A cross-border power transmission line construction management and control method, system, device and storage medium

Abstract

The application discloses a cross-border power transmission line construction management and control method, system, device and storage medium, relates to the technical field of cross-border power transmission construction management and control, and comprises the following steps: acquiring construction whole-process data; adopting a multi-factor coupling risk assessment algorithm to perform cross-span construction risk grading calculation, and obtaining risk early warning data; performing cross-border construction collaborative interaction for a cross-border construction subject, and outputting cross-border collaborative management and control information; collecting process technology parameters and quality detection data, and establishing process quality traceability chain data; combining orthographic images, laser radar point cloud data and multi-class disturbance source space coordinate information to obtain ecological disturbance information; and based on a three-dimensional digital twin model, superimposing various types of business data to develop digital twin simulation deduction management and control. The scheme can realize full-element and full-cycle digital management and control of cross-border cross-span construction, improve risk early warning precision and construction quality management and control level, take into account ecological protection, and is suitable for cross-border power transmission engineering construction in complex environments.

Description

Technical Field

[0001] This application relates to the field of cross-border power transmission construction management and control technology, and in particular to a method, system, equipment and storage medium for cross-border power transmission line construction management and control. Background Technology

[0002] With the continuous advancement of the digital transformation of the power grid, digital twin technology has been widely applied in the field of power grid infrastructure construction management and control. Existing power grid infrastructure process management and control methods based on digital twin technology construct a digital twin of the project's spatiotemporal sequence, collect three-dimensional feature points at the construction site, and compare them with the feature data of the twin model to achieve automated verification of construction progress. This effectively reduces the cost of manual verification and provides digital support for the progress management of conventional power grid infrastructure projects.

[0003] However, this traditional approach has significant shortcomings when applied to critical cross-border transmission line construction scenarios. First, it is only applicable to conventional power grid infrastructure projects within a single jurisdiction, failing to consider the multi-entity, cross-regional, and inconsistent standardization characteristics of cross-border collaborative transmission projects. It lacks cross-border collaborative scheduling and safety data exchange mechanisms, thus failing to support collaborative management of cross-border projects. Second, existing solutions focus solely on construction progress comparison and control, offering a single dimension of risk management. This makes them unsuitable for high-risk cross-border construction scenarios and unable to address the complex construction risks posed by the unique geology and climate of tropical rainforests. Third, current sensing methods are limited, relying solely on video image acquisition and 3D feature point extraction. In cross-border communication bandwidth-constrained scenarios, this results in large data transmission volumes and delayed responses to on-site anomalies. Fourth, existing technologies lack sufficient coverage for quality control throughout the entire construction process and fail to consider construction constraints in special ecological areas. This results in insufficient comprehensive control coverage and adaptability, making it difficult to meet the multi-dimensional construction management requirements of cross-border transmission projects.

[0004] In summary, existing digital twin management and control technologies for power grid infrastructure have limited adaptability and comprehensive management and control capabilities, and cannot meet the integrated management and control needs of cross-border collaborative construction, risk control in complex environments, real-time perception and processing, construction quality and ecological protection.

[0005] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0006] The main purpose of this application is to provide a method, system, equipment and storage medium for construction management and control of cross-border transmission lines, which aims to solve the technical problems of limited adaptability and comprehensive management and control capabilities of existing digital twin management and control technologies for power grid infrastructure, which cannot meet the integrated management and control needs of cross-border collaborative construction, risk control in complex environments, real-time perception and processing, construction quality and ecological protection.

[0007] To achieve the above objectives, this application proposes a method for construction management and control of cross-border transmission lines, the method comprising: Obtain data throughout the entire construction process; Based on the data from the entire construction process, a multi-factor coupled risk assessment algorithm is used to calculate the risk classification across the construction process, and risk warning data is obtained. It enables cross-border construction entities to negotiate construction plans, synchronize progress, issue work instructions, and coordinate emergency responses, while also providing cross-border collaborative management information. Collect process parameters and quality inspection data for each construction procedure, and establish a process quality traceability chain data; Collect orthophotos and lidar point cloud data, and combine them with spatial coordinate information of multiple disturbance sources to obtain ecological disturbance information; Based on a pre-built three-dimensional digital twin model, the aforementioned risk warning data, cross-border collaborative management and control information, process quality traceability chain data, and ecological disturbance information are overlaid to implement digital twin simulation and control.

[0008] In one embodiment, the step of using a multi-factor coupled risk assessment algorithm to perform risk classification calculations on the construction process and obtain risk warning data includes: Obtain the first risk factor, which includes at least geological risk factor, meteorological risk factor, equipment risk factor, operational risk factor, and environmental risk factor; The weight coefficients of each type of primary risk factor are determined by the analytic hierarchy process, and the measured values ​​of each type of primary risk factor are mapped to risk membership degree using the membership function. The comprehensive risk value is obtained by weighting and summing the weight coefficients and risk membership degrees of the various first risk factors. Based on the comprehensive risk value, construction risks are classified into corresponding risk levels, and corresponding risk warning data are matched.

[0009] In one embodiment, the step of using a multi-factor coupled risk assessment algorithm to perform risk classification calculations on the construction process and obtain risk warning data further includes: Identify the environmental conditions of the construction area. If the environmental conditions are a hot and humid tropical rainforest environment, then the stability of the red clay foundation, the intensity of thunderstorm activity, the tree growth rate, and the depth of rainwater infiltration on the slope are introduced as the second risk factors. Based on the weight calculation and risk membership mapping of the second risk factor and the first risk factor, the comprehensive risk value of the tropical rainforest in the hot and humid environment is obtained, and the construction risk classification and risk early warning data generation are completed.

[0010] In one embodiment, the steps of performing construction plan negotiation, progress synchronization, work instruction issuance, and emergency response for cross-border construction entities, and outputting cross-border collaborative management and control information include: Construct domestic dispatch domains, overseas dispatch domains, and border coordination gateways; The construction plan preparation, construction resource scheduling, construction progress control and on-site safety monitoring are executed through the domestic scheduling domain and the overseas scheduling domain respectively, while retaining their respective scheduling management authority, so as to obtain independent construction scheduling data on both sides; Based on the border coordination gateway, cross-border data interaction, work instruction verification and multi-terminal time synchronization are performed to obtain cross-border construction scheduling data; Implement cross-border construction plan consultation, dynamic progress synchronization, work instruction issuance and emergency coordination to obtain cross-border collaborative operation process data; Based on the aforementioned bilateral independent construction scheduling data, cross-border construction scheduling data, and cross-border collaborative operation process data, cross-border collaborative management and control information is generated.

[0011] In one embodiment, the step of collecting process parameters and quality inspection data for each construction process and establishing a process quality traceability chain includes: Identify the construction procedures of power transmission lines, and match the corresponding process parameter collection points and quality inspection nodes for foundation pouring, tower erection, conductor and ground wire laying, accessory installation, and grounding device laying. Based on the process parameter collection points and quality inspection nodes, the current construction scenario is identified. If it is determined to be a tropical rainforest season construction scenario, the process parameters of concrete construction and the curing temperature and humidity time history data are collected. Based on the process parameters of the concrete construction and the time history data of temperature and humidity during curing, and combined with the preset quality control threshold corresponding to the red clay foundation conditions, an abnormal quality judgment and early warning are executed. The construction time was determined by calculating the time history data of temperature and humidity during the maintenance period using maturity theory and equivalent age calculation model. Identify construction defects on concrete foundation surfaces and generate a quality defect log. The quality defect ledger is linked to the process parameters of the concrete construction, the curing temperature and humidity time history data, the construction team and the construction time to form a process quality traceability chain data.

[0012] In one embodiment, the step of acquiring orthophoto and lidar point cloud data, and combining spatial coordinate information of multiple disturbance sources to obtain ecological disturbance information includes: Collect orthophotos and lidar point cloud data, and obtain spatial coordinate information of various disturbance sources; By combining the spatial coordinate information of the various disturbance sources, orthophotos, lidar point cloud data, and a pre-constructed ecological baseline database of the construction area, the actual disturbance range of each disturbance source and the spatial overlap of each ecologically sensitive layer are calculated. Based on the actual disturbance range of the various disturbance sources and the spatial overlap of the ecologically sensitive layers, an ecological disturbance heatmap is generated using a spatial overlay analysis algorithm. Based on the ecological disturbance heat map, the disturbance range is determined. If the disturbance range is detected to touch the preset ecological sensitive area or the main migration route of wild animals, the corresponding ecological protection early warning is triggered, and the corresponding low-disturbance construction path optimization scheme is generated to optimize and adjust the construction layout and construction land area. Based on the aforementioned ecological disturbance heat map, ecological protection early warning information, and construction optimization and adjustment results, combined with the characteristics of vegetation coverage changes before and after construction, ecological disturbance information is generated.

[0013] In one embodiment, the steps of implementing digital twin simulation and control based on a pre-built three-dimensional digital twin model, overlaid with risk warning data, cross-border collaborative management and control information, process quality traceability chain data, and ecological disturbance information, include: Based on the pre-constructed three-dimensional digital twin model, a simulation scenario for the entire construction process is built; The risk warning data, cross-border collaborative management and control information, process quality traceability chain data and ecological disturbance information are superimposed onto the construction process simulation scenario, and simulation is performed under the construction process simulation scenario. In each simulation process, the spatial attitude of the conductor is deduced based on the construction conditions and meteorological conditions, and the minimum clearance distance between the conductor and the object being crossed is calculated. The minimum clearance distance is compared with the preset standard threshold. If the minimum clearance distance does not meet the preset standard threshold, a safety warning is triggered, and the laying tension is adjusted or the construction plan is optimized.

[0014] In one embodiment, prior to the step of overlaying the risk warning data, cross-border collaborative management and control information, process quality traceability chain data, and ecological disturbance information based on a pre-built three-dimensional digital twin model, the following steps are included: Collect the measured spatial coordinates of multiple sets of feature control points in the construction area, match them with the model coordinates of the corresponding control points in the initial digital twin model, and calculate the root mean square error of spatial registration. The initial digital twin model is iteratively calibrated based on the spatial registration root mean square error to obtain the final three-dimensional digital twin model.

[0015] In one embodiment, the step of acquiring data throughout the construction process includes: Establish an integrated sensing network encompassing the sky, air, ground, and tower, and combine it with a multi-type UAV collaborative operation mechanism to collect raw data from the construction site according to the optimal task allocation strategy; The original construction site data is preprocessed by performing video frame sampling, image dehazing and enhancement, sensor data filtering and outlier removal on the original construction site data. The preprocessed raw construction site data is subjected to feature extraction and state recognition using a lightweight edge-side deep learning model, and the edge-side analysis results are output. Based on the preprocessed original construction site data and the side analysis results, local caching, breakpoint resume, and data synchronization are performed to obtain the data for the entire construction process.

[0016] Furthermore, to achieve the above objectives, this application also proposes a cross-border transmission line construction management and control system, which includes: The acquisition module is used to acquire data throughout the entire construction process; The risk classification calculation module is used to perform risk classification calculations across the construction process based on the data of the entire construction process, and to obtain risk warning data. The cross-border collaborative management module is used to conduct construction plan negotiation, progress synchronization, work instruction issuance and emergency response for cross-border construction entities, and output cross-border collaborative management information. The quality traceability module is used to collect process parameters and quality inspection data for each construction process and establish a process quality traceability chain data. The ecological disturbance monitoring module is used to collect orthophotos and lidar point cloud data, and combine them with spatial coordinate information of multiple disturbance sources to obtain ecological disturbance information; The digital twin simulation and deduction module is used to implement digital twin simulation and deduction control based on a pre-built three-dimensional digital twin model, overlaying the risk warning data, cross-border collaborative management and control information, process quality traceability chain data, and ecological disturbance information.

[0017] In addition, to achieve the above objectives, this application also proposes a cross-border transmission line construction control device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the cross-border transmission line construction control method described above.

[0018] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the cross-border transmission line construction control method described above.

[0019] In addition, to achieve the above objectives, this application also provides a computer program product, which includes a computer program that, when executed by a processor, implements the steps of the cross-border transmission line construction management method described above.

[0020] This application proposes a method, system, equipment, and storage medium for construction management and control of cross-border transmission lines. The method includes: acquiring data of the entire construction process; based on the data of the entire construction process, using a multi-factor coupled risk assessment algorithm to calculate the risk classification of the cross-border construction process and obtain risk warning data; performing cross-border construction collaborative interaction for cross-border construction entities and outputting cross-border collaborative management and control information; collecting process parameters and quality inspection data of each construction procedure and establishing a procedure quality traceability chain data; collecting orthophoto and lidar point cloud data, and combining spatial coordinate information of multiple disturbance sources to obtain ecological disturbance information; and implementing digital twin simulation and deduction management and control based on a pre-constructed three-dimensional digital twin model, overlaying risk warning data, cross-border collaborative management and control information, procedure quality traceability chain data, and ecological disturbance information. This solution integrates a multi-dimensional technology system encompassing construction data perception, risk assessment, cross-border collaborative management and control, process quality traceability, ecological disturbance monitoring, and digital twin simulation, enabling integrated intelligent management and control of all elements and processes in the construction of cross-border transmission lines. It effectively addresses the limitations of existing digital twin management and control technologies for power grid infrastructure in terms of scenario adaptability and comprehensive management capabilities, and the inability to simultaneously address the technical challenges of cross-border collaborative construction, risk control in complex environments, real-time perception and processing, and integrated management and control of construction quality and ecological protection. Attached Figure Description

[0021] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0022] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating an embodiment of the cross-border transmission line construction management method of this application. Figure 2 This is a diagram illustrating the construction of a multi-source sensing acquisition and twin base provided in Embodiment 1 of this application; Figure 3 This is a schematic diagram of the cross-border hierarchical and partitioned collaborative scheduling and control process provided in Embodiment 1 of this application; Figure 4 This is a schematic diagram illustrating the full-process traceability and control of the construction procedures for cross-border power transmission lines, provided in Embodiment 1 of this application. Figure 5 This is a schematic diagram of ecological disturbance detection and closed-loop management during the construction of cross-border power lines provided in Embodiment 1 of this application; Figure 6 This is a flowchart illustrating Embodiment 2 of the cross-border transmission line construction management method of this application; Figure 7 This is a flowchart illustrating Embodiment 3 of the cross-border transmission line construction management method of this application; Figure 8 A simplified flowchart illustrating the construction control method for cross-border transmission lines provided in Embodiment 1 of this application; Figure 9 This is a schematic diagram of the module structure of the cross-border transmission line construction control system according to an embodiment of this application; Figure 10 This is a schematic diagram of the equipment structure of the hardware operating environment involved in the construction control method for cross-border transmission lines in this application embodiment.

[0024] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0025] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0026] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0027] The main solution of this application embodiment is as follows: acquiring data of the entire construction process; based on the data of the entire construction process, using a multi-factor coupled risk assessment algorithm to perform risk classification calculations for cross-construction processes, and obtaining risk warning data; performing cross-border construction collaborative interaction for cross-border construction entities, and outputting cross-border collaborative management and control information; collecting process parameters and quality inspection data of each construction procedure, and establishing procedure quality traceability chain data; collecting orthophoto and lidar point cloud data, and combining spatial coordinate information of multiple disturbance sources to obtain ecological disturbance information; and based on a pre-constructed three-dimensional digital twin model, superimposing risk warning data, cross-border collaborative management and control information, procedure quality traceability chain data, and ecological disturbance information to implement digital twin simulation and deduction management and control.

[0028] In this embodiment, for ease of description, the following description uses the cross-border transmission line construction management and control system as the implementing entity.

[0029] Due to the limited adaptability and comprehensive management capabilities of existing digital twin management and control technologies for power grid infrastructure, there are no dedicated risk assessment factors and cross-border data security and collaborative scheduling mechanisms for the complex operating conditions of cross-border transmission lines. They also lack real-time perception and processing capabilities for end-to-end collaboration and dynamic monitoring methods for construction ecology. As a result, it is difficult to meet the integrated management and control needs of cross-border collaborative construction, risk control in complex environments, real-time perception and processing, construction quality and ecological protection. Consequently, the management and control accuracy, real-time performance and adaptability are poor.

[0030] This application provides a solution that incorporates specific factors of red clay and rainfall infiltration into a multi-factor coupled risk assessment algorithm, sets up a three-layer cross-border collaborative scheduling gateway and a data anonymization mechanism, configures an edge computing front-end intelligent analysis unit and an ecological disturbance spatial overlay module, establishes a multi-type UAV collaborative scheduling model, realizes full-element and full-cycle digital management and control of cross-border cross-span construction, improves the accuracy of risk warning and the level of construction quality control, takes into account ecological protection, and is suitable for cross-border power transmission engineering construction in complex environments.

[0031] It should be noted that the executing entity in this embodiment can be a computing service device with data processing, network communication, and program execution functions, such as a tablet computer, personal computer, or mobile phone, or an electronic device capable of performing the above functions. The following uses a cross-border transmission line construction management and control system as an example to illustrate this embodiment and the subsequent embodiments.

[0032] Based on this, the embodiments of this application provide a method for construction management and control of cross-border transmission lines, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the cross-border transmission line construction management method of this application.

[0033] In this embodiment, the construction control method for cross-border transmission lines includes steps S10 to S40: Step S10: Obtain data for the entire construction process; It should be noted that the data for the entire construction process includes, but is not limited to, satellite remote sensing data, UAV-borne lidar and high-definition image data, ground-based IoT sensor data, data from online monitoring devices for poles and towers, and data reported by construction terminals on both sides of the border.

[0034] Please refer to Figure 2 In this embodiment, by constructing an integrated multi-dimensional perception system encompassing air, ground, and tower, and combining it with a layered processing logic of UAV collaborative scheduling and data collection, edge-cloud three-level data processing, and cross-border data fault-tolerant transmission, the system completes the collection of raw construction site data, data preprocessing, edge-side intelligent analysis, and data integration synchronization step by step. Ultimately, it generates complete and usable data for the entire construction process, achieving standardized and intelligent collection and processing of multi-source heterogeneous data in complex cross-border construction scenarios.

[0035] Optionally, step S10 may include steps S11 to S14: Step S11: Establish an integrated perception network encompassing the sky, air, ground, and tower; combine it with a multi-type UAV collaborative operation mechanism; and collect raw data from the construction site according to the optimal task allocation strategy. It should be noted that a multi-drone collaborative operation mechanism is constructed by utilizing three types of drones: heavy-duty transport drones, inspection and model-building drones, and operation-assistance drones. Among them, heavy-duty transport drones are responsible for the aerial transport of construction materials such as tower materials, insulators, and tools, with a single flight load of no less than 200 kg; inspection and model-building drones are equipped with lidar and high-definition dual-light cameras to complete 3D modeling of the construction site, progress inspection, and safety inspection, with a cloud density of no less than 50 points per square meter; and operation-assistance drones are equipped with special operation devices to complete construction assistance operations such as guide rope traction and tree pruning.

[0036] The optimal task allocation strategy is the task allocation optimization objective function corresponding to the multi-machine collaborative task scheduling model:

[0037] In the formula, For the overall cost of collaborative operations, For the number of drone models, This represents the total number of construction tasks. For the first Type of drone to perform the first The unit cost of the task For 0-1 decision variables, For the first Type of drone to perform the first The time taken for each task The weighting coefficient for employment options.

[0038] In this embodiment, constraints are constructed based on UAV endurance constraints, task timing constraints, airspace conflict constraints, and operational capability constraints. An improved genetic algorithm is used to solve the objective function, outputting the optimal UAV task allocation scheme and flight timing plan, and completing the collection of multi-dimensional raw data from the construction site.

[0039] Simultaneously, it integrates space-based, ground-based, and tower-based sensing to complete the comprehensive data collection. Among them, space-based sensing uses high-resolution satellite remote sensing data to obtain large-scale information on land cover changes and macro-construction progress at a revisit frequency of no less than once a week. Ground-based sensing collects data on foundation deformation, concrete curing, and on-site environmental parameters through IoT sensors deployed at the construction site, such as those for temperature, humidity, stress, settlement, and vibration. Tower-based sensing monitors the operation status of towers and surrounding environmental data in real time through video monitoring, tilt, and wind speed and direction sensors deployed on the towers, comprehensively supplementing the original data dimensions of the construction site.

[0040] Step S12: Perform video frame sampling, image dehazing and enhancement, sensor data filtering and outlier removal on the original construction site data to obtain the preprocessed original construction site data. In this embodiment, a three-level computing architecture of edge preprocessing, edge feature extraction, and cloud-side deep analysis is adopted. Through the edge computing front-end analysis unit deployed on the monitoring terminal on the tower side and the cross-border gateway device, the sampling of construction video frames and the dehazing and enhancement processing of construction site images are completed on the edge side. At the same time, the working condition data and environmental data collected by various IoT sensors are filtered and denoised, and outlier removal is performed to remove invalid and interference data, and the data form is standardized to obtain the preprocessed original data of the construction site.

[0041] Step S13: Use a lightweight edge-side deep learning model to extract features and identify the state of the preprocessed construction site raw data, and output edge-side analysis results data. In this embodiment, a lightweight edge-side deep learning model is used in the edge feature extraction unit deployed in the edge computing unit. The original convolutional neural network model is compressed and optimized through a combination of channel pruning, knowledge distillation, and quantization compression to adapt it to the computing power of the embedded hardware terminal. Based on the lightweight edge-side deep learning model, deep feature extraction is performed on the preprocessed images, videos, and sensor data to identify various construction violations and abnormal equipment states on-site, such as construction workers not wearing safety helmets, unauthorized entry into dangerous areas, illegal operation of machinery and equipment, foreign objects hanging on the conductors, and loose or fallen tower materials. Alarm information is output in real time, generating edge analysis result data that includes construction safety status and equipment operating status.

[0042] Step S14: Based on the preprocessed original construction site data and the side analysis results, perform local caching, breakpoint resume and data synchronization processing to obtain the full construction process data.

[0043] In this embodiment, the pre-processed raw construction site data and edge analysis results are locally cached and resumed from where they left off. When a cross-border communication link interruption is detected, the pre-processed raw construction site data and edge intelligent analysis results are cached and then uploaded to the cloud main system in batches after the communication link is restored, avoiding data loss or omission. At the same time, the edge computing unit adopts an industrial-grade wide-temperature design and a moisture-proof and sealed structure, which can operate stably in the complex environment of tropical rainforest with high temperature and high humidity, ranging from -40℃ to 85℃ and 95% relative humidity. This effectively reduces the bandwidth consumption of cross-border data transmission and the cloud computing pressure, and improves the real-time performance and stability of construction data acquisition and safety event response.

[0044] Through the above steps, the hierarchical collection, intelligent preprocessing, on-site safety identification, and stable cross-border transmission of multi-source heterogeneous construction data from the sky, air, ground, and tower are realized, and integrated to form full-dimensional construction process data covering construction progress, equipment status, safety conditions, and environmental parameters.

[0045] Step S20: Based on the data of the entire construction process, a multi-factor coupled risk assessment algorithm is used to calculate the risk classification across the construction process to obtain risk warning data; In this embodiment, a multi-factor coupled risk assessment algorithm is used to calculate the risk classification across the entire construction process based on real-time collected multi-source construction process data. The multi-factor coupled risk assessment algorithm adopts a method that combines the analytic hierarchy process (AHP) with fuzzy comprehensive evaluation.

[0046] Optionally, step S20 may include steps S21 to S24: Step S21, obtain the first risk factor; In this embodiment, the first risk factor includes at least five major categories and more than twenty sub-factors, namely geological risk factors, meteorological risk, equipment risk, operational risk, and environmental risk.

[0047] Among them, geological risk factors include the bearing capacity of red clay foundation, slope stability, and rainfall infiltration depth. Meteorological risk factors include wind speed, rainfall, thunderstorm intensity, and visibility; equipment risk factors include the stability of the crossing frame, the integrity rate of tools and equipment, and the condition of traction equipment; operational risk factors include the matching degree of personnel qualifications, the frequency of violations, and the degree of overlap of work areas; and environmental risk factors include the traffic volume of the objects being crossed, the ecological sensitivity level, and the degree of surrounding disturbance.

[0048] Step S22: Determine the weight coefficients of each type of primary risk factor using the analytic hierarchy process (AHP), and map the measured values ​​of each type of primary risk factor to risk membership using a membership function. It should be noted that the measured value mapping refers to mapping the real-time monitoring values ​​of risk factors to the 0~1 risk range through a standardized membership function, thereby realizing the conversion of monitoring values ​​into quantitative indicators of risk level; the risk membership degree is used to characterize the degree of danger of a single risk factor, and the larger the membership degree value, the higher the construction safety hazard of the corresponding risk factor.

[0049] In this embodiment, the Analytic Hierarchy Process (AHP) is used to hierarchically decompose and assign weights to various types of primary risk factors, scientifically determining the weight coefficients corresponding to each risk factor and achieving a quantitative distinction of the importance of risk factors. Simultaneously, a membership function corresponding to complex cross-border construction scenarios is constructed, mapping the collected real-time measured values ​​of each risk factor to obtain the risk membership degree corresponding to each type of risk factor.

[0050] Step S23: Obtain the comprehensive risk value by weighted summation based on the weight coefficients and risk membership degrees of the various first risk factors; In this embodiment, a weighted summation algorithm is used to fuse the weights of each risk factor with their corresponding risk membership degrees. A terrain correction coefficient and a cross-border coordination correction coefficient are introduced for two-dimensional error correction to obtain the comprehensive risk value for construction crossing the border. The comprehensive risk score calculation formula is as follows:

[0051] In the formula, The comprehensive risk value for construction involving crossing and spanning is given. The total number of risk factors. For the first Weighting coefficients of risk factors, For the first Membership function of risk factors, For the first Real-time monitoring values ​​of risk factors, This is a terrain correction factor, adjusted based on the terrain undulation and slope of the crossing sections. This is a cross-border coordination correction coefficient, adjusted based on the degree of construction coordination on both sides and the quality of the communication link.

[0052] Step S24: Based on the comprehensive risk value, the construction risks are divided into corresponding risk levels, and corresponding risk warning data is matched.

[0053] In this embodiment, based on the magnitude of the comprehensive risk value, the risk is divided into four levels: blue, yellow, orange, and red, corresponding to low risk, moderate risk, relatively high risk, and high risk, respectively, and corresponding early warning response measures are triggered.

[0054] Through the above steps, the system achieves accurate collection, quantitative assignment, coupled calculation, and hierarchical early warning of multi-dimensional and full-category risk factors for cross-border power transmission line crossing construction. This solves the problems of traditional construction risk assessment factors being singular, subjective in weighting, unsuitable for complex cross-border working conditions, and imprecise in grading. It significantly improves the scientificity and accuracy of construction risk assessment in complex cross-border geological, meteorological, and cross-domain collaborative scenarios.

[0055] Step S30: Perform cross-border construction collaborative interaction with cross-border construction entities, and output cross-border collaborative management and control information. Understandably, due to the fact that cross-border transmission line construction spans different jurisdictions, there are problems such as inconsistent dispatching standards, fragmented information exchange channels, difficulty in synchronizing progress, and a lack of collaborative response mechanisms for emergencies between domestic and foreign construction entities. This step addresses these issues by establishing a two-way collaborative interaction mechanism for cross-border construction. This mechanism supports collaborative matters such as construction plan negotiation, construction progress synchronization, issuance of work instructions, and emergency response, thereby opening up data and business channels between the construction entities on both sides. It forms cross-border collaborative management and control information, providing cross-border collaborative data support for digital twin simulation and control, and ensuring the orderly coordination of cross-border construction operations and the efficient and coordinated response to emergencies.

[0056] Optionally, step S30 may include step S31: Step S31 involves performing at least one of the following for cross-border construction entities: construction plan negotiation, progress synchronization, issuance of work instructions, and emergency response, and outputting cross-border collaborative management information.

[0057] Please refer to Figure 3 , Figure 3 This is a schematic diagram of a cross-border hierarchical and zoned collaborative scheduling and control process. In this embodiment, addressing industry pain points such as independent management systems on both sides of cross-border transmission line construction, high barriers to cross-domain data interaction, difficulty in unifying construction coordination timing, and lagging emergency response, a hierarchical and zoned collaborative scheduling architecture with domestic and foreign dual scheduling domains and a border coordination gateway is established. Based on multi-protocol adaptation, national cryptographic data security desensitization, instruction permission verification, and dual-mode clock synchronization technology, a full-cycle cross-border collaborative control mechanism is constructed, which includes day-ahead negotiation, intraday optimization, and real-time linkage. This enables plan interoperability, progress synchronization, instruction controllability, and emergency linkage among multiple entities involved in cross-border construction, ultimately generating standardized, traceable, and highly secure cross-border collaborative control information to support integrated closed-loop management of complex cross-border construction scenarios.

[0058] Optionally, step S31 may also include steps S311 to S315: Step S311: Construct the domestic dispatch domain, the overseas dispatch domain, and the border coordination gateway; It should be noted that the domestic dispatch domain refers to an independent dispatch and control area deployed on the domestic side of the cross-border project, which follows domestic power grid construction management specifications and dispatch standards, and is responsible for the scheduling of construction plans, resource dispatch, and safety control of the domestic section; the overseas dispatch domain refers to an independent dispatch and control area deployed on the foreign side of the cross-border project, which adapts to local engineering construction management regulations and construction procedures, and is responsible for the independent dispatch and on-site control of the overseas section of construction; the border coordination gateway refers to a cross-border collaborative interaction hub node deployed at the boundary of the two dispatch domains, used to realize cross-border protocol conversion, data security interaction, command verification, and timing synchronization.

[0059] Step S312: The construction plan preparation, construction resource scheduling, construction progress control and on-site safety monitoring are executed through the domestic scheduling domain and the overseas scheduling domain respectively, while retaining their respective scheduling management permissions, to obtain independent construction scheduling data on both sides; The project employs independent sub-modules for construction planning, resource allocation, progress control, and safety monitoring within both the domestic and international dispatch domains. These domains operate independently without interference, fully preserving independent dispatch management rights on both sides of the cross-border route and strictly adhering to the respective management systems and regulatory requirements of the China-Laos cross-border project. Each dispatch domain can independently complete basic management tasks within its jurisdiction, including construction plan arrangement, allocation of human and material resources, construction progress tracking and updates, and monitoring of on-site safety conditions, generating independent construction dispatch data for both the domestic and international sides.

[0060] Step S313: Based on the border coordination gateway, perform cross-border data interaction, work instruction verification and multi-terminal time synchronization to obtain cross-border construction scheduling data; The border coordination gateway deploys a protocol conversion unit, a data anonymization unit, an instruction verification unit, and a clock synchronization unit. The protocol conversion unit supports bidirectional transparent conversion between various power communication protocols such as IEC61850, IEC104, and Modbus and local construction management protocols on both sides. The data anonymization unit employs a cross-border data encryption transmission scheme based on the national cryptographic algorithms SM2 / SM3 / SM4, performing field-level anonymization and hash verification on sensitive data such as construction personnel information, equipment parameters, and coordinate locations to ensure secure cross-border data transmission and meet bilateral data security requirements. The instruction verification unit performs security audits and authorization verification on various cross-border work instructions, intercepting illegal instructions and unauthorized operations to mitigate security risks in cross-border remote dispatching. The clock synchronization unit uses GPS and BeiDou dual-mode time synchronization to achieve millisecond-level time alignment between domestic and foreign construction terminals and dispatching equipment, ensuring time consistency in collaborative operations. Through the collaborative processing of multiple units within the border coordination gateway, compliant, accurate, and unified cross-border construction dispatching data is generated.

[0061] Step S314 involves implementing cross-border construction plan negotiation, dynamic progress synchronization, issuance of work instructions, and emergency coordination to obtain cross-border collaborative operation process data. In this embodiment, a three-tiered cross-border collaboration mechanism is established, encompassing daily construction plan negotiation, dynamic adjustment of intraday progress, and real-time operational coordination, to achieve full-cycle collaborative management and control of cross-border construction. During the daily construction plan negotiation phase, both sides exchange the next day's construction plan through the border gateway, and after joint approval, a unified cross-border construction window arrangement is formed. During the intraday progress adjustment phase, the work sequence is adjusted according to real-time progress and weather changes, with both sides updating synchronously. During the real-time operational coordination phase, synchronous start-stop control of key cross-border construction processes is supported, ensuring coordinated cooperation between both sides for high-risk operations such as conductor and ground wire deployment and conductor hoisting.

[0062] Meanwhile, in the event of sudden equipment failure, extreme weather, or on-site emergencies, the cross-border emergency response mechanism is triggered to quickly issue emergency instructions, coordinate and allocate resources, and jointly handle on-site situations. It also records information on the entire cross-border collaborative operation process and generates cross-border collaborative operation process data.

[0063] Step S315: Based on the bilateral independent construction scheduling data, cross-border construction scheduling data, and cross-border collaborative operation process data, generate cross-border collaborative management and control information.

[0064] In this embodiment, the planning data, resource data, and progress and safety data of the independent scheduling on both sides are integrated, combined with the cross-border construction scheduling data after standardized interaction, security verification, and time synchronization of the border gateway, as well as the operation process data of cross-border planning negotiation, dynamic adjustment, real-time linkage, and emergency coordination throughout the entire process. Multi-dimensional data fusion, organization, classification and summarization are carried out to finally form standardized cross-border collaborative management and control information that includes construction plans, scheduling resources, construction progress, safety control, cross-border collaboration records, and emergency response information.

[0065] Through the above steps, a cross-border hierarchical and zoned scheduling system with independent control on both sides and coordinated border security has been constructed. This system not only ensures the autonomy and compliance of construction management on both sides of the border, but also achieves secure cross-domain data exchange, precise time synchronization, and efficient collaborative operations. It effectively solves the problems of inconsistent cross-border construction scheduling protocols, insecure data, asynchronous time sequences, poor coordination of high-risk operations, and untimely emergency response in traditional cross-border construction scheduling, thereby improving the accuracy and safety management level of collaborative control for cross-border transmission line crossing construction.

[0066] Step S40: Collect process parameters and quality inspection data for each construction process, and establish a process quality traceability chain data. It should be noted that the process parameters of the construction procedures include, but are not limited to, the controllable process execution parameters of the five core construction procedures: foundation pouring mix ratio, concrete pouring temperature, interlayer temperature difference, vibration frequency and amplitude, curing temperature and humidity, internal and external temperature difference, tower erection verticality, conductor and ground wire tension value, laying and traction speed, accessory installation alignment deviation, and grounding laying depth parameters. The quality inspection data refers to the structural strength, forming flatness, installation accuracy, density index, appearance defect detection results, compliance acceptance records, image retention data, and quality defect ledger data after each procedure is completed.

[0067] Please refer to Figure 4 , Figure 4This diagram illustrates the full-process traceability and control of quality during the construction of cross-border transmission lines. In this embodiment, considering the complex environment of the cross-border tropical rainforest and the construction conditions of the red clay foundation, a comprehensive process data collection and quality inspection node is established around five core construction procedures: foundation pouring, tower erection, conductor and ground wire deployment, accessory installation, and grounding device laying. This integrates real-time sensor monitoring, intelligent concrete strength prediction, and AI-based appearance defect recognition technologies to construct a process-level quality traceability system with a unique identifier for each tower. This achieves closed-loop quality control, ensuring that parameters are collectable, quality is inspectable, defects are traceable, and procedures are controllable throughout the entire construction process.

[0068] Optionally, step S40 may include steps S41 to S46: Step S41: Identify the construction procedures of the transmission line, and match the corresponding process parameter collection points and quality inspection nodes for foundation pouring, tower erection, conductor and ground wire laying, accessory installation, and grounding device laying. In this embodiment, each tower is treated as an independent traceability unit, with a unique identifier assigned to each tower. Corresponding process parameter acquisition nodes and quality inspection nodes are matched for each of the five core construction procedures. Each procedure node corresponds one-to-one and independently collects data, achieving full coverage of parameter acquisition and quality monitoring for all procedures from foundation construction, tower erection, conductor stringing, accessory installation to grounding, providing point-based support for procedure-level chain traceability.

[0069] Step S42: Based on the process parameter collection points and quality inspection nodes, identify the current construction scenario. If it is determined to be a tropical rainforest season construction scenario, collect the process parameters of concrete construction and the curing temperature and humidity time history data. In this embodiment, if a special construction scenario during the rainy season in a tropical rainforest is identified, a special monitoring process for the real-time monitoring subunit of concrete pouring quality is initiated. Temperature sensors, humidity sensors, and vibration frequency sensors are deployed at multiple points on the sidewalls of the foundation formwork, the inside of the reinforcing cage, and between concrete pouring layers to collect key process data in real time, including concrete placement temperature, temperature difference between pouring layers, vibration compaction characteristics, curing environment temperature and humidity, and temperature difference between the inside and outside of the foundation. The temperature sensors are sampled at intervals of no less than five minutes, with a measurement accuracy of no less than ±0.5℃, ensuring high-precision and continuous acquisition of concrete construction data under high temperature, high humidity, and rainy conditions, forming a complete time-series data sequence of curing temperature and humidity.

[0070] Step S43: Based on the process parameters of the concrete construction and the curing temperature and humidity time history data, and combined with the preset quality control threshold corresponding to the red clay foundation conditions, perform quality anomaly judgment and early warning. This embodiment also establishes a quality control threshold database for cross-border red clay foundations and tropical rainforest rainy season conditions. Real-time collected process parameters such as concrete pouring temperature, interlayer temperature difference, vibration amplitude and frequency, curing temperature and humidity, and internal and external temperature difference are compared and analyzed against preset thresholds. When the monitored data exceeds the compliant threshold range or abnormal construction conditions occur, the system automatically triggers on-site audible and visual alarms, providing timely warnings of potential quality problems such as inadequate concrete compaction, temperature-induced cracking, and curing failure, enabling early detection, early warning, and early handling of concrete construction quality issues.

[0071] Step S44: The construction time is determined by calculating the curing temperature and humidity time history data using maturity theory and equivalent age calculation model; In this embodiment, an early-age prediction algorithm for concrete strength based on maturity theory constructs an equivalent age calculation model based on the Arrhenius theorem using collected temperature and humidity time-history data from the entire curing process. This model fully considers the influence of ambient temperature on the cement hydration reaction rate, calculates the dynamic development curve of concrete foundation strength, and achieves intelligent prediction of early-age concrete strength. Subsequently, the time node for the foundation to reach its design strength is determined based on the strength prediction results. This is used to scientifically guide the optimal start time for the tower erection process, avoiding quality and safety hazards such as tower misalignment and foundation settlement caused by insufficient strength, and ensuring the scientific and standardized connection of processes.

[0072] Among them, the early prediction algorithm for concrete strength based on maturity theory refers to an intelligent algorithm that takes the temperature and humidity time series data of the entire concrete curing process as input, and quantifies the degree of cement hydration cumulative reaction according to the equivalent age integral mechanism corrected by temperature effect. It establishes a nonlinear mapping relationship between curing time, ambient temperature and concrete compressive strength, and can realize the continuous deduction and accurate prediction of the early strength growth law of concrete under complex rainforest high temperature and high humidity curing conditions without relying on traditional physical damage detection methods.

[0073] Step S45: Identify construction defects on the concrete foundation surface and generate a quality defect log. In this embodiment, the system is equipped with a basic appearance quality inspection unit based on AI image recognition. It acquires high-definition image data of the concrete foundation surface through drone aerial photography, and identifies typical appearance quality defects such as honeycomb, pitting, exposed reinforcement, and cracks on the foundation surface through a trained AI image recognition model. It locates the defect location, counts the defect type and scale, classifies and archives the defects, records them one by one, and generates a construction quality defect ledger, thereby realizing intelligent identification and systematic management of appearance quality defects.

[0074] Step S46: Associate the quality defect ledger with the process parameters of the concrete construction, the curing temperature and humidity timeline data, the construction team and the construction time to form a process quality traceability chain data.

[0075] In this embodiment, the unique identifier of a single tower is used as the traceability thread. The construction quality defect ledger generated by AI recognition is linked and bound in multiple dimensions with the concrete pouring process parameters of the corresponding time period, the temperature and humidity time history data of the whole process curing, the on-site construction team information, the specific construction time, the equipment condition, and the acceptance record. At the same time, the process data and quality inspection data of each process of tower erection, conductor and ground wire laying, accessory installation, and grounding device laying are connected to construct a process quality traceability chain data.

[0076] Through the above steps, a full-process quality traceability system for transmission lines adapted to the special working conditions of tropical rainforest rainy season and red clay foundation has been constructed. This system solves the problems of one-sided construction quality monitoring, lagging strength prediction, difficulty in defect location, and loose process control in traditional construction. It realizes intelligent quality control throughout the entire process, enabling monitoring of construction process parameters, early warning of quality hazards, prediction of strength cycles, identification of appearance defects, and traceability of quality problems. This significantly improves the level of refined control over the construction quality of transmission lines in complex cross-border environments and enhances the stability of project construction quality.

[0077] Step S50: Collect orthophotos and lidar point cloud data, and combine them with spatial coordinate information of multiple disturbance sources to obtain ecological disturbance information; Please refer to Figure 5 , Figure 5 This diagram illustrates the detection and closed-loop management of ecological disturbances during cross-border power line construction. In this embodiment, a comprehensive ecological baseline database is constructed by overlaying a pre-built digital twin model with a multi-dimensional ecological vector layer. Combined with UAV patrol data and spatial information on various disturbance sources at the construction site, spatial overlay analysis, heat map visualization, ecological early warning, and path optimization technologies are used to achieve dynamic monitoring of ecological disturbances throughout the entire construction process, risk warning, construction optimization, and vegetation restoration assessment. This accurately obtains comprehensive ecological disturbance information and achieves eco-friendly closed-loop management of cross-border construction.

[0078] Optionally, step S50 may include S51 to S55: Step S51: Collect orthophotos and lidar point cloud data, and obtain spatial coordinate information of various disturbance sources; It should be noted that orthophotos refer to high-definition aerial images of construction sites that have undergone geometric correction and projection transformation to eliminate the effects of terrain undulations and lens distortion and have unified geographic coordinate information. They can realistically reproduce the distribution of surface vegetation, the layout of construction sites, and landform features. The lidar point cloud data refers to the high-density three-dimensional spatial point set data obtained by airborne lidar scanning, which includes high-precision spatial information such as surface elevation, terrain undulation, ground feature outline, and vegetation vertical structure, and can accurately depict the three-dimensional landform features of the construction site. The various sources of disturbance include, but are not limited to, construction access roads, foundation excavation faces, material storage yards, temporary land occupation, and cableway erection lines.

[0079] Step S52: Combining the spatial coordinate information of the various disturbance sources, orthophotos, lidar point cloud data, and the pre-constructed ecological baseline database of the construction area, calculate the actual disturbance range of each disturbance source and the spatial overlap of each ecologically sensitive layer. In this embodiment, based on a digital twin model, layers of ecologically sensitive areas, rare plant distribution, wildlife migration routes, and key water and soil conservation areas are overlaid to build an ecological baseline database covering the entire construction area, achieving digital and visual storage of ecological baseline information. Through orthophotos collected by drones during regular patrols and LiDAR point cloud data, the spatial location and boundary range of various disturbance sources, such as construction access roads, foundation excavation faces, material storage areas, temporary land occupation, and cableway erection lines, are located. Combined with multiple ecologically sensitive layers in the ecological baseline database, a full-area spatial overlay calculation is performed to determine the actual spatial disturbance range of each type of construction disturbance source, as well as the spatial overlap area and overlap ratio between the disturbance area and each ecologically sensitive layer, quantifying the degree of disturbance impact of construction activities on ecologically sensitive areas.

[0080] Step S53: Based on the actual disturbance range of the various disturbance sources and the spatial overlap of the ecologically sensitive layers, an ecological disturbance heat map is generated using a spatial overlay analysis algorithm. In this embodiment, a spatial overlay analysis algorithm is used to calculate the spatial overlap between the disturbance range and each ecologically sensitive layer, generating an ecological disturbance heat map to visually display the disturbance intensity in different areas.

[0081] The specific implementation logic and parameter thresholds for the spatial overlay analysis algorithm to generate the ecological disturbance heatmap are as follows: First, the six types of static vector maps—pre-loaded Level 1 / Level 2 / Level 3 ecologically sensitive areas, wildlife migration corridors, rare plant distribution areas, and key water and soil conservation areas—are uniformly converted into 1m×1m standard raster units in the WGS84 coordinate system, along with five types of dynamic disturbance source layers—basic excavation faces, construction access roads, material storage yards, cableway lines, and temporary work faces—updated daily by drones. The boundaries are then calibrated using a digital twin base spatial registration algorithm, with a registration error threshold ≤0.3m. Finally, a raster weighted overlay algorithm is used to calculate the ecological disturbance overlap unit by unit. The calculation formula is as follows:

[0082] Among them, the weight of the first-level ecologically sensitive area Weight of main wildlife migration routes Weight of rare plant concentration areas Weight of secondary ecologically sensitive areas Weight of Level 3 General Ecological Zones , For the current grid and the first The overlapping area of ​​the ecosystem-like layers. Set a four-level thermal rendering threshold: raster perturbation value. Deep red severe perturbation, Orange-red moderate perturbation, The light yellow color indicates a slight disturbance. The light green area shows no obvious disturbance. The graded thermal layers are semi-transparently overlaid on the 3D digital twin scene, and the total area of ​​disturbance at each level is counted simultaneously to generate a daily disturbance log.

[0083] Step S54: Determine the disturbance range based on the ecological disturbance heat map. If the disturbance range is detected to touch a preset ecologically sensitive area or a major wildlife migration route, trigger a corresponding ecological protection early warning and generate a corresponding low-disturbance construction path optimization scheme to optimize and adjust the construction layout and construction land area. In this embodiment, the pre-loaded primary ecologically sensitive areas and main wildlife migration corridors are used as ecological protection thresholds. By comparing the disturbance range of the ecological disturbance heatmap with the ecological protection thresholds, it is determined whether the construction disturbance has intruded into highly sensitive ecological areas.

[0084] When the disturbance area touches a primary ecologically sensitive area or a major wildlife migration route, a red alert for ecological protection is triggered, and a low-disturbance construction path optimization scheme is generated based on a multi-objective optimization algorithm. The optimization algorithm comprehensively considers three objectives: construction schedule requirements, transportation costs, and ecological impact. Under the premise of meeting the construction schedule requirements, it adjusts material transportation routes, optimizes cableway layout, and reduces the temporary land occupation area to minimize the disturbance of construction to the ecological environment.

[0085] The implementation logic and parameter thresholds of the low-disturbance construction path optimization scheme are as follows: When the ecological disturbance heatmap identifies that the proportion of severely disturbed grid cells is 5% or the disturbance source intrudes into the 50m buffer zone of the primary ecologically sensitive area, a multi-objective optimization solution is automatically triggered to construct a function that minimizes the three objectives of ecology, construction period, and cost. The default weight configuration for ecologically sensitive areas is... , , The conventional construction scenario can be switched to , , Set a hard constraint threshold: upper limit for project duration increment. Upper limit of single-segment cost increment The optimization parameters are as follows: 10,000 yuan; optimized routes must not intrude into the core area of ​​the primary ecologically sensitive zone; the longitudinal slope of the construction access road must be ≤30°; and the single span of the cableway must be ≤2km. Optimization variables include the coordinates of nodes along the construction access road, the location and area of ​​the material storage yard, the cableway's start and end points and centerline, and staggered work schedules. An improved multi-objective genetic algorithm is used to solve the problem. The iteration termination threshold is ≥200 iterations or no decrease in the objective function for 30 consecutive generations. The final output consists of three compliant solutions, sorted in ascending order of total disturbance area, with details of disturbance reduction, construction period increment, and cost increment.

[0086] Subsequently, the output low-disturbance scheme is subjected to hard constraint verification. After meeting the requirements of zero intrusion into the first-level sensitive area and that the construction period and cost do not exceed the threshold, it is synchronized to the joint approval of the scheduling domains on both the domestic and foreign sides through the border coordination gateway. After approval, the digital twin construction planning model is updated and the disturbance heat map is regenerated to verify the optimization effect.

[0087] Step S55: Based on the ecological disturbance heat map, ecological protection early warning information, and construction optimization and adjustment results, combined with the vegetation coverage change characteristics before and after construction, ecological disturbance information is generated.

[0088] Furthermore, this embodiment also uses multiple phases of UAV aerial imagery data to compare the changes in vegetation cover between the original topography before construction and the site after construction, and calculates the vegetation restoration rate of the disturbed area based on the normalized vegetation index. Finally, by integrating the overall ecological baseline data, real-time ecological disturbance thermal distribution data, ecological early warning records, construction optimization and adjustment plans, and vegetation restoration assessment results, a full-chain ecological impact assessment system of construction disturbance-construction optimization-vegetation restoration is constructed. This system summarizes and generates complete ecological disturbance information including spatial disturbance range, disturbance intensity, ecological risk level, optimization measures, and vegetation restoration level, establishing a chain of ecological impact assessment for the entire process of cross-border transmission line construction, and achieving eco-friendly closed-loop management of transmission line construction in complex cross-border ecological scenarios.

[0089] Specifically, after construction is completed, the system enters a closed-loop assessment process for vegetation restoration. The Normalized Difference Vegetation Index (NDVI) is used as the core indicator for judging the effectiveness of ecological restoration. The system presets three levels of vegetation restoration evaluation thresholds: when NDVI ≥ 0.7, it is judged as complete vegetation restoration; when 0.4 ≤ NDVI < 0.7, it is judged as partial vegetation restoration; and when NDVI < 0.4, it is judged as damaged vegetation requiring artificial replanting and restoration. The system sets a long-term monitoring cycle threshold, that is, every 3 months after construction, site vegetation image data is collected by drone patrol, continuously monitored for 2 years, to achieve long-term dynamic tracking of ecological restoration after construction. Simultaneously, all ecological disturbance data, low-disturbance construction optimization plans, phased vegetation restoration assessment results, and replanting and rectification records are uniformly bound to the unique identifier of the corresponding tower and simultaneously incorporated into the process-level quality traceability chain, realizing dual-dimensional, full-cycle closed-loop traceability management of construction quality control and ecological disturbance restoration control.

[0090] Through the above steps, based on the spatial overlay analysis of digital twin models and multiple ecologically sensitive layers, the overlap between the construction disturbance range and the ecologically sensitive area can be quantitatively calculated. A low-disturbance construction path scheme can be automatically generated through a multi-objective optimization algorithm, minimizing the impact of the project on the tropical rainforest ecosystem while ensuring construction progress. The multi-type UAV collaborative operation scheduling model optimizes the solution with comprehensive cost and construction period as dual objectives, achieving optimal task allocation and airspace collaborative scheduling for different types of UAVs. Compared with manual scheduling methods, this improves material transportation efficiency, shortens the construction period, and reduces temporary land occupation and vegetation damage, providing technical support for the construction of cross-border power transmission projects in ecologically sensitive areas.

[0091] Step S60: Based on the pre-constructed three-dimensional digital twin model, the risk warning data, cross-border collaborative management and control information, process quality traceability chain data, and ecological disturbance information are superimposed to implement digital twin simulation and control.

[0092] In this embodiment, a three-dimensional digital twin model is used as the visualization carrier to integrate and overlay core business data from four dimensions in real time: construction risk distribution, cross-border collaborative scheduling, process quality traceability, and ecological disturbance monitoring, constructing a comprehensive, integrated, and visualized management and control scenario. The system supports free browsing of the three-dimensional scene, cross-sectional measurement, and layer switching, and is compatible with diverse observation modes such as first-person virtual inspection, third-person global monitoring, and multi-angle analysis of construction profiles. Simultaneously, it achieves intuitive visualization of the construction status through color coding and thermal layer overlay. Based on the real-world simulation scenario, it completes real-time monitoring of the construction site, virtual simulation of the construction process, and prediction of safety risks and faults, realizing digital simulation and management of the entire cross-border and cross-span construction process.

[0093] Optionally, step S60 may include steps S61 to S63: Step S61: Based on the pre-constructed three-dimensional digital twin model, construct a simulation scenario for the entire construction process; In this embodiment, a pre-constructed 3D digital twin model is used to replicate the topography, tower equipment, structures being crossed, ecological environment, and construction site of the cross-border transmission line crossing section, creating a simulation scenario for the entire construction process. This scenario fully adapts to all core construction procedures, including crossing frame erection, guide rope deployment, conductor raising, and crossing frame dismantling, realistically recreating the on-site construction environment, equipment operating status, and work procedures.

[0094] Step S62: Overlay the risk warning data, cross-border collaborative management and control information, process quality traceability chain data, and ecological disturbance information onto the construction process simulation scenario, and perform simulation under the construction process simulation scenario; In this embodiment, real-time linkage, overlay, and visualization mapping of multi-source business data with a 3D twin scene are achieved, and various construction progress information is displayed using differentiated visualization rules. Specifically, construction progress is presented intuitively using a color-coding mechanism, marking completed construction procedures in green, ongoing procedures in yellow, and procedures not yet started in gray. Construction risk distribution is overlaid onto the 3D terrain scene surface in the form of a heat map, with different color gradients distinguishing high, medium, and low risk levels. Construction quality status is intuitively reflected through the dynamic color changes of the single-tower 3D model, showing the compliance status of procedures and the distribution of defects and potential hazards. Real-time location information of drones, construction machinery, and personnel is attached to the on-site operation status, enabling dynamic and visual monitoring of construction resource locations. Simultaneously, based on the overlaid full-domain simulation scene, the entire construction process is replicated, simulated, and analyzed.

[0095] Step S63: In each simulation process, the spatial attitude of the conductor is deduced based on the construction conditions and meteorological conditions, and the minimum clearance distance between the conductor and the object being crossed is calculated. The simulation process includes simulation of the erection of the crossing frame, simulation of the deployment of the guide rope, simulation of the raising of the conductor, and simulation of the dismantling of the crossing frame.

[0096] During the simulation, the sag and spatial position of the conductor under different tensions and weather conditions are calculated using a physics engine, and the minimum clearance between the conductor and the object being crossed is calculated in real time. The formula for calculating the minimum clearance between the conductor and the object being crossed is:

[0097] In the formula, This is the minimum clearance distance between the conductor and the object it crosses. The length of the conductor in the crossing section. Let be the arc length of a point on the conductor from the starting end. The arc length of the conductor from the starting end The x-coordinate of the location, The arc length of the conductor from the starting end The ordinate at that location, The arc length of the conductor from the starting end Elevation of the location Let x be the x-coordinate of a feature point on the object being crossed. Let be the ordinate of a feature point on the object being crossed. The elevation of a feature point on the object being crossed.

[0098] Step S64: The minimum clearance distance is compared with a preset standard threshold. If the minimum clearance distance does not meet the preset standard threshold, a construction safety warning is triggered, indicating the risk location and risk level. Simultaneously, based on the results of physical simulation iterations, the optimal rectification strategy is matched. By dynamically fine-tuning the conductor tension, adjusting the traction construction sequence, and optimizing the on-site construction layout, potential safety hazards are quickly eliminated, ensuring the safety and compliance of high-risk crossing operations such as cross-border conductor deployment and conductor elevation.

[0099] Through the above steps, based on the digital twin's 3D visualization and physical simulation capabilities, we can achieve full-element visual monitoring, full-process simulation and pre-playing, precise verification of crossing safety distances, and proactive risk intervention in cross-border construction. This solves the shortcomings of traditional cross-border construction, which relies on manual experience for prediction, has delayed safety verification, and lacks visibility of risks. It significantly improves the safety management accuracy and scientific nature of construction plans for high-risk cross-border construction, and realizes digital, visual, and intelligent closed-loop management of the entire process of cross-border transmission line construction.

[0100] Through the methods described above, data on the entire construction process is obtained; based on this data, a multi-factor coupled risk assessment algorithm is used to calculate the risk classification across construction processes, resulting in risk warning data; cross-border construction entities are oriented towards construction plan negotiation, progress synchronization, work instruction issuance, and emergency response, outputting cross-border collaborative management and control information; process parameters and quality inspection data for each construction procedure are collected to establish a procedure quality traceability chain; orthophotos and lidar point cloud data are collected, combined with spatial coordinate information of multiple disturbance sources, to obtain ecological disturbance information; based on a pre-constructed three-dimensional digital twin model, risk warning data, cross-border collaborative management and control information, procedure quality traceability chain data, and ecological disturbance information are overlaid to implement digital twin simulation and deduction management and control. This solution integrates a multi-dimensional technology system encompassing construction data perception, risk assessment, cross-border collaborative management and control, process quality traceability, ecological disturbance monitoring, and digital twin simulation, enabling integrated intelligent management and control of all elements and processes in the construction of cross-border transmission lines. It effectively addresses the limitations of existing digital twin management and control technologies for power grid infrastructure in terms of scenario adaptability and comprehensive management capabilities, and the inability to simultaneously address the technical challenges of cross-border collaborative construction, risk control in complex environments, real-time perception and processing, and integrated management and control of construction quality and ecological protection.

[0101] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in Embodiment 1 above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 6 Step S20 also includes steps S201 to S202: Step S201: Identify the environmental conditions of the construction area. If the environmental conditions are a hot and humid tropical rainforest environment, then the stability of the red clay foundation, the intensity of thunderstorm activity, the tree growth rate, and the depth of rainwater infiltration on the slope are introduced as the second risk factors. Step S202: Based on the second risk factor and the first risk factor, perform weight calculation and risk membership mapping to obtain the comprehensive risk value under the hot and humid tropical rainforest environment, and complete the construction risk classification and risk warning data generation.

[0102] In this embodiment, since the construction sections of cross-border transmission lines are mostly located in the special environment of tropical rainforest with high humidity and heat, red clay softens when it gets wet, slopes are easily eroded, thunderstorms occur frequently, and the surrounding vegetation grows vigorously, the conventional first risk factor system cannot fully cover the special construction hazards in the rainforest. It has the problems of one-sided risk assessment and omission of some hazards. Therefore, this embodiment adds a second risk factor adapted to the rainforest conditions on the basis of the basic risk system of the first embodiment, and constructs a two-dimensional risk assessment system to achieve a refined and comprehensive assessment of construction risks in complex and humid environments.

[0103] Specifically, considering the hot and humid environment of tropical rainforests, the stability of red clay foundations, thunderstorm activity intensity, tree growth rate, and slope rainfall infiltration depth were included as secondary risk factors. The slope rainfall infiltration depth was calculated using a modified Green-Ampt model, with the following formula:

[0104] In the formula, for The depth of rainfall infiltration at any given moment. The saturated hydraulic conductivity of red clay, The matrix suction at the moistened frontal surface. The depth of surface water. This refers to the saturated volumetric water content of the soil. Initial volumetric water content of soil After obtaining the second risk factor, the analytic hierarchy process of the first embodiment is used to perform hierarchical decomposition and differentiated weight assignment on the first and second risk factors to distinguish the importance differences between conventional risk factors and rainforest-specific risk factors. At the same time, the working condition characteristics of the four newly added second risk factors are adapted to build a dedicated membership function, which maps the real-time monitoring and measured values ​​of each second risk factor to the standard risk range of 0 to 1, and obtains the risk membership of each second risk factor.

[0105] By integrating the weight coefficients and corresponding risk membership degrees of the first and second risk factors, and combining terrain correction coefficients and cross-border coordination correction coefficients, a weighted coupled calculation is performed to obtain a comprehensive construction risk value suitable for the complex working conditions of tropical rainforests with high humidity and heat. Finally, based on the comprehensive risk value, a four-level risk classification (blue, yellow, orange, and red) is completed, and corresponding early warning information and closed-loop response measures are matched to generate risk warning data suitable for the special construction scenarios in rainforests.

[0106] By incorporating tropical rainforest-specific risk factors such as red clay foundation characteristics, rainfall infiltration depth, and slope stability through the methods described above, and combining topographic correction coefficients and cross-border coordination correction coefficients, the system can more accurately reflect the true risk level of construction across complex environments. Compared to single-indicator assessment methods, this improves the accuracy and timeliness of risk warnings. The configured edge computing front-end intelligent analysis unit uses model lightweighting technology to identify construction violations and equipment anomalies locally, reducing cross-border data transmission bandwidth pressure and shortening safety incident response time. The construction quality full-process traceability module establishes a process-level quality traceability chain, combined with an early concrete strength prediction algorithm, which can effectively guide the process connection during rainy season construction and improve the first-time success rate of foundation construction.

[0107] Based on the first embodiment of this application, in the third embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 7 Before step S60, steps S601 to S602 are also included: Step S601: Collect the measured spatial coordinates of multiple sets of feature control points in the construction area, match the model coordinates of the corresponding control points in the initial digital twin model, and calculate the root mean square error of spatial registration. Step S602: Based on the root mean square error of spatial registration, perform iterative accuracy calibration on the initial digital twin model to obtain the final three-dimensional digital twin model.

[0108] In this embodiment, to address the problems of missing elements, insufficient modeling accuracy, large virtual-real mapping deviation, and inability to adapt to the simulation and deduction needs of cross-border complex construction in traditional digital twin models, this embodiment adopts a multi-source data fusion modeling and feature point registration and calibration mechanism to build a fully covered, high-precision, and virtual-real consistent three-dimensional digital twin model.

[0109] Specifically, firstly, a high-precision 3D topographic model is generated based on airborne lidar point cloud data and oblique photogrammetry data, with a topographic resolution of no less than 0.5 meters. Secondly, the BIM model of the tower structure, foundation design model, conductor and ground wire parameter model, and hardware insulator model are imported, and spatial assembly is completed according to the design coordinates. Then, the 3D model of the objects being crossed is overlaid, including highways, railways, rivers, existing power lines, important buildings, etc., and the grade, clearance requirements, and protection range of the objects being crossed are marked. Finally, meteorological environmental parameter layers and ecologically sensitive area distribution layers are integrated to form an initial digital twin scene, i.e., the initial digital twin model, which includes all elements of topography, equipment, environment, and ecology. After obtaining the initial digital twin model, to achieve real-time mapping between the digital twin model and the physical entity, this embodiment employs a feature control point matching method. The tower feet, foundation top surfaces, apex of the crossing frame, and feature points of the object being crossed are selected as control points for the crossing section. The measured spatial coordinates of these control points are obtained through RTK-GPS field measurements and compared with the corresponding coordinates in the digital twin model. The formula for calculating the root mean square error of spatial registration is:

[0110] In the formula, The root mean square error of spatial registration between the digital twin model and the physical entity. The number of feature control points, For the first The measured x-coordinates of each control point For the first Measured ordinates of each control point For the first Measured elevations of each control point For the first in the digital twin model The x-coordinates of the control points For the first in the digital twin model The ordinates of the control points For the first in the digital twin model Elevation of each control point.

[0111] When the root mean square error of spatial registration exceeds the set threshold, the model calibration process is triggered. Accuracy is restored through point cloud registration and model fine-tuning to obtain the final three-dimensional digital twin model.

[0112] Through the methods described above, a three-dimensional digital twin model of the construction of cross-border transmission line crossings is constructed using digital twin technology. This enables real-time mapping and two-way linkage between the physical construction scene and the digital model, solving the technical problems of information fragmentation, insufficient spatial perception, and difficulty in process traceability in traditional construction management.

[0113] For example, to help understand the implementation process of the cross-border transmission line construction control method obtained by combining this embodiment with the above embodiment one, please refer to... Figure 8 , Figure 8 A simplified flowchart of a method for construction management and control of cross-border transmission lines is provided, specifically: First, construction process data is collected through an integrated sensing network of space, air, ground, and towers, including satellite remote sensing data, UAV-borne lidar and high-definition image data, ground IoT sensor data, tower online monitoring device data, and data reported by construction terminals on both sides of the cross-border area.

[0114] Secondly, based on real-time collected multi-source data, combined with conventional risk factors and risk factors specific to the hot and humid rainforest environment, a multi-factor coupled risk assessment algorithm is used to calculate the risk classification of the entire construction process, generating four levels of risk warnings: blue, yellow, orange, and red.

[0115] Then, a cross-border hierarchical collaborative scheduling architecture is built, consisting of domestic and international dual scheduling domains and a border coordination gateway, to achieve independent control of construction on both sides, negotiation of cross-border operation plans, progress synchronization, emergency response, and output of standardized cross-border collaborative control information.

[0116] Furthermore, focusing on the five core construction procedures, a unique process-level quality traceability chain is constructed for each individual tower based on sensor monitoring, AI visual recognition, and intelligent concrete strength prediction technologies. This enables precise monitoring of construction processes, identification of quality defects, and closed-loop unlocking and control of procedures. Simultaneously, through drone patrol perception and spatial overlay analysis, the scope and intensity of ecological disturbances during construction are identified in real time. Combined with the normalized vegetation index, a long-term assessment of post-construction vegetation restoration is completed, achieving an eco-friendly closed-loop control of construction disturbance, optimization and rectification, and ecological restoration.

[0117] Finally, a three-dimensional digital twin model of the crossing section of the cross-border transmission line is constructed by multi-source data fusion modeling and feature point accuracy calibration. Multi-dimensional business data of risk, collaboration, quality and ecology are superimposed. Based on the physics engine, the construction process simulation, conductor attitude solution and minimum clearance distance verification are completed. The construction plan is dynamically optimized and the crossing safety hazards are eliminated. Finally, an intelligent management and control system for the entire construction process of cross-border transmission lines is formed, which integrates risk warning, cross-border collaboration, quality traceability, ecological protection and simulation control. It is effectively adapted to the complex cross-border construction scenarios of tropical rainforest red clay foundation, high humidity and heat, strong thunderstorms and ecological sensitivity.

[0118] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the construction management method for cross-border transmission lines in this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0119] This application also provides a construction management and control system for cross-border transmission lines; please refer to [reference needed]. Figure 9 The cross-border transmission line construction management and control system includes: Module 10 is used to acquire data throughout the entire construction process; The risk classification calculation module 20 is used to perform risk classification calculations across the construction process based on the data of the entire construction process, using a multi-factor coupled risk assessment algorithm, to obtain risk warning data. The cross-border collaborative management module 30 is used to perform cross-border construction collaborative interaction with cross-border construction entities and output cross-border collaborative management information. The quality traceability module 40 is used to collect process parameters and quality inspection data of each construction process and establish a process quality traceability chain data. The ecological disturbance monitoring module 50 is used to collect orthophotos and lidar point cloud data, and combine them with the spatial coordinate information of multiple disturbance sources to obtain ecological disturbance information. The digital twin simulation and deduction module 60 is used to implement digital twin simulation and deduction control based on a pre-built three-dimensional digital twin model, superimposed with the risk warning data, cross-border collaborative management and control information, process quality traceability chain data and ecological disturbance information.

[0120] The cross-border transmission line construction management and control system provided in this application, employing the cross-border transmission line construction management and control method described in the above embodiments, can solve the technical problem that existing digital twin management and control technologies for power grid infrastructure have limited adaptability and comprehensive management and control capabilities, and cannot simultaneously meet the integrated management and control needs of cross-border collaborative construction, complex environment risk control, real-time perception and processing, construction quality, and ecological protection. Compared with the prior art, the beneficial effects of the cross-border transmission line construction management and control system provided in this application are the same as those of the cross-border transmission line construction management and control method provided in the above embodiments, and other technical features of the cross-border transmission line construction management and control system are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0121] This application provides a cross-border transmission line construction control device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the cross-border transmission line construction control method in the above embodiment 1.

[0122] The following is for reference. Figure 10 The diagram illustrates a structural schematic suitable for implementing cross-border transmission line construction control equipment in the embodiments of this application. The cross-border transmission line construction control equipment in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 10 The cross-border transmission line construction control equipment shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0123] like Figure 10As shown, the cross-border transmission line construction control equipment may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to programs stored in read-only memory (ROM) 1002 or programs loaded from storage device 1003 into random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the cross-border transmission line construction control equipment. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the cross-border transmission line construction control equipment to exchange data wirelessly or via wired communication with other devices. Although the figure shows cross-border transmission line construction control equipment with various systems, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems may be implemented alternatively.

[0124] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0125] The cross-border transmission line construction management and control equipment provided in this application, employing the cross-border transmission line construction management and control method described in the above embodiments, can solve the technical problem that existing digital twin management and control technologies for power grid infrastructure have limited adaptability and comprehensive management and control capabilities, and cannot simultaneously meet the integrated management and control needs of cross-border collaborative construction, complex environment risk control, real-time perception and processing, construction quality, and ecological protection. Compared with the prior art, the beneficial effects of the cross-border transmission line construction management and control equipment provided in this application are the same as those of the cross-border transmission line construction management and control method provided in the above embodiments, and other technical features of the cross-border transmission line construction management and control equipment are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0126] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0127] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0128] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, which are used to execute the cross-border transmission line construction control method in the above embodiments.

[0129] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0130] The aforementioned computer-readable storage medium may be included in the cross-border transmission line construction management and control equipment; or it may exist independently and not be assembled into the cross-border transmission line construction management and control equipment.

[0131] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the cross-border transmission line construction control equipment, the equipment enables the following actions: acquiring data from the entire construction process; using a multi-factor coupled risk assessment algorithm based on the data to calculate risk levels for the cross-border construction process and obtain risk warning data; performing cross-border construction collaborative interaction with the cross-border construction entities and outputting cross-border collaborative control information; collecting process parameters and quality inspection data for each construction procedure and establishing a procedure quality traceability chain; collecting orthophoto and lidar point cloud data, and combining this with spatial coordinate information of multiple disturbance sources to obtain ecological disturbance information; and implementing digital twin simulation and control based on a pre-constructed three-dimensional digital twin model, overlaying risk warning data, cross-border collaborative control information, procedure quality traceability chain data, and ecological disturbance information.

[0132] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0133] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0134] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0135] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., computer programs) for executing the aforementioned cross-border transmission line construction control method. This addresses the technical problem that existing digital twin control technologies for power grid infrastructure have limited adaptability and comprehensive control capabilities, failing to simultaneously meet the integrated control needs of cross-border collaborative construction, complex environment risk control, real-time sensing and processing, construction quality, and ecological protection. Compared to existing technologies, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the cross-border transmission line construction control method provided in the above embodiments, and will not be elaborated upon here.

[0136] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the cross-border transmission line construction management method described above.

[0137] The computer program product provided in this application can solve the technical problem that existing digital twin management and control technologies for power grid infrastructure have limited adaptability and comprehensive management and control capabilities, and cannot simultaneously meet the integrated management and control needs of cross-border collaborative construction, complex environment risk control, real-time perception and processing, construction quality and ecological protection. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the cross-border transmission line construction management and control method provided in the above embodiments, and will not be repeated here.

[0138] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for construction management and control of cross-border transmission lines, characterized in that, The construction management and control methods for cross-border power transmission lines include: Obtain data throughout the entire construction process; Based on the data from the entire construction process, a multi-factor coupled risk assessment algorithm is used to calculate the risk classification across the construction process, and risk warning data is obtained. It enables cross-border construction entities to conduct collaborative interactions and outputs cross-border collaborative management information. Collect process parameters and quality inspection data for each construction procedure, and establish a process quality traceability chain data; Collect orthophotos and lidar point cloud data, and combine them with spatial coordinate information of multiple disturbance sources to obtain ecological disturbance information; Based on a pre-built 3D digital twin model, the aforementioned risk warning data, cross-border collaborative management and control information, process quality traceability chain data, and ecological disturbance information are overlaid to implement digital twin simulation and control.

2. The construction management and control method for cross-border transmission lines as described in claim 1, characterized in that, The steps of using a multi-factor coupled risk assessment algorithm to perform risk classification calculations for the construction process and obtain risk warning data include: Obtain the first risk factor, which includes at least geological risk factor, meteorological risk factor, equipment risk factor, operational risk factor, and environmental risk factor; The weight coefficients of each type of primary risk factor are determined by the analytic hierarchy process, and the measured values ​​of each type of primary risk factor are mapped to risk membership degree using the membership function. The comprehensive risk value is obtained by weighting and summing the weight coefficients and risk membership degrees of the various first risk factors. Based on the comprehensive risk value, construction risks are classified into corresponding risk levels, and corresponding risk warning data are matched.

3. The construction management and control method for cross-border transmission lines as described in claim 2, characterized in that, The step of using a multi-factor coupled risk assessment algorithm to perform risk classification calculations for the construction process and obtain risk warning data further includes: Identify the environmental conditions of the construction area. If the environmental conditions are a hot and humid tropical rainforest environment, then the stability of the red clay foundation, the intensity of thunderstorm activity, the tree growth rate, and the depth of rainwater infiltration on the slope are introduced as the second risk factors. Based on the weight calculation and risk membership mapping of the second risk factor and the first risk factor, the comprehensive risk value of the tropical rainforest in the hot and humid environment is obtained, and the construction risk classification and risk warning data generation are completed.

4. The construction management and control method for cross-border transmission lines as described in claim 1, characterized in that, The steps for performing cross-border construction collaborative interaction with cross-border construction entities and outputting cross-border collaborative management and control information include: It outputs cross-border collaborative management information to cross-border construction entities in at least one of the following: construction plan negotiation, progress synchronization, issuance of work instructions, and emergency response.

5. The construction management method for cross-border transmission lines as described in claim 4, characterized in that, The steps for outputting cross-border collaborative management and control information for cross-border construction entities, including at least one of the following: construction plan negotiation, progress synchronization, work instruction issuance, and emergency response coordination, include: Construct domestic dispatch domains, overseas dispatch domains, and border coordination gateways; The construction plan preparation, construction resource scheduling, construction progress control and on-site safety monitoring are executed through the domestic scheduling domain and the overseas scheduling domain respectively, while retaining their respective scheduling management authority, so as to obtain independent construction scheduling data on both sides; Based on the border coordination gateway, cross-border data interaction, work instruction verification and multi-terminal time synchronization are performed to obtain cross-border construction scheduling data; Implement cross-border construction plan consultation, dynamic progress synchronization, work instruction issuance and emergency coordination to obtain cross-border collaborative operation process data; Based on the aforementioned bilateral independent construction scheduling data, cross-border construction scheduling data, and cross-border collaborative operation process data, cross-border collaborative management and control information is generated.

6. The construction management and control method for cross-border transmission lines as described in claim 1, characterized in that, The steps for collecting process parameters and quality inspection data for each construction process and establishing a process quality traceability chain include: Identify the construction procedures of power transmission lines, and match the corresponding process parameter collection points and quality inspection nodes for foundation pouring, tower erection, conductor and ground wire laying, accessory installation, and grounding device laying. Based on the process parameter collection points and quality inspection nodes, the current construction scenario is identified. If it is determined to be a tropical rainforest season construction scenario, the process parameters of concrete construction and the curing temperature and humidity time history data are collected. Based on the process parameters of the concrete construction and the time history data of temperature and humidity during curing, and combined with the preset quality control threshold corresponding to the red clay foundation conditions, an abnormal quality judgment and early warning are executed. The construction time was determined by calculating the time history data of temperature and humidity during the maintenance period using maturity theory and equivalent age calculation model. Identify construction defects on concrete foundation surfaces and generate a quality defect log. The quality defect ledger is linked to the process parameters of the concrete construction, the curing temperature and humidity time history data, the construction team and the construction time to form a process quality traceability chain data.

7. The construction management method for cross-border transmission lines as described in claim 1, characterized in that, The steps for acquiring orthophoto and lidar point cloud data, and combining spatial coordinate information of multiple disturbance sources to obtain ecological disturbance information include: Collect orthophotos and lidar point cloud data, and obtain spatial coordinate information of various disturbance sources; By combining the spatial coordinate information of the various disturbance sources, orthophotos, lidar point cloud data, and a pre-constructed ecological baseline database of the construction area, the actual disturbance range of each disturbance source and the spatial overlap of each ecologically sensitive layer are calculated. Based on the actual disturbance range of the various disturbance sources and the spatial overlap of the ecologically sensitive layers, an ecological disturbance heatmap is generated using a spatial overlay analysis algorithm. Based on the ecological disturbance heat map, the disturbance range is determined. If the disturbance range is detected to touch the preset ecological sensitive area or the main migration route of wild animals, the corresponding ecological protection early warning is triggered, and the corresponding low-disturbance construction path optimization scheme is generated to optimize and adjust the construction layout and construction land area. Based on the aforementioned ecological disturbance heat map, ecological protection early warning information, and construction optimization and adjustment results, combined with the characteristics of vegetation coverage changes before and after construction, ecological disturbance information is generated.

8. The construction management method for cross-border transmission lines as described in claim 1, characterized in that, The steps for implementing digital twin simulation and control based on a pre-built 3D digital twin model, overlaid with risk warning data, cross-border collaborative management and control information, process quality traceability chain data, and ecological disturbance information, include: Based on the pre-constructed three-dimensional digital twin model, a simulation scenario for the entire construction process is built; The risk warning data, cross-border collaborative management and control information, process quality traceability chain data and ecological disturbance information are superimposed onto the construction process simulation scenario, and simulation is performed under the construction process simulation scenario. In each simulation process, the spatial attitude of the conductor is deduced based on the construction conditions and meteorological conditions, and the minimum clearance distance between the conductor and the object being crossed is calculated. The minimum clearance distance is compared with the preset standard threshold. If the minimum clearance distance does not meet the preset standard threshold, a safety warning is triggered, and the laying tension is adjusted or the construction plan is optimized.

9. The construction management method for cross-border transmission lines as described in claim 8, characterized in that, Prior to the step of overlaying the risk warning data, cross-border collaborative management and control information, process quality traceability chain data, and ecological disturbance information onto the pre-constructed 3D digital twin model, the following steps are included: Collect the measured spatial coordinates of multiple sets of feature control points in the construction area, match them with the model coordinates of the corresponding control points in the initial digital twin model, and calculate the root mean square error of spatial registration. The initial digital twin model is iteratively calibrated based on the spatial registration root mean square error to obtain the final three-dimensional digital twin model.

10. The construction management method for cross-border transmission lines as described in claim 1, characterized in that, The steps for obtaining data throughout the entire construction process include: Establish an integrated sensing network encompassing the sky, air, ground, and tower, and combine it with a multi-type UAV collaborative operation mechanism to collect raw data from the construction site according to the optimal task allocation strategy; The original construction site data is preprocessed by performing video frame sampling, image dehazing and enhancement, sensor data filtering and outlier removal on the original construction site data. The preprocessed raw construction site data is subjected to feature extraction and state recognition using a lightweight edge-side deep learning model, and the edge-side analysis results are output. Based on the preprocessed original construction site data and the side analysis results, local caching, breakpoint resume, and data synchronization are performed to obtain the data for the entire construction process.

11. A construction control system for cross-border power transmission lines, characterized in that, The cross-border power transmission line construction management and control system includes: The acquisition module is used to acquire data throughout the entire construction process; The risk classification calculation module is used to perform risk classification calculations across the construction process based on the data of the entire construction process, and to obtain risk warning data. The cross-border collaborative management module is used to perform cross-border construction collaborative interactions with cross-border construction entities and output cross-border collaborative management information. The quality traceability module is used to collect process parameters and quality inspection data for each construction process and establish a process quality traceability chain data. The ecological disturbance monitoring module is used to collect orthophotos and lidar point cloud data, and combine them with spatial coordinate information of multiple disturbance sources to obtain ecological disturbance information; The digital twin simulation and deduction module is used to implement digital twin simulation and deduction control based on a pre-built three-dimensional digital twin model, overlaying the risk warning data, cross-border collaborative management and control information, process quality traceability chain data, and ecological disturbance information.

12. A construction control device for cross-border power transmission lines, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the cross-border transmission line construction control method as described in any one of claims 1 to 10.

13. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the cross-border transmission line construction control method as described in any one of claims 1 to 10.

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