the changes of the safety distance evaluation coefficient of the corrected large-load line and the dynamic scenario warning distance evaluation coefficient over time, and conduct a numerical comparison between the safety distance evaluation coefficient of the corrected large-load line and the dynamic scenario warning distance evaluation coefficient. If the dynamic scenario warning distance evaluation coefficient is less than or equal to the safety distance evaluation coefficient of the corrected large-load line, the warning system issues a warning signal for the dynamic scenario. If the dynamic scenario warning distance evaluation coefficient is greater than the safety distance evaluation coefficient of the corrected large-load line, the warning system continuously monitors the dynamic scenario.

[0015] Further, the specific transmission process of transmitting an instruction to the safety distance warning device according to the comparison result is as follows: Generate a warning instruction based on the analysis result, encode the warning instruction into a signal format recognizable by the warning device, confirm the transmission channel, transmit the warning instruction through the transmission channel to the warning device, and the warning device decodes the received signal and converts it into an execution instruction.

[0016] Further, the specific process of dividing the warning signal and the warning processing plan into three levels according to the comparison result is as follows: Divide the safety distance evaluation coefficient of the corrected large-load line into three extreme values according to a predefined ratio to obtain the first corrected safety distance evaluation coefficient of the large-load line, the second corrected safety distance evaluation coefficient of the large-load line, and the third corrected safety distance evaluation coefficient of the large-load line. If the dynamic scenario warning distance evaluation coefficient is less than or equal to the first corrected safety distance evaluation coefficient of the large-load line, the warning system issues a first-level warning signal for the dynamic scenario. If the dynamic scenario warning distance evaluation coefficient is less than or equal to the second corrected safety distance evaluation coefficient of the large-load line and greater than the first corrected safety distance evaluation coefficient of the large-load line, the warning system issues a second-level warning signal for the dynamic scenario. If the dynamic scenario warning distance evaluation coefficient is less than or equal to the third corrected safety distance evaluation coefficient of the large-load line and greater than the second corrected safety distance evaluation coefficient of the large-load line, the warning system issues a third-level warning signal for the dynamic scenario.

[0017] Further, the specific process of matching the corresponding warning signal and warning processing plan according to the comparison difference between the safety distance evaluation coefficient of the corrected large-load line and the dynamic scenario warning distance evaluation coefficient is as follows: Match the warning processing plan according to the warning signal level. When the warning system issues a first-level warning signal for the dynamic scenario, the warning system executes the first-level warning processing plan. When the warning system issues a second-level warning signal for the dynamic scenario, the warning system executes the second-level warning processing plan. When the warning system issues a third-level warning signal for the dynamic scenario, the warning system executes the third-level warning processing plan.

[0018] The embodiment of the present application provides a safety distance warning device based on a heavy-load line, including a sensor, a central processor, and an alarm device: Sensor module: used to collect relevant data of the heavy-load line, environmental relevant data of the heavy-load line, and dynamic scenario relevant data; Central processor module: used to analyze the relevant data of the heavy-load line, correct the initial safety distance evaluation coefficient of the heavy-load line according to the environmental relevant data of the heavy-load line, analyze the dynamic scenario relevant data, compare the corrected safety distance evaluation coefficient of the heavy-load line with the dynamic scenario warning distance evaluation coefficient, and divide the warning signal and the warning processing plan into three levels according to the comparison result; Alarm module: used to receive the instruction transmitted by the central processor and execute the warning processing plan.

[0019] One or more technical solutions provided in the embodiment of the present application have at least the following technical effects or advantages:

[0020] 1. By providing a warning processing plan according to the warning signal, dividing the warning signal and the warning processing plan into three levels according to the comparison result, so as to match the corresponding warning signal and warning processing plan according to the comparison difference between the corrected safety distance evaluation coefficient of the heavy-load line and the dynamic scenario warning distance evaluation coefficient, thereby achieving the effect of improving the warning accuracy of the warning system and effectively solving the problem of insufficient warning accuracy of the warning system in the prior art.

[0021] 2. By comparing the corrected safety distance evaluation coefficient of the heavy-load line with the dynamic scenario warning distance evaluation coefficient, and then transmitting an instruction to the safety distance warning device according to the comparison result, thereby achieving the effect of improving the safety of the heavy-load line and effectively solving the problem of insufficient safety of the heavy-load line in the prior art.

[0022] 3. By correcting the initial safety distance evaluation coefficient of the heavy-load line according to the environmental relevant data of the heavy-load line, so as to obtain the corrected safety distance evaluation coefficient of the heavy-load line, thereby achieving the effect of improving the environmental adaptability of the warning system and effectively solving the problem of insufficient environmental adaptability of the warning system in the prior art. Description of the Drawings

[0023] Figure 1 It is a flowchart of the safety distance warning method based on the heavy-load line provided by the embodiment of the present application;

[0024] Figure 2 It is a schematic diagram of the initial safety distance evaluation coefficient of the heavy-load line in the embodiment of the present application. Detailed Embodiment

[0025] Embodiments of the present application provide a safety distance warning method and device based on high-load lines, which solve the problem of insufficient warning accuracy in the prior art. By providing a warning processing solution according to the warning signal, the warning signal and the warning processing solution are divided into three levels according to the comparison result. Thus, the corresponding warning signal and warning processing solution are matched according to the comparison difference between the corrected safety distance evaluation coefficient of the high-load line and the dynamic scenario warning distance evaluation coefficient, achieving the effect of improving the warning accuracy of the warning system.

[0026] The technical solution in the embodiments of the present application is to solve the above problem of insufficient warning accuracy of the warning system, and the general idea is as follows:

[0027] By collecting and analyzing the data of the high-load line, its environment and the dynamic scenario, the initial safety distance evaluation coefficient is obtained, and then it is corrected according to the environmental data to obtain the corrected safety distance evaluation coefficient. Comparing the corrected safety distance evaluation coefficient with the dynamic scenario warning distance evaluation coefficient, sending an instruction to the warning device according to the result, emitting a warning signal, and providing a hierarchical warning processing solution, achieving the effect of improving the warning accuracy of the warning system.

[0028] To better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments.

[0029] As Figure 1 shown, it is a flowchart of the safety distance warning method based on high-load lines provided by the embodiments of the present application. This method is applied to a safety distance warning device based on high-load lines, and this method includes the following steps: collecting the relevant data of the high-load line, the environmental relevant data of the high-load line, and the dynamic scenario relevant data, analyzing the relevant data of the high-load line to obtain the initial safety distance evaluation coefficient of the high-load line, correcting the initial safety distance evaluation coefficient of the high-load line according to the environmental relevant data of the high-load line to obtain the corrected safety distance evaluation coefficient of the high-load line, analyzing the dynamic scenario relevant data to obtain the dynamic scenario warning distance evaluation coefficient; comparing the corrected safety distance evaluation coefficient of the high-load line with the dynamic scenario warning distance evaluation coefficient, transmitting an instruction to the safety distance warning device according to the comparison result, emitting a warning signal for the dynamic scenario; providing a warning processing solution according to the warning signal, dividing the warning signal and the warning processing solution into three levels according to the comparison result, and matching the corresponding warning signal and warning processing solution according to the comparison difference between the corrected safety distance evaluation coefficient of the high-load line and the dynamic scenario warning distance evaluation coefficient.

[0030] Further, the specific steps for collecting the relevant data of high-load lines, the environmental relevant data of high-load lines, and the dynamic scenario relevant data are as follows: The relevant data of high-load lines include the load rate of high-load lines, the spacing of high-load lines, and the cross-sectional area of high-load lines; the environmental relevant data of high-load lines include environmental humidity, environmental wind speed, and environmental temperature; the dynamic scenario relevant data include the distance between the dynamic obstacle and the line, the moving speed of the dynamic obstacle, and the wind speed near the high-load line.

[0031] In this embodiment, the load rate of the high-load line refers to the ratio of the actual current carried by the line to its rated current, which is obtained by real-time monitoring through the SCADA (Supervisory Control And Data Acquisition) system of the power system.

[0032] The spacing of the high-load line refers to the distance between the center lines of two adjacent conductors in the line, which can be obtained from the design drawings of the high-load line.

[0033] The cross-sectional area of the high-load line refers to the cross-sectional area of the high-load line (the total cross-sectional area of the conductors in the high-load line), which can be obtained from the design drawings of the high-load line.

[0034] The environmental humidity refers to the water vapor content in the air around the dynamic scenario, which can be real-time monitored by a humidity sensor.

[0035] The environmental wind speed refers to the wind speed at the location of the dynamic scenario, which can be real-time monitored by an anemometer.

[0036] The environmental temperature refers to the air temperature of the environment where the dynamic scenario is located, which can be real-time monitored by a temperature sensor.

[0037] The distance between the dynamic obstacle and the line refers to the vertical distance between the dynamic obstacle and the line, which can be measured by a laser rangefinder installed on the dynamic scenario.

[0038] The moving speed of the dynamic obstacle refers to the moving speed of the dynamic obstacle relative to the line, which can be directly obtained by a speed sensor.

[0039] Further, the specific analysis process for analyzing the relevant data of large-load lines is as follows: The current of large-load lines is monitored in real time through a power monitoring system. The load rate of large-load lines is calculated based on the current of large-load lines. The spacing and cross-sectional area of large-load lines are obtained from the design drawings of large-load lines. The weight factors of the load rate of large-load lines, the weight factors of the spacing of large-load lines, and the weight factors of the cross-sectional area of large-load lines are obtained from the database. The load rate of large-load lines, the spacing of large-load lines, and the cross-sectional area of large-load lines are arranged in a sequence according to the number of large-load lines. The load rate of large-load lines, the spacing of large-load lines, and the cross-sectional area of large-load lines are corrected using the corresponding weight factors, and the results of each correction process are coupled and averaged to obtain the initial safety distance evaluation coefficient of large-load lines.

[0040] In this embodiment, the specific method for obtaining the initial safety distance evaluation coefficient of large-load lines is as follows:

[0041]

[0042] β + γ + δ = 1;

[0043] In the formula, BNU represents the initial safety distance evaluation coefficient of large-load lines, which is used to evaluate the initial safety distance of large-load lines when not affected by the environment. A number of large-load line monitoring points are set, X0 = 1, 2, 3,..., a, where a represents the total number of large-load line monitoring points. represents the load rate of the large-load line under the X0th large-load line monitoring point, and α represents the weight factor of the load rate of the large-load line. represents the spacing of the large-load line under the X0th large-load line monitoring point, and β represents the weight factor of the spacing of the large-load line. represents the cross-sectional area of the large-load line under the X0th large-load line monitoring point, and γ represents the weight factor of the cross-sectional area of the large-load line.

[0044] When the system runs, the mapping table of weight factors is obtained from the database, and the corresponding weight factors are quickly extracted according to the current load rate of large-load lines, the spacing of large-load lines, and the cross-sectional area of large-load lines, such as the weight factor of the load rate of large-load lines, the weight factor of the spacing of large-load lines, and the weight factor of the cross-sectional area of large-load lines. This mapping table defines a clear set of association rules, which converts the specific values of the load rate of large-load lines, the spacing of large-load lines, and the cross-sectional area of large-load lines into their corresponding weight factors. Under this mechanism, whether it is to achieve one-to-one exact matching or the many-to-one relationship where multiple parameters converge into a single weight, the dynamic acquisition of weight factors can be effectively achieved.

[0045] In a specific embodiment, when a = 1, the data examples of the initial safety distance evaluation coefficient for high-load lines are as shown in the following table.

[0046] Table 1 Data examples of the initial safety distance evaluation coefficient for high-load lines

[0047]

[0048] When the weight factors of the load rate, the spacing, and the cross-sectional area of the high-load line are 0.8, 0.1, and 0.1 respectively, through Figure 2 and the data in Table 1, it can be seen that when the spacing and the cross-sectional area of the high-load line remain fixed, the greater the load rate of the high-load line, the greater the initial safety distance evaluation coefficient of the high-load line.

[0049] The higher the load rate of the high-load line will accelerate the aging of the insulating material, and a larger safety distance is required to ensure the insulation performance. The larger the spacing of the high-load line, the smaller the risk of electromagnetic interference and arc flashover between the conductors. A larger cross-sectional area can improve the current-carrying capacity of the line. Therefore, when the spacing of the high-load line is larger or the cross-sectional area of the high-load line is larger, the safety distance can be reserved slightly smaller.

[0050] Furthermore, the specific steps for correcting the initial safety distance evaluation coefficient of the high-load line according to the environmental-related data of the high-load line are as follows: Install environmental monitoring equipment including temperature and humidity sensors and an anemometer along the high-load line to monitor the environmental-related data of the high-load line in real time. Transmit the environmental-related data of the high-load line to the early warning system, and establish a mathematical model of the relationship between environmental factors and safety distance, including the influence of environmental humidity on insulation performance, the influence of environmental wind speed on line vibration, and the influence of environmental temperature on line resistance and heat loss. Input the initial safety distance evaluation coefficient calculated from the load rate, spacing, and cross-sectional area into the early warning system, and input the environmental-related data of the high-load line into the mathematical model of the relationship between environmental factors and safety distance for calculation to obtain the environmental correction factor of the initial safety distance evaluation coefficient of the high-load line. Combine the environmental correction factor of the initial safety distance evaluation coefficient of the high-load line with the initial safety distance evaluation coefficient to obtain the corrected safety distance evaluation coefficient of the high-load line.

[0051] In this embodiment, the specific method for obtaining the corrected safety distance evaluation coefficient of the high-load line is as follows:

[0052] DGV = BNU * ε;

[0053] Where, DGV represents the safety distance evaluation coefficient of the corrected large-load line, BNU represents the initial safety distance evaluation coefficient of the large-load line, which is used to evaluate the initial safety distance of the large-load line when not affected by the environment, and ε represents the environmental correction factor of the initial safety distance evaluation coefficient of the large-load line.

[0054] Install humidity and temperature sensors and anemometers along the large-load line, start the monitoring equipment, and collect environmental humidity, environmental wind speed, and environmental temperature data in real time. Transmit the collected data wirelessly to the early warning system. Establish a mathematical model for the relationship between environmental factors (humidity, wind speed, temperature) and safety distance, including the influence function of environmental humidity on insulation performance, the influence function of environmental wind speed on line vibration, and the influence function of environmental temperature on line resistance and heat loss. Input the initial safety distance evaluation coefficient of the large-load line into the early warning system, input the real-time monitored environmental-related data into the mathematical model of the relationship between environmental factors and safety distance, calculate the environmental correction factor, and combine the environmental correction factor with the initial safety distance evaluation coefficient to obtain the safety distance evaluation coefficient of the corrected large-load line.

[0055] Furthermore, the specific steps for analyzing the dynamic scenario-related data are as follows: Real-time monitor the distance between the dynamic obstacle and the line and the moving speed of the dynamic obstacle through sensors in the dynamic scenario. Obtain the weight factor of the distance between the dynamic obstacle and the line, the weight factor of the moving speed of the dynamic obstacle, and the weight factor of the wind speed near the large-load line from the database. Arrange the distance between the dynamic obstacle and the line, the moving speed of the dynamic obstacle, and the wind speed near the large-load line in a time series. Perform ratio processing between the real-time value and the standard value for the distance between the dynamic obstacle and the line, the moving speed of the dynamic obstacle, and the wind speed near the large-load line respectively. Perform correction processing on the results of each ratio processing using the corresponding weight factor, and couple and average the results of each correction processing to obtain the dynamic scenario early warning distance evaluation coefficient.

[0056] In this embodiment, the specific method for obtaining the dynamic scenario early warning distance evaluation coefficient is as follows:

[0057]

[0058] μ + ρ + σ = 1;

[0059] Where, FHB represents the dynamic scenario early warning distance evaluation coefficient, which is used to evaluate the early warning distance between the dynamic scenario and the large-load line. Set several time monitoring points, t0 = 1, 2, 3,..., a, where a represents the total number of time monitoring points. denotes the distance between the dynamic obstacle and the line at the t0th time monitoring point, μ denotes the weight factor of the distance between the dynamic obstacle and the line, and KMX0 denotes the distance between the standard dynamic obstacle and the line. denotes the speed at which the dynamic obstacle moves at the t0th time monitoring point, ρ denotes the weight factor of the speed at which the dynamic obstacle moves, and QTH0 denotes the speed at which the standard dynamic obstacle moves. denotes the wind speed near the high-load line at the t0th time monitoring point, σ denotes the weight factor of the wind speed near the high-load line, and HKJ0 denotes the wind speed near the standard high-load line.

[0060] When the system is running, obtain the mapping table of weight factors through the database, and quickly extract the corresponding weight factors according to the current distance between the dynamic obstacle and the line, the speed at which the dynamic obstacle moves, and the wind speed near the high-load line, such as the weight factor of the distance between the dynamic obstacle and the line, the weight factor of the speed at which the dynamic obstacle moves, and the weight factor of the wind speed near the high-load line. This mapping table defines a clear set of association rules, which converts the specific values of the distance between the dynamic obstacle and the line, the speed at which the dynamic obstacle moves, and the wind speed near the high-load line into their corresponding weight factors. Under this mechanism, whether it is to achieve an exact one-to-one match or a one-to-many relationship where multiple parameters converge into a single weight, the dynamic acquisition of weight factors can be effectively achieved.

[0061] The moving speed of the dynamic obstacle and the wind speed near the high-load line jointly affect the relative speed and trajectory between the obstacle and the line.

[0062] Furthermore, the specific comparison process of comparing the corrected safety distance evaluation coefficient of the high-load line with the dynamic scenario warning distance evaluation coefficient is as follows: Extract the scaling factor of the dynamic scenario warning distance evaluation coefficient from the database, use the scaling factor to scale the dynamic scenario warning distance evaluation coefficient to obtain the scaled dynamic scenario warning distance evaluation coefficient, and compare the corrected safety distance evaluation coefficient of the high-load line with the scaled dynamic scenario warning distance evaluation coefficient to determine whether the warning system needs to issue a warning signal for the dynamic scenario.

[0063] In this embodiment, data on the corrected safety distance evaluation coefficient of the heavy load line and the dynamic scenario warning distance evaluation coefficient are collected in real time. The scaling factor of the dynamic scenario warning distance evaluation coefficient is extracted from the database, and the dynamic scenario warning distance evaluation coefficient is scaled using the scaling factor to obtain the scaled dynamic scenario warning distance evaluation coefficient. The corrected safety distance evaluation coefficient of the heavy load line and the scaled dynamic scenario warning distance evaluation coefficient are compared in real time. If the scaled dynamic scenario warning distance evaluation coefficient is less than or equal to the corrected safety distance evaluation coefficient of the heavy load line, the following steps are executed: 1. Confirm that the warning condition is met and prepare to send a warning signal. 2. Check the status of the warning system to ensure that the system can work properly. 3. Send a warning signal. If the scaled dynamic scenario warning distance evaluation coefficient is greater than the corrected safety distance evaluation coefficient of the heavy load line, the following steps are executed: (1). Confirm that the current scenario has not reached the warning condition. (2). Continue to monitor the dynamic scenario and relevant environmental data. (3). Keep the warning system in a standby state and be ready to respond to possible changes at any time.

[0064] Further, the specific transmission process of transmitting the instruction to the safety distance warning device according to the comparison result is as follows: According to the analysis result, a warning instruction is generated, the warning instruction is encoded into a signal format recognizable by the warning device, the transmission channel is confirmed, and the warning instruction is transmitted to the warning device through the transmission channel. The warning device decodes the received signal and converts it into an execution instruction.

[0065] In this embodiment, the alarm instruction includes the alarm level, the type of danger, and the recommended emergency measures, and the continuous monitoring instruction includes maintaining the current monitoring frequency, not changing the warning status, and continuing to collect data.

[0066] According to the analysis result, a specific warning instruction is generated. The instruction usually contains information such as the warning level, type, and recommended measures. The warning instruction is encoded into a signal format that can be recognized by the warning device, and the availability of the transmission channel is confirmed, including wired and wireless transmissions. Send: The encoded instruction is sent through a communication interface (such as RS-232, RS-485, Ethernet, Wi-Fi, Bluetooth, etc.). Transmission: The instruction is transmitted through the selected transmission medium (such as cables, radio waves, etc.). Receive: The communication interface of the warning device receives the transmitted instruction. Decode: The warning device decodes the received signal and converts it into an executable instruction. After receiving the instruction, the warning device sends a confirmation signal back to the control center to verify that the instruction has been correctly received and processed. After receiving the confirmation signal, the control center records the transmission status, and the warning device executes corresponding operations according to the received instruction, such as activating an alarm, displaying a warning message, starting an emergency shutdown procedure, etc.

[0067] Further, the specific process of dividing the warning signal and the warning handling plan into three levels according to the comparison result is as follows: The corrected safety distance evaluation coefficient of the large-load line is divided into three extreme values according to a predefined ratio, obtaining the first corrected safety distance evaluation coefficient of the large-load line, the second corrected safety distance evaluation coefficient of the large-load line, and the third corrected safety distance evaluation coefficient of the large-load line. If the dynamic scenario warning distance evaluation coefficient is less than or equal to the first corrected safety distance evaluation coefficient of the large-load line, the warning system issues a first-level warning signal for the dynamic scenario. If the dynamic scenario warning distance evaluation coefficient is less than or equal to the second corrected safety distance evaluation coefficient of the large-load line and greater than the first corrected safety distance evaluation coefficient of the large-load line, the warning system issues a second-level warning signal for the dynamic scenario. If the dynamic scenario warning distance evaluation coefficient is less than or equal to the third corrected safety distance evaluation coefficient of the large-load line and greater than the second corrected safety distance evaluation coefficient of the large-load line, the warning system issues a third-level warning signal for the dynamic scenario.

[0068] In this embodiment, the basis for determining the division of the three warning levels, for example, according to the level of safety risk, the specific numerical boundaries for dividing the corrected safety distance evaluation coefficient of the large-load line into the first, second, and third corrected safety distance evaluation coefficients of the large-load line are determined. According to the predefined ratio and standard, the corrected safety distance evaluation coefficient is divided into three levels. The first corrected safety distance evaluation coefficient of the large-load line corresponds to the highest risk level. The second corrected safety distance evaluation coefficient of the large-load line corresponds to the medium risk level. The third corrected safety distance evaluation coefficient of the large-load line corresponds to the lowest risk level. By monitoring the system to obtain the warning distance evaluation coefficient of the dynamic scenario in real time, comparing the real-time monitored dynamic scenario warning distance evaluation coefficient with the corrected safety distance evaluation coefficients of the large-load line at the three levels. If the dynamic scenario warning distance evaluation coefficient is less than or equal to the first corrected safety distance evaluation coefficient of the large-load line, the warning system issues a first-level warning signal indicating the highest risk. If the dynamic scenario warning distance evaluation coefficient is less than or equal to the second corrected safety distance evaluation coefficient of the large-load line and greater than the first corrected safety distance evaluation coefficient of the large-load line, the warning system issues a second-level warning signal indicating the medium risk. If the dynamic scenario warning distance evaluation coefficient is less than or equal to the third corrected safety distance evaluation coefficient of the large-load line and greater than the second corrected safety distance evaluation coefficient of the large-load line, the warning system issues a third-level warning signal indicating the lower risk. Record the time of issuance, level, and corresponding dynamic scenario information of the warning signal, report the warning information to relevant management personnel and operators, and initiate corresponding emergency response plans and disposal measures according to the level of the warning signal.

[0069] Further, the specific process of matching the corresponding warning signal and warning processing plan according to the comparison difference between the safety distance evaluation coefficient of the corrected heavy-load line and the dynamic scenario warning distance evaluation coefficient is as follows: match the warning processing plan according to the warning signal level. When the warning system issues a first-level warning signal for the dynamic scenario, the warning system executes the first-level warning processing plan. When the warning system issues a second-level warning signal for the dynamic scenario, the warning system executes the second-level warning processing plan. When the warning system issues a third-level warning signal for the dynamic scenario, the warning system executes the third-level warning processing plan.

[0070] In this embodiment, the dynamic scenario includes a construction site. In the scenario of construction near a heavy-load line, the first-level warning processing plan includes immediately stopping construction: the system uses both wired and wireless connection transmission methods to send emergency stop signals (including distance, obstacle type, air humidity, wind speed, and load rate of the transmission line) multiple times, including sound alarms and visual alarms, and notifies the construction site to immediately stop all activities. Activate the emergency plan and execute the predetermined emergency evacuation procedure. Dispatch professional personnel to conduct on-site safety inspections to check for equipment damage or personnel casualties and take corresponding measures. After resuming construction, increase the monitoring frequency of the equipment and gradually transition the wired and wireless connection transmission methods to the wireless connection transmission method as the number of monitoring times increases. The second-level warning processing plan includes using a sound alarm to issue a warning to the construction site, including only distance and obstacle type, suspending construction activities, increasing the monitoring frequency, ensuring the reliability of the warning signal, and optimizing the receiving terminal of the wireless transmission by adjusting the parameters of the network layer and optimizing the Medium Access Control (MAC) layer protocol to reduce collisions and improve channel utilization. The third-level warning processing plan includes not issuing an alarm, storing the distance from the route in the database. When the third-level warning persists within the predefined time, reduce the monitoring frequency and data collection frequency. During peak construction, use an intelligent control system to perform adaptive scheduling of energy. Conduct preventive maintenance on the warning system to prevent accidents caused by equipment failures.

[0071] The safety distance warning device based on a heavy-load line provided by the embodiment of the present application includes: a sensor, a central processor, and an alarm device: a sensor module: used to collect relevant data of the heavy-load line, environmental relevant data of the heavy-load line, and relevant data of the dynamic scenario; a central processor module: used to analyze the relevant data of the heavy-load line, correct the initial safety distance evaluation coefficient of the heavy-load line according to the environmental relevant data of the heavy-load line, analyze the relevant data of the dynamic scenario, compare the corrected safety distance evaluation coefficient of the heavy-load line with the dynamic scenario warning distance evaluation coefficient, and divide the warning signal and warning processing plan into three levels according to the comparison result; an alarm module: used to receive the instruction transmitted by the central processor and execute the warning processing plan.

[0072] Those skilled in the art will understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0073] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for realizing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0074] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that realizes the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0075] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in one Figure 1 flow or multiple flows and / or blocks Figure 1 or multiple blocks.

[0076] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the present invention.

[0077] Obviously, those skilled in the art can make various modifications and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and variations.

Claims

1. A safety distance warning method based on a heavy load line, characterized in that: The following steps are involved: Collect relevant data of heavy-load lines, environmental data of heavy-load lines, and dynamic scene-related data, analyze the relevant data of heavy-load lines, obtain the initial safety distance assessment coefficient of heavy-load lines, correct the initial safety distance assessment coefficient of heavy-load lines according to the environmental data of heavy-load lines, obtain the corrected safety distance assessment coefficient of heavy-load lines, analyze the dynamic scene-related data, and obtain the dynamic scene warning distance assessment coefficient; Compare the corrected safety distance assessment coefficient of the heavy-load line with the dynamic scene warning distance assessment coefficient, transmit instructions to the safety distance warning device according to the comparison result, and issue a warning signal for the dynamic scene; Provide early warning processing plan according to the early warning signal, divide the early warning signal and early warning processing plan into three levels according to the comparison results, and match the corresponding early warning signal and early warning processing plan according to the comparison difference between the corrected safety distance assessment coefficient of the heavy load line and the dynamic scene early warning distance assessment coefficient.

2. The safety distance warning method based on heavy load lines according to claim 1 is characterized in that: The specific steps of collecting the relevant data of the heavy load line, the environment-related data of the heavy load line and the dynamic scene-related data are as follows: The relevant data of heavy-load lines include the load rate of heavy-load lines, the spacing of heavy-load lines, and the cross-sectional area of ​​heavy-load lines; Environmental data related to heavy-load lines include ambient humidity, ambient wind speed, and ambient temperature; The dynamic scene related data include the distance between the dynamic obstacle and the line, the speed of the dynamic obstacle movement and the wind speed near the heavy load line.

3. The safety distance warning method based on heavy load lines according to claim 1 is characterized in that: The specific analysis process of analyzing the relevant data of the heavy load line is as follows: The current of the heavy-load line is monitored in real time by the power monitoring system, the load rate of the heavy-load line is calculated by the current of the heavy-load line, the spacing of the heavy-load line and the cross-sectional area of ​​the heavy-load line are obtained by the design drawings of the heavy-load line, the weight factors of the load rate of the heavy-load line, the weight factors of the spacing of the heavy-load line and the weight factors of the cross-sectional area of ​​the heavy-load line are obtained from the database, the load rate of the heavy-load line, the spacing of the heavy-load line and the cross-sectional area of ​​the heavy-load line are arranged in sequence according to the number of heavy-load lines, the load rate of the heavy-load line, the spacing of the heavy-load line and the cross-sectional area of ​​the heavy-load line are corrected using the corresponding weight factors, and the results of each correction are coupled and averaged to obtain the initial safety distance assessment coefficient of the heavy-load line.

4. The safety distance warning method based on heavy load lines according to claim 1 is characterized in that: The specific steps of correcting the initial safety distance assessment coefficient of the heavy-load line according to the environmental data of the heavy-load line are: Environmental monitoring equipment including temperature and humidity sensors and anemometers are installed along the heavy-load lines to monitor the environmental data of the heavy-load lines in real time. The environmental data of the heavy-load lines are transmitted to the early warning system, and a mathematical model of the relationship between environmental factors and safety distance is established, including the influence of environmental humidity on insulation performance, the influence of environmental wind speed on line vibration, and the influence of ambient temperature on line resistance and heat loss. The initial safety distance assessment coefficient calculated from the load rate, spacing and cross-sectional area is input into the early warning system, and the environmental data of the heavy-load lines is input into the mathematical model of the relationship between environmental factors and safety distance for calculation to obtain the environmental correction factor of the initial safety distance assessment coefficient of the heavy-load lines. The environmental correction factor of the initial safety distance assessment coefficient of the heavy-load lines is combined with the initial safety distance assessment coefficient to obtain a corrected safety distance assessment coefficient for the heavy-load lines.

5. The safety distance warning method based on heavy load lines according to claim 1 is characterized in that: The specific steps of analyzing dynamic scene related data are: Through the sensors in the dynamic scene, the distance between the dynamic obstacle and the line and the speed of the dynamic obstacle are monitored in real time. The weight factors of the distance between the dynamic obstacle and the line, the weight factors of the speed of the dynamic obstacle and the wind speed near the heavy-load line are obtained from the database. The distance between the dynamic obstacle and the line, the speed of the dynamic obstacle and the wind speed near the heavy-load line are arranged in time series. The distance between the dynamic obstacle and the line, the speed of the dynamic obstacle and the wind speed near the heavy-load line are processed between the real-time value and the standard value respectively. The corresponding weight factor is used to correct the result of each proportion processing, and the results of each correction processing are coupled and averaged to obtain the dynamic scene warning distance evaluation coefficient.

6. The safety distance warning method based on heavy load lines according to claim 1 is characterized in that: The specific comparison process of comparing the corrected safety distance assessment coefficient of the heavy load line with the dynamic scene warning distance assessment coefficient is as follows: The scaling factor of the dynamic scene warning distance assessment coefficient is extracted from the database, and the dynamic scene warning distance assessment coefficient is scaled using the scaling factor to obtain the scaled dynamic scene warning distance assessment coefficient. The corrected heavy load line safety distance assessment coefficient is compared with the scaled dynamic scene warning distance assessment coefficient to determine whether the warning system needs to issue a warning signal for the dynamic scene.

7. The safety distance warning method based on heavy load lines according to claim 1 is characterized in that: The specific transmission process of transmitting the instruction to the safety distance warning device according to the comparison result is as follows: Based on the analysis results, a warning instruction is generated, encoded into a signal format recognized by the warning device, the transmission channel is confirmed, and the warning instruction is transmitted to the warning device through the transmission channel. The warning device decodes the received signal and converts it into an execution instruction.

8. The safety distance warning method based on heavy load lines according to claim 1 is characterized in that: The specific process of dividing the warning signals and warning processing schemes into three levels according to the comparison results is as follows: The revised heavy-load line safety distance assessment coefficient is divided into three extreme values ​​according to a predefined proportion, and the first revised heavy-load line safety distance assessment coefficient, the second revised heavy-load line safety distance assessment coefficient and the third revised heavy-load line safety distance assessment coefficient are obtained. If the dynamic scene warning distance assessment coefficient is less than or equal to the first revised heavy-load line safety distance assessment coefficient, the warning system issues a first-level warning signal for the dynamic scene. If the dynamic scene warning distance assessment coefficient is less than or equal to the second revised heavy-load line safety distance assessment coefficient and is greater than the first revised heavy-load line safety distance assessment coefficient, the warning system issues a second-level warning signal for the dynamic scene. If the dynamic scene warning distance assessment coefficient is less than or equal to the third revised heavy-load line safety distance assessment coefficient and is greater than the second revised heavy-load line safety distance assessment coefficient, the warning system issues a third-level warning signal for the dynamic scene.

9. The safety distance warning method based on heavy load lines according to claim 1, characterized in that: The specific process of matching the corresponding warning signal and warning processing scheme according to the comparison difference between the corrected safety distance assessment coefficient of the heavy load line and the dynamic scene warning distance assessment coefficient is as follows: The warning processing plan is matched according to the warning signal level. When the warning system issues a level one warning signal for a dynamic scene, the warning system executes the level one warning processing plan. When the warning system issues a level two warning signal for a dynamic scene, the warning system executes the level two warning processing plan. When the warning system issues a level three warning signal for a dynamic scene, the warning system executes the level three warning processing plan.

10. A device using the safety distance warning method based on a heavy load line as claimed in any one of claims 1 to 9, characterized in that: Includes sensors, central processing unit and alarm device: Sensor module: used to collect relevant data of heavy-load lines, environmental data of heavy-load lines, and dynamic scene-related data; Central processing unit module: used to analyze the relevant data of the heavy-load line, correct the initial safety distance assessment coefficient of the heavy-load line according to the environmental data of the heavy-load line, analyze the dynamic scene related data, compare the corrected safety distance assessment coefficient of the heavy-load line with the dynamic scene warning distance assessment coefficient, and divide the warning signal and warning processing plan into three levels according to the comparison results; Alarm module: used to receive instructions transmitted by the central processing unit and execute early warning processing solutions.

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