Method and system for assessing aging risk of overhead transmission line based on time and environmental accumulation effect

Abstract

This application relates to a method and system for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment. The method includes plotting the actual and theoretical cumulative tensile strength loss curves of the analyzed overhead transmission line; correcting the theoretical cumulative tensile strength loss curve using the actual curve to obtain a corrected tensile strength curve; predicting the predicted cumulative tensile strength loss of the analyzed overhead transmission line using the corrected curve; and jointly assessing the aging status of the analyzed overhead transmission line by combining the predicted cumulative tensile strength loss and strain data. The aging risk assessment method and system for overhead transmission lines based on the cumulative effects of time and environment disclosed in this application determines the specific impact values ​​of each influencing factor based on the joint analysis of historical and predicted data, and provides aging risk assessment results with time reference values ​​to guide the operation and maintenance of overhead transmission lines.

Description

Technical Field

[0001] This application relates to the field of power grid safety management technology, and in particular to a method and system for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment. Background Technology

[0002] As overhead transmission lines age and are affected by environmental factors, they undergo varying degrees of aging, severely impacting their normal operation and jeopardizing power supply safety. Aging can lead to broken strands and wires, insufficient tensile strength in conductors to withstand actual loads, or the inability of transmission towers to bear weight, ultimately causing the entire line to malfunction.

[0003] Existing conductor condition assessments mainly rely on mechanical models, rarely considering the actual operating environment of the lines, making them difficult to directly apply to the production and maintenance of transmission lines. Sag measurement models are used to measure distances, which generally rely on collecting data and injecting it into the sag measurement model to obtain sag data. These data exist independently, and it is difficult to determine their actual correlation with factors such as environmental factors and operational factors. At the same time, they cannot participate in subsequent aging risk prediction. Other independent models also have similar problems.

[0004] Currently, there are also prediction methods based on fuzzy logic, which predict based on parameters such as deformation and stress. However, these methods require simplifying the parameters into high, medium, and low risks, and then combining them to obtain the high, medium, and low risk assessment results for the corresponding overhead transmission lines. This assessment method is relatively simplistic, lacks sufficient reference value, and is difficult to provide specific time reference values. Summary of the Invention

[0005] This application provides a method and system for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment. It determines the specific impact values ​​of each influencing factor based on the joint analysis of historical data and predicted data, and provides an aging risk assessment result with time reference value to guide the operation and maintenance of overhead transmission lines.

[0006] The above-mentioned objective of this application is achieved through the following technical solution:

[0007] Firstly, this application provides a method for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment, including:

[0008] Obtain historical tensile strength loss data for the analysis object of the overhead transmission line;

[0009] Plot the cumulative curve of actual tensile strength loss of the analysis object of the overhead transmission line based on historical tensile strength loss data;

[0010] The cumulative curve of theoretical tensile strength loss of the analysis object of overhead transmission line is calculated based on the computational model;

[0011] The theoretical tensile strength loss cumulative curve is corrected using the actual tensile strength loss cumulative curve to obtain the tensile strength correction curve;

[0012] The cumulative loss of predicted tensile strength of the analysis object of the overhead transmission line is predicted using the tensile strength correction curve.

[0013] The aging status of the overhead transmission line analysis object is assessed by combining the predicted cumulative loss of tensile strength and the strain data of the analysis object, and the aging risk assessment results are obtained.

[0014] In one possible implementation of the first aspect, correcting the theoretical tensile strength loss accumulation curve using the actual tensile strength loss accumulation curve includes:

[0015] Place the actual tensile strength loss cumulative curve and the theoretical tensile strength loss cumulative curve in the same coordinate system and align them;

[0016] Calculate the residual between the actual tensile strength loss cumulative curve and the theoretical tensile strength loss cumulative curve;

[0017] Adjust the weights of the parameters that influence the change in tensile strength to reduce the residual to an acceptable range;

[0018] The cumulative curve of theoretical tensile strength loss is corrected using weighted correlation influence parameters.

[0019] In one possible implementation of the first aspect, the associated influence parameters of tensile strength variation include dynamic influence parameters and static influence parameters;

[0020] Dynamic influencing parameters include meteorological environmental factors, which include temperature, dependent loads, and wind loads.

[0021] Static influence parameters include conductor intrinsic parameters and long-term drift parameters. Conductor intrinsic parameters include self-weight, span, elastic modulus and coefficient of linear expansion, while long-term drift parameters include creep.

[0022] Among them, static influence parameters are involved in generating the theoretical tensile strength loss cumulative curve, while dynamic influence parameters are not involved in generating the theoretical tensile strength loss cumulative curve.

[0023] In one possible implementation of the first aspect, when meteorological environmental factors are involved in correcting the cumulative curve of theoretical tensile strength loss, an amplification factor is assigned to the dynamic influence parameter according to the time period.

[0024] In one possible implementation of the first aspect, adjusting the weights of the parameters relating to the change in tensile strength and reducing the residual to an allowable range includes:

[0025] By cropping the actual tensile strength loss cumulative curve and the theoretical tensile strength loss cumulative curve along the time dimension, a set of comparative analysis curves is obtained.

[0026] Determine the weights of the parameters that influence the change in tensile strength in the previous set of comparative analysis curves;

[0027] The weights of the correlation parameters of tensile strength change determined by the previous comparative analysis curve group are used to adjust the next analysis curve group, and the correlation parameters of tensile strength change are adjusted a second time according to the adjustment results, so that the residual of the next analysis curve group is reduced to the allowable range.

[0028] Repeat the above process of adjusting the weights of the related influence parameters until the adjustment process is complete.

[0029] In one possible implementation of the first aspect, determining the weights of the correlation parameters affecting the tensile strength variation in the previous set of comparative analysis curves includes:

[0030] The actual tensile strength loss cumulative curve in the comparative analysis curve group is trimmed using dynamic influence parameters. The part of the actual tensile strength loss cumulative curve corresponding to the dynamic influence parameters is the dynamic segment, and the remaining part is the static segment.

[0031] Calculate the average tensile strength loss in the dynamic segment;

[0032] The proportions of temperature, dependent load, and wind load borne are determined based on the average tensile strength loss of the dynamic section.

[0033] Calculate the static average compensation difference of the static segment;

[0034] The residuals of the analysis curve set are reduced to an allowable range by adjusting the cumulative curve of theoretical tensile strength loss using the temperature bearing ratio, dependent load bearing ratio, wind load bearing ratio, and static average compensation difference.

[0035] In one possible implementation of the first aspect, when the dynamic segment corresponds to at least two of the dynamic influence parameters, it further includes:

[0036] In a dynamic segment that corresponds to only one of the dynamic influence parameters, determine the initial bearing ratio of temperature, the initial bearing ratio of dependent load, and the initial bearing ratio of wind load;

[0037] Use the initial temperature load ratio, the initial load ratio of the dependent load, and the initial wind load ratio to check at least two of the dynamic segments of the corresponding dynamic influence parameters to obtain the reference difference;

[0038] Adjust the initial temperature load ratio, the initial load ratio of the dependent load, and the initial load ratio of the wind load based on the reference difference, so that the difference between the cumulative tensile strength loss of all dynamic segments and the actual tensile strength loss of all dynamic segments is within the allowable range.

[0039] Secondly, this application provides an aging risk assessment device for overhead transmission lines based on the cumulative effects of time and environment, comprising:

[0040] The data acquisition unit is used to acquire historical tensile strength loss data of the overhead transmission line analysis object;

[0041] The first data processing unit is used to plot the cumulative curve of actual tensile strength loss of the overhead transmission line analysis object based on historical tensile strength loss data.

[0042] The second data processing unit is used to calculate the theoretical tensile strength loss cumulative curve of the overhead transmission line analysis object based on the calculation model.

[0043] The correction processing unit is used to correct the theoretical tensile strength loss accumulation curve using the actual tensile strength loss accumulation curve, so as to obtain the tensile strength correction curve;

[0044] The prediction processing unit is used to predict the cumulative tensile strength loss of the analysis object of the overhead transmission line using the tensile strength correction curve.

[0045] The assessment unit is used to jointly predict the cumulative loss of tensile strength and combine the strain data of the overhead transmission line analysis object to assess the aging status of the analysis object and obtain the aging risk assessment result.

[0046] Thirdly, this application provides an aging risk assessment system for overhead transmission lines based on the cumulative effects of time and environment, the system comprising:

[0047] One or more memories for storing instructions; and

[0048] One or more processors are configured to call and execute the instructions from the memory to perform the methods described in the first aspect and any possible implementation thereof.

[0049] Fourthly, this application provides a computer-readable storage medium, the computer-readable storage medium comprising:

[0050] The program, when run by a processor, is executed as described in the first aspect and any possible implementation thereof.

[0051] Fifthly, this application provides a computer program product, including program instructions that, when run by a computing device, execute the method described in the first aspect and any possible implementation thereof.

[0052] Sixthly, this application provides a chip system including a processor for implementing the functions involved in the foregoing aspects, such as generating, receiving, transmitting, or processing the data and / or information involved in the foregoing methods.

[0053] This chip system can consist of chips or include chips and other discrete components.

[0054] In one possible design, the chip system also includes a memory for storing necessary program instructions and data. The processor and the memory can be decoupled and located on different devices, connected via wired or wireless means, or the processor and the memory can be coupled to the same device. Attached Figure Description

[0055] Figure 1 This is a flowchart illustrating the steps of an overhead transmission line aging risk assessment method based on the cumulative effects of time and environment provided in this application.

[0056] Figure 2 This is a schematic diagram of an actual tensile strength loss cumulative curve provided in this application.

[0057] Figure 3 This is a schematic diagram of a theoretical tensile strength loss cumulative curve provided in this application.

[0058] Figure 4 This is a schematic diagram of a tensile strength correction curve provided in this application. Detailed Implementation

[0059] The technical solutions in this application will be further described in detail below with reference to the accompanying drawings.

[0060] This application discloses a method for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment. Please refer to [link / reference needed]. Figure 1 In some examples, the aging risk assessment method for overhead transmission lines based on the cumulative effects of time and environment disclosed in this application includes the following steps:

[0061] S101, Obtain historical tensile strength loss data of the overhead transmission line analysis object;

[0062] S102, Plot the cumulative curve of actual tensile strength loss of the analysis object of the overhead transmission line based on historical tensile strength loss data;

[0063] S103, Calculate the cumulative curve of theoretical tensile strength loss of the analysis object of the overhead transmission line based on the calculation model;

[0064] S104, the theoretical tensile strength loss cumulative curve is corrected using the actual tensile strength loss cumulative curve to obtain the tensile strength correction curve;

[0065] S105, using the tensile strength correction curve to predict the cumulative loss of the predicted tensile strength of the analysis object of the overhead transmission line;

[0066] S106. The cumulative loss of tensile strength and the strain data of the overhead transmission line analysis object are combined to evaluate the aging status of the overhead transmission line analysis object and obtain the aging risk assessment result.

[0067] Specifically, in step S101, it is first necessary to obtain the historical tensile strength loss data of the overhead transmission line analysis object. Here, the overhead transmission line analysis object refers to the overhead transmission line to be analyzed in the technical solution of this application, and the historical tensile strength loss data refers to the accumulation of tensile strength loss that has occurred over time.

[0068] In step S102, please refer to Figure 2 The detection data obtained in step S101 at each time point are defined as the cumulative loss value relative to the initial tensile strength (rather than the stage difference). A discrete set of points is plotted in a Cartesian coordinate system with time (service years) as the x-axis and the cumulative loss value as the y-axis.

[0069] Since the cumulative loss is irreversible, the set of discrete points shows an upward trend as the horizontal coordinate increases. Subsequently, the least squares fitting algorithm is used to perform nonlinear regression on these discrete points to generate a continuous and strictly monotonically increasing curve of the cumulative change of tensile strength loss, which serves as the basis for subsequent prediction of degradation trajectory.

[0070] It should be noted that the historical tensile strength loss data here is a cumulative value, that is, the loss relative to the initial tensile strength occurring at a specific point in time, not the tensile strength loss relative to the previous point in time. Therefore, the cumulative curve of actual tensile strength loss obtained here is monotonically increasing.

[0071] It should be noted that historical tensile strength loss data can be expressed numerically or as a percentage, for example, in Figure 2 The percentage is used to represent the percentage loss of tensile strength of the overhead transmission line at the current point in time.

[0072] In step S103, as Figure 3As shown, it is necessary to calculate the cumulative curve of theoretical tensile strength loss of the analysis object of the overhead transmission line based on the calculation model. The calculation models used here include thermal aging models (empirical formulas, Harvey models, CIGRE models), mechanical models and environmental corrosion models. The processing method is to input the relevant data into the model and then obtain the cumulative curve of theoretical tensile strength loss.

[0073] Choose one of the models described above. Specifically, if the main problem of the line is long-term high-temperature operation, the thermal aging (annealing) model should be used first; if the line is located in an area with frequent wind vibration, the mechanical fatigue model should be used first; and for coastal areas or areas with severe industrial pollution, the environmental corrosion model should be used first.

[0074] However, it should be noted that the cumulative loss curve of theoretical tensile strength here has the following drawbacks:

[0075] Most existing models focus on a single aging mechanism; however, the aging of actual circuits is a complex process involving the combined effects of thermal, mechanical, and environmental stresses. A single model cannot fully reflect this coupled effect.

[0076] Existing models generally assume that damage accumulates linearly. However, in real-world environments, damage is not linear but exhibits distinct stage-based characteristics.

[0077] Existing models require precise data input, but in reality, obtaining precise data is difficult, especially micro-environmental data and actual operational data, which are often missing.

[0078] Therefore, the theoretical tensile strength loss cumulative curve obtained here is only for reference. It is necessary to correct the theoretical tensile strength loss cumulative curve using the actual tensile strength loss cumulative curve in step S104 to obtain the tensile strength correction curve, such as... Figure 4 As shown, the tensile strength correction curve is a partial extension of the theoretical tensile strength loss cumulative curve, and is a line segment with a fixed slope.

[0079] The obtained tensile strength correction curve can predict the cumulative loss of tensile strength of the overhead transmission line analysis object, which is the content in step S105. The specific prediction method is to extend the tensile strength correction curve, for example, by extending it for 3-6 months or 12 months.

[0080] Specifically, the preferred extension period is 3 months, 6 months, or 12 months. Among them, 3 months corresponds to a short-term operation and maintenance cycle, 6 months corresponds to a half-year work plan, and 12 months corresponds to an annual overhaul plan. When the extension period exceeds 12 months, the confidence interval of the fitted extrapolation expands sharply, and the prediction error increases significantly, so it is not recommended.

[0081] The reason for strictly limiting the extension time is that the accuracy of the extension will decrease with the extension time. In order to ensure the accuracy of predicting the cumulative loss of tensile strength, in step S106, the aging condition of the overhead transmission line analysis object is evaluated by combining the predicted cumulative loss of tensile strength with the strain data of the analysis object, and the aging risk assessment result is obtained.

[0082] The following methods are used in combination:

[0083] Rule 1: If the strain is small and the tensile strength loss is small, then the risk of aging is low;

[0084] Rule 2: If the strain is small and the tensile strength loss is moderate, then the aging risk is low;

[0085] Rule 3: If the strain is small and the tensile strength loss is large, then the aging risk is medium;

[0086] Rule 4: If the strain is moderate and the tensile strength loss is small, then the aging risk is moderate;

[0087] Rule 5: If the strain is moderate and the tensile strength loss is moderate, then the aging risk is moderate;

[0088] Rule 6: If the strain is medium and the tensile strength loss is large, then the aging risk is medium;

[0089] Rule 7: If the strain is large and the tensile strength loss is small, then the aging risk is medium;

[0090] Rule 8: If the strain is large and the tensile strength loss is medium, then the aging risk is high;

[0091] Rule 9: If the strain is large and the tensile strength loss is large, then the risk of aging is high;

[0092] The above nine rules correspond to nine different situations. The strain is generally taken as the average value of the past year to the past three years as a reference value. At the same time, three numerical ranges are given, which correspond to the small strain range, the medium strain range and the large strain range, respectively.

[0093] In some possible implementations, the strain is obtained based on actual testing, the limiting strain is calculated based on the inherent parameters of the overhead transmission line, and 0-50% of the limiting strain value is taken as the small strain value range, 50%-80% of the limiting strain value is taken as the medium strain value range, and 80%-100% of the limiting strain value is taken as the large strain value range.

[0094] The tensile strength loss is handled in the same way. First, the ultimate tensile strength loss is determined (calculated or given reference value). 0-50% of the ultimate tensile strength loss value is taken as the small tensile strength loss value range, 50%-80% of the ultimate tensile strength loss value is taken as the medium tensile strength loss value range, and 80%-100% of the ultimate tensile strength loss value is taken as the large tensile strength loss value range.

[0095] Using the above method, strain and tensile strength can be represented by large, medium, and small values. Then, according to the rules recorded above, the aging risk assessment results (low risk, medium risk, high risk) for the corresponding time can be given.

[0096] In some cases, the specific methods for correcting the theoretical tensile strength loss cumulative curve using the actual tensile strength loss cumulative curve are as follows:

[0097] Place the actual tensile strength loss cumulative curve and the theoretical tensile strength loss cumulative curve in the same coordinate system and align them;

[0098] Calculate the residual between the actual tensile strength loss cumulative curve and the theoretical tensile strength loss cumulative curve;

[0099] Adjust the weights of the parameters that influence the change in tensile strength to reduce the residual to an acceptable range;

[0100] The cumulative curve of theoretical tensile strength loss is corrected using weighted correlation influence parameters.

[0101] In the above method, it is necessary to determine the specific impact parameters of the associated impact parameters. In this application, the associated impact parameters are explained as follows:

[0102] The parameters relating to changes in tensile strength include dynamic and static parameters.

[0103] Dynamic influencing parameters include meteorological environmental factors, which include temperature, dependent loads, and wind loads.

[0104] Static influence parameters include conductor intrinsic parameters and long-term drift parameters. Conductor intrinsic parameters include self-weight, span, elastic modulus and coefficient of linear expansion, while long-term drift parameters include creep.

[0105] Among them, static influence parameters are involved in generating the theoretical tensile strength loss cumulative curve, while dynamic influence parameters are not involved in generating the theoretical tensile strength loss cumulative curve.

[0106] In the above context, static influence parameters refer to the inherent property parameters of the overhead transmission line analysis object that remain constant or exhibit deterministic unidirectional drift during its service life. Specifically, these include:

[0107] Conductor parameters: including but not limited to conductor weight, span, elastic modulus and coefficient of linear expansion. These parameters are known fixed values ​​during design and commissioning, and determine the basic mechanical response of the conductor under long-term tension.

[0108] Long-term drift parameters: mainly include creep parameters. These parameters describe the irreversible plastic deformation trend of the conductor material over time under constant stress, and have a unidirectional nature of time accumulation.

[0109] When constructing the theoretical tensile strength loss cumulative curve, only the above-mentioned static influence parameters are introduced into the theoretical calculation model (such as thermal aging model, creep model or mechanical model) as input quantities. The theoretical curve generated in this way represents the long-term degradation baseline of the line under ideal standard working conditions, determined by its own material properties.

[0110] Dynamic influencing parameters refer to factors that fluctuate randomly in real time with the external meteorological environment, mainly including meteorological environmental factors. Specifically, these include: temperature, dependent loads (such as icing loads), and wind loads.

[0111] In the scheme of this application, the dynamic influence parameters are explicitly excluded from generating the cumulative curve of theoretical tensile strength loss. The specific reasons are as follows:

[0112] The dynamic influence parameters have strong instantaneous randomness and unpredictability in the future. If they are bound to the theoretical model, the prediction in step S105 will fail because it is impossible to obtain real-time future input.

[0113] Dramatic fluctuations in dynamic parameters can cause theoretical curves to exhibit irregular sawtooth oscillations, failing to accurately reflect the long-term monotonic cumulative physical nature of tensile strength loss.

[0114] It should be noted that the fact that the dynamic influence parameters are not included in the theoretical calculation does not mean that their role is ignored. Rather, they are compensated for through other steps in the scheme of this application, resulting in long-term cumulative effect compensation.

[0115] The additional strength loss caused by the long-term effect of dynamic parameters is objectively recorded and implicitly contained in the cumulative tensile strength loss curve generated based on historical test data in step S102. In the subsequent step S104, the theoretical curve is corrected using the actual curve, thereby indirectly compensating for the long-term cumulative effect of dynamic parameters. Real-time risk assessment: The risk of sudden overload caused by dynamic parameters is independently assessed using the strain data index introduced separately in step S106.

[0116] Based on the above, we can conclude that the theoretical tensile strength loss cumulative curve includes a baseline and a dynamic line. In practice, the dynamic line is directly related to time. For example, temperature, dependent loads (such as icing loads), and wind loads can all be divided by time periods. High temperatures are more likely to occur in summer, dependent loads are more likely to occur in winter, and the time point corresponding to wind loads needs to be determined based on local historical meteorological data.

[0117] In other words, when generating the theoretical tensile strength loss cumulative curve, the time effect is considered at the same time. When the corresponding time arrives, an amplification factor is applied. Specifically, when meteorological environmental factors are involved in correcting the theoretical tensile strength loss cumulative curve, an amplification factor is applied to the dynamic influence parameter according to the time period.

[0118] One possible process is as follows:

[0119] Theoretical tensile strength loss cumulative curve representation:

[0120] L theoretical (t) = L baseline (t) + ΔL env (t);

[0121] Among them, L baseline (t) is the baseline loss function driven by static influence parameters (including conductor self-weight, span, elastic modulus, coefficient of linear expansion and creep parameters), representing the base degradation trend under ideal standard working conditions;

[0122] F env (t) represents the amplification factor of dynamic environmental influence;

[0123] ΔL env (t) represents the additional loss increment caused by the dynamic environment.

[0124]

[0125] When generating the cumulative curve of theoretical tensile strength loss, traverse each calculation step along the time axis (e.g., with a month or quarter as the smallest unit), assign an amplification factor to the corresponding dynamic influence parameter according to the time interval to which the current time point belongs, and participate in the calculation as follows:

[0126] Establish a corrected relationship between ambient temperature T(t) and baseline loss rate:

[0127] α T (t) = exp[β T × (T(t) - T ref ) ];

[0128] Where T(t) is the average monthly ambient temperature for the current time period, Tref The reference temperature (usually 20℃) is β T The temperature acceleration factor (determined by the material activation energy, typically ranging from 0.03 to 0.08 / ℃ for aluminum conductors) occurs when T(t) ≤ T ref At that time, α T (t) is set to 1.00.

[0129] Dependent load amplification factor α I Determination:

[0130] The load is mainly icing, establishing a mapping relationship between icing thickness and additional stress. According to the design specifications for overhead transmission lines, the icing thickness d(t) corresponds to the additional load G per unit length of conductor. ice (t), the amplification factor is determined by the following formula:

[0131] α I (t) = 1 + γ I × [ G ice (t) / G self ];

[0132] Among them, G self For the conductor's self-weight load, G ice (t) represents the additional load corresponding to the ice thickness in the current time period, γ I This is the load-strength loss conversion factor (ranging from 0.5 to 2.0, determined experimentally based on the conductor structure).

[0133] Wind load amplification factor α W Determination:

[0134] Wind load is characterized by wind speed v(t). According to the quasi-static wind load calculation formula, the wind load P wind (t) ∝ v(t) 2 The magnification factor is determined by the following formula:

[0135] α W (t) = 1 + γ W × [ P wind (t) / P ref ];

[0136] Among them, P ref For reference wind pressure (corresponding to the basic design wind speed), γ W This is the wind-induced vibration damage factor (ranging from 0.05 to 0.30, determined by the fatigue characteristics of the conductor).

[0137] Overall magnification factor F env (t):

[0138] When multiple dynamic factors act together within a certain time period, the comprehensive dynamic amplification factor F env (t) is expressed as a product of multiples:

[0139] F env (t) = α T (t) × α I (t) × α W (t);

[0140] In a preferred embodiment of this application, the overall amplification factor is determined by multiplication; in another embodiment, a superposition method may also be used.

[0141] One of the two methods can be used, with the multiplication form being preferred for multi-factor coupling scenarios. In this application, the multiplication form is used to reflect the accelerated aging effect of multi-factor coupling.

[0142] In some cases, the weights of the parameters relating to the change in tensile strength are adjusted to reduce the residual to an acceptable range as follows:

[0143] By cropping the actual tensile strength loss cumulative curve and the theoretical tensile strength loss cumulative curve along the time dimension, a set of comparative analysis curves is obtained.

[0144] Determine the weights of the parameters that influence the change in tensile strength in the previous set of comparative analysis curves;

[0145] The weights of the correlation parameters of tensile strength change determined by the previous comparative analysis curve group are used to adjust the next analysis curve group, and the correlation parameters of tensile strength change are adjusted a second time according to the adjustment results, so that the residual of the next analysis curve group is reduced to the allowable range.

[0146] Repeat the above process of adjusting the weights of the related influence parameters until the adjustment process is complete.

[0147] This approach is a recursive sliding window parameter calibration strategy. Its core is not to fit the entire curve all at once, but to gradually approximate the actual curve by dividing the time into segments, passing weights segment by segment, and making repeated secondary adjustments.

[0148] Specifically, firstly, the cumulative curve L of the actual tensile strength loss over time is analyzed. actual (t) and the cumulative curve of theoretical tensile strength loss L theoretical (t) Perform segmentation, specifically, divide the entire service time axis into several continuous and non-overlapping time windows with a predetermined time step Δt (e.g., Δt=2 years or Δt=3 years) as the interval.

[0149] The actual curve segments and theoretical curve segments within each time window constitute a set of comparative analysis curves G. k , where k=1, 2, …, N, N is the total number of windows, and all windows are arranged in chronological order.

[0150] Each set of comparative analysis curves satisfies:

[0151] G k = { L actual (t), L theoretical (t) | t ∈ [t {k-1} , t k ]}

[0152] Where t0 is the start time (commissioning time), t N This is the current detection time.

[0153] Recursive weight transfer and secondary adjustment:

[0154] For the first set of comparative analysis curves G1 (i.e. the earliest time window), the weight vector W0 of the associated influence parameters is initialized to a preset empirical value or a value recommended by the standard model.

[0155] The first parameter optimization is performed within G1 to make the residual e1(t) = L within this window. actual (t)-L theoretical Minimizing the root mean square error of G(t) yields the optimal weight vector W1 of G1.

[0156] For the k-th set of comparative analysis curves G k (k≥2), its weight adjustment adopts a recursive two-stage strategy:

[0157] Phase 1 – Weight Transfer:

[0158] The optimal weight vector W_{k-1} obtained after optimization of the previous group G_{k-1} is taken as the current group G. k The initial weight vector, i.e.:

[0159] W_k^{(0)} = W_{k-1}

[0160] This step ensures that the parameters transition continuously in value between adjacent time windows, avoiding unreasonable inflection points or jumps in the correction curve due to sudden parameter changes, which conforms to the physical law that the aging process of overhead transmission lines has a gradual and continuous change.

[0161] Phase Two – Second Adjustment:

[0162] Starting with W_k^{(0)} as the search starting point, within the current time window G kWithin the range, a local optimization algorithm is used to perform secondary fine-tuning of W_k^{(0)}. The optimization objective is to make G k The residual sequence e within k RMSE of (t) k Minimize and constrain RMSE k Less than or equal to the preset allowable threshold RMSE threshold (such as RMSE) threshold =3%).

[0163] If the optimal weight vector after the second adjustment is denoted as W_k^*, then it must satisfy:

[0164] W_k^* = argmin_{W} RMSE_k(W), and RMSE_k(W_k^*) ≤ RMSE_threshold

[0165] Meanwhile, to prevent overfitting, a constraint is imposed on W_k^: ∥W_k^ - W_k^{(0)}∥ ≤ δ, where δ is the preset maximum allowable parameter variation amplitude (e.g., δ is taken as ±20% of the previous set of weight values).

[0166] Iterative progress and termination conditions:

[0167] Proceeding sequentially along the time axis, the above "weight transfer + secondary adjustment" process is executed for k=1, 2, …, N in turn, until all the comparative analysis curve groups are covered.

[0168] When the last group G N After the second adjustment, the weight sequence {W_1^, W_2^, …,W_N^*} on the entire time axis is obtained. This weight sequence is concatenated in chronological order and substituted into the theoretical calculation model to recalculate the loss value on the entire time axis, thus obtaining the corrected tensile strength loss cumulative curve.

[0169] In a more preferred embodiment, the time step Δt is not fixed, but dynamically adjusted according to the rate of change of the residual between the actual curve and the theoretical curve:

[0170] When the residual change rate is small (i.e. the two curves are parallel and the deviation is stable), a larger time step (e.g., Δt = 4 years) is used to improve computational efficiency.

[0171] When the residual change rate is large (i.e., the two curves intersect or the deviation increases sharply), a smaller time step (e.g., Δt=1 year) is used to increase the density and accuracy of parameter calibration.

[0172] The dynamic adjustment of the time step is expressed by the formula:

[0173] Δtk =Δt base ×(1+σ·|RMSE k -RMSE {k-1} | / RMSE {k-1} )

[0174] Where, Δt base The base step size is used, and σ is the sensitivity adjustment coefficient (ranging from 0.5 to 2.0). By dynamically adjusting the step size, a balance between computational accuracy and computational efficiency is achieved.

[0175] In some cases, the weights of the parameters that determine the correlation of tensile strength variation in the previous set of comparative analysis curves include:

[0176] The actual tensile strength loss cumulative curve in the comparative analysis curve group is trimmed using dynamic influence parameters. The part of the actual tensile strength loss cumulative curve corresponding to the dynamic influence parameters is the dynamic segment, and the remaining part is the static segment.

[0177] Calculate the average tensile strength loss in the dynamic segment;

[0178] The proportions of temperature, dependent load, and wind load borne are determined based on the average tensile strength loss of the dynamic section.

[0179] Calculate the static average compensation difference of the static segment;

[0180] The residuals of the analysis curve set are reduced to an allowable range by adjusting the cumulative curve of theoretical tensile strength loss using the temperature bearing ratio, dependent load bearing ratio, wind load bearing ratio, and static average compensation difference.

[0181] A specific implementation method is as follows:

[0182] Dynamic and static segment trimming of the actual curve:

[0183] Get the current comparison analysis curve group G k The actual tensile strength loss cumulative curve L in actual (t) Based on historical meteorological data of the geographical location of the overhead transmission line analysis object, identify whether each time point within the time window is significantly affected by the dynamic environment.

[0184] The time period affected by the dynamic environment is designated as dynamic segment D, and the dynamic environment impact includes, but is not limited to:

[0185] High-temperature periods when the ambient temperature exceeds a preset temperature threshold (e.g., continuously exceeding 30°C);

[0186] Strong wind periods when the wind speed exceeds a preset wind speed threshold (e.g., greater than 10 m / s);

[0187] Ice accumulation periods when the ice thickness exceeds a preset thickness threshold (e.g., greater than 5 mm);

[0188] The remaining time periods within the time window, excluding the dynamic segment D, are marked as static segments S.

[0189] Therefore, the actual tensile strength loss cumulative curve is cut as: L actual (t) = L D (t) ∪ L S (t);

[0190] Among them, L D (t) represents the actual loss curve segment corresponding to the dynamic segment, L S (t) represents the actual loss curve segment corresponding to the static segment.

[0191] Calculation of average tensile strength loss in dynamic segment:

[0192] Calculate the average tensile strength loss A within the dynamic segment D. D The calculation formula is as follows:

[0193] A D = (1 / T D ) × ∫{t∈D} L actual (t) dt

[0194] Or discrete form:

[0195] A D = (1 / n D )×Σ{ti∈D} L actual (t i )

[0196] Among them, T D n is the total duration of the dynamic segment. D This represents the number of data points within the dynamic segment.

[0197] Determining the proportion of loss borne by the three factors in dynamic segment

[0198] Based on the synchronous meteorological monitoring data within the time range corresponding to dynamic segment D, the temperature influence factor F is calculated respectively. T Attachment load (icing) influence factor F I Wind load influence factor F W .

[0199] The calculation methods for each impact factor are as follows:

[0200] Temperature influence factor: F T = Σ max(0, T(t i ) - T ref ) × Δti This refers to the accumulation of the portion exceeding the reference temperature over time.

[0201] Dependent load influence factor: F I = Σ G ice (t i ) × Δt i This refers to the accumulation of the additional load from icing over time.

[0202] Wind load influence factor: F W = Σ v(t i )² × Δt i That is, the accumulation of the square of the wind speed over time (characterizing the energy of the wind load).

[0203] Then the temperature bearing ratio β T β, the proportion of load borne by the dependent load I Wind load bearing ratio β W Determine them respectively using the following formulas:

[0204] β T = F T / (F T + F I + F W ),

[0205] β I = F I / (F T + F I + F W ),

[0206] β W = F W / (F T + F I + F W ),

[0207] And it satisfies the normalization constraint: β T + β I +β W = 1.

[0208] The above three sharing ratios are respectively compared with the average loss A of the dynamic segment. D Multiplying these components yields the loss components borne by temperature, dependent load, and wind load during the dynamic segment:

[0209] A T = β T × A D A I = β I × A D AW = β W × A D ;

[0210] Calculation of static average compensation difference for static segments:

[0211] For the static segment S, which is not significantly affected by dynamic environmental factors, the actual loss in this segment mainly reflects the combined effect of static influence parameters (such as self-weight, span, elastic modulus, and creep).

[0212] The average deviation between the actual curve and the theoretical curve within the static segment S is calculated as the static average compensation difference C. S :

[0213] C S = (1 / n S ) × Σ_{t i ∈S} [ L actual (t i ) - L theoretical (t i ) ]

[0214] Where, n S This represents the number of data points within the static segment.

[0215] The C S The value reflects a systematic deviation in the static background parameter setting of the theoretical model. When C S When C > 0, it indicates that the theoretical model underestimates the static background loss and needs to be compensated upwards; when C S When the value is less than 0, it indicates that the theoretical model has overestimated the static background loss and needs to be compensated downwards.

[0216] Theoretical curve adjustment based on weight allocation and compensation difference:

[0217] The temperature bearing ratio β obtained from the above calculation T β, the proportion of load borne by the dependent load I Wind load bearing ratio β W and static average compensation difference C S For the current comparative analysis curve group G k The cumulative curve of theoretical tensile strength loss L theoretical (t) is adjusted in the following segments:

[0218] Adjustment of dynamic segment D:

[0219] Within the dynamic segment D, the theoretical curve is weighted and amplified according to the three dynamic bearing ratios to obtain the adjusted theoretical loss value L'. theoretical (t):

[0220] L' theoretical(t)= L theoretical (t) + A T × β T' + A I × β I' + A W × β W' ;

[0221] Where, β T' β I' β W' This is the dynamic segment correction weight coefficient after proportional allocation, and its value is the same as the aforementioned β. T β I β W It shows a positive correlation and can be normalized and scaled according to the specific meteorological data amplitude within the time window.

[0222] Adjustment of static segment S:

[0223] Within the static segment S, the theoretical curve is shifted as a whole by C. S The adjusted theoretical loss value L' is obtained. theoretical (t):

[0224] L' theoretical (t) = L theoretical (t) +C S ;

[0225] Residual verification:

[0226] Calculate and adjust the current comparative analysis curve group G k residual e' k (t) = L actual (t) - L' theoretical (t). If e' k RMSE of (t) k If the weights are less than the preset allowable threshold, then the weights for that group are determined; if they are greater than the threshold, then the weights for β are adjusted. T β I β W and C S Perform small-scale iterative adjustments until the accuracy requirements are met.

[0227] When a dynamic segment corresponds to at least two of the dynamic influence parameters, it is handled in the following way:

[0228] In a dynamic segment that corresponds to only one of the dynamic influence parameters, determine the initial bearing ratio of temperature, the initial bearing ratio of dependent load, and the initial bearing ratio of wind load;

[0229] Use the initial temperature load ratio, the initial load ratio of the dependent load, and the initial wind load ratio to check at least two of the dynamic segments of the corresponding dynamic influence parameters to obtain the reference difference;

[0230] Adjust the initial temperature load ratio, the initial load ratio of the dependent load, and the initial load ratio of the wind load based on the reference difference, so that the difference between the cumulative tensile strength loss of all dynamic segments and the actual tensile strength loss of all dynamic segments is within the allowable range.

[0231] The purpose of this method is to use the single-factor pure segment to calibrate the independent damage coefficients of each factor, and then use the multi-factor coupled segment as the verification field to solve the coupling synergy effect through global closed constraints, so as to finally realize dynamic weight decoupling and accurate allocation in the multi-factor superposition scenario.

[0232] A specific implementation method is as follows:

[0233] Within the preceding or subsequent time windows, dynamic segments corresponding to only a single dynamic influence parameter are selected as calibration reference segments, specifically including:

[0234] Pure temperature segment: The time period when the ambient temperature exceeds the preset threshold but the wind speed is lower than the preset threshold and there is no icing;

[0235] Pure wind load segment: The time period during which the wind speed exceeds the preset threshold but the ambient temperature is below the preset threshold and there is no icing;

[0236] Purely dependent load segment: The time period in which the icing thickness exceeds the preset threshold but the ambient temperature and wind speed are both below the preset threshold.

[0237] Within each of the aforementioned pure segments, the initial temperature bearing ratio β is calculated using the residual minimization method in step S104. T0 Initial load-bearing ratio β I0 Initial proportion of wind load β W0 .

[0238] The initial proportion of this group's contribution satisfies the normalization constraint: β T0 +β I0 +β W0 =1 represents the intrinsic damage weight of each factor under the condition of no coupling interference.

[0239] Verification and reference difference calculation of multi-factor coupling segment:

[0240] The above initial bearing ratio β T0 β I0 β W0 Applying to a coupled dynamic segment containing at least two dynamic influence parameters, calculate the theoretical cumulative tensile strength loss L within that coupled segment. coupled_theoretical :

[0241] L coupled_theoretical = L baseline_coupled + β T0 × E T +β I0 × E I +β W0 × E W ;

[0242] Among them, E T E I E W These represent the cumulative environmental intensity values ​​of temperature, dependent load, and wind load within the coupling segment, respectively. baseline_coupled This represents the static background loss within the coupling segment.

[0243] E T E I E W The calculation method is as follows:

[0244] Temperature cumulative intensity value E T =∑max(0,T(t i )−T ref )×Δt i ;

[0245] Cumulative strength value of attached load E I =∑G ice (t) i )×Δt i ;

[0246] cumulative wind load intensity value E W =∑v(t i ) 2 ×Δt i ;

[0247] Obtain the actual cumulative tensile strength loss L within the coupling segment. coupled_actual And calculate the reference difference Δ_coupled:

[0248] Δ_coupled = L coupled_actual - L coupled_theoretical

[0249] When Δ_coupled > 0, it means that the initial weights underestimate the synergistic damage effect under multi-factor coupling; when Δ_coupled < 0, it means that the initial weights overestimate the coupling effect.

[0250] Secondary weighting adjustment based on global total amount conservation:

[0251] To ensure that the cumulative theoretical loss and the cumulative actual loss of all dynamic segments (including single-factor pure segments and multi-factor coupled segments) are closed-loop as a whole, the following global constraint is introduced:

[0252] Σ_{k=1}^{N_D} L theoretical_adjusted (k) = Σ_{k=1}^{N_D} L_actual(k) ± ε

[0253] Where, N D ε represents the total number of all dynamic segments, and ε is the preset global allowable deviation threshold (e.g., ±2% of the total actual loss of all dynamic segments).

[0254] Under the aforementioned global constraints, with β T0 β I0 β W0 Starting from the initial search point, a nonlinear optimization algorithm (such as sequential quadratic programming or genetic algorithm) is used to jointly adjust the proportions of the three components. The search objective is to minimize the absolute value of the global deviation, |Δ_global|.

[0255] min | Δglobal | = | Σ_{k=1}^{N_D} [ L actual (k) - L theoretical_adjusted (k,β T β I β W ) ] |

[0256] Simultaneously apply constraint condition: β T +β I +β W =1, and the change in each proportion relative to the initial value does not exceed the preset fluctuation range (such as ±30%), in order to avoid overfitting.

[0257] The optimal solution β obtained after the above optimization T *、β I *、β W * represents the final dynamic weight allocation result after considering the coupling effect of multiple factors.

[0258] Through the above method, this application realizes that when multiple factors coexist in a dynamic influence parameter, there is no need to establish complex nonlinear coupled physical equations, and the collaborative calibration of the weights of multiple factors can be completed simply by global total conservation constraints.

[0259] This application also provides a device for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment, including:

[0260] The data acquisition unit is used to acquire historical tensile strength loss data of the overhead transmission line analysis object;

[0261] The first data processing unit is used to plot the cumulative curve of actual tensile strength loss of the overhead transmission line analysis object based on historical tensile strength loss data.

[0262] The second data processing unit is used to calculate the theoretical tensile strength loss cumulative curve of the overhead transmission line analysis object based on the calculation model.

[0263] The correction processing unit is used to correct the theoretical tensile strength loss accumulation curve using the actual tensile strength loss accumulation curve, so as to obtain the tensile strength correction curve;

[0264] The prediction processing unit is used to predict the cumulative tensile strength loss of the analysis object of the overhead transmission line using the tensile strength correction curve.

[0265] The assessment unit is used to jointly predict the cumulative loss of tensile strength and combine the strain data of the overhead transmission line analysis object to assess the aging status of the analysis object and obtain the aging risk assessment result.

[0266] Furthermore, the correction of the theoretical tensile strength loss cumulative curve using the actual tensile strength loss cumulative curve includes:

[0267] Place the actual tensile strength loss cumulative curve and the theoretical tensile strength loss cumulative curve in the same coordinate system and align them;

[0268] Calculate the residual between the actual tensile strength loss cumulative curve and the theoretical tensile strength loss cumulative curve;

[0269] Adjust the weights of the parameters that influence the change in tensile strength to reduce the residual to an acceptable range;

[0270] The cumulative curve of theoretical tensile strength loss is corrected using weighted correlation influence parameters.

[0271] Furthermore, the parameters relating to changes in tensile strength include dynamic and static parameters;

[0272] Dynamic influencing parameters include meteorological environmental factors, which include temperature, dependent loads, and wind loads.

[0273] Static influence parameters include conductor intrinsic parameters and long-term drift parameters. Conductor intrinsic parameters include self-weight, span, elastic modulus and coefficient of linear expansion, while long-term drift parameters include creep.

[0274] Among them, static influence parameters are involved in generating the theoretical tensile strength loss cumulative curve, while dynamic influence parameters are not involved in generating the theoretical tensile strength loss cumulative curve.

[0275] Furthermore, when meteorological environmental factors are involved in correcting the cumulative curve of theoretical tensile strength loss, an amplification factor is assigned to the dynamic influence parameters according to the time period.

[0276] Furthermore, adjusting the weights of the parameters relating to the change in tensile strength and reducing the residual to an acceptable range includes:

[0277] By cropping the actual tensile strength loss cumulative curve and the theoretical tensile strength loss cumulative curve along the time dimension, a set of comparative analysis curves is obtained.

[0278] Determine the weights of the parameters that influence the change in tensile strength in the previous set of comparative analysis curves;

[0279] The weights of the correlation parameters of tensile strength change determined by the previous comparative analysis curve group are used to adjust the next analysis curve group, and the correlation parameters of tensile strength change are adjusted a second time according to the adjustment results, so that the residual of the next analysis curve group is reduced to the allowable range.

[0280] Repeat the above process of adjusting the weights of the related influence parameters until the adjustment process is complete.

[0281] Furthermore, the weights of the parameters relating to the tensile strength variation in the previous comparative analysis curve set were determined, including:

[0282] The actual tensile strength loss cumulative curve in the comparative analysis curve group is trimmed using dynamic influence parameters. The part of the actual tensile strength loss cumulative curve corresponding to the dynamic influence parameters is the dynamic segment, and the remaining part is the static segment.

[0283] Calculate the average tensile strength loss in the dynamic segment;

[0284] The proportions of temperature, dependent load, and wind load borne are determined based on the average tensile strength loss of the dynamic section.

[0285] Calculate the static average compensation difference of the static segment;

[0286] The residuals of the analysis curve set are reduced to an allowable range by adjusting the cumulative curve of theoretical tensile strength loss using the temperature bearing ratio, dependent load bearing ratio, wind load bearing ratio, and static average compensation difference.

[0287] Furthermore, when the dynamic segment corresponds to at least two of the dynamic influence parameters, it also includes:

[0288] In a dynamic segment that corresponds to only one of the dynamic influence parameters, determine the initial bearing ratio of temperature, the initial bearing ratio of dependent load, and the initial bearing ratio of wind load;

[0289] Use the initial temperature load ratio, the initial load ratio of the dependent load, and the initial wind load ratio to check at least two of the dynamic segments of the corresponding dynamic influence parameters to obtain the reference difference;

[0290] Adjust the initial temperature load ratio, the initial load ratio of the dependent load, and the initial load ratio of the wind load based on the reference difference, so that the difference between the cumulative tensile strength loss of all dynamic segments and the actual tensile strength loss of all dynamic segments is within the allowable range.

[0291] In one example, the unit in any of the above devices may be one or more integrated circuits configured to implement the above methods, such as one or more application-specific integrated circuits (ASICs), or one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs), or a combination of at least two of these integrated circuit forms.

[0292] For example, when the units in the device can be implemented through a processing element scheduler, the processing element can be a general-purpose processor, such as a central processing unit (CPU) or other processor capable of calling programs. Alternatively, these units can be integrated together to form a system-on-a-chip (SOC).

[0293] In this application, various objects such as messages / information / devices / network elements / systems / apparatus / actions / operations / processes / concepts may be named. It is understood that these specific names do not constitute a limitation on the relevant objects. The names may be changed depending on the scenario, context, or usage habits. The understanding of the technical meaning of the technical terms in this application should be mainly determined from their functions and technical effects embodied / performed in the technical solution.

[0294] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0295] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0296] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0297] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0298] It should also be understood that in the various embodiments of this application, "first," "second," etc., are merely used to indicate that multiple objects are different. For example, a first time window and a second time window are only used to indicate different time windows. They should not have any effect on the time windows themselves, and the aforementioned "first," "second," etc., should not impose any limitations on the embodiments of this application.

[0299] It should also be understood that, in the various embodiments of this application, unless otherwise specified or in case of logical conflict, the terms and / or descriptions between different embodiments are consistent and can be referenced by each other, and the technical features in different embodiments can be combined to form new embodiments according to their inherent logical relationships.

[0300] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a computer-readable storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned computer-readable storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0301] This application also provides an aging risk assessment system for overhead transmission lines based on the cumulative effects of time and environment, the system comprising:

[0302] One or more memories for storing instructions; and

[0303] One or more processors are configured to retrieve and execute the instructions from the memory, performing the methods described above.

[0304] This application also provides a computer program product including instructions that, when executed, cause the terminal device and the network device to perform operations corresponding to the methods described above.

[0305] This application also provides a chip system including a processor for implementing the functions involved in the above description, such as generating, receiving, transmitting, or processing the data and / or information involved in the above methods.

[0306] This chip system can consist of chips or include chips and other discrete components.

[0307] The processor mentioned above can be a CPU, a microprocessor, an ASIC, or one or more integrated circuits that execute a program to control the method of transmitting the feedback information described above.

[0308] In one possible design, the chip system also includes a memory for storing necessary program instructions and data. The processor and the memory can be decoupled and located on different devices, connected via wired or wireless means to support the chip system in implementing the various functions described in the above embodiments. Alternatively, the processor and the memory can also be coupled to the same device.

[0309] Optionally, the computer instructions are stored in memory.

[0310] Optionally, the memory can be a storage unit within the chip, such as a register or cache. Alternatively, the memory can be a storage unit located outside the chip within the terminal, such as a ROM or other types of static storage devices that can store static information and instructions, such as RAM.

[0311] It is understood that the memory in this application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0312] Non-volatile memory can be ROM, programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory.

[0313] Volatile memory can be RAM, which is used as an external cache. There are many different types of RAM, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct memory bus random access memory.

[0314] The embodiments described in this specific implementation are preferred embodiments of this application and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A method for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment, characterized in that, include: Obtain historical tensile strength loss data for the analysis object of the overhead transmission line; Plot the cumulative curve of actual tensile strength loss of the analysis object of the overhead transmission line based on historical tensile strength loss data; The cumulative curve of theoretical tensile strength loss of the analysis object of overhead transmission line is calculated based on the computational model; The theoretical tensile strength loss cumulative curve is corrected using the actual tensile strength loss cumulative curve to obtain the tensile strength correction curve; The cumulative loss of predicted tensile strength of the analysis object of the overhead transmission line is predicted using the tensile strength correction curve. The aging status of the overhead transmission line analysis object is assessed by combining the predicted cumulative loss of tensile strength and the strain data of the analysis object, and the aging risk assessment results are obtained.

2. The method for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment as described in claim 1, characterized in that, The correction of the theoretical tensile strength loss cumulative curve using the actual tensile strength loss cumulative curve includes: Place the actual tensile strength loss cumulative curve and the theoretical tensile strength loss cumulative curve in the same coordinate system and align them; Calculate the residual between the actual tensile strength loss cumulative curve and the theoretical tensile strength loss cumulative curve; Adjust the weights of the parameters that influence the change in tensile strength to reduce the residual to an acceptable range; The cumulative curve of theoretical tensile strength loss is corrected using weighted correlation influence parameters.

3. The method for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment as described in claim 2, characterized in that, The parameters relating to changes in tensile strength include dynamic and static parameters. Dynamic influencing parameters include meteorological environmental factors, which include temperature, dependent loads, and wind loads. Static influence parameters include conductor intrinsic parameters and long-term drift parameters. Conductor intrinsic parameters include self-weight, span, elastic modulus and coefficient of linear expansion, while long-term drift parameters include creep. Among them, static influence parameters are involved in generating the theoretical tensile strength loss cumulative curve, while dynamic influence parameters are not involved in generating the theoretical tensile strength loss cumulative curve.

4. The method for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment as described in claim 3, characterized in that, When meteorological and environmental factors are involved in correcting the cumulative curve of theoretical tensile strength loss, an amplification factor is assigned to the dynamic influence parameter according to the time period.

5. The method for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment as described in claim 4, characterized in that, Adjusting the weights of the parameters relating to changes in tensile strength and reducing the residual to an acceptable range includes: By cropping the actual tensile strength loss cumulative curve and the theoretical tensile strength loss cumulative curve along the time dimension, a set of comparative analysis curves is obtained. Determine the weights of the parameters that influence the change in tensile strength in the previous set of comparative analysis curves; The weights of the correlation parameters of tensile strength change determined by the previous comparative analysis curve group are used to adjust the next analysis curve group, and the correlation parameters of tensile strength change are adjusted a second time according to the adjustment results, so that the residual of the next analysis curve group is reduced to the allowable range. Repeat the above process of adjusting the weights of the related influence parameters until the adjustment process is complete.

6. The method for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment as described in claim 5, characterized in that, The weights of the parameters relating to the tensile strength variation in the previous comparative analysis curve set are determined by: The actual tensile strength loss cumulative curve in the comparative analysis curve group is trimmed using dynamic influence parameters. The part of the actual tensile strength loss cumulative curve corresponding to the dynamic influence parameters is the dynamic segment, and the remaining part is the static segment. Calculate the average tensile strength loss in the dynamic segment; The proportions of temperature, dependent load, and wind load borne are determined based on the average tensile strength loss of the dynamic section. Calculate the static average compensation difference of the static segment; The residuals of the analysis curve set are reduced to an allowable range by adjusting the cumulative curve of theoretical tensile strength loss using the temperature bearing ratio, dependent load bearing ratio, wind load bearing ratio, and static average compensation difference.

7. The method for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment as described in claim 6, characterized in that, When the dynamic segment corresponds to at least two of the dynamic influence parameters, it also includes: In a dynamic segment that corresponds to only one of the dynamic influence parameters, determine the initial bearing ratio of temperature, the initial bearing ratio of dependent load, and the initial bearing ratio of wind load; Use the initial temperature load ratio, the initial load ratio of the dependent load, and the initial wind load ratio to check at least two of the dynamic segments of the corresponding dynamic influence parameters to obtain the reference difference; Adjust the initial temperature load ratio, the initial load ratio of the dependent load, and the initial load ratio of the wind load based on the reference difference, so that the difference between the cumulative tensile strength loss of all dynamic segments and the actual tensile strength loss of all dynamic segments is within the allowable range.

8. A device for assessing the aging risk of overhead transmission lines based on the cumulative effects of time and environment, characterized in that, include: The data acquisition unit is used to acquire historical tensile strength loss data of the overhead transmission line analysis object; The first data processing unit is used to plot the cumulative curve of actual tensile strength loss of the overhead transmission line analysis object based on historical tensile strength loss data. The second data processing unit is used to calculate the theoretical tensile strength loss cumulative curve of the overhead transmission line analysis object based on the calculation model. The correction processing unit is used to correct the theoretical tensile strength loss accumulation curve using the actual tensile strength loss accumulation curve, so as to obtain the tensile strength correction curve; The prediction processing unit is used to predict the cumulative tensile strength loss of the analysis object of the overhead transmission line using the tensile strength correction curve. The assessment unit is used to jointly predict the cumulative loss of tensile strength and combine the strain data of the overhead transmission line analysis object to assess the aging status of the analysis object and obtain the aging risk assessment result.

9. A risk assessment system for aging of overhead transmission lines based on the cumulative effects of time and environment, characterized in that, The system includes: One or more memories for storing instructions; and One or more processors are configured to retrieve and execute the instructions from the memory to perform the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes: The program, when run by the processor, executes the method as described in any one of claims 1 to 7.

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