A pressure-resistant coaxial cable torque threshold setting method based on big data

Abstract

This invention relates to the field of cable data setting technology and discloses a method for setting the torque threshold of pressure-resistant coaxial cables based on big data. The method includes: acquiring target cable usage information; performing general and specific analyses based on whether the target cable has usage information; and marking the target cable based on the analysis conclusions. This method for setting the torque threshold of pressure-resistant coaxial cables based on big data reduces cable failure risk and improves safety through geographic information coupling, damage tolerance design, and a three-level threshold system. It avoids "one-size-fits-all" scrapping, enables the downgraded reuse of cables with damage levels I-III, saves maintenance costs, achieves intelligent decision-making based on big data and distributed monitoring, and realizes refined management through a three-level progressive approach of unified analysis + partial analysis + location analysis. It also introduces time decay correction and fatigue life prediction, covering the entire process of cables from factory delivery to retirement, achieving full lifecycle management.

Description

Technical Field

[0001] This invention relates to the field of cable data setting technology, specifically to a method for setting the torque threshold of a pressure-resistant coaxial cable based on big data. Background Technology

[0002] Compression-resistant coaxial cables (also known as high-strength coaxial cables, military / industrial grade coaxial cables, or shielded coaxial cables) play a crucial role in communications, military, aerospace, and industrial automation. These cables typically operate in harsh environments and withstand mechanical stresses such as tension, bending, and compression. Torque control is critical when connecting or installing these coaxial cables. The core of this big data-based torque threshold setting method for compression-resistant coaxial cables is to introduce the concept of "big data" into the torque threshold setting process. Through large-scale, multi-dimensional data collection, including the cable's physical properties, torque test data during the connection process, operational data under different environments, and failure mode data, a model capable of predicting the optimal torque threshold or failure probability is established using statistics, machine learning, and optimization algorithms. This aims to address the problems of low accuracy, poor adaptability, lack of data-driven approaches, and dynamic optimization in existing compression-resistant coaxial cable torque threshold setting methods. This proposed big data analysis-based torque threshold setting method for compression-resistant coaxial cables can more accurately and scientifically determine the torque threshold, improving the connection reliability and service life of the cable.

[0003] The existing method for setting torque thresholds for pressure-resistant coaxial cables based on big data cannot adapt to the specific circumstances of the purchasing user, thus failing to conduct appropriate tests and set thresholds accordingly. This can easily lead to increased production and usage costs, reduced adaptability, and when there are no purchasing users, it is impossible to determine suitable usage scenarios based on their test results, which can easily increase the scrap rate and production costs. Therefore, its practicality has certain limitations. Summary of the Invention

[0004] This invention provides a method for setting the torque threshold of a pressure-resistant coaxial cable based on big data, which helps to solve the problems mentioned in the background art.

[0005] This invention provides the following technical solution: a method for setting the torque threshold of a pressure-resistant coaxial cable based on big data, comprising:

[0006] Obtain the target cable usage information;

[0007] If no usage information is available for the target cable, perform a general analysis.

[0008] The target cable is marked based on the general analysis results;

[0009] If usage information exists for the target cable, a dedicated analysis will be performed;

[0010] If the target cable meets the usage information requirements, mark the target cable as qualified and then encapsulate it.

[0011] If the target cable does not meet the usage information requirements, a general analysis is performed.

[0012] As an optional solution to the big data-based method for setting the torque threshold of a pressure-resistant coaxial cable as described in this invention, the method for obtaining target cable usage information specifically includes:

[0013] Obtain the production database, denoted as ;

[0014] Retrieve relevant information about the target cable from the production database;

[0015] Retrieve the corresponding batch information from the production database using the batch ID of the target cable, designate it as the target batch, and denote it as [missing information]. ;

[0016] Retrieve the corresponding buyer information from the production database using the user ID of the target batch, denoted as . ;

[0017] Buyer determination function To determine whether there are target buyers;

[0018] like If so, it is determined that there is a target user who wants to buy.

[0019] Then, it is determined that the target cable has usage information;

[0020] like If so, it is determined that there are no target buyers.

[0021] Therefore, it is determined that the target cable does not have usage information.

[0022] As an optional solution to the big data-based method for setting the torque threshold of pressure-resistant coaxial cables described in this invention, the following is included: Specialized analysis is performed, specifically:

[0023] Identify target users for purchase;

[0024] Obtain the delivery address of the target customer, and denote it as... ;

[0025] Obtain the user address of the target purchasing user, denoted as ;

[0026] Address analysis function Determine whether the user's address and the delivery address are consistent;

[0027] like If so, it is determined that the user's address and the delivery address are inconsistent;

[0028] Therefore, the target cable is determined to be non-compliant with the usage information requirements;

[0029] like If so, it is determined that the user's address and the delivery address are consistent;

[0030] Then obtain the geographical information of the delivery address;

[0031] Define the analysis area;

[0032] Within the analysis region, several location points are defined to form a location set, denoted as [location set]. ;

[0033] Geographic information determination function To determine whether there are differences in geographical information within the analysis area;

[0034] like Then a unified analysis of the target cable is performed;

[0035] If the target cable conforms to the unified standard, then the target cable is deemed to meet the usage information requirements;

[0036] If the target cable does not meet the unified standard, then the target cable is deemed not to meet the usage information requirements.

[0037] like Then, a sectional analysis is performed on the target cable;

[0038] If the target cable conforms to the sub-standard, then the target cable is deemed to meet the usage information requirements.

[0039] If the target cable does not meet the sub-standard, then the target cable is deemed not to meet the usage information requirements.

[0040] As an optional solution to the big data-based method for setting the torque threshold of a pressure-resistant coaxial cable as described in this invention, the method involves: performing a unified analysis of the target cable, specifically:

[0041] Obtain geographic information of the analysis area;

[0042] Obtain the delivery time for the target batch;

[0043] Calculate the overall correction factor;

[0044] Calculate the three-level threshold;

[0045] Test points are evenly marked along the entire length of the target cable to form a set of torque test acquisition points;

[0046] A test scenario matrix is ​​constructed to simulate all the extreme operating conditions that cables may encounter in actual service.

[0047] Perform all scenario tests at each data acquisition point, record the torque measurement values, and obtain the test matrix, denoted as... ;

[0048] Each test value is compared with the limit threshold to generate a binary decision matrix, denoted as . ;

[0049] Through global decision function To determine whether the target cable conforms to a unified standard;

[0050] like If so, the target cable is determined to conform to the unified standard;

[0051] like If so, the target cable is determined to be non-compliant with the unified standard.

[0052] As an optional solution to the big data-based method for setting the torque threshold of a pressure-resistant coaxial cable as described in this invention, the method involves: performing a sectional analysis of the target cable, specifically:

[0053] Discretize all locations within the analysis area where cables may be laid into geographic grid points;

[0054] For each geographic grid point, obtain complete microenvironment parameters;

[0055] right Calculate the comprehensive correction factor for each geographical point;

[0056] right Calculate the three-level threshold for each geographic point;

[0057] right A threshold matrix is ​​constructed from the geographical points to form a threshold distribution;

[0058] The most stringent threshold among all geographic points is selected as the reference standard and set as the reference threshold.

[0059] Strain acquisition points are evenly distributed along the length of the cable to be tested.

[0060] Each geographical point Generate independent test scenarios and build a test scenario set;

[0061] For each cable sampling point, the extreme environmental scenarios corresponding to all geographical points are traversed, and the torque response values ​​are recorded to form a test matrix. ;

[0062] Execute distribution standard determination.

[0063] As an optional solution to the big data-based method for setting the torque threshold of a pressure-resistant coaxial cable as described in this invention, the following is a method for performing distribution standard determination:

[0064] For each cable sampling point, determine whether it exceeds the reference threshold to form an exceedance judgment matrix;

[0065] For any point exceeding the standard Calculate its influence weight ;

[0066] Based on the overall impact level determination function The overall impact level of the cable is classified in order to conduct an assessment of the impact of local exceedances.

[0067] Based on the distribution determination function Determine whether the target cable meets the sub-standards;

[0068] like If so, the target cable is determined to conform to the sub-standard;

[0069] like If so, the target cable is determined to be non-compliant with the sub-standard.

[0070] As an optional solution to the big data-based method for setting the torque threshold of a pressure-resistant coaxial cable as described in this invention, the following is included: General analysis is performed, specifically:

[0071] Calculate the three-level threshold;

[0072] Test points are evenly marked along the entire length of the target cable to form a set of torque test acquisition points;

[0073] A test scenario matrix is ​​constructed to simulate all the extreme operating conditions that cables may encounter in actual service.

[0074] Perform all scenario tests at each data acquisition point, record the torque measurement values, and obtain the test matrix, denoted as... ;

[0075] Each test value is compared with the limit threshold to generate a binary decision matrix, denoted as . ;

[0076] Through global decision function To determine whether the target cable meets general requirements;

[0077] like If so, the target cable is determined to be non-compliant with general requirements;

[0078] Then, perform location analysis;

[0079] like If so, the target cable is determined to meet the general requirements;

[0080] Then, after marking the target cable as qualified, it is packaged.

[0081] As an optional solution to the big data-based method for setting the torque threshold of a pressure-resistant coaxial cable as described in this invention, the following is included: Position analysis is performed, specifically:

[0082] Extract all locations of sampling points where the torque exceeds the limit threshold from the test matrix, forming a set of sampling points exceeding the limit, denoted as . ;

[0083] Collect strain data at various sampling points on the cable to obtain strain distribution curves;

[0084] Analyze strain data to identify hotspots where strain exceeds limits;

[0085] Determine the direction of torsion and identify helical deformation caused by torque overload;

[0086] Plot the strain distribution curve along the cable axis to determine the start point, peak point, and end point of the damage region, denoted as . , as well as ;

[0087] Determine the usage conditions for abnormal areas.

[0088] As an optional solution to the big data-based method for setting the torque threshold of a pressure-resistant coaxial cable as described in this invention, the determination of the usage conditions for abnormal areas specifically includes:

[0089] Damage is assessed based on the extent of local strain exceeding the limit, resulting in a quantitative classification of damage severity, denoted as follows: ;

[0090] Calculate the remaining torsional strength based on the damage level, denoted as . ;

[0091] Based on the remaining torsional strength, determine the torque threshold of the abnormal region, denoted as . ;

[0092] Determine the service conditions for abnormal areas based on the damage level and remaining torsional strength.

[0093] The present invention has the following beneficial effects:

[0094] 1. This big data-based method for setting the torque threshold of pressure-resistant coaxial cables queries the production database, verifies the correlation between batches and users, and determines whether usage information exists. If usage information exists, it enters dedicated analysis (customized threshold); otherwise, it enters general analysis (default threshold). This breaks down data silos between production and usage, provides a unique data source for subsequent analysis, distinguishes between customized and general analysis paths, and balances computational cost and accuracy.

[0095] 2. This big data-based method for setting torque thresholds for pressure-resistant coaxial cables extracts user and address information, verifies the validity of delivery addresses, obtains geographical information, and judges the environmental consistency within the analysis area. For homogeneous environments, a unified analysis (single threshold) is performed; for heterogeneous environments, a partial analysis (multiple thresholds with the strictest threshold) is performed. Based on correction coefficients for temperature, humidity, air pressure, corrosion, and laying method, a three-level threshold system is calculated. Fake orders are excluded through address verification to ensure the validity of the analysis target. The method automatically identifies homogeneous / heterogeneous environments to avoid oversimplification or overcomplication. Six types of environmental correction coefficients are introduced to reduce the deviation between the threshold and the actual working conditions.

[0096] 3. This big data-based method for setting torque thresholds for pressure-resistant coaxial cables, when performing general analysis, measures torque at multiple locations and in multiple scenarios to generate a test matrix. If any point or scenario exceeds the limit, it is deemed unqualified, triggering location analysis. BOTDA / OTDR is used to extract adjacent points to form abnormal areas. Based on the over-limit ratio (100-110%, 110-130%, 130-150%, ≥150%), damage levels I-IV are assessed. Remaining strength and safety factor are calculated, generating mild, moderate, and severe degradation schemes or scrapping decisions. Qualified cables are marked "qualified," and unqualified cables are marked with damage level and degradation conditions before encapsulation. Multi-scenario composite testing (temperature change / pressure / fatigue) is conducted to cover most failure modes as much as possible. Based on the principle of "any over-limit is unqualified," the safety margin is ensured without compromise, improving defect location accuracy. The four-level damage classification + quantitative degradation strategy enables differentiated operation and maintenance. Based on fracture mechanics and Miner's theory, the remaining life is scientifically predicted, and a cable health record is established to achieve full life cycle traceability. Attached Figure Description

[0097] Figure 1 This is a flowchart of the method for setting the torque threshold of a pressure-resistant coaxial cable based on big data according to the present invention. Detailed Implementation

[0098] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0099] Example 1: A method for setting the torque threshold of a pressure-resistant coaxial cable based on big data, see reference [link to documentation]. Figure 1 include:

[0100] Obtain the target cable usage information;

[0101] If no usage information is available for the target cable, perform a general analysis.

[0102] The target cable is marked based on the general analysis results;

[0103] If usage information exists for the target cable, a dedicated analysis will be performed;

[0104] If the target cable meets the usage information requirements, mark the target cable as qualified and then encapsulate it.

[0105] If the target cable does not meet the usage information requirements, a general analysis is performed.

[0106] Specifically, obtaining the target cable usage information includes:

[0107] Obtain the production database, denoted as The production database is a database that stores the batches of cables produced, information on the partners who purchased the cables, and information on the buyers associated with each production batch.

[0108] Retrieve relevant information about the target cable from the production database. The relevant information about the target cable includes the batch ID of the target cable and the user ID of each batch. The user ID of the batch is a unique identifier of the buyer associated with that production batch.

[0109] Retrieve the corresponding batch information from the production database using the batch ID of the target cable, designate it as the target batch, and denote it as [missing information]. : ;

[0110] in, This is a batch extraction function used to retrieve batch information corresponding to the target cable from the production database. Indicates the target cable;

[0111] Retrieve the corresponding buyer information from the production database using the user ID of the target batch, denoted as . : ;

[0112] in, This is a function for extracting buyer information, used to retrieve buyer information corresponding to the target batch from the production database. The buyer information includes the buyer's company name, delivery address, and user address, etc. The user address includes all addresses that can be retrieved on the public platform, such as company address and factory address.

[0113] Buyer determination function Determine if there are target buyers: ;

[0114] in, This indicates an empty set, meaning that there is no corresponding buyer information for the target batch;

[0115] like If so, it is determined that there is a target user who wants to buy.

[0116] Then, it is determined that the target cable has usage information;

[0117] like If so, it is determined that there are no target buyers.

[0118] Therefore, it is determined that the target cable does not have usage information.

[0119] By employing the above methods, including geographic information coupling, damage tolerance design, and a three-tier threshold system, the risk of cable failure is reduced, safety is improved, and "one-size-fits-all" scrapping is avoided. This enables the downgraded reuse of cables with damage levels I-III, saving operation and maintenance costs. Based on big data and distributed monitoring, a leap from experience-based thresholds to data-driven dynamic thresholds is achieved, enabling intelligent decision-making. A three-tiered approach of unified analysis, sectional analysis, and location analysis is implemented to achieve refined management. Time decay correction and fatigue life prediction are introduced to cover the entire process of cables from factory delivery to retirement, achieving full lifecycle management.

[0120] Example 2 is an improvement on Example 1. This method for setting the torque threshold of a pressure-resistant coaxial cable based on big data undergoes specialized analysis, specifically as follows:

[0121] Identify target users for purchase;

[0122] Obtain the delivery address of the target customer, and denote it as... : ;

[0123] in, This is a data query function used to extract the delivery address, geographic coordinates, or text address of a target cable batch from a production database or order management system.

[0124] Obtain the user address of the target purchasing user, denoted as : ;

[0125] in, This is a retrieval function, an API call interface used to retrieve user addresses from third-party platforms. This represents the total number of platforms for which the search address is located, such as business registration, corporate websites, map services, bidding platforms, etc. For the first Platform identifier;

[0126] Address analysis function The system determines whether the user's address and delivery address match. If the target user's address includes the target user's delivery address (i.e., they match), it indicates the user may not immediately install and use the product after receiving it. In this case, a threshold can be set using a general standard. If the target user's address does not include the target user's delivery address (i.e., they do not match), it indicates the user may immediately install and use the product after receiving it. In this case, the threshold can be adjusted by analyzing the temperature and environmental conditions within the delivery address area.

[0127] ;

[0128] in, This indicates that the target purchaser's address contains the target purchaser's delivery address.

[0129] like If so, it is determined that the user's address and the delivery address are inconsistent;

[0130] Therefore, the target cable is determined to be non-compliant with the usage information requirements;

[0131] like If so, it is determined that the user's address and the delivery address are consistent;

[0132] Then, obtain the geographical information of the delivery address, which includes information on factors that affect the cable, such as temperature. ;

[0133] in, The actual ambient temperature (°C) at the delivery address, usually taken as a historical extreme value or annual average. The relative humidity (%RH) is a parameter that affects the degradation of the mechanical properties of cable insulation materials after they absorb moisture. Atmospheric pressure (kPa). Altitude (m) is used to calculate barometric pressure correction and ultraviolet radiation intensity. Corrosion levels include Slight corrosion, medium corrosion and Severe corrosion, determined according to ISO 12944 or local contamination profiles. Other parameters include soil thermal resistivity (for direct burial) and vibration spectrum (for industrial areas).

[0134] Define the analysis area, which is the administrative region of the city where the delivery address is located;

[0135] Within the analysis region, several location points are defined to form a location set, denoted as [location set]. : ;

[0136] in, This includes all locations within the area, including delivery addresses;

[0137] Geographic information determination function To determine whether there are discrepancies in the geographical information within the analysis area: ;

[0138] like If the geographic information of all locations within the analysis area is consistent, then a unified analysis of the target cable can be performed.

[0139] If the target cable conforms to the unified standard, then the target cable is deemed to meet the usage information requirements;

[0140] If the target cable does not meet the unified standard, then the target cable is deemed not to meet the usage information requirements.

[0141] like If so, it indicates that there are some locations within the analysis area where the geographical information differs from that of other locations, and a sectional analysis of the target cable should be performed.

[0142] If the target cable conforms to the sub-standard, then the target cable is deemed to meet the usage information requirements.

[0143] If the target cable does not meet the sub-standard, then the target cable is deemed not to meet the usage information requirements.

[0144] Specifically, a unified analysis of the target cable is performed as follows:

[0145] Obtain geographic information for the analysis area, including the region's average annual temperature. Regional average relative humidity Regional atmospheric pressure wait;

[0146] Get the delivery time for the target batch, i.e., the default delivery time is the usage time: ;

[0147] in, For: the delivery timestamp of the target batch recorded in the production database, which serves as the start time of cable service and is used to calculate material aging degradation;

[0148] Calculate the comprehensive correction coefficient, which is to prevent over-correction in extreme environments from causing the threshold to be too low, and set a lower limit protection (not less than 0.6): ;

[0149] in, , This is the temperature correction factor, calculated based on the temperature resistance rating of the cable insulation material. It determines the correction factor between the actual ambient temperature and the reference temperature (25℃). Higher temperatures increase the activity of the material's molecular chains, leading to decreased mechanical strength, thus requiring a lower threshold. The specific formula is as follows: ;

[0150] in, The long-term allowable operating temperature of cable insulation material. The industry-standard benchmark ambient temperature is the reference starting point for all threshold calculations.

[0151] In the formula for comprehensive correction coefficient, This is a humidity correction factor. When the ambient humidity exceeds the baseline value (60% RH), moisture will seep into the insulation layer, reducing its stiffness and compressive strength. For every 10% RH exceeding the threshold, the threshold decreases by approximately 2%. The specific formula is as follows: ;

[0152] in, The humidity effect coefficient represents the strength reduction rate caused by each 1% RH exceeding the limit. This is the baseline relative humidity; humidity correction is only calculated when the relative humidity exceeds this value. ;

[0153] In the formula for comprehensive correction coefficient, This is an altitude / air pressure correction factor. Low air pressure in high-altitude areas reduces heat dissipation, and the thin air accelerates the oxidation of the sheathing material. The correction factor adjusts linearly with the degree of air pressure deviation from standard atmospheric pressure. The specific formula is: ;

[0154] in, This is a pressure correction factor, representing the percentage change in intensity for every 1% deviation in air pressure. 0.15 and 10.325 are standard atmospheric pressures, i.e., sea level reference values;

[0155] In the formula for comprehensive correction coefficient, This is a corrosion correction factor, calculated based on the regional corrosion level. Slight corrosion, medium corrosion and Severe corrosion directly assigns a preset degradation coefficient. The corrosive environment weakens the strength of the metal sheath. The specific formula is as follows: ;

[0156] in, The corrosive environment level is a three-tiered standard based on the concentration of pollutants in the air (SO2, salt spray, etc.), including... Mild corrosion (such as in clean inland areas). Medium corrosion (such as in coastal industrial areas) and Severe corrosion (such as in chemical plants and docks);

[0157] Calculate a three-level threshold, which includes an operational threshold. Warning threshold and limit threshold : ;

[0158] in, This refers to the standard test torque corresponding to the target cable model. Specifically, based on the cable model and specifications, the reference torque value under standard operating conditions is retrieved from the company's standard library or IEC standards. 0.5, 0.75, and 0.9 are three levels of safety margin factors, which are empirical values ​​derived from engineering experience. This is a time decay correction factor; when the usage time exceeds one year, i.e. Its formula is ;

[0159] in, When the usage time is less than one year, that is , ;

[0160] Strain sensors or marked test points are evenly distributed along the entire length of the target cable to form a set of torque test acquisition points: ;

[0161] in, The test points are located along the entire length of the target cable. , This is the total length of the cable. , This is a maximum value function used to return the larger of the two values. Here, at least five data collection points are required. The rounding up sign represents the smallest integer not less than the value within the parentheses;

[0162] A test scenario matrix is ​​constructed to simulate all the extreme operating conditions that cables may encounter in actual service, including temperature cycling, mechanical stress, and fatigue aging. ;

[0163] The test scenarios included static torsion at room temperature. Low temperature ( -20℃) Twist ,high temperature( +15℃) Torsion Composite torsion with axial pressure (50N) And fatigue cycle torsion (100 times). ;

[0164] Perform all scenario tests at each data acquisition point, record the torque measurement values, and obtain the test matrix, denoted as... :

[0165] ;

[0166] in, This represents the test data cell stored in a two-dimensional array, the first... Line number List, For the first The collection point is at the [number]th [location]. The measured torque values ​​under each test scenario. This is a torque measurement function that takes the cable object, its location, and the scene as input and outputs the measured torque. This means for all From 1 to ,all From 1 to That is, to traverse the entire test matrix;

[0167] Each test value is compared with the limit threshold to generate a binary decision matrix, denoted as . : ;

[0168] Through global decision function Determine whether the target cable conforms to a unified standard: ;

[0169] in, This indicates that there is at least one pair. Make If a test is established, it means that if any one of the data collection points in the test matrix exceeds the threshold in any test scenario, the entire test is deemed unqualified.

[0170] like If so, the target cable is determined to conform to the unified standard;

[0171] like If so, the target cable is determined to be non-compliant with the unified standard.

[0172] This embodiment also provides a sectional analysis of the target cable, specifically:

[0173] All possible locations where cables may be laid within the analysis area, such as streets, industrial parks, and factory areas, are discretized into geographic grid points, with each point representing a typical laying environment:

[0174] ;

[0175] in, This is a geographic grid sampling function used to discretize continuous administrative regions into equidistant grid points. This indicates the grid resolution, meaning each grid cell has an area of ​​1 square kilometer, ensuring the accuracy of microenvironment analysis. , Indicates the first The latitude of each grid point Indicates the first Longitude of each grid point This indicates the altitude of the point. This indicates the land use type (such as industrial land, green belt, road), which affects the laying method. That is, at least three sampling points. This is used to ensure that the minimum number of sampling points is 3, to avoid analysis distortion when the area is too small, and to calculate the number of grid points required to calculate the area of ​​the region.

[0176] For each geographic grid point, query meteorological, geological, and corrosion databases to obtain complete microenvironment parameters: ;

[0177] in, This is a geographic information query function used to call meteorological / geological APIs to retrieve environmental parameters for specified coordinates. The cable laying method for this grid point, such as direct burial, conduit, overhead, or cable trench, is determined by urban planning data or on-site surveys and serves as the basis for selecting correction factors to influence [the grid points]. coefficient, For the first The actual ambient temperature at each grid point reflects differences in local heat island effects, water body regulation, and other factors. For the first The relative humidity at each grid point affects the moisture absorption expansion and strength degradation of the insulation material. For the first The atmospheric pressure at each grid point decreases with altitude, and this parameter affects heat dissipation efficiency. For the first The absolute elevation of each grid point directly affects air pressure, ultraviolet radiation intensity, and temperature gradient. For the first The environmental corrosion level (G1, G2, G3) of each grid point is determined by the concentration of polluting gases and salt spray. For the first The thermal resistance characteristics of the underground soil at each grid point affect the heat dissipation of the cable during direct burial.

[0178] right Calculate the overall correction factor for each geographic point: ;

[0179] in, This is a correction factor for the laying method. Different laying methods result in different levels of cable heat dissipation and mechanical protection. Direct burial has poor heat dissipation and requires derating, with a corresponding factor of 0.95. Overhead laying has good heat dissipation and can slightly increase the capacity, with a corresponding factor of 1.05. Conduit laying is the standard case, with a corresponding factor of 1.00. The specific formula is as follows: ;

[0180] right Calculate the three-level threshold for each geographic point: ;

[0181] right A threshold matrix is ​​constructed from the geographic points to form a threshold distribution: ;

[0182] The most stringent threshold among all geographic points is selected as the reference standard, defined as the reference threshold, and denoted as . This achieves "barrel effect" protection to ensure the safety of the entire area being laid: ;

[0183] Right now, ;

[0184] in, This is a function to find the minimum value, used in... Select the minimum value of the corresponding threshold from each grid point. , as well as For the first The three-level thresholds are calculated from each grid point. The reference limit threshold is the most stringent (lowest) limit threshold among all grid points, used to unify acceptance standards;

[0185] Strain sampling points are evenly distributed along the length of the cable under test, with a density sufficient to capture local defects, focusing on connectors and stress concentration areas. ;

[0186] in, That is, at least one point every 0.5 meters and at least eight points;

[0187] Each geographical point Generate independent test scenarios and build a test scenario collection: ;

[0188] The test scenarios included static torsion at room temperature. Low temperature ( -20℃) Twist ,high temperature( +15℃) Torsion Composite torsion with axial pressure (50N) And fatigue cycle torsion (100 times). ;

[0189] For each cable sampling point, the extreme environmental scenarios corresponding to all geographical points are traversed, and the torque response values ​​are recorded to form a test matrix. The test needs to cover combined stresses such as temperature, pressure, and vibration.

[0190] ;

[0191] in, For test data index, indicating the first... The cable collection point is at the [number]th [location]. Torque values ​​under different geographic-scene combinations;

[0192] Execute distribution standard determination.

[0193] Specifically, the distribution standard determination is as follows:

[0194] For each cable sampling point, determine whether it exceeds the reference threshold, and form an exceedance judgment matrix: ;

[0195] in, It is a binary decision variable, with a value of 1 (exceeding the reference threshold) or 0 (not exceeding the reference threshold). This indicates an indicator function that outputs 1 when the condition inside the parentheses is true, and 0 otherwise. The mathematical expression of;

[0196] For any point exceeding the standard Calculate its influence weight :

[0197] ;

[0198] in, The formula for the torque over-limit range is: , Indicates the point exceeding the standard. Distance to the nearest non-exceeding point The attenuation characteristic length is an empirical constant used to control the attenuation rate. , It is a natural exponential function used to simulate the spatial decay of the effect of defects; the effect decreases the further away from the defect point.

[0199] Based on the overall impact level determination function The overall impact level of the cable is classified to conduct a local over-limit impact assessment. When the torque at a certain sampling point exceeds the reference threshold, the defect is determined to be a local disturbance or a systemic risk by comprehensively evaluating the response gradient of neighboring points, the magnitude of the over-limit, and the location weight.

[0200] ;

[0201] in, This represents the weight of the largest influence among all data collection points, reflecting the intensity of the most severe defect. This represents the sum of the influence weights of all data collection points, reflecting the global impact range of the defect. This indicates negligible damage, meaning the damage affects less than 5% of the cable length and the stress concentration factor is less than 1.1. In this case, no special treatment is needed; normal inspection is sufficient. This indicates a minor impact, meaning an influence range of 5-15%, a stress coefficient of 1.1-1.3, and a VSWR change of <0.02. In this case, the monitoring frequency for this segment should be increased, such as shortening it to 3 months. Significant impacts are indicated by an impact range >15% or a stress coefficient >1.3, with a VSWR change of 0.02~0.05. In such cases, the capacity should be immediately reduced by 40%, or the testing cycle should be shortened to one month. This indicates a fatal condition, meaning the stress coefficient is greater than 1.7 or VSWR is greater than 0.05, indicating a decrease in insulation resistance. In this case, the device should be stopped immediately and the replacement process should be initiated.

[0202] Based on the distribution determination function Determine whether the target cable meets the sub-standards: ;

[0203] in, This indicates that all conditions must be met simultaneously.

[0204] like If all collection points are within acceptable limits, or if the impact of exceeding the limits is "negligible" or "minor", then the target cable is deemed to meet the sectional standard, meaning the target cable can be used in the analysis area by zone, and a "Zoned Usage Map" is generated, marking the applicable threshold corresponding to each sub-region gk.

[0205] like If the target cable does not meet the sectional standard, it means that the target cable cannot be used in the analysis area. In this case, the coordinate set of the out-of-standard points and the impact level assessment report will be output.

[0206] Example 3 is an improvement on Example 2. In this example, a general analysis is performed, specifically:

[0207] Calculate a three-level threshold, which includes an operational threshold. Warning threshold and limit threshold : ;

[0208] in, The standard test torque corresponding to the cable model of the target cable is obtained by looking up the reference torque value of the model under standard operating conditions from the enterprise standard library or IEC standard based on the cable model and specifications.

[0209] Strain sensors or marked test points are evenly distributed along the entire length of the target cable to form a set of torque test acquisition points: ;

[0210] in, The test points are located along the entire length of the target cable. , This refers to the total length of the cable.

[0211] A test scenario matrix is ​​constructed to simulate all the extreme operating conditions that cables may encounter in actual service, including temperature cycling, mechanical stress, and fatigue aging. ;

[0212] The test scenarios included static torsion at room temperature. Low temperature ( -20℃) Twist ,high temperature( +15℃) Torsion Composite torsion with axial pressure (50N) And fatigue cycle torsion (100 times). ;

[0213] Perform all scenario tests at each data acquisition point, record the torque measurement values, and obtain the test matrix, denoted as... :

[0214] ;

[0215] Each test value is compared with the limit threshold to generate a binary decision matrix, denoted as . : ;

[0216] Through global decision function Determine whether the target cable meets the general requirements: ;

[0217] in, This indicates that at least one cell in the test matrix exceeds the limit;

[0218] like If so, the target cable is determined to be non-compliant with general requirements;

[0219] Then, perform location analysis;

[0220] like If so, the target cable is determined to meet the general requirements;

[0221] Then, after marking the target cable as qualified, it is packaged.

[0222] Specifically, location analysis is performed as follows:

[0223] Extract all locations of sampling points where the torque exceeds the limit threshold from the test matrix, forming a set of sampling points exceeding the limit, denoted as . : ;

[0224] in, This indicates that at least one test scenario exists. (between 1 and m), such that the first... The torque at each sampling point exceeds the limit threshold, which is used to determine whether the limit is exceeded point by point;

[0225] Strain data at various points along the cable are collected using distributed fiber optic sensors to obtain strain distribution curves. ;

[0226] in, This is a strain data matrix used to record the strain value at each acquisition point. This is a sensor data acquisition function used to call the distributed fiber optic sensing system and return the strain / temperature / vibration measurements from all acquisition points to digitize the physical signals and provide raw data for subsequent analysis.

[0227] Analyze strain data to identify hotspots where strain exceeds limits, i.e., areas of concentrated local strain: ;

[0228] in, For collection points strain value, This is the strain threshold used to identify hotspots;

[0229] Using a helical multi-core fiber optic sensor, the direction of torsion is determined, and helical deformation caused by torque overload is identified. ;

[0230] in, This is a sign function used to determine the direction of twist. and Indicates hotspot locations where strain exceeds limits Adjacent collection points, This is a function to determine the direction of torsion. It compares the signs of the strain gradients at adjacent points to determine clockwise or counterclockwise torsion. It outputs 1 for positive torsion, -1 for negative torsion, and 0 for no torsion.

[0231] Plot the strain distribution curve along the cable axis to determine the start point, peak point, and end point of the damage region, denoted as . , as well as :

[0232] ;

[0233] ;

[0234] ;

[0235] BOTDA / OTDR ;

[0236] ;

[0237] in, This indicates that the minimum position coordinate is taken from the set of hotspots to determine the leftmost boundary of the damaged region. This is a function for determining the position of the maximum value, used to return the value that makes the maximum value possible. The largest value, This is a strain function that returns strain values ​​when the input position is given. Used to locate the peak point of the most severe damage, in order to quantify the degree of damage. This indicates that the maximum position coordinate is taken from the hotspot set to determine the rightmost boundary of the damaged area. Commonly calibrated damage length, BOTDA / OTDR This indicates a distributed fiber optic sensing and measurement interface, used to input the location of the acquisition point and return high-precision strain / loss data for that point. BOTDA (Brillouin Optical Time Domain Analysis) is used for strain measurement, and OTDR (Optical Time Domain Reflectometer) is used for breakpoint / loss location. This means performing an interval extraction operation on each out-of-limit point, merging the damage intervals corresponding to all out-of-limit acquisition points to form a complete set of abnormal regions, avoiding omission of multiple damage points, and generating continuous or discrete abnormal regions covering all defects.

[0238] Determine the usage conditions for abnormal areas.

[0239] The specific conditions for determining the use of abnormal areas are as follows:

[0240] Damage is assessed based on the extent of local strain exceeding the limit, resulting in a quantitative classification of damage severity, denoted as follows: : ;

[0241] in, The torque over-limit ratio is defined as follows: [100%, 110%) represents the elastic deformation range, where the material can recover when the torque over-limit ratio is in this range; [110%, 130%) represents the initial plastic deformation, where permanent damage occurs when the torque over-limit ratio is in this range; [130%, 150%) represents the risk of structural tearing, approaching failure; and [150%, +∞) represents the destruction of structural integrity, resulting in immediate failure.

[0242] Calculate the remaining torsional strength based on the damage level, denoted as . : ;

[0243] in, The torque threshold when it is undamaged is, i.e. , The damage coefficient is determined by the damage level: 0.15 for Level I, 0.30 for Level II, 0.50 for Level III, and 1.0 for Level IV, representing the proportion of strength loss. ;

[0244] Based on the remaining torsional strength, determine the torque threshold of the abnormal region, denoted as . : ;

[0245] in, This is the downgraded safety factor, which is more conservative than the original safety factor of 1.2, and is usually taken as 1.5-2.0. It is used to provide an additional safety margin for damaged cables and prevent secondary failures.

[0246] Determine the service conditions for the abnormal area based on the damage level and remaining torsional strength: .

[0247] This embodiment reduces the risk of cable failure and improves safety by using geographic information coupling, damage tolerance design, and a three-level threshold system. It avoids "one-size-fits-all" scrapping, enables the downgraded reuse of cables with damage levels I-III, saves operation and maintenance costs, and achieves a leap from experience-based thresholds to data-driven dynamic thresholds based on big data and distributed monitoring. It realizes intelligent decision-making, and achieves refined management through a three-level progressive approach of unified analysis, partial analysis, and location analysis. It introduces time decay correction and fatigue life prediction, covering the entire process of cables from factory delivery to retirement, and realizes full life cycle management.

Claims

1. A method for setting a torque threshold for a crush resistant coaxial cable based on big data, the method comprising: include: ​ Obtain the target cable usage information; If no usage information is available for the target cable, perform a general analysis. The target cable is marked based on the general analysis results; If usage information exists for the target cable, a dedicated analysis will be performed; If the target cable meets the usage information requirements, mark the target cable as qualified and then encapsulate it. If the target cable does not meet the usage information requirements, a general analysis is performed; A specialized analysis will be conducted, specifically: Identify target users for purchase; Obtaining the delivery address of the target purchasing user, denoted as ; Obtaining the user address of the target purchase user, denoted as ; By the address analysis function whether the user address and the delivery address are consistent; If then it is determined that the user address does not match the delivery address; Therefore, the target cable is determined to be non-compliant with the usage information requirements; If then it is determined that the user address and the delivery address are consistent; Then obtain the geographical information of the delivery address; Define the analysis area; A number of position points are set in the analysis region to form a position set, denoted as ; Determining function by geographic information whether there is a difference in geographic information within the analysis region; If a uniform analysis is performed on the target cable; If the target cable conforms to the unified standard, then the target cable is deemed to meet the usage information requirements; If the target cable does not meet the unified standard, then the target cable is deemed not to meet the usage information requirements. If then the target cable is analyzed in sections; If the target cable conforms to the sub-standard, then the target cable is deemed to meet the usage information requirements. If the target cable does not meet the sub-standard, then the target cable is deemed not to meet the usage information requirements. A unified analysis of the target cable is performed, specifically as follows: Obtain geographic information of the analysis area; Obtain the delivery time for the target batch; Calculate the overall correction factor: ； wherein , is a temperature correction factor, with the specific formula being: ； wherein, is the long-term permissible operating temperature for cable insulation material, is the reference ambient temperature for industry standards; The comprehensive correction coefficient formula is: is a humidity correction coefficient, and a specific formula is: ； wherein is the humidity influence coefficient, is the reference relative humidity; In the formula for comprehensive correction coefficient, The altitude / barometric pressure correction factor is calculated using the following formula: ； wherein Pc is the pressure correction factor, and 10.325 is the standard atmospheric pressure. The comprehensive correction coefficient formula is is a corrosion correction coefficient, and a specific formula is: ； wherein, is a corrosion environment rating, including light corrosion, medium corrosion, and heavy corrosion; computing a three-level threshold comprising an operational threshold , a pre-warning threshold , and a limit threshold : ； in, The standard test torque corresponding to the cable model of the target cable. This is a time decay correction factor; when the usage time exceeds one year, the formula is as follows: , When the usage time is less than one year, ; Test points are evenly marked along the entire length of the target cable to form a set of torque test acquisition points; A test scenario matrix is ​​constructed to simulate all the extreme operating conditions that cables may encounter in actual service. All the scene tests are performed for each acquisition point, the torque measurements are recorded, and a test matrix is obtained, noted ; Each test value is compared to the limit threshold to generate a binary decision matrix, denoted as ; If any test value exceeds the corresponding limit threshold, the target cable is deemed not to meet the unified standard. When all test values ​​do not exceed the corresponding limit threshold, the target cable is deemed to meet the unified standard; The target cable is analyzed in sections, specifically as follows: Discretize all locations within the analysis area where cables may be laid into geographic grid points; For each geographic grid point, obtain complete microenvironment parameters; right Calculate the comprehensive correction factor for each geographical point; right Calculate the three-level threshold for each geographic point; right A threshold matrix is ​​constructed from the geographical points to form a threshold distribution; The most stringent threshold among all geographic points is selected as the reference standard and set as the reference threshold. Strain acquisition points are evenly distributed along the length of the cable to be tested. Each geographical point Generate independent test scenarios and build a test scenario set; For each cable collection point, traverse all the corresponding extreme environmental scenarios of the geographical points, record the torque response value, and form a test matrix ; Execution distribution standard determination; A general analysis is performed, specifically as follows: Calculate the three-level threshold; Test points are evenly marked along the entire length of the target cable to form a set of torque test acquisition points; A test scenario matrix is ​​constructed to simulate all the extreme operating conditions that cables may encounter in actual service. All the scene tests are performed for each acquisition point, the torque measurements are recorded, and a test matrix is obtained, noted ; Each test value is compared to the limit threshold to generate a binary decision matrix, denoted as ; If any test value exceeds the corresponding limit threshold, the target cable is deemed not to meet the general requirements. Then, perform location analysis; When all test values ​​do not exceed the corresponding limit threshold, the target cable is deemed to meet the general requirements; Then, after marking the target cable as qualified, it is packaged.

2. The method for setting the torque threshold of a pressure-resistant coaxial cable based on big data according to claim 1, characterized in that: Obtain the target cable usage information, specifically: acquiring a production database, denoted as ; Retrieve relevant information about the target cable from the production database; Obtain the corresponding batch information from the production database through the batch ID of the target cable, and define it as the target batch, denoted as ; Obtain the corresponding buyer information from the production database through the user ID of the target batch, denoted as ; By a buyer determination function determines whether a target buyer exists; If then it is determined that a target buying user exists; Then, it is determined that the target cable has usage information; If then it is determined that there is no target purchase user; Therefore, it is determined that the target cable does not have usage information.

3. The big data based crush resistance coaxial cable torque threshold setting method of claim 1, wherein: The distribution criteria are determined as follows: For each cable sampling point, determine whether it exceeds the reference threshold to form an exceedance judgment matrix; For any out-of-gage point , calculate its influence weight ; by the overall impact level determination function , the overall impact level of the cable is divided to evaluate the local over-standard impact Based on whether each cable collection point exceeds the reference threshold and its influence weight, it is determined whether the target cable meets the sub-standard. When the sub-standards are met, the target cable is deemed to conform to the sub-standards. If the sub-standard is not met, the target cable is deemed not to meet the sub-standard.

4. The big data based crush resistance coaxial cable torque threshold setting method of claim 1, wherein: The location analysis is performed as follows: Extract all locations of sampling points where the torque exceeds the limit threshold from the test matrix, forming a set of sampling points exceeding the limit, denoted as . ; Collect strain data at various sampling points on the cable to obtain strain distribution curves; Analyze strain data to identify hotspots where strain exceeds limits; Determine the direction of torsion and identify helical deformation caused by torque overload; Draw the strain distribution curve along the cable axial direction to determine the start point, peak point and end point of the damage area, respectively denoted as , and ; Determine the usage conditions for abnormal areas.

5. The big data based crush resistance coaxial cable torque threshold setting method of claim 1, wherein: The conditions for using the abnormal region are determined as follows: According to the local strain exceeding amplitude, the damage rating is evaluated, the damage degree quantization grading is formed, and is recorded as ; According to the damage level, the residual torsional strength is calculated, denoted as ; Based on the remaining torsional strength, determine the torque threshold of the abnormal region, denoted as . ; Determine the service conditions for abnormal areas based on the damage level and remaining torsional strength.

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