A method and system for assisting in the design optimization of cable laying

Abstract

The application relates to an auxiliary design optimization method and system for cable laying, and relates to the technical field of cable design optimization.The application comprises the following steps: collecting a historical maximum wind speed as a regional wind force feature based on an environment monitoring log of an optical cable overhead area; collecting an average erection height, a power pole spacing, a power pole vertical height difference and a power pole type as overhead scene features; based on a scheme fitness evaluation function and a preset optical cable hook quantity, taking the maximum coverage distance as a constraint, combining the optical cable attribute features, the regional wind force features and the overhead scene features to optimize an optical cable hook layout scheme, and outputting an optimal scheme; and constructing the optical cable overhead area according to the optimal scheme.The application solves the problems that, in traditional cable laying, the optical cable hook layout scheme lacks comprehensive consideration of actual environment features and scene features of overhead, leading to uneven wind force distribution, large optical cable swing amplitude, insufficient stability, poor scheme optimization pertinence and low efficiency.

Description

Technical Field

[0001] This application relates to the field of cable design optimization, and in particular to an auxiliary design optimization method and system for cable laying. Background Technology

[0002] With the continuous advancement of communication network construction, the stability of overhead optical cable laying is crucial to communication transmission quality. Meanwhile, environmental factors such as wind have an increasingly significant impact on optical cable safety, making the optimization of hook placement schemes a key technical issue for ensuring the reliability of overhead optical cables. Currently, traditional optical cable hook placement methods rely heavily on experience and judgment, failing to fully consider the actual environmental characteristics and scenarios of overhead installations, thus making them unsuitable for complex and ever-changing overhead conditions.

[0003] Existing hook deployment methods lack comprehensive consideration of actual environmental and scenario characteristics, resulting in insufficient targeting of the solutions. Not only is it difficult to maximize the uniformity of wind force distribution and minimize the sway amplitude of optical cables, but it also leads to redundant design or insufficient support, affecting the stability of optical cable laying and increasing the complexity and cost of later maintenance. Summary of the Invention

[0004] To address the aforementioned technical problems, this application provides an auxiliary design optimization method and system for cable laying, which improves upon the shortcomings of traditional cable laying methods, such as uneven wind distribution, large optical cable sway amplitude, poor laying stability, and low optimization efficiency caused by insufficient integration of actual overhead environmental characteristics and overhead scene characteristics, and insufficient targeted solutions.

[0005] The embodiments of this application disclose the following technical solutions:

[0006] In a first aspect, embodiments of this application provide an auxiliary design optimization method for cable laying, the method comprising:

[0007] Based on environmental monitoring logs of the overhead optical cable area, the maximum wind speed within a historical time range is collected as the regional wind force characteristic.

[0008] The average erection height, pole spacing, vertical height difference of power poles, and power pole type during the overhead fiber optic cable process are collected as features of the overhead scene.

[0009] Based on the scheme fitness evaluation function and the preset number of optical cable hooks, with the maximum coverage distance of the optical cable hooks as a constraint, the optical cable hook deployment scheme is optimized according to the optical cable attribute characteristics, the wind characteristics of the area, and the characteristics of the overhead scene, and the optimal hook deployment scheme is output.

[0010] Within the overhead optical cable area, the optical cable hooks are installed according to the optimal hook layout scheme.

[0011] Secondly, embodiments of this application provide an auxiliary design optimization system for cable laying, the system comprising:

[0012] The wind force feature acquisition module is used to collect the maximum wind speed within a historical time range as the regional wind force feature based on the environmental monitoring logs of the optical cable overhead area.

[0013] The overhead scene acquisition module is used to collect the average erection height, pole spacing, vertical height difference of poles, and pole type during the overhead fiber optic cable process as features of the overhead scene.

[0014] The hook scheme optimization module is used to optimize the optical cable hook deployment scheme based on the scheme fitness evaluation function and the preset number of optical cable hooks, with the maximum coverage distance of the optical cable hooks as a constraint, according to the optical cable attribute characteristics and the wind characteristics and overhead scene characteristics of the area, and output the optimal hook deployment scheme.

[0015] The optimal solution implementation module is used to carry out optical cable hook construction according to the optimal hook layout scheme within the overhead optical cable area.

[0016] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0017] This application proposes an auxiliary design optimization method and system for cable laying. The method achieves scientific optimization of auxiliary design for cable laying by dynamically configuring the weight ratio of high wind speed frequencies in the overhead optical cable area, constructing a scheme fitness evaluation function, simulating the overhead optical cable space using digital twin technology, generating multiple sets of hook placement sequences and conducting simulation tests, and outputting the optimal hook placement scheme based on scheme fitness. First, based on environmental monitoring logs, high wind speed frequencies are statistically analyzed, and the sway amplitude weight adjustment coefficient is matched to correct the initial weights and obtain the weight ratio of the suitable indicators. Then, a scheme fitness evaluation function is constructed by combining wind distribution uniformity and optical cable sway amplitude. Next, optical cable attributes, regional wind force, and overhead scene characteristics are integrated, and an overhead optical cable simulation space is constructed using digital twin technology. Then, multiple sets of hook placement sequences are generated, and predicted data is obtained through testing in the simulation space. This data is then substituted into the scheme fitness evaluation function to calculate the fitness. Finally, through clustering iteration and optimization-avoidance strategies, the optimal hook placement scheme is output and applied to actual optical cable hook construction.

[0018] This technical solution addresses the shortcomings of traditional cable laying methods, such as uneven wind distribution, large cable sway, poor laying stability, and low optimization efficiency, by integrating dynamic weight adjustment driven by high wind speed frequency, virtual simulation testing supported by digital twins, fitness evaluation integrating multi-dimensional indicators, and solution optimization based on iterative optimization. It achieves precise matching between the cable hook deployment scheme and the wind speed environment, providing technical support for improving the wind resistance safety of cable laying. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 A flowchart illustrating an auxiliary design optimization method for cable laying provided in an embodiment of this application;

[0021] Figure 2 This is a schematic diagram of a cable laying auxiliary design optimization system provided in an embodiment of this application.

[0022] The components represented by each number in the attached diagram are explained below:

[0023] Wind force feature acquisition module 01, overhead scene acquisition module 02, hook scheme optimization module 03, and optimal scheme implementation module 04. Detailed Implementation

[0024] This application provides an auxiliary design optimization method and system for cable laying, which solves the technical problems in the prior art where the optical cable hook laying scheme does not fully combine regional wind characteristics, overhead scene characteristics and optical cable attribute characteristics, making it difficult to adapt to complex environments, resulting in uneven wind distribution, large optical cable sway amplitude, poor laying stability and low optimization efficiency.

[0025] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] In the description of this application, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the stated features. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0027] In the description of this application, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this application is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed in this application.

[0028] Example 1, as shown in the appendix Figure 1 As shown, this application provides an auxiliary design optimization method for cable laying, the method comprising the following steps:

[0029] S110: Based on the environmental monitoring logs of the overhead optical cable area, the maximum wind speed within the historical time range is collected as the regional wind force characteristic;

[0030] In this embodiment of the application, in order to accurately obtain regional wind characteristics to support the subsequent optimization of the optical cable hook deployment scheme, it is necessary to extract key wind data from the environmental monitoring log and collect the maximum wind speed within the historical time range to reflect the extreme intensity of wind action in the region and provide core basis for evaluating the stability of optical cables in strong wind environments.

[0031] Specifically, the first step is to define the historical time range for data collection, which should cover different seasons and climate stages, to ensure that the collected wind data can comprehensively reflect the long-term wind force change characteristics of the region.

[0032] Specifically, environmental monitoring logs from the past three years should be selected as the source of wind data. Furthermore, the environmental monitoring logs should be filtered to extract wind monitoring records directly related to the area where the fiber optic cable is overhead, while excluding interfering data from irrelevant areas.

[0033] In addition, when extracting wind data from environmental monitoring logs, attention should also be paid to the sampling frequency and accuracy of environmental monitoring equipment to ensure the reliability of the raw data.

[0034] For example, if the environmental monitoring equipment records the wind speed value every 10 minutes with an accuracy of 0.1 m / s, then during the wind data acquisition process, the wind speed records for the area need to be checked one by one to avoid the inclusion of abnormal values ​​due to equipment failure or data transmission errors.

[0035] For cases with outliers, data cleaning methods must be used. For example, if a wind speed record deviates significantly from the data of surrounding monitoring points during the same period, it should be identified as an outlier and removed to ensure the accuracy of maximum wind speed extraction.

[0036] Finally, the historical maximum wind speed collected from the environmental monitoring logs through the above steps will serve as the core parameter of the regional wind force characteristics. Combined with subsequent characteristics of the overhead scene and the optical cable properties, it will provide key environmental constraints for optimizing the optical cable hook deployment scheme.

[0037] S120: Collect the average erection height, pole spacing, pole vertical height difference, and pole type during the overhead optical cable process as features of the overhead scene;

[0038] In this embodiment of the application, in order to fully capture the physical characteristics of the overhead optical cable scenario, it is necessary to systematically collect four key features: the average erection height, the spacing between power poles, the vertical height difference between power poles, and the type of power pole. These features directly affect the stress distribution, support stability, and swaying state of the optical cable under wind force.

[0039] Specifically, the first step is to collect data on the average installation height. The average installation height refers to the average height of the optical cable in the overhead area, which needs to be calculated by measuring the optical cable height at multiple monitoring points in the overhead area.

[0040] The monitoring points should cover the entire overhead area and be evenly distributed along the fiber optic cable sections between power poles. For example, three monitoring points should be selected between every two adjacent power poles, using a high-precision laser rangefinder with an accuracy controlled within ±0.05 meters. The average installation height can be obtained by summing the height values ​​of all monitoring points and dividing by the number of monitoring points.

[0041] Secondly, data on the spacing between power poles was collected. The spacing between power poles refers to the horizontal distance between two adjacent power poles, which is a key parameter determining the span length of optical cables.

[0042] Specifically, when collecting data on the spacing between power poles, the center position of the power pole should be used as the measurement reference. A total station should be used to measure the distance between each pair of adjacent power poles, and the measurement results should be recorded with an accuracy of 0.1 meters. For areas with undulating terrain, it is necessary to ensure that the horizontal projected distance is measured, rather than the distance along the slope of the ground.

[0043] For example, in a certain overhead section, the horizontal distance between three adjacent power poles is 50.3 meters between poles 1 and 2, and 49.8 meters between poles 2 and 3. Therefore, the distance between power poles in this area is 50.3 meters and 49.8 meters.

[0044] Next, the vertical height difference of the power poles is collected. The vertical height difference of the power poles refers to the difference in vertical height between the tops of two adjacent power poles, reflecting the slope characteristics of the fiber optic cable installation.

[0045] Specifically, when collecting the vertical height difference of power poles, it is necessary to first measure the actual height of each power pole (the vertical distance from the ground to the top of the pole), and then calculate the difference in height between two adjacent power poles (taking the absolute value).

[0046] When measuring the height of utility poles, a drone equipped with a lidar can be used for scanning, and ground markers can be used for calibration to ensure that the height measurement accuracy is within ±0.1 meters.

[0047] Finally, the types of utility poles were collected. Utility poles are classified according to their material, load-bearing capacity, and structural form. Common pole types include cement poles, steel poles, and wooden poles. Different types of utility poles vary significantly in load-bearing capacity, wind resistance, and service life.

[0048] Specifically, when collecting information on the types of power poles, it is necessary to conduct on-site surveys and record the type identification of each power pole (such as the production nameplate on the pole). For power poles without clear identification, they can be identified by combining their appearance characteristics (such as material texture and structural shape) with historical construction records, and then classified and recorded as power pole types such as "cement pole", "steel pole", and "wooden pole".

[0049] In addition, during the data collection process, all collected data must be reviewed and verified. For example, by comparing the spacing between adjacent power poles with the values ​​marked on the design drawings, if the deviation exceeds ±0.5 meters, the measurement must be repeated. The determination of the power pole type must be confirmed by two or more technicians to ensure the accuracy of the measurement data.

[0050] Ultimately, the collected average erection height, pole spacing, vertical height difference between poles, and pole type will collectively constitute the characteristic data of the overhead scene. This data, in conjunction with regional wind characteristics and optical cable attribute characteristics, will provide accurate scene parameter support for subsequent use in constructing an overhead optical cable simulation space and simulating and optimizing hook deployment schemes.

[0051] S130: Based on the scheme fitness evaluation function and the preset number of optical cable hooks, with the maximum coverage distance of the optical cable hooks as a constraint, the optical cable hook deployment scheme is optimized according to the optical cable attribute characteristics and the wind force characteristics and overhead scene characteristics of the area, and the optimal hook deployment scheme is output.

[0052] In this embodiment of the application, in order to achieve accurate optimization of the hook deployment scheme in the scenario of overhead optical cable laying, it is necessary to comprehensively utilize the scheme fitness evaluation function, preset parameters and multi-dimensional features, and determine the optimal scheme through simulation and optimization steps to ensure the stability of the optical cable under wind force.

[0053] Specifically, the first step is to configure optimization evaluation indicators, which serve as the basis for constructing the scheme fitness evaluation function. These indicators include wind distribution uniformity and optical cable sway amplitude, to quantitatively assess the impact of different hook deployment schemes on optical cable stability.

[0054] Furthermore, based on the weighting of the indicators, the uniformity of wind distribution and the amplitude of optical cable sway are incorporated into the calculation to construct a scheme fitness evaluation function.

[0055] The configuration of the indicator weight ratio is based on the environmental monitoring logs of the optical cable overhead area. The number of times the wind speed is greater than the preset wind speed threshold is counted within the historical time range. Then, the swing amplitude weight adjustment coefficient is obtained by matching the high wind speed frequency. The initial swing amplitude weight is corrected to obtain the adaptive swing amplitude weight. The adaptive distribution uniformity weight is obtained by subtracting the adaptive swing amplitude weight from 1. The two are combined to generate the weight.

[0056] Furthermore, the adaptability of the scheme is positively correlated with the uniformity of wind distribution, that is, the more uniform the wind distribution on the optical cable, the higher the adaptability of the scheme; and negatively correlated with the sway amplitude of the optical cable, that is, the smaller the sway amplitude of the optical cable, the higher the adaptability of the scheme.

[0057] Furthermore, the properties and characteristics of the optical cable to be laid are collected, including the type and specifications of the optical cable. These characteristics directly affect the mechanical properties and wind resistance of the optical cable and are the basic data for simulating the construction of an aerial optical cable simulation space.

[0058] Furthermore, by utilizing digital twin technology, the characteristics of optical cables, regional wind force, and overhead scene features are input into the simulation model to construct an overhead optical cable simulation space consistent with the actual scene, providing a simulated virtual test environment for verifying the hook deployment scheme.

[0059] Based on this, with the maximum coverage distance of the optical cable hooks as a constraint, multiple different optical cable hook deployment sequences are generated by randomly distributing the preset number of optical cable hooks.

[0060] Subsequently, in the simulated space of the overhead optical cable, the optical cable motion simulation test was carried out for each optical cable hook deployment sequence to simulate the dynamic state of the optical cable under strong wind, and the predicted wind force distribution uniformity and the predicted maximum sway amplitude of the optical cable corresponding to each hook deployment scheme were output.

[0061] Meanwhile, based on the scheme fitness evaluation function, the predicted data output above are substituted into the calculation to obtain the scheme fitness of each optical cable hook deployment sequence.

[0062] Furthermore, optimization is performed based on the fitness of multiple schemes. Iterative optimization is achieved through sorting, clustering, and optimization-avoidance methods to finally output the optimal hook placement scheme with the highest fitness.

[0063] This step, through a combination of digital twin simulation and multi-round iterative optimization, achieves precise optimization of the hook deployment scheme under the constraint of the maximum coverage distance of the optical cable hook, providing a strong guarantee for the stability of the overhead optical cable laying.

[0064] Step S130 in the method provided in this application embodiment includes:

[0065] Configure optimization evaluation indicators, wherein the optimization evaluation indicators include wind force distribution uniformity and optical cable sway amplitude;

[0066] Based on the weighting of the indicators, a scheme fitness evaluation function is constructed according to the wind distribution uniformity and the optical cable sway amplitude. The scheme fitness is positively correlated with the wind distribution uniformity and negatively correlated with the optical cable sway amplitude.

[0067] Collect the optical cable type and specifications of the optical cable to be laid as optical cable attribute characteristics;

[0068] Using digital twin technology, an aerial simulation space for optical cables is constructed based on the optical cable's attribute characteristics, regional wind characteristics, and aerial scene characteristics.

[0069] With the maximum coverage distance of the optical cable hooks as a constraint, the optical cable hooks are randomly distributed based on the preset number of optical cable hooks to generate multiple optical cable hook deployment sequences.

[0070] Within the simulated space of the overhead optical cable, the optical cable is simulated to move according to the multiple optical cable hooks deployment sequence, and multiple predicted wind force distribution uniformity and multiple predicted maximum optical cable swing amplitude are output.

[0071] Based on the scheme fitness evaluation function, the fitness of multiple schemes is evaluated according to the multiple predicted wind distribution uniformity and the multiple predicted maximum sway amplitude of optical cables.

[0072] Based on the fitness of the multiple schemes, the optical cable hook deployment scheme is optimized, and the optimal hook deployment scheme is output.

[0073] In this embodiment of the application, in order to achieve scientific optimization and precise adaptation of the optical cable hook deployment scheme, it is necessary to focus on the stability requirements of the optical cable under wind action, and to achieve precise adaptation of the hook deployment scheme to the wind environment by constructing quantitative evaluation indicators, integrating multi-dimensional features, and relying on digital twin simulation and iterative optimization.

[0074] First, a basic framework for evaluating the scheme is established by configuring optimization evaluation indicators.

[0075] Among them, the optimization evaluation indicators include wind force distribution uniformity and optical cable sway amplitude. Wind force distribution uniformity is used to reflect the balance of wind load on each section of the optical cable, while optical cable sway amplitude is used to reflect the extreme value of dynamic displacement of the optical cable under strong winds.

[0076] Specifically, wind load uniformity can be quantified by the ratio of the maximum difference to the mean wind load in different sections of the optical cable. The calculation formula can be expressed as "Wind load uniformity = 1 - Maximum difference in wind load / Mean wind load". The sway amplitude of the optical cable can be measured by the maximum sway amplitude at characteristic points such as mid-span and hook connection. These two types of indicators together constitute a comprehensive evaluation dimension for the wind resistance performance of the hook deployment scheme.

[0077] For example, an overhead optical cable section is divided into 10 monitoring sections, with wind loads of 2.1 N / m, 2.3 N / m, 2.2 N / m, etc. for each monitoring section. The calculated average wind load is 2.2 N / m, and the maximum difference is 0.3 N / m. Therefore, the wind distribution uniformity index is 1 - 0.3 / 2.2 ≈ 0.86, indicating that the wind distribution is relatively uniform.

[0078] Meanwhile, the maximum swing amplitude at the mid-span of the overhead section of the optical cable is 0.8 meters, and the maximum swing amplitude at the hook connection is 0.3 meters, which comprehensively reflects that the optical cable swing is relatively gentle under this hook deployment scheme.

[0079] Furthermore, an evaluation function for the fitness of the scheme is constructed according to the dynamically adjusted weight ratio of the indicators.

[0080] In the local method provided in this application embodiment, the "configuration process of the indicator weight ratio" includes:

[0081] Based on the environmental monitoring logs of the overhead optical cable area, the number of times the wind speed exceeded the preset wind speed threshold within the historical time range is counted and set as the high wind speed frequency.

[0082] The sway amplitude weight adjustment coefficient is obtained based on the high wind speed frequency matching, and the initial sway amplitude weight is corrected to obtain the adaptive sway amplitude weight. The initial sway amplitude weight is 0.5, and the adaptive sway amplitude weight does not exceed 0.8.

[0083] The adaptation distribution uniformity weight is obtained by subtracting the adaptation swing amplitude weight from 1, and the index weight ratio is generated by combining the adaptation swing amplitude weight.

[0084] In this embodiment of the application, in order to accurately adapt the weight ratio of the indicators to the wind resistance requirements of optical cables under different wind speed environments and to achieve a scientific evaluation of the wind resistance performance of the hook deployment scheme, it is necessary to dynamically adjust the weight of the swing amplitude based on the high wind speed frequency of the optical cable overhead area, and then construct a reasonable weight ratio of the indicators.

[0085] Specifically, based on the environmental monitoring logs of the overhead optical cable area, the number of times the wind speed exceeded the preset wind speed threshold within a historical time range was counted to obtain the high wind speed frequency.

[0086] The preset wind speed threshold can be determined based on the climate characteristics of the area where the optical cable is located and the wind-resistant design parameters of the optical cable itself. For example, in general areas, 8 m / s can be used as the preset wind speed threshold to identify high wind speed situations that have a significant impact on the swaying of the optical cable.

[0087] Furthermore, by traversing the wind speed data recorded in the environmental monitoring logs, the number of times the condition "wind speed > preset wind speed threshold" is met is counted, thereby quantifying the frequency of high wind speeds in the area and providing a basis for subsequent weight adjustments.

[0088] Furthermore, the swing amplitude weight adjustment coefficient is obtained based on the high wind speed frequency matching, and the initial swing amplitude weight is corrected to obtain the appropriate swing amplitude weight.

[0089] The swing amplitude weighting adjustment coefficient is obtained by dividing the high wind speed frequency range and establishing a mapping relationship between the high wind speed frequency range and the coefficient.

[0090] Specifically, based on historical environmental monitoring logs of the overhead optical cable area and actual cases of wind-induced swaying damage during optical cable maintenance, the high wind speed frequency (unit: times / year, statistical period: 1 year) should be divided into multiple intervals. The thresholds of these intervals can be dynamically adjusted according to the regional climate characteristics.

[0091] Based on this, a corresponding sway amplitude weighting adjustment coefficient is matched for each high wind speed frequency range. The value of the sway amplitude weighting adjustment coefficient is determined based on the correlation analysis between high wind speed frequency in the overhead optical cable area and the risk of optical cable sway damage, and the value range is usually between 0.5 and 1.2.

[0092] Specifically, for the range of 0 ≤ high wind speed frequency < 10 times / year, since the risk of high wind speed is extremely low, the corresponding sway amplitude weight adjustment coefficient is 0.5 to reduce the weight of sway amplitude in the evaluation; while for the range of high wind speed frequency ≥ 50 times / year, since high wind speed occurs extremely frequently and sway directly threatens the safe operation of optical cables, the corresponding sway amplitude weight adjustment coefficient is 1.2 to maximize the influence of sway amplitude in the scheme evaluation.

[0093] Finally, through the high-wind-speed frequency range division and swing amplitude weight adjustment coefficient mapping of the above steps, the swing amplitude weight adjustment coefficient can accurately correlate high-wind-speed frequency with optical cable swing risk, providing a reliable basis for the reasonable allocation of subsequent indicator weight ratios.

[0094] Furthermore, the initial swing amplitude weight is corrected based on the obtained swing amplitude weight adjustment coefficient to obtain an appropriate swing amplitude weight.

[0095] Specifically, the correction process for the initial swing amplitude weight should follow the principle of "the product of the initial swing amplitude weight and the adjustment coefficient as the basis and the threshold constraint as the boundary". First, the initial correction result is obtained by calculating the formula "initial value of the adaptive swing amplitude weight = initial swing amplitude weight × swing amplitude weight adjustment coefficient". Then, the result is subjected to threshold verification to finally determine the adaptive swing amplitude weight.

[0096] The initial sway amplitude weight is fixed at 0.5, which is a basic value set based on a balanced consideration of the initial importance of two indicators: wind force distribution uniformity and optical cable sway amplitude.

[0097] In addition, the core of threshold verification is to ensure that the weight of the adaptation swing amplitude does not exceed 0.8, so as to avoid the excessive weight of a single indicator in the scheme adaptability evaluation, which would lead to insufficient consideration of other key factors such as wind distribution uniformity, thereby ensuring the accuracy of the evaluation.

[0098] For example, if the high wind speed frequency in a certain optical cable overhead area is 45 times / year, which falls within the range of "30≤frequency<50 times / year", and the matching swing amplitude weight adjustment coefficient is 0.9, then the initial value of the adaptive swing amplitude weight is 0.5×0.9=0.45. This value is less than 0.8, and after threshold verification, it is directly determined as the adaptive swing amplitude weight.

[0099] In addition, if the frequency of high wind speed in another area is 60 times / year, which falls within the "frequency ≥ 50 times / year" range, the sway amplitude weight adjustment coefficient is 1.2, and the initial value of the adaptive sway amplitude weight is 0.5 × 1.2 = 0.6, which also meets the threshold requirement and is directly used as the final adaptive sway amplitude weight.

[0100] Conversely, if the swing amplitude weight adjustment coefficient for an extremely high wind speed area is 1.7 (although such cases are rare in actual applications, this is used to illustrate the role of the threshold), then the initial value = 0.5 × 1.7 = 0.85. At this time, the threshold constraint needs to be triggered to forcibly set the adaptive swing amplitude weight to 0.8 in order to maintain the rationality of the indicator weight ratio.

[0101] Furthermore, after obtaining the adaptive swing amplitude weight, the swing amplitude weight is subtracted from 1 to obtain the adaptive distribution uniformity weight, and the index weight ratio is generated by combining the adaptive swing amplitude weight.

[0102] Specifically, the calculation of the uniformity of the adaptation distribution follows the principle of "the sum of the weights is 1". It is derived from the formula "the uniformity of the adaptation distribution weight = 1 - the weight of the adaptation swing amplitude". This calculation logic ensures that the weight ratio of the two indicators, wind distribution uniformity and optical cable swing amplitude, forms a dynamic balance.

[0103] Among them, when the weight of the adaptation swing amplitude increases due to the increase in the frequency of high wind speed, the weight of the adaptation distribution uniformity decreases accordingly, and vice versa, so that the weight ratio of the indicators can always match the core risk points under different wind speed environments.

[0104] Meanwhile, the range of values ​​for the uniformity of the adaptation distribution corresponds to the weight of the adaptation sway amplitude. Since the weight of the adaptation sway amplitude does not exceed 0.8, the weight of the uniformity of the adaptation distribution is not less than 0.2. This range ensures that the sway amplitude index dominates in areas with frequent high wind speeds, while also ensuring that the wind distribution uniformity index still plays an important role in areas with low wind speeds, so as to avoid a certain type of index being completely ignored.

[0105] For example, if the adaptive swing amplitude weight obtained after correction for a certain optical cable overhead area is 0.45, then the adaptive distribution uniformity weight can be calculated by formula = 1 - 0.45 = 0.55. At this time, the index weight ratio is a combination of swing amplitude weight 0.45 and distribution uniformity weight 0.55, which is suitable for the transition area from occasional to frequent high wind speeds, taking into account both the constraint of swing risk and the consideration of force uniformity.

[0106] In addition, if the adaptive swing amplitude weight of another region is 0.6, then the adaptive distribution uniformity weight = 1 - 0.6 = 0.4. The weight ratio of the indicators reflects that the swing amplitude weight is dominant, and more emphasis is placed on suppressing the swing threat caused by frequent high wind speeds.

[0107] Furthermore, when the weight of the adaptation swing amplitude is 0.8, the weight of the adaptation distribution uniformity is 1-0.8=0.2. The weight of the indicators highlights the core position of the swing amplitude, which is suitable for the evaluation of the scheme under extreme high wind speed environment.

[0108] Finally, the weighting of the indicators generated through the above steps will be applied to the construction of the scheme adaptability evaluation function. This will enable the function to dynamically adjust the weighting of wind force distribution uniformity and optical cable sway amplitude according to the risk characteristics of different wind speed environments, thereby providing an accurate and reasonable quantitative basis for evaluating the wind resistance performance of the hook deployment scheme.

[0109] Furthermore, based on the weighted proportions of the acquired indicators, a scheme fitness evaluation function is constructed according to the uniformity of wind distribution and the amplitude of optical cable sway. The scheme fitness is positively correlated with the uniformity of wind distribution and negatively correlated with the amplitude of optical cable sway.

[0110] Specifically, wind distribution uniformity and optical cable sway amplitude are integrated into a single evaluation index through a weighted calculation method. The scheme fitness evaluation function expression is "Scheme fitness = Fit distribution uniformity weight × Wind distribution uniformity - Fit sway amplitude weight × Optical cable sway amplitude".

[0111] Among them, the value range of wind force distribution uniformity is 0-1, and the closer the value is to 1, the more uniform the wind force distribution is; the value of optical cable swing amplitude needs to be normalized. For example, based on the maximum swing amplitude allowed for this type of optical cable, the actual swing amplitude is converted into a value of 0-1. The closer the value is to 0, the more slight the swing is.

[0112] Ultimately, the scheme adaptability evaluation function reflects the evaluation logic that "the more uniform the wind distribution and the smaller the swing amplitude, the higher the scheme adaptability." Furthermore, through dynamically adjusted weight proportions, the function can accurately adapt to the core requirements of different wind speed environments.

[0113] Specifically, in areas with frequent high wind speeds, the negative impact of the sway amplitude on the adaptability of the scheme is more significant because the adaptation sway amplitude has a higher weight; in areas with low wind speeds, the uniformity of the adaptation distribution has a higher weight, and the positive contribution of the uniformity of wind distribution is more prominent.

[0114] For example, if the uniformity of the adaptation distribution in a certain area is 0.55 and the weight of the adaptation swing amplitude is 0.45, and the wind distribution uniformity of a certain hook deployment scheme is 0.82 and the normalized optical cable swing amplitude is 0.35, then the fitness of the scheme = 0.55 × 0.82 - 0.45 × 0.35 = 0.2935.

[0115] In addition, the wind distribution uniformity of the other scheme is 0.75 and the oscillation amplitude is 0.2. Therefore, the suitability of the scheme is 0.55×0.75-0.45×0.2=0.3225. Obviously, the latter scheme has a higher suitability, indicating that its wind resistance performance is better.

[0116] Furthermore, the type and specifications of the optical cable to be laid are collected as optical cable attribute characteristics. Among these, the collection of optical cable attribute characteristics must cover the core parameters that affect its wind resistance and mechanical response.

[0117] Specifically, optical cable types include metal armored optical cables, non-metal reinforced core optical cables, flame-retardant optical cables, etc. Different types correspond to different structural strengths (such as armored optical cables have stronger wear resistance) and wind resistance characteristics (such as non-metallic optical cables are lighter and more susceptible to strong winds).

[0118] In addition, optical cable specifications cover quantitative parameters such as outer diameter (e.g., 8mm, 12mm), weight per unit length (e.g., 1.2kg / m, 1.8kg / m), tensile strength (e.g., 1500N, 2000N), and elastic modulus (e.g., 80GPa, 100GPa). These parameters directly determine the stress deformation law of optical cables under wind force.

[0119] Specifically, during the process of collecting optical cable attribute characteristics, it is necessary to ensure the accuracy of the collected data by consulting the optical cable manufacturer's technical manual and conducting on-site sampling and testing. For example, for a batch of metal armored optical cables, it is necessary to record that its type is "armored stranded optical cable", and its specifications are outer diameter 11.5mm, unit length weight 1.6kg / m, tensile strength 1800N, and elastic modulus 90GPa, so as to provide accurate physical attribute input for subsequent digital twin simulation.

[0120] Furthermore, digital twin technology is used to simulate and construct an overhead optical cable simulation space based on the acquired optical cable attribute characteristics, regional wind force characteristics, and overhead scene characteristics.

[0121] Specifically, the simulation construction of the optical cable overhead simulation space first requires the establishment of a basic model framework for multi-dimensional data fusion. The physical parameters in the optical cable attribute characteristics (such as the structural strength corresponding to the optical cable type, the outer diameter, weight per unit length, tensile strength, elastic modulus, etc. in the specification parameters) are transformed into the material properties of the digital model. By giving the optical cable overhead simulation space the same mechanical parameters as reality, such as density, elastic modulus, Poisson's ratio, it is ensured that it can reproduce the real stress and deformation characteristics in the simulation.

[0122] Meanwhile, by integrating data such as historical maximum wind speed, wind direction distribution patterns, and high wind speed frequency from the regional wind characteristics, and relying on existing computational fluid dynamics algorithms (such as the Reynolds time-averaged equation), a dynamic wind field model is constructed to simulate the effect of airflow on optical cables under different wind speeds and directions, and to generate wind pressure distribution data along the length of the optical cable, so that the application of wind load is more in line with the actual wind environment.

[0123] In addition, it is necessary to recreate the real optical cable erection environment based on the characteristics of the optical cable overhead scene, construct a 3D model of the power poles at a 1:1 scale, accurately input parameters such as the spacing between power poles, the vertical height difference, and the average erection height, and integrate environmental elements such as terrain undulations and surrounding obstacles to form a spatial scene that is highly consistent with the actual optical cable overhead area.

[0124] In addition, during the model building process, multi-source data verification is required to ensure accuracy. For example, the simulated static sag of the optical cable is compared with the actual measured data on site, and the deviation is controlled within ±3%. The wind pressure value output by the wind field model is calibrated with the wind tunnel test data, and the error does not exceed 5%.

[0125] Ultimately, through the steps described above—converting the optical cable's attribute characteristics into digital model material parameters, constructing a dynamic wind field model based on regional wind characteristics, restoring the real erection environment according to the characteristics of the optical cable overhead scene, and performing multi-source data verification—a simulated space for the optical cable overhead scene was constructed that can accurately reproduce the interaction between "optical cable-wind power-optical cable erection scene," providing a reliable digital twin environment for the simulation test of subsequent hook deployment schemes.

[0126] Furthermore, after the optical cable overhead simulation space is constructed, the optical cable hooks are randomly distributed based on the preset number of optical cable hooks, constrained by the maximum coverage distance of the optical cable hooks, to generate multiple corresponding optical cable hook deployment sequences.

[0127] Specifically, the generation of the optical cable hook deployment sequence needs to be carried out under the dual constraints of "preset number of optical cable hooks" and "maximum coverage distance".

[0128] The preset number of optical cable hooks is calculated based on the total length of the optical cable, the spacing between power poles, and industry standards. For example, no less than 60 optical cable hooks need to be installed for every 50-meter span. The maximum coverage distance is the maximum allowable interval between optical cable hooks, such as the industry standard which stipulates that it should not exceed 1.5 meters, to avoid excessive sag of the optical cable due to insufficient support.

[0129] Meanwhile, a variety of hook distribution schemes are constructed by random generation to cover the wind resistance performance possibilities under different support modes, providing a sufficient sample basis for subsequent iterative optimization.

[0130] Specifically, on the optical cable path between each power pole, starting from the power pole body, the coordinates of the optical cable hook positions are randomly generated within the range of [0, maximum coverage distance], and the spacing between adjacent optical cable hooks must not exceed the maximum coverage distance, until the preset number of optical cable hooks is reached.

[0131] For example, between two power poles spaced 45 meters apart, the preset number of optical cable hooks is 50. 50 locations need to be randomly assigned within the range of 0-45 meters to ensure that the distance between adjacent points is ≤1.5 meters, thus forming a differentiated optical cable hook layout sequence. Each optical cable hook layout sequence corresponds to a set of optical cable hook position coordinate data, which serves as the input for subsequent simulated motion tests.

[0132] Furthermore, within the constructed optical cable overhead simulation space, the optical cable is simulated to move according to the multiple optical cable hook deployment sequences, thereby outputting multiple corresponding predicted wind force distribution uniformity and multiple predicted maximum optical cable swing amplitude.

[0133] Specifically, the optical cable motion simulation test is achieved through dynamic simulation. That is, in the digital twin space, extreme wind loads (such as historical maximum wind speeds) in the regional wind characteristics are applied to the optical cable model corresponding to the sequence of optical cable hooks to simulate the dynamic response process of the optical cable under strong winds, including the optical cable swing trajectory and the force distribution of each segment of the optical cable.

[0134] Meanwhile, during the simulated motion test of the optical cable, it is necessary to collect two key types of data in real time, including the predicted uniformity of wind force distribution and the predicted maximum sway amplitude of the optical cable.

[0135] Specifically, the wind load uniformity is predicted by calculating the uniformity index of wind load on different sections of the optical cable (e.g., every 2 meters is a section) under maximum wind speed conditions. The formula "predicted wind load uniformity = 1 - (maximum wind load difference / average wind load)" can be used to quantify the degree of uniformity of wind load distribution on the optical cable. Furthermore, the average value can be taken from the prediction results of multiple simulations to reduce the error of a single simulation.

[0136] Secondly, the maximum swing amplitude of the optical cable is obtained by tracking the dynamic displacement of characteristic points such as the mid-span and hook connection under the action of maximum wind speed, and recording the maximum swing amplitude within a preset time (such as 10 minutes of strong wind) to reflect the dynamic stability of the optical cable. Similarly, the average value of the prediction results of multiple simulations can be combined to improve the reliability of the data.

[0137] For example, a certain optical cable hook deployment sequence was subjected to three simulated optical cable motion tests under the action of maximum wind speed. The first test yielded a wind load uniformity index of 0.86 and a maximum mid-span swing amplitude of 0.7 meters for 10 sections. The second test yielded 0.88 and 0.68 meters, and the third test yielded 0.85 and 0.72 meters. After taking the average, the prediction results for this sequence were: predicted wind force distribution uniformity (0.86+0.88+0.85) / 3≈0.86 and predicted maximum swing amplitude (0.7+0.68+0.72) / 3≈0.7 meters.

[0138] Finally, by conducting simulated motion tests on all fiber optic cable hook deployment sequences, multiple sets of mean-optimized predictive data can be generated, providing a more accurate basis for evaluating the suitability of the solution.

[0139] Based on this, and using the constructed scheme fitness evaluation function, multiple corresponding scheme fitnesss are obtained by evaluating the obtained multiple predicted wind force distribution uniformity and multiple predicted maximum optical cable swing amplitude.

[0140] Specifically, the fitness assessment of the scheme involves substituting the predicted data of each optical cable hook deployment sequence into the constructed scheme fitness evaluation function, and obtaining the fitness value of a single scheme through weighted calculation.

[0141] Similarly, before calculating the fitness value of the scheme, the predicted maximum swing amplitude of the optical cable needs to be normalized. That is, the actual swing amplitude is converted into a value of 0-1 based on the safe swing threshold of the optical cable type to ensure that it is consistent with the value range of wind distribution uniformity.

[0142] Furthermore, the predicted wind distribution uniformity and the normalized predicted maximum sway amplitude are substituted into the constructed scheme fitness evaluation function to calculate the scheme fitness value of the corresponding hook deployment sequence.

[0143] Specifically, the calculation expression of the scheme fitness evaluation function is "Scheme fitness = Adaptation distribution uniformity weight × Predicted wind force distribution uniformity - Adaptation swing amplitude weight × Predicted maximum swing amplitude (after normalization)". This scheme fitness evaluation function integrates the two types of indicators according to dynamically adjusted weight ratios, and quantifies the wind resistance performance of the optical cable hook deployment scheme.

[0144] Among them, the weight of uniformity of adaptation distribution and the weight of adaptation swing amplitude are the proportion of the index weights configured based on high wind speed frequency in the early stage. The sum of the two is 1 to ensure that the evaluation results are comparable in a unified dimension.

[0145] For example, the predicted wind force distribution uniformity of a certain optical cable hook deployment sequence is 0.86, the normalized predicted maximum swing amplitude is 0.35, the corresponding adaptation distribution uniformity weight is 0.55, and the adaptation swing amplitude weight is 0.45. Then the fitness of the scheme = 0.55×0.86-0.45×0.35=0.3155.

[0146] In addition, the predicted wind distribution uniformity of another optical cable hook deployment sequence is 0.78, and the predicted maximum swing amplitude after normalization is 0.28. Under the same weight configuration, the fitness of the scheme is 0.55×0.78-0.45×0.28=0.303. Obviously, the fitness of the latter scheme is lower than that of the former, indicating that the optical cable hook deployment scheme of the former has better wind resistance performance.

[0147] Similarly, calculate the fitness of the remaining optical cable hook deployment sequences. That is, substitute the predicted wind distribution uniformity and the normalized predicted maximum swing amplitude of each sequence into the fitness evaluation function of "fitness = uniformity of distribution × predicted wind distribution uniformity - uniformity of swing amplitude × predicted maximum swing amplitude (normalized)" to obtain multiple fitness values ​​corresponding to each sequence.

[0148] Based on this, the optical cable hook deployment scheme is optimized by obtaining the fitness of multiple schemes, so as to output the optimal hook deployment scheme.

[0149] The method provided in this application embodiment includes the step of "optimizing the optical cable hook deployment scheme based on the fitness of the multiple schemes and outputting the optimal hook deployment scheme" as follows:

[0150] Based on the fitness of the multiple schemes, the multiple optical cable hook deployment sequences are arranged in descending order of fitness, and the optical cable hook deployment sequence is regarded as the initial solution to obtain the initial solution sequence;

[0151] The first P solutions of the initial solution sequence are designated as excellent solutions, and the last J solutions are designated as inferior solutions. The J inferior solutions are clustered around the excellent solutions to obtain P solution sets. The sum of P and J is the number of initial solutions, and J is N times P, where N is greater than or equal to 20 and less than or equal to 50.

[0152] The solution with the minimum fitness among the P solution sets is designated as the inferior solution, resulting in P inferior solutions. A strategy of seeking better solutions and avoiding worse solutions is then configured based on the P excellent solutions and the P inferior solutions.

[0153] According to the optimization and deoptimization strategy, the optimal hook placement scheme is found based on the P solution sets, and the optimal hook placement scheme is output.

[0154] In this embodiment of the application, in order to accurately select the scheme with the best wind resistance performance from a large number of potential optical cable hook deployment schemes, it is necessary to achieve targeted optimization of the scheme's adaptability through a combination of clustering grouping, strategy configuration and iterative optimization process, so as to ensure that the final output scheme can adapt to the wind environment of the region to the greatest extent.

[0155] Specifically, the fiber optic hook deployment sequence is first sorted and grouped based on the fitness of multiple schemes. That is, by arranging the schemes from largest to smallest fitness and treating the fiber optic hook deployment sequence as the initial solution, an initial solution sequence is obtained.

[0156] Furthermore, the first P optical cable hook deployment sequences with the highest fitness are defined as optimal solutions, and the last J optical cable hook deployment sequences with lower fitness are defined as inferior solutions.

[0157] Here, J is taken as 20-50 times P to ensure that there are enough potential solutions for optimization exploration. For example, when P=5, J can be 100-250, and the total number of initial solutions is 105-255. This avoids limiting the optimization due to too few solutions, while also preventing an excessive number from increasing the computational load.

[0158] Furthermore, the existing K-means clustering algorithm is used to cluster J inferior solutions with the best solution as the center, so that each solution set contains one best solution and several inferior solutions with similar characteristics (such as the distribution density of optical cable hooks and the sequence of support points with similar positions in the middle of the span), forming P independent solution sets, which lays the foundation for targeted optimization of optical cable hook distribution scheme.

[0159] Furthermore, in each solution set, the inferior solution with the lowest fitness is defined as the poor solution, thereby identifying the "performance bottleneck" within that solution set. For example, a solution set may have an optimal solution fitness of 0.85 and contain 20 inferior solutions. Among these, the inferior solution with a fitness of 0.3 is designated as the poor solution, representing the solution in the group that most needs improvement.

[0160] Based on this, a strategy of seeking the best and avoiding the worst is configured based on P excellent solutions and P poor solutions.

[0161] The method provided in this application includes the following steps: "Configuring a strategy to favor the best and avoid the worst based on P excellent solutions and P poor solutions".

[0162] Randomly select a first solution set from the P solution sets, obtain the first optimal solution, the first poor solution, and multiple first inferior solutions in the first solution set, and obtain the fitness of the first optimal solution, the fitness of the first poor solution, and the average fitness of the multiple first inferior solutions.

[0163] The deviation between the fitness of the optimal solution and the fitness of the inferior solution is calculated to obtain the fitness deviation of the optimal solution;

[0164] The deviation of the fitness of the inferior solution and the mean fitness of the inferior solution are calculated to obtain the fitness deviation of the inferior solution;

[0165] If the fitness deviation of the optimal solution is greater than or equal to the fitness deviation of the poor solution, then the optimization strategy is set as the optimization strategy, wherein the optimization strategy is to adjust the inferior solutions in the same solution set according to a predetermined optimization step size, with the optimal solution as the direction.

[0166] If the fitness deviation of the optimal solution is less than the fitness deviation of the poor solution, then the optimization strategy is set as the inferior solution avoidance strategy, wherein the inferior solution avoidance strategy is to adjust the inferior solutions in the same solution set according to a predetermined optimization step size, with the direction of moving away from the inferior solution.

[0167] In this embodiment of the application, in order to achieve precise optimization of the optical cable hook deployment scheme, it is necessary to quantify the difference in the impact of the excellent solution and the poor solution on the inferior solution, and to configure a targeted optimization strategy to ensure that the inferior solution is adjusted towards a better performance direction.

[0168] Specifically, the first solution set is randomly selected from the P solution sets as the sample for strategy configuration. This solution set contains one first optimal solution (the optical cable hook deployment sequence with the highest fitness), one first poor solution (the optical cable hook deployment sequence with the lowest fitness), and multiple first inferior solutions (optical cable hook deployment sequences between the optimal and poor solutions).

[0169] Furthermore, by extracting the fitness of the first optimal solution and the fitness of the first poor solution, and calculating the average fitness of multiple first inferior solutions, basic data is provided for subsequent deviation analysis.

[0170] Furthermore, the deviation between the fitness of the best solution and the average fitness of the worst solution is calculated to obtain the fitness deviation of the best solution. The specific calculation formula can be expressed as "fitness deviation of the best solution = fitness of the best solution - average fitness of the worst solutions". This fitness deviation of the best solution reflects the performance advantage of the best solution relative to the average level of the worst solutions.

[0171] Meanwhile, the deviation between the fitness of the inferior solution and the average fitness of the poor solution is calculated to obtain the fitness deviation of the inferior solution. The specific calculation formula can be expressed as "Fitness deviation of inferior solution = Average fitness of poor solution - Fitness of inferior solution". This fitness deviation of inferior solution reflects the extent of the performance disadvantage of the inferior solution relative to the average level of the poor solution.

[0172] Based on this, optimization strategies are configured differently according to the deviation comparison results. Specifically, if the fitness deviation of the optimal solution is greater than or equal to the fitness deviation of the poor solution, it indicates that moving towards the optimal solution can bring more significant performance improvement, and the optimization strategy is set as the optimization-oriented strategy.

[0173] The core of the optimization strategy is to replicate the key features of the optimal solution and adjust the inferior solutions within the same solution set according to a predetermined optimization step size. For example, if the optimal solution places a fiber optic cable hook every 0.8 meters in the mid-span region, the optimization strategy will gradually adjust the spacing of the fiber optic cable hooks in the mid-span region of the inferior solution from 1.2 meters to about 0.8 meters to approximate the support pattern of the optimal solution.

[0174] Conversely, if the fitness deviation of the optimal solution is less than that of the poor solution, it indicates that avoiding the defects of the poor solution is more critical for performance improvement. In this case, the optimization strategy should be set as the inferior solution avoidance strategy.

[0175] Specifically, the inferior solution avoidance strategy needs to identify typical problems of the inferior solution and adjust the inferior solution in the opposite direction by the same predetermined step size, moving away from the configuration pattern of the inferior solution. For example, if the inferior solution causes excessive swaying of the optical cable due to only one optical cable hook being installed every 1.5 meters on the windward side, the inferior solution avoidance strategy will further reduce the hook spacing on the windward side from 1.3 meters to less than 1.0 meter to avoid the shortcomings of the inferior solution.

[0176] The setting of the predetermined optimization step size needs to take into account both optimization efficiency and accuracy. It is usually determined based on the difference between the minimum adjustment unit of the optical cable hook (such as 0.05 meters) and the solution within the solution set. If the predetermined optimization step size is too large, the optimization will be unstable. If the predetermined optimization step size is too small, the number of iterations will increase. The general range is 0.05-0.2 meters.

[0177] Ultimately, by configuring the above steps to mitigate deviations, we can ensure that the optimization direction of each solution set matches its own performance characteristics. This fully leverages the advantages of superior solutions while effectively avoiding the shortcomings of inferior solutions, laying a scientific foundation for subsequent iterative optimization.

[0178] Furthermore, in accordance with the configured optimization and optimization strategy, the optical cable hook deployment scheme is optimized for each of the P solution sets to output the optimal hook deployment scheme.

[0179] The method provided in this application embodiment includes the step of "optimizing the optical cable hook deployment scheme according to the P solution sets based on the optimization and degradation avoidance strategy, and outputting the optimal hook deployment scheme" as follows:

[0180] Following the optimization and optimization strategy, the inferior solutions in the P solution sets are adjusted according to the predetermined optimization step size to obtain P updated solution sets;

[0181] Identify the P updated solution sets. Within the same updated solution set, if the fitness of the inferior solution is greater than or equal to the fitness of the superior solution, then the inferior solution replaces the superior solution. If the fitness of the inferior solution is less than or equal to the fitness of the poor solution, then the poor solution replaces the poor solution.

[0182] Perform iterative optimization until a preset number of convergences is reached, output P current updated solution sets, and select the optimal solution of the optimal updated solution set as the optimal hook placement scheme, wherein the optimal updated solution set is the solution set with the largest sum of fitness of the schemes in the P current updated solution sets.

[0183] In this embodiment of the application, in order to continuously improve the wind resistance performance of the optical cable hook deployment scheme through continuous optimization and iteration, and finally select the optimal scheme, it is necessary to strictly follow the closed-loop process of "adjustment-replacement-iteration-selection" to ensure that each round of optimization can move towards better performance. At the same time, the reliability and universal applicability of the optimal scheme are ensured by comparing multiple solution sets.

[0184] Specifically, firstly, following the strategy of seeking the best and avoiding the worst, the inferior solutions in the P solution sets are adjusted according to a predetermined optimization step size. The predetermined optimization step size is a fine-tuning unit set based on the actual accuracy requirements of the optical cable hook deployment.

[0185] Furthermore, during the adjustment process, for the solution set that adopts the optimization strategy, based on the distribution characteristics of the optical cable hooks in the optimal solution, the hook positions in the inferior solution that differ significantly from the optimal solution are moved towards the optimal solution by a predetermined optimization step length.

[0186] For example, if the spacing between hooks in the middle region of the optimal solution is 0.8 meters and the spacing in the corresponding region of the inferior solution is 1.2 meters, then the hook positions of the inferior solution will be moved closer to the middle in increments of 0.1 meters, gradually reducing the spacing.

[0187] Furthermore, for the solution set adopting the inferior solution avoidance strategy, with the optical cable hook distribution defects far away from the inferior solution as the target, the unreasonable configurations similar to the inferior solution in the inferior solution are adjusted in reverse. For example, if the optical cable hook density on the windward side of the inferior solution is 0.5 per meter, and the corresponding area of ​​the inferior solution is 0.6 per meter, then the number of hooks is increased in a step of 0.1 meters to increase the density to more than 0.7 per meter.

[0188] Finally, through the adjustments made in the above steps, each inferior solution in the solution set generates a new optical cable hook deployment sequence, forming P updated solution sets.

[0189] Furthermore, the generated P updated solution sets are identified and replaced to achieve dynamic optimization within the solution sets.

[0190] Specifically, within the same updated solution set, the fitness of the adjusted inferior solution is compared with that of the original superior solution and the original inferior solution. If the fitness of an inferior solution is greater than or equal to that of the superior solution, it means that the performance of the inferior solution has surpassed or reached the level of the current superior solution after adjustment. At this time, the inferior solution is used to replace the original superior solution, so that the optimal performance of the solution set is improved.

[0191] Conversely, if the fitness of a suboptimal solution is less than or equal to that of a poor solution, it indicates that the performance of the suboptimal solution has further declined after adjustment and has become a new performance bottleneck. In this case, the suboptimal solution should be used to replace the original poor solution to clarify the direction that needs the most improvement within the solution set.

[0192] For example, if the fitness of the original optimal solution in an updated solution set is 0.85, and the fitness of a suboptimal solution after adjustment reaches 0.88 (0.88 > 0.85), then the suboptimal solution replaces the original optimal solution. Similarly, if the fitness of the original suboptimal solution is 0.3, and the fitness of a suboptimal solution after adjustment drops to 0.28 (0.28 < 0.3), then the suboptimal solution replaces the original suboptimal solution. This dynamic replacement ensures that each solution set always maintains the latest state of optimal and suboptimal solutions.

[0193] Furthermore, repeat the adjustment and replacement process above to iterate and optimize.

[0194] Specifically, in the iterative optimization process, each iteration recalculates the mean fitness and deviation of inferior solutions based on the excellent and inferior solutions of the current solution set, dynamically updates the optimization and avoidance strategies, and adjusts inferior solutions according to the predetermined optimization step size until the preset number of convergences is reached.

[0195] The preset number of convergence iterations is set according to the actual optimization needs, typically ranging from 30 to 100 rounds. For example, if set to 50 rounds, the iteration stops when the number of iterations reaches 50, regardless of whether the performance continues to improve, in order to balance the optimization effect and computational cost. If, during the iteration process, the fitness improvement of the solution is less than 0.001 for several consecutive rounds (e.g., 5 rounds), convergence can be determined in advance to shorten the iteration cycle.

[0196] Finally, after the iterative optimization is completed, P current updated solution sets are output. At the same time, by calculating the sum of the fitness of all solutions in each updated solution set, the updated solution set with the largest sum is selected as the optimal updated solution set.

[0197] Among them, the solution set with the largest sum of fitness is the solution set with the best overall performance. The best solutions within it not only have outstanding performance, but the performance of other solutions within the solution set is also at a high level, and it has stronger stability and reliability.

[0198] Therefore, the optimal solution of the updated solution set is determined as the final optimal hook deployment scheme. This scheme can achieve the best balance between wind distribution uniformity and optical cable sway amplitude, adapt to the regional wind environment to the greatest extent, and provide a strong guarantee for the safe and stable operation of the optical cable.

[0199] S140: Within the overhead optical cable area, optical cable hooks are installed according to the optimal hook layout scheme.

[0200] In this embodiment of the application, in order to transform the optimal hook layout scheme obtained by virtual simulation optimization into an actual executable construction operation, it is necessary to strictly follow the scheme parameters and on-site construction specifications to ensure that the construction quality is consistent with the simulation expectations, and ultimately achieve the optimal wind resistance performance of the optical cable in the actual wind environment.

[0201] Specifically, before construction, it is necessary to complete the parameter analysis and on-site verification of the optimal hook layout scheme, and convert the data such as the location coordinates, distribution density, and spacing settings of the optical cable hooks in the scheme into specific markings on the construction drawings, and mark the hook installation points between each power pole, the key support positions in the middle of the span, and the densification requirements for special sections (such as high wind pressure areas and undulating terrain).

[0202] Simultaneously, construction personnel were organized to analyze the proposed solutions to clarify the core design elements of the optimal hook placement scheme. For example, in an area with high wind speeds occurring 50 times per year, the optimal hook placement scheme involves placing one fiber optic cable hook every 0.8 meters in the mid-span area, reducing the spacing on the windward side to 0.6 meters. The construction personnel needed to be informed of the crucial role of this optimal hook placement scheme in suppressing fiber optic cable swaying to ensure strict adherence to parameter requirements during construction.

[0203] In addition, during construction, the coordinates of the optical cable hook positions in the optimal hook layout scheme are used as a benchmark. Combined with the characteristics of the overhead optical cable scenario, such as the spacing between power poles and the vertical height difference of power poles, tools such as laser rangefinders are used to accurately locate the installation point of each hook in order to avoid a decrease in the optical cable support effect due to positional deviation.

[0204] For special sections required by the optimal hook deployment scheme, such as the fiber optic cable hook densification section in areas with frequent high wind speeds, the installation density needs to be checked additionally. For example, in sections where the optimal hook deployment scheme requires two hooks per meter, the installation density needs to be counted and checked section by section after construction to ensure consistency with the scheme.

[0205] Meanwhile, the construction operation must comply with the industry standards for optical cable laying. The contact parts between the optical cable hook and the optical cable must be equipped with an insulating protective sleeve to avoid wear on the outer layer of the optical cable due to friction. The fixing strength of the hook must meet the preset standard and be verified by tensile test before subsequent construction can proceed.

[0206] Finally, after construction is completed, on-site acceptance and performance verification are required. The deviation between the actual optical cable hook layout position and the optimal hook layout scheme should be compared to ensure that the positional error of all installation points does not exceed ±0.05 meters and the spacing error does not exceed ±0.1 meters.

[0207] Meanwhile, by combining the historical maximum wind speed in the regional wind characteristics, the swaying of the optical cable under natural wind conditions is monitored through drone photography or manual observation. If an abnormal swaying amplitude is found in a certain section (such as exceeding the simulation prediction value by 10%), it is necessary to check whether the hook installation in that area meets the requirements of the plan, and make secondary adjustments if necessary.

[0208] For example, if the sway amplitude at the mid-span of a certain construction section is found to be larger than the predicted value after inspection, it is found that the actual spacing of the optical cable hooks is 0.9 meters, which exceeds the 0.8 meters required by the optimal hook layout scheme. Therefore, it is necessary to add optical cable hooks to correct the spacing of the optical cable hooks until it meets the design standard of the optimal hook layout scheme.

[0209] Ultimately, by strictly adhering to the optimal hook deployment scheme during construction and strengthening process control and acceptance verification, the actual optical cable hook deployment is highly consistent with the virtual simulation optimization results. This ensures that the optical cable can maintain stable operation under different wind conditions, fully leverages the wind resistance advantages of the optimal hook deployment scheme, and reduces the risk of optical cable damage caused by wind.

[0210] The embodiments of this application, through the specific implementation methods described above, achieve the following technical effects:

[0211] This application proposes an auxiliary design optimization method for cable laying. First, based on environmental monitoring logs of the overhead optical cable area, the maximum wind speed within a historical time range is collected as the regional wind force characteristic. At the same time, the average erection height, the spacing between power poles, and other overhead scene characteristics are also collected. Next, wind force distribution uniformity and optical cable sway amplitude are configured as optimization evaluation indicators. The weight ratio of the indicators is dynamically adjusted according to the frequency of high wind speeds to construct a scheme fitness evaluation function. Then, the optical cable type and specifications are collected as optical cable attribute characteristics. Digital twin technology is used to integrate the three types of characteristics to construct an overhead optical cable simulation space. Subsequently, with the maximum coverage distance as a constraint, multiple sets of hook placement sequences are generated. The predicted wind force distribution uniformity and the predicted maximum optical cable sway amplitude are simulated and tested in the overhead optical cable simulation space, and the scheme fitness is calculated. Finally, through clustering iteration and optimization-avoidance strategies, the optimal hook placement scheme is output and used in actual construction.

[0212] The method provided in this application, through the technical solution of "feature acquisition - weight configuration - simulation testing - iterative optimization - construction implementation", solves the problems of uneven wind distribution, excessive sway amplitude, and poor stability caused by the lack of specificity of the scheme and insufficient consideration of dynamic factors in traditional cable laying. It achieves accurate adaptation of the hook layout scheme to the wind speed environment, improves the wind resistance safety and optimization efficiency of cable laying, and provides reliable technical support for cable laying auxiliary design.

[0213] Example 2, as shown in the appendix Figure 2 As shown, based on the inventive concept of the cable laying auxiliary design optimization method provided in Embodiment 1, this application also provides a cable laying auxiliary design optimization system, specifically including:

[0214] The wind force feature acquisition module 01 is used to collect the maximum wind speed within a historical time range as the regional wind force feature based on the environmental monitoring logs of the optical cable overhead area.

[0215] The overhead scene acquisition module 02 is used to collect the average erection height, pole spacing, vertical height difference of power poles, and power pole type during the overhead optical cable process as features of the overhead scene.

[0216] The hook scheme optimization module 03 is used to optimize the optical cable hook deployment scheme based on the scheme fitness evaluation function and the preset number of optical cable hooks, with the maximum coverage distance of the optical cable hooks as a constraint, according to the optical cable attribute characteristics and the wind characteristics and overhead scene characteristics of the area, and output the optimal hook deployment scheme.

[0217] The optimal solution implementation module 04 is used to carry out optical cable hook construction in the optical cable overhead area according to the optimal hook layout scheme.

[0218] In one embodiment, the hook scheme optimization module 03 is also used for:

[0219] Configure optimization evaluation indicators, wherein the optimization evaluation indicators include wind force distribution uniformity and optical cable sway amplitude;

[0220] Based on the weighting of the indicators, a scheme fitness evaluation function is constructed according to the wind distribution uniformity and the optical cable sway amplitude. The scheme fitness is positively correlated with the wind distribution uniformity and negatively correlated with the optical cable sway amplitude.

[0221] Collect the optical cable type and specifications of the optical cable to be laid as optical cable attribute characteristics;

[0222] Using digital twin technology, an aerial simulation space for optical cables is constructed based on the optical cable's attribute characteristics, regional wind characteristics, and aerial scene characteristics.

[0223] With the maximum coverage distance of the optical cable hooks as a constraint, the optical cable hooks are randomly distributed based on the preset number of optical cable hooks to generate multiple optical cable hook deployment sequences.

[0224] Within the simulated space of the overhead optical cable, the optical cable is simulated to move according to the multiple optical cable hooks deployment sequence, and multiple predicted wind force distribution uniformity and multiple predicted maximum optical cable swing amplitude are output.

[0225] Based on the scheme fitness evaluation function, the fitness of multiple schemes is evaluated according to the multiple predicted wind distribution uniformity and the multiple predicted maximum sway amplitude of optical cables.

[0226] Based on the fitness of the multiple schemes, the optical cable hook deployment scheme is optimized, and the optimal hook deployment scheme is output.

[0227] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, the above description focuses on specific embodiments of this specification. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0228] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

[0229] This specification and accompanying drawings are merely illustrative examples of this application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from its scope. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application intends to include such modifications and variations.

Claims

1. A method for auxiliary design optimization of cable laying, characterized in that, The methods include: Based on environmental monitoring logs of the overhead optical cable area, the maximum wind speed within a historical time range is collected as the regional wind force characteristic. The average erection height, pole spacing, vertical height difference of power poles, and power pole type during the overhead fiber optic cable process are collected as features of the overhead scene. Based on the scheme fitness evaluation function and the preset number of optical cable hooks, and with the maximum coverage distance of the optical cable hooks as a constraint, the optical cable hook deployment scheme is optimized according to the optical cable attribute characteristics, regional wind characteristics, and overhead scene characteristics, and the optimal hook deployment scheme is output, including: Configure optimization evaluation indicators, wherein the optimization evaluation indicators include wind force distribution uniformity and optical cable sway amplitude; Based on the weighting of the indicators, a scheme fitness evaluation function is constructed according to the wind distribution uniformity and the optical cable sway amplitude. The scheme fitness is positively correlated with the wind distribution uniformity and negatively correlated with the optical cable sway amplitude. In the optical cable overhead area, the optical cable hooks are installed according to the optimal hook layout scheme. The optimization of the optical cable hook deployment scheme based on the optical cable's attribute characteristics, regional wind characteristics, and overhead scene characteristics includes: Collect the optical cable type and specifications of the optical cable to be laid as optical cable attribute characteristics; Using digital twin technology, an aerial simulation space for optical cables is constructed based on the optical cable's attribute characteristics, regional wind characteristics, and aerial scene characteristics. With the maximum coverage distance of the optical cable hooks as a constraint, the optical cable hooks are randomly distributed based on the preset number of optical cable hooks to generate multiple optical cable hook deployment sequences. Within the simulated space of the overhead optical cable, the optical cable is simulated to move according to the multiple optical cable hooks deployment sequence, and multiple predicted wind force distribution uniformity and multiple predicted maximum optical cable swing amplitude are output. Based on the scheme fitness evaluation function, the fitness of multiple schemes is evaluated according to the multiple predicted wind distribution uniformity and the multiple predicted maximum sway amplitude of optical cables. Based on the fitness of the multiple schemes, the optical cable hook deployment scheme is optimized, and the optimal hook deployment scheme is output.

2. The auxiliary design optimization method for cable laying according to claim 1, characterized in that, The configuration process for the weighting of the indicators includes: Based on the environmental monitoring logs of the overhead optical cable area, the number of times the wind speed exceeded the preset wind speed threshold within the historical time range is counted and set as the high wind speed frequency. The sway amplitude weight adjustment coefficient is obtained based on the high wind speed frequency matching, and the initial sway amplitude weight is corrected to obtain the adaptive sway amplitude weight. The initial sway amplitude weight is 0.5, and the adaptive sway amplitude weight does not exceed 0.

8. The adaptation distribution uniformity weight is obtained by subtracting the adaptation swing amplitude weight from 1, and the index weight ratio is generated by combining the adaptation swing amplitude weight.

3. The auxiliary design optimization method for cable laying according to claim 1, characterized in that, Based on the fitness of the multiple schemes, the optical cable hook deployment scheme is optimized, and the optimal hook deployment scheme is output, including: Based on the fitness of the multiple schemes, the multiple optical cable hook deployment sequences are arranged in descending order of fitness, and the optical cable hook deployment sequence is regarded as the initial solution to obtain the initial solution sequence; The first P solutions of the initial solution sequence are designated as excellent solutions, and the last J solutions are designated as inferior solutions. The J inferior solutions are clustered around the excellent solutions to obtain P solution sets. The sum of P and J is the number of initial solutions, and J is N times P, where N is greater than or equal to 20 and less than or equal to 50. The solution with the minimum fitness among the P solution sets is designated as the inferior solution, resulting in P inferior solutions. A strategy of seeking better solutions and avoiding worse solutions is then configured based on the P excellent solutions and the P inferior solutions. According to the optimization and deoptimization strategy, the optimal hook placement scheme is found based on the P solution sets, and the optimal hook placement scheme is output.

4. The auxiliary design optimization method for cable laying according to claim 3, characterized in that, Based on P excellent solutions and P poor solutions, configure a strategy to favor the best and avoid the worst, including: Randomly select a first solution set from the P solution sets, obtain the first optimal solution, the first poor solution, and multiple first inferior solutions in the first solution set, and obtain the fitness of the first optimal solution, the fitness of the first poor solution, and the average fitness of the multiple first inferior solutions. The deviation between the fitness of the optimal solution and the fitness of the inferior solution is calculated to obtain the fitness deviation of the optimal solution; The deviation of the fitness of the inferior solution and the mean fitness of the inferior solution are calculated to obtain the fitness deviation of the inferior solution; If the fitness deviation of the optimal solution is greater than or equal to the fitness deviation of the poor solution, then the optimization strategy is set as the optimization strategy, wherein the optimization strategy is to adjust the inferior solutions in the same solution set according to a predetermined optimization step size, with the optimal solution as the direction. If the fitness deviation of the optimal solution is less than the fitness deviation of the poor solution, then the optimization strategy is set as the inferior solution avoidance strategy, wherein the inferior solution avoidance strategy is to adjust the inferior solutions in the same solution set according to a predetermined optimization step size, with the direction of moving away from the inferior solution.

5. The auxiliary design optimization method for cable laying according to claim 3, characterized in that, According to the aforementioned optimization and degradation avoidance strategy, the optimal cable hook deployment scheme is searched based on the P solution sets, and the optimal hook deployment scheme is output, including: Following the optimization and optimization strategy, the inferior solutions in the P solution sets are adjusted according to the predetermined optimization step size to obtain P updated solution sets; Identify the P updated solution sets. Within the same updated solution set, if the fitness of the inferior solution is greater than or equal to the fitness of the superior solution, then the inferior solution replaces the superior solution. If the fitness of the inferior solution is less than or equal to the fitness of the poor solution, then the poor solution replaces the poor solution. Perform iterative optimization until a preset number of convergences is reached, output P current updated solution sets, and select the optimal solution of the optimal updated solution set as the optimal hook placement scheme, wherein the optimal updated solution set is the solution set with the largest sum of fitness of the schemes in the P current updated solution sets.

6. A cable laying auxiliary design optimization system, characterized in that, The system is used to execute the auxiliary design optimization method for cable laying as described in any one of claims 1-5, the system comprising: The wind force feature acquisition module is used to collect the maximum wind speed within a historical time range as the regional wind force feature based on the environmental monitoring logs of the optical cable overhead area. The overhead scene acquisition module is used to collect the average erection height, pole spacing, vertical height difference of poles, and pole type during the overhead fiber optic cable process as features of the overhead scene. The hook scheme optimization module is used to optimize the optical cable hook deployment scheme based on the scheme fitness evaluation function and the preset number of optical cable hooks, with the maximum coverage distance of the optical cable hooks as a constraint, according to the optical cable attribute characteristics and the wind characteristics and overhead scene characteristics of the area, and output the optimal hook deployment scheme. The optimal solution implementation module is used to carry out optical cable hook construction according to the optimal hook layout scheme within the overhead optical cable area.

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