Power transmission line crossing safety assessment method based on three-dimensional simulation model

Abstract

The invention provides an electric power transmission line crossing safety assessment method based on a three-dimensional simulation model, and relates to the technical field of electric power engineering safety assessment, and the method comprises the steps: S1, multi-source data collection and preprocessing: obtaining crossing region space data and meteorological load data through an unmanned plane laser radar, satellite remote sensing and a total station, constructing a basic database through noise reduction, coordinate unification and format conversion; s2, construction of a high-precision three-dimensional simulation model: establishing a component-level three-dimensional model of the power transmission line and the spanning object by using a BIM technology, integrating to form a complete scene containing terrain and vegetation, and performing high-precision modeling: fusing an unmanned aerial vehicle laser radar and the BIM technology to realize millimeter-level precision three-dimensional modeling, and comprehensively restoring a spanning scene space relationship; and multi-load coupling analysis: considering the comprehensive action of static, dynamic and extreme meteorological loads, and solving the problem of one-sided load calculation of a traditional method.

Description

Technical Field

[0001] The present invention relates to the technical field of power engineering safety assessment, specifically a power transmission line crossing safety assessment method based on a three-dimensional simulation model, which is suitable for safety quantitative assessment and risk warning of complex scenarios such as transmission lines crossing roads, railways, rivers, and buildings. Background Art

[0002] Safety assessment of power transmission lines crossing complex terrain or buildings (structures) is a key step in power transmission line projects. Traditional assessment methods mainly rely on two-dimensional drawings combined with empirical formulas, which have the following shortcomings:

[0003] Incomplete spatial analysis: The three-dimensional spatial relationship between the transmission line and the crossing object cannot be accurately simulated, and the impact of dynamic factors such as conductor sag, wind deflection, and icing on the safety distance is easily overlooked.

[0004] Rough load calculation: only static loads (such as the weight of the conductor) are considered, lacking coupled analysis of extreme weather conditions (strong winds, heavy rain, icing) and dynamic loads on crossing structures (such as vibration caused by vehicle traffic);

[0005] The evaluation indicators are single: whether the safety distance meets the standards is often used as the only criterion, and a comprehensive evaluation system including structural stress, fatigue life, and failure probability has not been established.

[0006] While existing technologies utilize drone modeling or finite element analysis for local structural verification (e.g., the 3D modeling method for power transmission lines disclosed in CN108564321A), a comprehensive technical system spanning data acquisition, 3D modeling, and multi-dimensional safety assessment has yet to be established. Furthermore, the system lacks the ability to dynamically simulate scenarios across their entire lifecycle. Therefore, a systematic safety assessment method based on high-precision 3D simulation models is urgently needed to achieve accurate modeling, multi-load coupling analysis, and quantitative safety assessment across scenarios. Summary of the Invention

[0007] (1) Purpose of the invention

[0008] A three-dimensional simulation model-based safety assessment method for power transmission line crossings is provided. Through multi-source data fusion modeling, multi-physics field coupling analysis, and multi-level safety indicator evaluation, it solves the problems of inaccurate spatial analysis, extensive load calculation, and a single evaluation system in traditional methods, thereby improving the safety and reliability of transmission line crossing projects.

[0009] (2) Technical solution

[0010] The present invention provides a method for assessing the safety of power transmission line crossings based on a three-dimensional simulation model, comprising the following steps:

[0011] S1. Multi-source data collection and preprocessing

[0012] Spatial data acquisition: Use drone lidar scanning to obtain three-dimensional point cloud data of regional terrain, vegetation, and buildings (structures), with an accuracy of ≤5cm; combine with satellite remote sensing imagery (resolution ≤0.5m) to extract large-scale geographic information; use total stations to measure key parameters such as tower coordinates and conductor suspension point elevations, with an error of ≤2mm.

[0013] Meteorological and load data collection: Access real-time data from regional meteorological stations (wind speed, temperature, humidity, ice thickness), collect historical extreme meteorological data (recurrence period ≥ 50 years); conduct on-site surveys on the frequency and load parameters of dynamic load sources (such as road vehicles and railway trains).

[0014] Data preprocessing: Build a standardized basic database through point cloud noise reduction (moving least squares method), geographic coordinate unification (WGS84 to engineering coordinate system), and data format conversion (LAS to OBJ).

[0015] S2. Construction of high-precision three-dimensional simulation model

[0016] Geometric modeling: Based on pre-processed data, BIM technology is used to establish a three-dimensional model of the transmission line (including towers, conductors, insulators, and hardware) with component-level accuracy (such as segmented modeling of insulator strings). Parametric modeling methods are used to achieve dynamic adjustment of conductor sag with changes in temperature and tension.

[0017] Spanning object modeling: Detailed modeling of spanning objects such as roads / railways (including bridge structures), rivers (including water level variation range), and buildings, with key dimensions (such as height limit, clear width) and material properties (elastic modulus, density) marked.

[0018] Scenario integration: Import the transmission line model and the spanning object model into a simulation platform (such as ANSYS Space Claim) to create a complete three-dimensional scene including terrain, vegetation, and atmospheric boundary layer, and set the origin of the coordinate system to the center of the tower foundation at the midpoint of the span.

[0019] S3, Multi-physics coupled load analysis

[0020] Static load calculation:

[0021] Wire deadweight load: F g =ρ·A·L·g (ρ is the conductor density, A is the cross-sectional area, L is the span, and g is the acceleration due to gravity);

[0022] Insulator string tension: Calculates conductor tension distribution based on the catenary equation, taking into account the insulator string's deadweight and wind load.

[0023] Dynamic load simulation:

[0024] Wind load: Davenport pulsating wind speed spectrum is used to simulate the natural wind field and calculate the wind deflection angle of the conductor (θ=arctan(F w / F g ), F w is the wind load per unit length);

[0025] Ice load: Based on the IEC60826 standard, the increase in conductor weight and windage due to ice thickness is calculated, taking into account the uneven distribution of ice.

[0026] Vibration load: For dynamic spanning structures such as railway bridges, the measured vibration acceleration time history curve (sampling frequency ≥ 100Hz) is imported and a simple harmonic vibration load is applied.

[0027] Boundary condition setting: The bottom of the tower is set as a fixed constraint, tension boundaries are applied at both ends of the conductor, and the spanning support structure is set with constraint conditions according to the actual foundation form (pile foundation / gravity type).

[0028] S4. Calculation of multi-level security assessment indicators

[0029] Space safety indicators:

[0030] Clearance distance: Calculate the minimum vertical distance Dv and horizontal distance D_h between the conductor (taking into account windage / sag) and the crossing object to determine whether the regulatory requirements are met (e.g., clearance of highway crossings ≥ 7m);

[0031] Clearance margin: M = D_{actual} - D_{required}, where D_{actual} is the simulation calculated distance and D_{required} is the standard minimum distance.

[0032] Structural safety indicators:

[0033] Stress intensity: Extract the equivalent stress σ of key components such as tower main materials and conductor hardware, and calculate the safety factor S = σ yield / σ(σ yield is the material yield strength);

[0034] Fatigue life: Based on Miner's linear cumulative damage theory, the fatigue damage degree D = \sum(n_i / N_i) under alternating loads is calculated to predict the remaining life of the component.

[0035] Failure risk indicators:

[0036] Fuzzy comprehensive evaluation: Establish a multi-level evaluation system that includes meteorological conditions, equipment aging, and operation and maintenance level. Use the analytic hierarchy process (AHP) to determine indicator weights and calculate the failure probability Pf through the fuzzy membership function.

[0037] Risk level classification: The safety status is divided into four levels (safe, warning, dangerous, serious danger), corresponding to the threshold range: P f <0.1, 0.1≤P f <0.3, 0.3≤P f <0.5, P f ≥0.5.

[0038] S5. Visual evaluation and early warning output

[0039] 3D visualization: Dynamic rendering across scenes is achieved in the simulation platform, supporting multi-viewing (bird's eye view / roaming) and real-time annotation of key indicators (such as wire windage trajectory and stress cloud map);

[0040] Report generation: Automatically output the "Span Safety Assessment Report", which includes 3D model files, load analysis data, safety index calculation table, and risk level conclusions;

[0041] Early warning mechanism: When M<0 or P f When the value is ≥0.3, a graded warning (yellow / red warning) is triggered, and corrective suggestions are given (such as adjusting the conductor sag and installing a wind deflection protection device).

[0042] The present invention provides a method for assessing the safety of power transmission line crossings based on a three-dimensional simulation model, which has the following beneficial effects:

[0043] High-precision modeling: Integrating drone lidar and BIM technology to achieve millimeter-level precision 3D modeling, fully restoring spatial relationships across scenes;

[0044] Multi-load coupling analysis: Considering the combined effects of static, dynamic, and extreme meteorological loads, it solves the problem of one-sided load calculation in traditional methods;

[0045] Quantitative assessment system: Establish multi-level indicators covering spatial safety, structural safety, and failure risk, achieving an upgrade from single distance verification to systematic safety assessment;

[0046] Strong engineering practicality: Visualization results and early warning mechanisms directly serve design optimization and operation and maintenance decision-making, significantly improving the safety and economy of transmission line crossing projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Attachment Figure 1 Intuitively display the core process of the method and reflect the logical sequence of each step.

[0048] Attachment Figure 2 With parametric modeling as the core, the dynamic adjustment mechanism of conductor sag with environmental variables is demonstrated.

[0049] Attachment Figure 3 Focus on evaluation indicators and early warning logic.

[0050] Attachment Figure 4 Clarify the triggering conditions for risk grading.

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments are briefly introduced below.

[0052] The drawings described below only relate to some embodiments of the present invention, but are not intended to limit the present invention. DETAILED DESCRIPTION

[0053] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the described embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0054] The present invention proposes a method for assessing the safety of power transmission line crossings based on a three-dimensional simulation model, comprising the following steps:

[0055] S1. Multi-source data collection and preprocessing

[0056] Spatial data acquisition: Use drone lidar scanning to obtain three-dimensional point cloud data of regional terrain, vegetation, and buildings (structures), with an accuracy of ≤5cm; combine with satellite remote sensing imagery (resolution ≤0.5m) to extract large-scale geographic information; use total stations to measure key parameters such as tower coordinates and conductor suspension point elevations, with an error of ≤2mm.

[0057] Meteorological and load data collection: Access real-time data from regional meteorological stations (wind speed, temperature, humidity, ice thickness), collect historical extreme meteorological data (recurrence period ≥ 50 years); conduct on-site surveys on the frequency and load parameters of dynamic load sources (such as road vehicles and railway trains).

[0058] Data preprocessing: Build a standardized basic database through point cloud noise reduction (moving least squares method), geographic coordinate unification (WGS84 to engineering coordinate system), and data format conversion (LAS to OBJ).

[0059]

[0060] S2. Construction of high-precision three-dimensional simulation model

[0061] Geometric modeling: Based on pre-processed data, BIM technology is used to establish a three-dimensional model of the transmission line (including towers, conductors, insulators, and hardware) with component-level accuracy (such as segmented modeling of insulator strings). Parametric modeling methods are used to achieve dynamic adjustment of conductor sag with changes in temperature and tension.

[0062] Spanning object modeling: Detailed modeling of spanning objects such as roads / railways (including bridge structures), rivers (including water level variation range), and buildings, with key dimensions (such as height limit, clear width) and material properties (elastic modulus, density) marked.

[0063] Scenario integration: Import the transmission line model and the spanning object model into a simulation platform (such as ANSYS Space Claim) to create a complete three-dimensional scene including terrain, vegetation, and atmospheric boundary layer, and set the origin of the coordinate system to the center of the tower foundation at the midpoint of the span.

[0064] S3, Multi-physics coupled load analysis

[0065] Static load calculation:

[0066] Wire deadweight load: F g =ρ·A·L·g (ρ is the conductor density, A is the cross-sectional area, L is the span, and g is the acceleration due to gravity);

[0067] Insulator string tension: Calculates conductor tension distribution based on the catenary equation, taking into account the insulator string's deadweight and wind load.

[0068] Dynamic load simulation:

[0069] Wind load: Davenport pulsating wind speed spectrum is used to simulate the natural wind field and calculate the wind deflection angle of the conductor (θ=arctan(F w / F g ), F w is the wind load per unit length);

[0070] Ice load: Based on the IEC60826 standard, the increase in conductor weight and windage due to ice thickness is calculated, taking into account the uneven distribution of ice.

[0071] Vibration load: For dynamic spanning structures such as railway bridges, the measured vibration acceleration time history curve (sampling frequency ≥ 100Hz) is imported and a simple harmonic vibration load is applied.

[0072] Boundary condition setting: The bottom of the tower is set as a fixed constraint, tension boundaries are applied at both ends of the conductor, and the spanning support structure is set with constraint conditions according to the actual foundation form (pile foundation / gravity type).

[0073] S4. Calculation of multi-level security assessment indicators

[0074] Space safety indicators:

[0075] Clearance distance: Calculate the minimum vertical distance Dv and horizontal distance D_h between the conductor (taking into account windage / sag) and the crossing object to determine whether the regulatory requirements are met (e.g., clearance of highway crossings ≥ 7m);

[0076] Clearance margin: M = D_{actual} - D_{required}, where D_{actual} is the simulation calculated distance and D_{required} is the standard minimum distance.

[0077] Structural safety indicators:

[0078] Stress intensity: Extract the equivalent stress σ of key components such as tower main materials and conductor hardware, and calculate the safety factor S = σ yield / σ(σ yield is the material yield strength);

[0079] Fatigue life: Based on Miner's linear cumulative damage theory, the fatigue damage degree D = \sum(n_i / N_i) under alternating loads is calculated to predict the remaining life of the component.

[0080] Failure risk indicators:

[0081] Fuzzy comprehensive evaluation: Establish a multi-level evaluation system that includes meteorological conditions, equipment aging, and operation and maintenance level. Use the analytic hierarchy process (AHP) to determine indicator weights and calculate the failure probability Pf through the fuzzy membership function.

[0082] Risk level classification: The safety status is divided into four levels (safe, warning, dangerous, serious danger), corresponding to the threshold range: P f <0.1, 0.1≤P f <0.3, 0.3≤P f <0.5, P f ≥0.5.

[0083] S5. Visual evaluation and early warning output

[0084] 3D visualization: Dynamic rendering across scenes is achieved in the simulation platform, supporting multi-viewing (bird's eye view / roaming) and real-time annotation of key indicators (such as wire windage trajectory and stress cloud map);

[0085] Report generation: Automatically output the "Span Safety Assessment Report", which includes 3D model files, load analysis data, safety index calculation table, and risk level conclusions;

[0086] Early warning mechanism: When M<0 or P f When the value is ≥0.3, a graded warning (yellow / red warning) is triggered, and corrective suggestions are given (such as adjusting the conductor sag and installing a wind deflection protection device).

[0087] Take a 500kV transmission line crossing a highway as an example:

[0088] Data collection: Using a DJI M300RTK drone equipped with a RieglVUX-1 lidar, we acquired point cloud data of the highway bridge (120m long, 26m wide) and surrounding terrain, and measured the tower coordinates (X=1000, Y=2000, Z=150m).

[0089] Model construction: A wire model (LGJ-400 / 35, diameter 26.82 mm) was created in Autodesk Revit. The bridge model was simulated using Beam188 units, and the highway height limit was set to 5.5 m.

[0090] Load analysis: Applying a design wind speed of 30 m / s (corresponding to a 50-year return period), the maximum wind deflection angle of the conductor is calculated to be 18°. At this time, the minimum clearance between the conductor and the bridge deck is 6.2 m (the standard requires ≥ 7 m), triggering a yellow warning.

[0091] Evaluation and Optimization: It is recommended to increase the tower height by 2m, re-simulate and calculate the clearance distance to 7.3m, ensure the safety factor meets the standard, and output the optimized design plan.

Claims

1. A method for assessing the safety of power transmission line crossings based on a three-dimensional simulation model, characterized in that: The following steps are involved: S1. Multi-source data acquisition and preprocessing: Using UAV lidar, satellite remote sensing, and total stations to obtain spatial data and meteorological payload data across regions, a basic database is constructed through noise reduction, coordinate unification, and format conversion. S2. Construction of high-precision 3D simulation models: Using BIM technology to build component-level 3D models of transmission lines and crossing structures, integrating them to form a complete scene including terrain and vegetation; S3. Multi-physics coupled load analysis: Calculate static loads (self-weight, tension), dynamic loads (wind, icing, vibration), and set boundary conditions for coupled simulation. S4. Calculation of multi-level safety assessment indicators: Obtain spatial safety indicators (clearance distance, clearance margin), structural safety indicators (stress intensity, fatigue life), and failure risk indicators (fuzzy comprehensive failure probability); S5. Visual evaluation and warning output: Dynamic rendering of 3D scenes, generation of evaluation reports, and triggering of graded warnings based on indicator thresholds.

2. The method according to claim 1, characterized in that The spatial data acquisition accuracy in S1 meets the following requirements: the UAV lidar point cloud accuracy is ≤5cm, and the total station measured parameter error is ≤2mm.

3. The method according to claim 1, characterized in that The three-dimensional modeling in S2 adopts a parametric method to achieve dynamic adjustment of the conductor sag with temperature and tension, and the modeling accuracy reaches the component level.

4. The method according to claim 1, wherein The dynamic load simulation in S3 includes: wind load calculation based on Davenport spectrum, IEC standard icing load calculation, and vibration load application based on measured vibration time history curves.

5. The method according to claim 1, wherein The failure risk index calculation in S4 adopts the analytic hierarchy process (AHP) to determine the weight, combines the fuzzy membership function to calculate the failure probability Pf, and divides it into four risk levels.

6. The method according to claim 1, characterized in that The three-dimensional visualization in S5 supports multi-view viewing and real-time annotation of key indicators, and the early warning mechanism is triggered when the gap margin M<0 or Pf≥0.3.

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