A tower weak point evaluation method based on multi-working-condition ice shedding jump oscillation analysis

Abstract

This invention relates to the field of tower assessment technology, specifically a method for assessing weak points in towers based on multi-condition de-icing jump oscillation analysis. The method includes: S1, constructing a finite element model of an iced transmission tower system; S2, constructing a condition database based on several influencing factors; S3, performing de-icing jump oscillation simulations on each condition in the condition database based on the finite element model to obtain a set of simulation results; S4, identifying and locating weak points in the transmission towers based on the simulation result set, where weak points are characterized by locations in the simulation result set where the frequency of stress exceeding limits, deformation exceeding limits, or internal force abrupt changes is greater than a preset frequency; and S5, analyzing and evaluating the weak points to obtain assessment results. This method achieves accurate location and identification assessment of weak points in towers under the oscillation effect of de-icing impact, and provides technical support for subsequent preventative reinforcement and structural optimization of the towers.

Description

Technical Field

[0001] This invention relates to the field of tower assessment technology, specifically a method for assessing weak points in towers based on multi-condition de-icing jump oscillation analysis. Background Technology

[0002] Overhead transmission lines are critical infrastructure of the power system, and their safe operation is crucial to the national economy and people's livelihood. In the central and southern regions of my country and the mountainous areas of southwest China, low temperatures, rain, snow, and ice in winter often lead to severe icing on the conductors. When weather conditions change, the icing often occurs unevenly and asynchronously, causing violent ice-breaking phenomena. This process is not only a major cause of electrical faults such as phase-to-phase flashover and line tripping, but also a major source of disasters that can cause mechanical damage to transmission towers and even collapse.

[0003] The instant the ice detaches, the elastic potential energy accumulated in the conductor is released, transforming into violent vertical jumps and back-and-forth oscillations. This dynamic effect is extremely dangerous: on the one hand, the large jumps significantly reduce the electrical clearance between the conductor and the ground wire, making it highly susceptible to discharge; on the other hand, and more critically, the jumping process generates dynamic unbalanced tension at the conductor suspension point that far exceeds the static ice load. This tension is transmitted as shock waves through the insulator strings and hardware to the main structure of the tower, such as the crossarm and tower body, forming a periodic, high-amplitude dynamic impact load that poses multiple threats to the tower: it may cause instantaneous overload failure of components; it may cause fatigue damage and crack initiation at key connection points during repeated "ice-detachment" cycles; and it may even trigger local resonance, drastically amplifying the dynamic response and accelerating structural failure.

[0004] Existing methods are mostly based on simplified models, failing to fully consider the transient and nonlinear nature of the de-icing process and the dynamic interaction between the tower and conductor systems. Traditional design treats the mechanical calculations of the tower and conductor relatively independently; this "decoupling" approach cannot accurately reflect the load transmission path and structural force redistribution during the strongly coupled dynamic process of de-icing jumps. While there is a deep understanding of the conductor's behavior, the local dynamic response characteristics, internal force distribution patterns, and identification of potential weak points of the tower as the main load-bearing component under the impact of de-icing remain insufficient. In engineering practice, weak points are often only deduced after a tower collapse, which is costly and time-consuming. Summary of the Invention

[0005] The purpose of this invention is to solve the technical problem that potential weak points of transmission towers cannot be identified and assessed under the condition of jumping oscillation caused by ice shedding in transmission lines. It realizes the accurate location, identification and assessment of weak points of towers under the oscillation effect of ice shedding impact, and provides technical support for the subsequent preventive reinforcement and structural optimization of towers.

[0006] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: This invention provides a method for assessing weak points in transmission towers based on multi-condition de-icing jump oscillation analysis, comprising: S1, constructing a finite element model of an icing transmission tower system; S2, constructing a condition library based on several influencing factors; S3, performing de-icing jump oscillation simulations on each condition in the condition library based on the finite element model to obtain a set of simulation results; S4, identifying and locating weak points in the transmission towers based on the set of simulation results, wherein the weak points are characterized by locations in the set of simulation results where the frequency of stress exceeding limits, deformation exceeding limits, or internal force abrupt changes is greater than a preset frequency; and S5, analyzing and evaluating the weak points to obtain evaluation results.

[0007] This solution constructs a finite element model of the icing-covered transmission tower system, builds a case library by combining multiple operating conditions and influencing factors, and performs simulations step by step. This overcomes the technical problem of simplified analysis based on a single operating condition in existing technologies, which leads to biased analysis. It realistically recreates the strongly coupled dynamic process of de-icing jump oscillation. By combining the simulation results from multiple operating conditions with the frequency of stress exceeding limits, deformation exceeding limits, and internal force mutations, weak points are identified. This solves the technical problem of accurately locating potential weak points in towers in existing technologies, improving the accuracy and targeting of weak point identification. Through analysis and evaluation of weak points, precise location and scientific assessment of weak points in towers under de-icing oscillation conditions are achieved. This overcomes the lag in existing technologies that can only infer weak points after a disaster, providing a reliable theoretical basis and technical support for preventive reinforcement and structural optimization of transmission towers. It reduces the risk of tower damage and collapse caused by de-icing disasters, ensuring the safe and stable operation of overhead transmission lines.

[0008] Optionally, the step of constructing a working condition library based on several working condition influencing factors includes: S2-1, setting a benchmark working condition, wherein the benchmark working condition is a working condition in which the parameters of each working condition influencing factor are all set to preset benchmark values; S2-2, based on the benchmark working condition, using the control variable method to change only the parameter of one working condition influencing factor, while keeping the benchmark values ​​of the other working condition influencing factors unchanged, to form several single-factor working conditions; S2-3, based on the benchmark working condition, combining different parameter levels of several working condition influencing factors to form several multi-factor coupled working conditions; S2-4, summarizing the benchmark working condition, the single-factor working conditions, and the multi-factor coupled working conditions to construct a working condition library.

[0009] Optionally, the step of performing de-icing jump oscillation simulation on each working condition in the working condition library includes: S3-1, setting the time step and total analysis time for nonlinear transient dynamic simulation analysis, wherein the total analysis time is not less than the oscillation decay time of de-icing jump; S3-2, performing nonlinear transient dynamic simulation analysis on each working condition in the working condition library based on the time step and the total analysis time to obtain time history data of the iced transmission tower line system, and then summarizing the time history data of all working conditions to obtain a set of simulation results.

[0010] Optionally, the weak points of the transmission tower can be identified and located based on the simulation result set using the following first identification method: S4-1, Based on the simulation result set, extract the internal force time history data of each component in the transmission tower under different working conditions, and then obtain the peak internal force of each component; S4-2, Calculate the attention score of each component based on the peak internal force, the attention score characterizes the stress performance of each component under different working conditions, and designate the component parts with the attention score greater than the preset attention score threshold as weak points.

[0011] Optionally, the weak points of the transmission tower can be identified and located based on the simulation result set using the following second identification method: S4-3, based on the simulation result set, extract the stress time history data of each component in the transmission tower under different working conditions; S4-4, calculate the theoretical stress concentration coefficient based on the cross-sectional properties of each component and the stress time history data, and identify the component parts with the theoretical stress concentration coefficient greater than the preset theoretical stress concentration coefficient threshold as weak points.

[0012] Optionally, the icing-covered transmission tower system includes transmission conductors, transmission ground wires, insulator strings, and transmission towers; the steps of constructing the finite element model of the icing-covered transmission tower system include: S1-1, using cable elements to simulate the transmission conductors and the transmission ground wires, using two-force bar elements to simulate the insulator strings, and using spatial beam elements to simulate the transmission towers; S1-2, assigning values ​​to the cross-sectional area, elastic modulus, coefficient of linear expansion, and unit mass of the transmission conductors and the transmission ground wires, and assigning values ​​to the elastic modulus, density, and Poisson's ratio of the transmission towers; S1-3, setting fixed constraints at the base of the transmission towers, and setting continuous constraints on adjacent spans of conductors through tension towers or straight-line towers; S1-4, setting Rayleigh damping coefficients for the transmission conductors and transmission towers to construct the finite element model of the icing-covered transmission tower system.

[0013] Optionally, the evaluation results include the identified weak points and their corresponding adverse working conditions and time history data; the method further includes: S6-1, storing the weak points, the corresponding adverse working conditions and time history data in a structured manner to obtain a tower weak point database.

[0014] Optionally, the weak points include strength weak points, fatigue weak points, and resonance weak points; the method further includes: S6-2, improving the strength weak points by increasing the cross-section of the component; improving the fatigue weak points by changing the connection details or adding a damper; and improving the resonance weak points by installing a tuned mass damper, increasing the local stiffness, or increasing the local mass.

[0015] Optionally, the time history data includes conductor response data, displacement / acceleration data, component internal force data, connection point force data, and stress distribution data; the conductor response data includes vertical displacement time history data of the mid-span of the conductor at the de-icing span and tension time history data of the suspension point; the displacement / acceleration data includes vertical and lateral displacement of the end nodes of each phase crossarm, vertical and lateral displacement of the nodes at typical tower heights, and acceleration time history data; the component internal force data includes axial force time history data, shear force time history data, and bending moment time history data of the crossarm root section, the tower slope section, and the main diagonal member intersection section; the connection point force data includes dynamic reaction force data at the conductor suspension point and its distribution data on the crossarm; the stress distribution data includes time history data of surface stress cloud maps for weak areas.

[0016] Optionally, the factors affecting the operating conditions include de-icing method, de-icing rate, ice thickness, spacing, number of speeds, wind speed, and de-icing speed; the parameter levels of the de-icing method include uniform de-icing across the entire section, de-icing from the middle to the end, de-icing from the end to the middle, and zipper-style de-icing; the parameter level of the de-icing rate is classified according to percentage; the parameter level of the ice thickness is classified according to millimeters; and the parameter levels of the de-icing speed include edge de-icing, secondary edge de-icing, and middle de-icing.

[0017] The beneficial effects of this invention are: By constructing a finite element model of a realistic icing-covered transmission tower-line system, and employing reasonable element simulation, parameter assignment, and constraint settings, the mechanical characteristics of tower-line coupling were realistically reproduced. This overcomes the shortcomings of traditional simplified models and decoupling analyses, which cannot reflect the strongly coupled dynamic process of ice removal jumping, providing a reliable foundation for subsequent simulation analysis. A complete operating condition library was constructed through baseline operating conditions, single-factor operating conditions, and multi-factor coupled operating conditions, taking into account various influencing factors such as ice removal methods and ice thickness, avoiding the one-sidedness of single-condition analysis, and comprehensively covering complex ice removal scenarios in the field. Through nonlinear transient dynamic simulation, the operating conditions were traversed one by one, and multi-dimensional time history data were obtained and summarized to form a simulation result set. This captured the transient characteristics and dynamic response laws of ice removal jumping oscillation, providing comprehensive and accurate data support for weak point identification.

[0018] Two identification methods were employed to pinpoint weak points: peak internal force and attention scores were used to identify high-response areas under various stress conditions, while stress time history data and theoretical stress concentration coefficients were used to identify stress concentration areas inherent in the structure itself. This ensured the accuracy and specificity of weak point identification, overcoming the misjudgment and omission problems of traditional single-method identification and breaking the lag in post-disaster weak point deduction. Through analysis and evaluation of weak points, the corresponding adverse working conditions and time history data were identified, allowing for further classification of weak points and the provision of targeted improvement plans. This achieved a closed loop of identification-evaluation-improvement. Furthermore, the construction of a tower weak point database provided traceable technical support for subsequent tower operation, maintenance, and reinforcement optimization.

[0019] This invention clearly defines the time-history data and the parameter levels of influencing factors under operating conditions, ensuring the rigor and feasibility of the technical solution and adapting it to the evaluation needs of transmission towers of different specifications and in different scenarios. It achieves precise location, scientific assessment, and targeted improvement of weak points in towers under de-icing oscillation conditions, effectively reducing the risk of tower component failure, fatigue damage, and even collapse caused by de-icing disasters. This ensures the safe and stable operation of overhead transmission lines and provides theoretical basis and technical support for preventive maintenance and structural optimization of transmission lines in areas prone to freezing, demonstrating significant engineering application value and practical significance. Attached Figure Description

[0020] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings. The drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings.

[0021] Figure 1 This is a flowchart of a method for assessing weak points of towers based on multi-condition de-icing jump oscillation analysis in this invention; Figure 2 This is a flowchart of a comprehensive identification of weak points in a tower under multiple working conditions, provided in an embodiment of the present invention. Figure 3 This is a front view of a finite element model of a transmission tower in an icing transmission tower system according to the present invention. Figure 4 This is a side view of a finite element model of a transmission tower in an icing transmission tower system according to the present invention. Figure 5 This is a top view of the finite element model of a transmission tower in an icing transmission tower system according to the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only one preferred embodiment of this invention and are only used to explain this invention. They do not limit the scope of protection of this invention. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0023] Reference Figure 1 This invention provides a method for assessing weak points in towers based on multi-condition de-icing jump oscillation analysis, comprising: S1. Construct a finite element model of the icing transmission tower system.

[0024] S2. Construct a working condition library based on several influencing factors.

[0025] S3. Based on the finite element model, perform ice-breaking jump oscillation simulation on each working condition in the working condition library to obtain a set of simulation results.

[0026] S4. Based on the simulation results set, identify and locate the weak points of the transmission towers. Weak points are characterized by locations in the simulation results set where the frequency of stress exceeding limits, deformation exceeding limits, or sudden changes in internal forces is greater than the preset frequency. The preset frequency is reasonably set based on the structural design specifications of the transmission towers, engineering operation and maintenance experience, and the probability of de-icing disasters.

[0027] S5. Analyze and evaluate the weaknesses to obtain the evaluation results.

[0028] This solution constructs a finite element model of the icing-covered transmission tower system, builds a case library by combining multiple operating conditions and influencing factors, and performs simulations step by step. This overcomes the technical problem of simplified analysis based on a single operating condition in existing technologies, which leads to biased analysis. It realistically recreates the strongly coupled dynamic process of de-icing jump oscillation. By combining the simulation results from multiple operating conditions with the frequency of stress exceeding limits, deformation exceeding limits, and internal force mutations, weak points are identified. This solves the technical problem of accurately locating potential weak points in towers in existing technologies, improving the accuracy and targeting of weak point identification. Through analysis and evaluation of weak points, precise location and scientific assessment of weak points in towers under de-icing oscillation conditions are achieved. This overcomes the lag in existing technologies that can only infer weak points after a disaster, providing a reliable theoretical basis and technical support for preventive reinforcement and structural optimization of transmission towers. It reduces the risk of tower damage and collapse caused by de-icing disasters, ensuring the safe and stable operation of overhead transmission lines.

[0029] An icing-covered transmission tower system includes transmission conductors, ground wires, insulator strings, and transmission towers. The steps for constructing a finite element model of this system include: S1-1. Cable elements are used to simulate the transmission conductors and ground wires, two-force bar elements are used to simulate the insulator strings, and spatial beam elements are used to simulate the transmission towers. Cable elements are finite element units that can only withstand axial tension and cannot withstand compression or bending moments. They are used to simulate the large deformation mechanical characteristics of flexible suspension structures such as conductors and ground wires, closely reflecting the actual stress characteristics of only being able to withstand tension. Two-force bar elements are simplified to bar elements that only transmit axial tension / compression and do not withstand bending moments. They are used to simulate insulator strings, consistent with their actual stress characteristics of only transmitting linear tension. Spatial beam elements are three-dimensional beam elements that can withstand axial force, shear force, bending moment, and torque. They are used to simulate rigid components such as the main members, diagonal members, and crossarms of the tower, and can accurately calculate internal forces and deformations under complex stress conditions.

[0030] S1-2. Assign values ​​to the cross-sectional area, elastic modulus, coefficient of linear expansion, and unit mass of the transmission conductor and the transmission ground wire, and assign values ​​to the elastic modulus, density, and Poisson's ratio of the transmission tower.

[0031] S1-3. Fixed constraints are set at the base of the transmission towers, and continuous constraints are set on adjacent spans of conductors through tension towers or straight-line towers. Fixed constraints refer to restricting all translational and rotational degrees of freedom of the tower base nodes to simulate the actual boundary conditions of the rigid connection between the tower and the foundation. Continuous constraints refer to applying constraints to adjacent spans of conductors through tension towers / straight-line towers to ensure the mechanical continuity of the multi-span tower-line system and simulate the inter-span force transmission relationship of actual lines.

[0032] S1-4. Rayleigh damping coefficients are set for the transmission lines and towers to construct a finite element model of the icing transmission tower system. Rayleigh damping coefficient: A damping model used in finite element dynamics simulation, consisting of mass damping coefficient and stiffness damping coefficient, used to simulate energy dissipation of the structure during vibration, making the dynamic response more realistic.

[0033] The steps for constructing a working condition library based on several influencing factors include: S2-1. Set the baseline operating condition. The baseline operating condition is the operating condition in which all parameters of the influencing factors of each operating condition are set to preset baseline values. Baseline operating condition: Select the most common and representative operating condition of the line as the comparison baseline for subsequent control variable analysis of single-factor and multi-factor operating conditions.

[0034] It should be noted that the factors affecting the operating conditions include the de-icing method, de-icing rate, icing thickness, span distance, number of spans, wind speed, and de-icing span position. The parameter levels for the de-icing method include uniform de-icing across the entire section, de-icing from the middle to the ends, de-icing from the ends to the middle, and zipper-style de-icing. The parameter level for the de-icing rate is based on percentages. The parameter level for icing thickness is based on millimeters. The parameter levels for the de-icing span position include edge de-icing, secondary edge de-icing, and middle edge de-icing. The baseline operating condition consists of preset baseline de-icing method, baseline de-icing rate, baseline icing thickness, baseline span distance, baseline number of spans, baseline wind speed, and baseline de-icing span position.

[0035] S2-2. Based on the aforementioned baseline operating conditions, the controlled variable method is used to change only the parameter of one operating condition influencing factor, while keeping the baseline values ​​of the remaining operating condition influencing factors unchanged, thus forming several single-factor operating conditions. Controlled variable method: Only the parameter of one operating condition influencing factor is changed each time, while the baseline values ​​of the remaining factors are kept unchanged. This method is used to analyze the influence of a single factor on the de-icing oscillation response.

[0036] S2-3. Based on the benchmark working condition, different parameter levels of several working condition influencing factors are combined to form several multi-factor coupled working conditions. At the same time, the parameter combinations of multiple working condition influencing factors are changed to simulate complex actual de-icing scenarios on site, avoiding the one-sidedness of single working condition analysis.

[0037] S2-4. Summarize the baseline working conditions, the single-factor working conditions, and the multi-factor coupled working conditions to construct a working condition library.

[0038] The step of performing de-icing jump oscillation simulation on each working condition in the working condition library includes: S3-1. Set the time step and total analysis time for the nonlinear transient dynamics simulation analysis. Nonlinear transient dynamics simulation: Considering geometric nonlinearity (large deformation of the conductor) and material nonlinearity (stress-strain nonlinearity), this time-domain dynamics analysis is used to simulate the transient impact and oscillation process during ice removal. The total analysis time should not be less than the oscillation decay time of the ice removal jump. The oscillation decay time refers to the time from the occurrence of ice removal until the structural vibration amplitude decays to a negligible level (e.g., less than 5% of the initial amplitude), ensuring that the simulation time covers the complete dynamic response process.

[0039] S3-2. Based on the time step and the total analysis time, perform nonlinear transient dynamic simulation analysis on each working condition in the working condition library to obtain the time history data of the icing transmission tower line system, and then summarize the time history data of all working conditions to obtain the simulation result set.

[0040] The time history data includes conductor response data, displacement / acceleration data, component internal force data, connection point force data, and stress distribution data. Conductor response data includes the time history data of vertical displacement at the mid-span of the conductor in the de-icing section and the time history data of tension at the suspension points. Displacement / acceleration data includes the time history data of vertical and lateral displacements at the end nodes of each phase crossarm, the vertical and lateral displacements at nodes at typical tower heights, and acceleration. Component internal force data includes the time history data of axial force, shear force, and bending moment at the crossarm root section, the tower slope section, and the section at the intersection of the main diagonal members. Connection point force data includes the dynamic reaction force data at the conductor suspension points and its distribution data on the crossarm. Stress distribution data includes the time history data of surface stress contour maps for weak areas.

[0041] Weak points of transmission towers are identified and located based on the simulation result set using the following first identification method: S4-1. Based on the simulation results set, extract the internal force time history data of each component in the transmission tower under different working conditions, and then obtain the peak internal force of each component. Peak internal force: the maximum absolute value of the internal force time history data of the component under a certain working condition, reflecting the most unfavorable stress state of the component under that working condition.

[0042] S4-2. Calculate the attention score for each component based on the peak internal force. The attention score characterizes the stress performance of each component under different working conditions. The attention score is a weighted score of the peak internal force of the component under multiple working conditions, used to measure the overall stress risk of the component under all working conditions. The higher the score, the more dangerous the stress. Component parts with attention scores greater than a preset attention score threshold are designated as weak points. Weak points include strength weak points, fatigue weak points, and resonance weak points.

[0043] Weak points of transmission towers are identified and located based on the simulation result set using the following second identification method: S4-3. Based on the simulation results set, extract the stress time history data of each component in the transmission tower under different working conditions.

[0044] S4-4. Calculate the theoretical stress concentration factor based on the cross-sectional properties of each component and the stress time history data. The theoretical stress concentration factor is the ratio of the maximum local stress of a component to the nominal stress. It is used to quantify the stress amplification effect caused by geometric discontinuities (such as abrupt changes in cross-section, holes, and welds) and reflect the geometric weakness of the structure. Component locations with a theoretical stress concentration factor greater than a preset theoretical stress concentration factor threshold are designated as weak points. Weak points include strength weak points, fatigue weak points, and resonance weak points.

[0045] The assessment results include the identified weaknesses and their corresponding adverse operating conditions and time history data.

[0046] The method further includes: S6-1, performing structured storage of the weak points, the corresponding adverse working conditions, and time history data to obtain a tower weak point database. Adverse working conditions refer to specific combinations of working conditions that cause a component to become a weak point; these are the most dangerous scenarios in which the component is most likely to fail. Structured storage: The weak points, corresponding working conditions, and time history data are organized and stored in a unified format (such as database tables or JSON) to facilitate subsequent querying, analysis, and reuse.

[0047] S6-2. Improve the strength weak points by increasing the cross-section of the component; improve the fatigue weak points by changing the connection details or adding dampers; improve the resonance weak points by installing tuned mass dampers, increasing local stiffness, or increasing local mass.

[0048] This invention overcomes the limitations of single-condition or single-factor analysis by constructing a multi-factor coupled condition library, comprehensively covering all possible scenarios of ice-breaking jumps. This makes the evaluation results closer to engineering practice and more reliable. Extending the analysis focus from conductor jump height to the dynamic response of the tower itself, it clearly reveals the stress distribution pattern, internal force transmission path, and the specific locations most prone to damage or failure under ice-breaking impact (such as crossarm ends, tower slope changes, and suspension connection points). The output evaluation report not only identifies weak points but also associates them with the most unfavorable operating conditions leading to these weak points (such as "large span + thick icing + ice breaking in the middle span"), providing direct and quantitative design basis for subsequent targeted anti-icing reinforcement measures (such as local reinforcement, replacement of high-strength components, and installation of damping devices). This method can be applied during the transmission line design phase or before modification, identifying design defects in advance, optimizing tower structure, and improving the line's anti-icing capability from the source, demonstrating significant preventative and economic benefits.

[0049] As one implementation method, taking a 220kV double-circuit long-span line on the same tower as the evaluation object, the method of this invention is applied to evaluate the weak points of the tower: Step S1: Based on the design drawings and material parameters of the target line, a refined three-dimensional tower-line system coupling model is established on a finite element analysis platform such as ANSYS. Reference Figures 3 to 5 S1.1 Geometric Modeling: Based on the tower structure diagram, spatial beam elements (such as Beam188) are used to accurately simulate the main tower structure, diagonal members, crossarms, and connecting plates. The conductors and ground wires are simulated using only tension cable elements (such as Link10) to mimic their flexible large deformation characteristics. Insulator strings are modeled using two-force bar elements, with their length and string type parameters specified in the design. The conductors and ground wires (i.e., conductor-ground wires) in the transmission line can be considered as suspension structures, exhibiting strong geometric nonlinearity. A catenary model is established using a local coordinate system, and the catenary equations are obtained based on the static equilibrium equations. in, Indicates the position of the conductor. The vertical coordinates (i.e., sag height) at the location. Represents the horizontal coordinate along the span direction. This represents the horizontal stress at the lowest point of the conductor, with dimensions in MPa. This indicates the conductor-to-ground ratio, in units of... ; This indicates the span, which is the horizontal distance between two adjacent towers. This indicates the height difference between the two suspension points; express (When suspended at the same height), the horizontal span of the catenary of the conductor wire; This represents the hyperbolic sine function.

[0050] It is understandable that the established catenary equation takes into account the height difference between the two towers. The general form of the conductor is used to accurately calculate the spatial curve shape of the conductor under its own weight and tension. It is the core basis for determining the initial form of the conductor when establishing the finite element model, ensuring that the initial state of the simulation is consistent with the actual line. This invention uses a local coordinate system to establish the catenary model in order to facilitate the accurate positioning of the initial position of each conductor segment in the finite element software.

[0051] S1.2 Material and Section Properties: Assign realistic elastic modulus, density, and Poisson's ratio to the tower materials. Input the cross-sectional area, elastic modulus, coefficient of linear expansion, and unit mass of the transmission conductors and ground wires. For critical connection points (such as the connection nodes between crossarms and tower body, and hanging points), consider using more refined sub-models or assigning contact properties to capture local stresses. The cross-section of the tower angle steel is not circular; the equation for calculating the icing load per unit surface area is: In the formula, Ice load per unit area ; This indicates the basic ice thickness (mm), which is usually determined based on local observations or empirical values. The height-increasing coefficient representing the thickness of the ice layer; This indicates the conductor-to-ground ratio, in units of... ; After calculating the icing load per unit surface area of ​​the angle steel, it is applied to the tower model together with the self-weight load of the tower frame. The icing of the tower is simulated by changing the material density of the members. The calculation formula is as follows: In the formula, This is the equivalent density, and the unit is... ; The cross-sectional area of ​​the angle steel component is given in units of... ; Density of steel components, unit: ; This is the acceleration due to gravity.

[0052] S1.3 Boundary Conditions and Connections: Fixed constraints at the tower base accurately simulate the connection between the conductor and the crossarm of the tower via the insulator string. Adjacent spans of conductor are modeled for continuity via tension towers or straight-line towers to reflect the constraint effect of a multi-span continuous system.

[0053] S1.4 Damping and Nonlinear Settings: Set a reasonable Rayleigh damping coefficient for the conductor (e.g., take 2%-10% for the critical damping ratio), and turn on the large deformation effect (NLGEOM, ON) for analysis to accurately capture geometric nonlinearity.

[0054] Step S2: To comprehensively cover de-icing scenarios that may occur in actual operation, construct a hierarchical, multi-factor operating condition library: S2.1 Establishing Baseline Operating Conditions: Select the most common operating conditions of the line as the baseline, for example: "Five-span tension section, span 500m, conductor type JL / G1A-400 / 50, icing thickness 15mm, middle span (third span) whole span (100%) uniform de-icing, no wind, no elevation difference". Under non-uniform icing conditions, the total icing mass and total icing equivalent effect on the conductor can be expressed as: In the formula, This indicates the total icing mass of the entire conductor. This indicates the number of segments into which the gear ratio is divided. Indicates the total length of the gap. Indicates the first Duan Di The icing mass of each unit. This represents the total icing equivalent load (total gravity) of the entire conductor span. Indicates the first The icing equivalent load of the section, Indicates the first Duan Di The equivalent concentrated force of ice covering each unit.

[0055] The equivalent concentrated force at each node under uniform icing conditions is: In the formula, It represents the equivalent icing thickness (the thickness when the total icing mass is equivalent to that of uniform icing). Indicates the outer diameter of the conductor. This indicates the density of ice. Represents gravitational acceleration. This indicates the number of segments into which the gear range is divided.

[0056] S2.2 Single-factor impact analysis: Using the controlled variable method, under the baseline operating condition, only one key parameter is changed systematically each time: de-icing method: Four typical modes are set: "from the middle to both sides", "from both sides to the middle", "uniform throughout", and "one-way zipper". "De-icing from the middle to both sides" is identified as the unfavorable de-icing method with the largest conductor (ground) jump height and the most significant dynamic impact on the tower, and is therefore the focus of the analysis.

[0057] De-icing rate: Five levels are set: 20%, 40%, 60%, 80%, and 100%, simulating partial to complete de-icing.

[0058] Ice thickness: Based on the division of ice zones, various design values ​​are set, such as 10mm, 15mm, 20mm, and 25mm.

[0059] Gear length: To cater to the characteristics of large gear lengths, 300m, 500m, 700m, 900m, etc. are available.

[0060] Wind speed: Considering the combined effect of wind and de-icing, horizontal wind loads of 0 m / s, 5 m / s, 10 m / s, and 15 m / s are set (converted to nodal loads according to the specifications).

[0061] De-icing position: Analyze the different effects of de-icing on the side section, the secondary side section, and the middle section.

[0062] S2.3 Multi-factor coupled working conditions: Through single-factor analysis and multi-factor combination, a hierarchical and systematic set of working conditions is formed. In particular, factors with significant influence (such as large span, thick icing, and intermediate span de-icing) can be selected and combined to form extremely unfavorable working conditions, such as "span 700m + icing 20mm + 100% de-icing rate".

[0063] Step S3: For each working condition in the working condition library, perform nonlinear transient dynamic analysis (time history analysis) to calculate and extract the time history curve of the jump height of the conductor (ground) wire, the displacement and acceleration time history curve of the key nodes of the transmission tower, and the dynamic internal force and stress time history curve of the tower components (including the tower body, crossarm, and hanging point) under each working condition.

[0064] S3.1 Solution settings: Use a suitable direct integration method (such as the Newmark-β method), set a sufficiently small time step to ensure convergence (such as 0.01s), and the total analysis time covers the main oscillation decay process of the ice-breaking jump (usually 50-100s).

[0065] S3.2 Key Output Monitoring: During the simulation, the time history data of the following key locations are recorded simultaneously: Conductor Response: Time history of vertical displacement (jump height) at the mid-span of the conductor in the de-icing section, and time history of tension at the suspension point. Displacement / Acceleration: Time history of vertical and lateral displacement and acceleration at the ends of each phase crossarm and at nodes at typical heights on the tower. Component Internal Forces: Focus on the time histories of axial force, shear force, and bending moment at key sections such as the root of the crossarm, the slope change point of the tower, and the intersection of the main diagonal members. Connection Point Forces: Dynamic reaction force at the conductor suspension point and its distribution on the crossarm. Stress Distribution: For suspected weak areas, output the surface stress cloud map changes over time.

[0066] Reference Figure 2 Step S4: Based on the simulation result set (time history data of key locations) obtained in Step S3, in-depth mining is performed. The working condition library is traversed through the time history data set obtained from the simulation, including the dynamic response results of internal forces, stresses, displacements, etc. of each component under different de-icing conditions, and multi-path analysis is performed on the dynamic response results. Using a combination of peak statistical analysis and stress spectrum analysis methods, tower components and connection parts that repeatedly exhibit high dynamic stress, large deformation, or sudden increase in internal forces under various de-icing conditions are identified, and these parts are defined as potential weak points.

[0067] Path 1: Peak value comparison analysis. Extract the peak internal forces of each component under different working conditions and statistically analyze its stress performance under multiple working conditions. Based on the identification logic of attention scoring, filter out components with consistently high response: that is, components with consistently high peak internal forces and abnormal stress performance under multiple working conditions. Path 2: Stress concentration factor calculation. Calculate the theoretical stress concentration factor based on stress time history data and section properties. Determine stress concentration areas. Based on the identification logic of geometric weakness, identify the parts where local stress amplification is caused by geometric abrupt changes and connection details. Path 3: Response sensitivity analysis. Analyze the degree of influence of changes in working condition parameters (such as de-icing rate, ice thickness, wind speed, etc.) on the structural response. Identify high-sensitivity areas: that is, the parts most sensitive to parameter changes and with the most drastic response fluctuations, reflecting the structure's vulnerability to changes in working conditions.

[0068] By integrating the identification results from the above paths, a comprehensive assessment of weak points is made. Locations that simultaneously meet at least two of the following criteria—"continuous high response," "stress concentration," and "parameter sensitivity"—are identified as core weak points, while locations meeting only a single characteristic are designated as secondary weak points for focused attention. This method achieves multi-dimensional comprehensive assessment, avoiding misjudgments and omissions based on a single criterion. It outputs a list of weak points and a location map, providing a structured list (including component number, location, risk type, and corresponding adverse working conditions) and a visual location map, offering intuitive guidance for subsequent evaluation, reinforcement, and maintenance.

[0069] Furthermore, S4.1, Peak Response Statistics: Extract the peak internal forces of each component under different working conditions, calculate the component attention score, and screen out components with consistently high response. For each tower component... In every de-icing condition Below, from its internal force time history data Extract the peak value of its absolute value: In the formula, Indicates tower components In de-icing conditions The peak value of the internal force (take the maximum absolute value). Represents internal force time history data. Represents a time variable. This indicates the total duration of the dynamic response.

[0070] To evaluate the overall performance of a component under all operating conditions, a component attention score is introduced. : In the formula, Representation of components Attention rating This indicates the total number of operating conditions in the operating condition database. Indicates working conditions The weighting coefficient represents the importance of the operating condition; extreme operating conditions have a higher weighting. Representing components In de-icing conditions The response score is determined by After normalization, the higher the peak value, the higher the score.

[0071] Set attention score threshold To satisfy all The components were listed as potential weak points.

[0072] S4.2 Stress Spectrum Analysis: Calculate the dynamic stress time history and theoretical stress concentration factor for the selected components to identify geometric or connection weak points. For the target component, calculate the stress time history of key points based on its cross-sectional properties and dynamic internal force time history. For members subjected to combined bending and axial forces, the edge stress can be expressed as: in, Indicates edge stress, These represent the time histories of bending moment and axial force at the cross-section, respectively. Let represent the flexural modulus and area of ​​the cross section, respectively. Calculate the theoretical stress concentration factor at this critical point using the following formula: in, Indicates the theoretical stress concentration factor. These represent the actual maximum stress at the critical point of the component and the nominal stress of the component under the same load, respectively.

[0073] Set a preset theoretical stress concentration factor threshold. To satisfy all The components were identified as potential weak points, and it was determined that the part had a geometric weakness.

[0074] S4.3 Modal and Frequency Analysis: Extract the main vibration frequencies of the tower during the ice-breaking jump and compare them with the natural frequencies of the tower structure's finite element model. If the jump excitation frequency is found to be close to a certain local frequency of the structure (such as the first-order bending frequency of the crossarm), then there is a risk of resonance at that location.

[0075] Step S5: Establish a weak point database and safety assessment criteria. All potential weak point information identified in Step S4 is structured and stored to form a database. A dynamic response database of tower weak points is created, containing all identified potential weak points and their corresponding worst-case operating conditions and maximum dynamic response values. Based on the fatigue strength of the tower material, the dynamic load factor in the design specifications, and the safety margin, stress exceedance and fatigue damage assessment criteria for weak points are formulated. Records include: weak point ID, associated component, spatial location, corresponding worst-case operating condition (combination), maximum dynamic response value (internal force / stress), dynamic amplification factor, fatigue damage degree D, risk type (overload, fatigue, resonance), etc. Multi-level safety assessment criteria are established: Strength criterion: Maximum dynamic stress ≤ material yield strength / dynamic load safety factor K1 (e.g., 1.5). Fatigue criterion: Cumulative damage degree D ≤ allowable value (e.g., 0.5, corresponding to safe life). Deformation criterion: Critical node displacement ≤ allowable displacement during normal structural operation.

[0076] Furthermore, evaluation criteria can include static strength safety, fatigue life damage, and connection reliability. Static strength safety is assessed by comparing the maximum dynamic stress of the component with the material's yield strength. The dynamic stress time history of the component is processed using the rainflow counting method, and fatigue life damage under repeated de-icing loads is evaluated using SN curves. Connection reliability is assessed by comparing the dynamic unbalanced tension at the suspension point with the rated mechanical loads of the insulator string and fittings.

[0077] Step S6: Generate a comprehensive assessment report and reinforcement decision recommendations. Based on the database and assessment results, an illustrated assessment report is automatically generated, including a weak point location diagram, the most unfavorable working condition combination, dynamic response quantitative data, safety assessment results, and targeted anti-icing reinforcement design recommendations. Specifically, the core content of the report includes a weak point distribution map, a detailed diagnosis report, and quantitative reinforcement recommendations. Weak Point Distribution Map: All identified weak points are highlighted on the tower's 3D model and colored according to risk level (high, medium, low). Detailed Diagnosis Report: For each high-risk weak point, the most unfavorable working condition parameters, specific dynamic response data, violated assessment criteria, and predicted failure mode are listed. Quantitative Reinforcement Recommendations: For strength weak points, it is recommended to increase the component cross-section, add stiffening ribs, or use higher strength materials. For fatigue weak points, it is recommended to improve connection details (such as grinding welds, using high-strength bolts), and add dampers to reduce stress amplitude. For resonance risk points, it is recommended to adjust their natural frequency by increasing local stiffness or mass, or to install a tuned mass damper (TMD).

[0078] Through the above systematic process, this invention realizes a complete technical closed loop from global modeling to working condition simulation, data mining, and precise diagnosis, providing a powerful tool for the anti-icing and disaster prevention of transmission towers, including post-disaster remediation and pre-disaster prevention.

[0079] Compared with the prior art, the present invention has the following beneficial effects based on the above embodiments: By constructing a finite element model of a realistic icing-covered transmission tower-line system, and employing reasonable element simulation, parameter assignment, and constraint settings, the mechanical characteristics of tower-line coupling were realistically reproduced. This overcomes the shortcomings of traditional simplified models and decoupling analyses, which cannot reflect the strongly coupled dynamic process of ice removal jumping, providing a reliable foundation for subsequent simulation analysis. A complete operating condition library was constructed through baseline operating conditions, single-factor operating conditions, and multi-factor coupled operating conditions, taking into account various influencing factors such as ice removal methods and ice thickness, avoiding the one-sidedness of single-condition analysis, and comprehensively covering complex ice removal scenarios in the field. Through nonlinear transient dynamic simulation, the operating conditions were traversed one by one, and multi-dimensional time history data were obtained and summarized to form a simulation result set. This captured the transient characteristics and dynamic response laws of ice removal jumping oscillation, providing comprehensive and accurate data support for weak point identification.

[0080] Two identification methods—peak force statistics and stress spectrum analysis—are employed to pinpoint and locate weak points. The peak force method and the attention score method identify high-response areas under various stress conditions, while the stress time history data and theoretical stress concentration coefficients identify stress concentration areas inherent in the structure itself. This ensures the accuracy and specificity of weak point identification, overcoming the misjudgment and omission problems of traditional single-method identification and breaking the lag in post-disaster weak point deduction. Through analysis and evaluation of weak points, the corresponding adverse working conditions and time history data are clarified, allowing for further classification of weak points and the provision of targeted improvement plans. This achieves a closed loop of identification-evaluation-improvement. Furthermore, the construction of a tower weak point database provides traceable technical support for subsequent tower operation, maintenance, and reinforcement optimization.

[0081] This invention clearly defines the time-history data and the parameter levels of influencing factors under operating conditions, ensuring the rigor and feasibility of the technical solution and adapting it to the evaluation needs of transmission towers of different specifications and in different scenarios. It achieves precise location, scientific assessment, and targeted improvement of weak points in towers under de-icing oscillation conditions, effectively reducing the risk of tower component failure, fatigue damage, and even collapse caused by de-icing disasters. This ensures the safe and stable operation of overhead transmission lines and provides theoretical basis and technical support for preventive maintenance and structural optimization of transmission lines in areas prone to freezing, demonstrating significant engineering application value and practical significance.

[0082] The specific embodiments described above are preferred embodiments of a tower weak point assessment method based on multi-condition de-icing jump oscillation analysis of this application. They are not intended to limit the specific implementation scope of this application. The scope of this application includes but is not limited to the specific embodiments described above. All equivalent changes made in accordance with the shape and structure of this application are within the protection scope of this application.

Claims

1. A method for assessing weak points in towers based on multi-condition de-icing jump oscillation analysis, characterized in that, include: S1. Construct a finite element model of the icing-covered transmission tower system; S2. Construct a working condition library based on several influencing factors; S3. Based on the finite element model, perform ice-breaking jump oscillation simulation on each working condition in the working condition library to obtain a set of simulation results; S4. Based on the simulation result set, identify and locate the weak points of the transmission tower. The weak points are characterized by the location in the simulation result set where the frequency of stress exceeding the limit, deformation exceeding the limit, or internal force change is greater than the preset frequency. S5. Analyze and evaluate the weaknesses to obtain evaluation results.

2. The method for assessing weak points of towers based on multi-condition de-icing jump oscillation analysis according to claim 1, characterized in that, The steps for constructing a working condition database based on several influencing factors include: S2-1. Set a baseline working condition, wherein the parameters of each working condition influencing factor are all set to preset baseline values. S2-2. Based on the aforementioned benchmark conditions, the control variable method is used to change only the parameters of one type of influencing factor, while keeping the benchmark values ​​of the remaining influencing factors unchanged, in order to form several single-factor conditions. S2-3. Based on the aforementioned benchmark working condition, different parameter levels of several working condition influencing factors are combined to form several multi-factor coupled working conditions. S2-4. Summarize the baseline working conditions, the single-factor working conditions, and the multi-factor coupled working conditions to construct a working condition library.

3. The method for assessing weak points of towers based on multi-condition de-icing jump oscillation analysis according to claim 1, characterized in that, The step of performing de-icing jump oscillation simulation on each working condition in the working condition library includes: S3-1. Set the time step and total analysis time for nonlinear transient dynamics simulation analysis. The total analysis time shall not be less than the oscillation decay time of the ice-breaking jump. S3-2. Based on the time step and the total analysis time, perform nonlinear transient dynamic simulation analysis on each working condition in the working condition library to obtain the time history data of the icing transmission tower line system, and then summarize the time history data of all working conditions to obtain the simulation result set.

4. The method for assessing weak points of towers based on multi-condition de-icing jump oscillation analysis according to claim 1, characterized in that, Weak points of transmission towers are identified and located based on the simulation result set using the following first identification method: S4-1. Based on the simulation results set, extract the internal force time history data of each component in the transmission tower under different working conditions, and then obtain the peak value of the internal force of each component; S4-2. Calculate the attention score of each component based on the internal force peak value. The attention score represents the stress performance of each component under different working conditions. Component parts with attention scores greater than the preset attention score threshold are regarded as weak points.

5. The method for assessing weak points of towers based on multi-condition de-icing jump oscillation analysis according to claim 1, characterized in that, Weak points of transmission towers are identified and located based on the simulation result set using the following second identification method: S4-3. Based on the simulation results set, extract the stress time history data of each component in the transmission tower under different working conditions; S4-4. Calculate the theoretical stress concentration factor based on the cross-sectional properties of each component and the stress time history data, and designate the component parts with the theoretical stress concentration factor greater than the preset theoretical stress concentration factor threshold as weak points.

6. The method for assessing weak points of towers based on multi-condition de-icing jump oscillation analysis according to claim 1, characterized in that, The ice-covered transmission tower system includes transmission conductors, transmission ground wires, insulator strings, and transmission towers; The steps for constructing the finite element model of the icing transmission tower system include: S1-1. Cable elements are used to simulate the transmission conductor and the transmission ground wire, two-force bar elements are used to simulate the insulator string, and spatial beam elements are used to simulate the transmission tower. S1-2. Assign values ​​to the cross-sectional area, elastic modulus, coefficient of linear expansion, and unit mass of the transmission conductor and the transmission ground wire; assign values ​​to the elastic modulus, density, and Poisson's ratio of the transmission tower. S1-3. Set fixed constraints at the base of the transmission tower and set continuous constraints on adjacent spans of conductors through tension towers or straight towers. S1-4. Set Rayleigh damping coefficients for transmission lines and transmission towers to construct a finite element model of the icing transmission tower system.

7. The method for assessing weak points of towers based on multi-condition de-icing jump oscillation analysis according to claim 3, characterized in that, The evaluation results include the identified weaknesses and their corresponding adverse operating conditions and time history data; the method also includes: S6-1. The weak points, the corresponding adverse working conditions, and the time history data are stored in a structured manner to obtain a database of weak points of the tower.

8. The method for assessing weak points of towers based on multi-condition de-icing jump oscillation analysis according to claim 1, characterized in that, The weak points include strength weak points, fatigue weak points, and resonance weak points; the method further includes: S6-2, improving the strength weak points by increasing the cross-section of the component; improving the fatigue weak points by changing the connection details or adding a damper; and improving the resonance weak points by installing a tuned mass damper, increasing the local stiffness, or increasing the local mass.

9. The method for assessing weak points of towers based on multi-condition de-icing jump oscillation analysis according to claim 3, characterized in that, The time history data includes conductor response data, displacement / acceleration data, component internal force data, connection point force data, and stress distribution data; the conductor response data includes vertical displacement time history data of the mid-span of the conductor in the de-icing section and tension time history data of the suspension point; the displacement / acceleration data includes vertical and lateral displacement of the end nodes of each phase crossarm, vertical and lateral displacement of the nodes at typical tower heights, and acceleration time history data; the component internal force data includes axial force time history data, shear force time history data, and bending moment time history data of the crossarm root section, the tower slope section, and the main diagonal member intersection section; the connection point force data includes dynamic reaction force data at the conductor suspension point and its distribution data on the crossarm; The stress distribution data includes time history data of surface stress cloud maps for weak areas.

10. The method for assessing weak points of towers based on multi-condition de-icing jump oscillation analysis according to claim 2, characterized in that, The factors affecting the operating conditions include de-icing method, de-icing rate, ice thickness, spacing, number of speeds, wind speed, and de-icing speed. The parameter levels of the de-icing method include uniform de-icing throughout the entire section, de-icing from the middle to the ends, de-icing from the ends to the middle, and zipper-style de-icing. The parameter levels of the de-icing rate are classified according to percentages. The parameter levels of the ice thickness are classified according to millimeters. The parameter levels of the de-icing speed include edge de-icing, secondary edge de-icing, and middle de-icing.

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