A method and system for measuring the tension of an overhead catenary elastic sling

Abstract

This application relates to the field of catenary elastic sling monitoring, and provides a method and system for measuring the tension of catenary elastic slings to solve the problems of insufficient accuracy of tension measurement and weak analysis ability. This application includes: based on the wind load and humidity of the catenary elastic sling, correlating the creep rate of the sling material at different temperatures with the weight coefficient of tension attenuation, and constructing a mapping database; using a radar array to monitor the parabolic deformation of the elastic sling under the sliding impact of the pantograph, combining with the yield strength temperature attenuation curve corresponding to the sling material, correcting the parameters of the parabolic equation, and inversely generating tension distribution data; analyzing the vibration frequency components in the phase difference signal, correlating the tension data with the historical creep rate in the same temperature range of the database, and establishing a cross-domain coupling relationship; using a convolutional neural network to fuse the weight coefficient of the creep rate and the vibration distortion characteristics to obtain a predicted value of tension attenuation. The technical solution provided by this application improves the accuracy of tension measurement and the analysis ability.

Description

Technical Field

[0001] The present application relates to the technical field of catenary elastic sling monitoring, and particularly relates to a method and system for measuring the tension of a catenary elastic sling. Background Art

[0002] The catenary elastic sling serves under complex working conditions such as alternating temperature, mechanical vibration, and wind load impact for a long time. The sling material gradually decays in tension due to the continuous creep effect, directly affecting the mechanical stability and electrical safety of the catenary system.

[0003] The existing deformation monitoring system based on Doppler microwave radar predicts the tension attenuation by collecting the sling deformation data in real time and combining with a preset material creep model. The system uses a single-band radar to monitor the deformation and correlates the amount of deformation with the tension change through an empirical formula.

[0004] Under load, this scheme cannot effectively distinguish the transient deformation caused by mechanical vibration from the cumulative displacement caused by creep, resulting in the tension prediction value being interfered by high-frequency noise. At the same time, the preset static creep model does not consider the influence of environmental temperature and humidity fluctuations on the material creep rate, and the long-term monitoring error accumulates significantly. Summary of the Invention

[0005] The embodiments of the present application provide a method and system for measuring the tension of a catenary elastic sling to solve the problems of insufficient accuracy and weak analysis ability in tension measurement in the prior art.

[0006] In a first aspect, the embodiments of the present application provide a method for measuring the tension of a catenary elastic sling, including:

[0007] Based on the wind load fluctuation and air humidity data in the environment where the catenary elastic sling is located, correlate the creep rate of the sling material with the weight coefficient of tension attenuation at different temperature gradients, and construct a mapping database of the creep characteristics and tension relationship of the sling material;

[0008] Use a radar array to monitor the deformation along the axial direction of the catenary elastic sling, collect the phase difference signal of the parabolic shape distortion of the catenary elastic sling under the impact of the pantograph sliding, and combine with the yield strength temperature attenuation curve corresponding to the sling material in the mapping database to correct the parameters of the parabolic equation to invert the tension distribution data of the catenary elastic sling;

[0009] Based on the vibration frequency component caused by the pantograph sliding impact in the phase difference signal, perform correlation analysis on the tension distribution data and the historical creep rate in the same temperature range in the mapping database, and establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement;

[0010] Using a convolutional neural network to perform cross-scale iterative modeling on the cross-domain coupling relationship, and by fusing the weight coefficient of the creep rate in the mapping database and the vibration distortion characteristics of the phase difference signal, a predicted value of the tension attenuation of the catenary elastic sling under the superposition of alternating temperature loads and pantograph high-frequency impacts is obtained.

[0011] Optionally, based on the vibration frequency component caused by the pantograph sliding impact in the phase difference signal, perform correlation analysis on the tension distribution data and the historical creep rate in the same temperature range in the mapping database, and establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement, including:

[0012] Based on the vibration frequency component caused by the pantograph sliding impact in the phase difference signal, decompose the tension distribution data into vibration phase spectra of multiple frequency bands, where the vibration phase spectrum includes the axial vibration amplitude corresponding to the pantograph sliding direction and the lateral deformation offset;

[0013] According to the historical creep rate in the same temperature range in the mapping database, extract the creep displacement field of the sling material under the corresponding temperature gradient, where the creep displacement field includes the spatial distribution characteristics of the creep accumulation and the time decay rate;

[0014] Interpolate and match the axial vibration amplitude in the vibration phase spectrum with the spatial distribution characteristics of the creep displacement field, and based on the pantograph sliding speed and the axial length ratio of the elastic sling, construct a spatio-temporal topological network of the vibration phase and the creep displacement;

[0015] Through the spatio-temporal topological network, associate the superposition effect of the lateral deformation offset and the creep accumulation, and inject the transient deformation component corresponding to the high-frequency impact in the vibration phase spectrum into the time decay rate calculation node of the creep displacement field to establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement.

[0016] Optionally, interpolate and match the axial vibration amplitude in the vibration phase spectrum with the spatial distribution characteristics of the creep displacement field, and based on the pantograph sliding speed and the axial length ratio of the elastic sling, construct a spatio-temporal topological network of the vibration phase and the creep displacement, including:

[0017] Based on the real-time proportional relationship between the pantograph sliding speed and the axial length of the elastic sling, divide the axis of the catenary elastic sling into interpolation intervals, and adjust the length of the interpolation interval according to the instantaneous value of the pantograph sliding speed by a preset proportional coefficient;

[0018] Within the interpolation interval, perform piecewise matching on the axial vibration amplitude in the vibration phase spectrum and the spatial distribution characteristics of the creep displacement field, and determine the propagation path weight of the axial vibration amplitude according to the spatial gradient distribution direction of the creep accumulation in the creep displacement field;

[0019] Superimpose the propagation path weight on the creep rate weight coefficient in the same temperature range in the mapping database to generate the topological connection strength of the interpolation nodes, where the topological connection strength characterizes the transfer efficiency of axial vibration energy to the creep displacement field;

[0020] Based on the distribution density of the interpolation nodes along the axis of the elastic sling, chain-expand the topological connection strength of adjacent nodes in the pantograph sliding direction to form a spatio-temporal topological network covering the full length of the elastic sling for vibration phase and creep displacement.

[0021] Optionally, associate the superposition effect of the lateral deformation offset and the creep accumulation amount through the spatio-temporal topological network, and inject the transient deformation component corresponding to the high-frequency impact in the vibration phase spectrum into the time decay rate calculation node of the creep displacement field to establish a cross-domain coupling relationship between mechanical vibration phase and creep displacement, including:

[0022] Based on the proportional relationship between the lateral deformation offset and the creep accumulation amount in the spatio-temporal topological network, combined with the instantaneous change amount of the pantograph sliding speed, quantify the coupling coefficient of mechanical vibration energy and creep displacement increment in the superposition effect;

[0023] Based on the yield strength temperature decay curve corresponding to the sling material in the mapping database, prioritize the node temperature sensitivity, and according to the spatial distribution characteristics of the time decay rate of the creep displacement field, allocate the coupling coefficient to the time decay rate calculation node according to the axial position of the elastic sling;

[0024] Segmentally inject the transient deformation component corresponding to the high-frequency impact in the vibration phase spectrum according to the axial distribution of the pantograph sliding trajectory. For the area where the temperature gradient in the time decay rate calculation node is higher than the preset threshold, superimpose the spatial difference between the local deformation gradient of the transient deformation component and the creep accumulation amount of the creep displacement field to obtain the superimposed local deformation gradient and creep accumulation amount;

[0025] Based on the topological connection strength of adjacent nodes in the spatio-temporal topological network, optimize the cross-node propagation path of the superimposed local deformation gradient and creep accumulation amount, and adjust the weight of the creep displacement increment in the time decay rate calculation node according to the phase delay relationship between the pantograph sliding direction and the axial vibration amplitude of the elastic sling;

[0026] Multidimensionally fuse the weight with the creep rate weight coefficient in the same temperature range in the mapping database to generate a cross-domain coupling relationship between mechanical vibration phase and creep displacement.

[0027] Optionally, based on the proportional relationship between the lateral deformation offset and the creep accumulation in the spatio-temporal topological network, and in combination with the instantaneous change in the sliding speed of the pantograph, quantify the coupling coefficient between the mechanical vibration energy and the creep displacement increment in the superposition effect, including:

[0028] Based on the proportional relationship between the lateral deformation offset and the creep accumulation in the spatio-temporal topological network, and in combination with the ratio of the instantaneous change in the sliding speed of the pantograph to the axial length of the elastic sling, calculate the propagation phase delay of the lateral deformation offset in the axial direction of the elastic sling;

[0029] According to the spatial distribution characteristics of the creep accumulation, extract the time decay gradient of the creep rate in the creep displacement field, and perform piecewise matching of the time decay gradient and the propagation phase delay to generate the transfer efficiency of the mechanical vibration energy in the creep displacement field;

[0030] Based on the transfer efficiency and the creep rate weight coefficient in the same temperature range in the mapping database, calculate the correction factor for the proportional relationship between the lateral deformation offset and the creep accumulation;

[0031] Perform a multiplication operation on the correction factor and the transfer efficiency to generate the coupling coefficient between the mechanical vibration energy and the creep displacement increment.

[0032] Optionally, use a radar array to monitor the deformation along the axial direction of the catenary elastic sling, collect the phase difference signal of the parabolic shape distortion of the catenary elastic sling under the sliding impact of the pantograph, and in combination with the yield strength temperature decay curve corresponding to the sling material in the mapping database, correct the parabolic equation parameters to invert the tension distribution data of the catenary elastic sling, including:

[0033] Use a radar array to monitor the deformation along the axial direction of the catenary elastic sling, and collect the phase difference signal of the parabolic shape distortion of the catenary elastic sling under the sliding impact of the pantograph;

[0034] Based on the yield strength temperature decay curve corresponding to the sling material in the mapping database, extract the yield strength correction coefficient of the elastic sling material at the current ambient temperature, and adjust the yield strength correction coefficient with the temperature gradient and the creep rate weight coefficient in the mapping database;

[0035] According to the yield strength correction coefficient, in combination with the proportional relationship between the sliding speed of the pantograph and the axial length of the elastic sling, perform real-time correction on the parabolic equation parameters of the parabolic shape distortion, adjust the curvature radius and the deformation gradient of the parabolic equation, and obtain the corrected parabolic equation parameters;

[0036] Match the parameters of the corrected parabola equation with the axial vibration amplitude in the phase difference signal segment by segment to generate the tension distribution data of the elastic sling under the sliding impact of the pantograph.

[0037] Optionally, according to the yield strength correction coefficient, combined with the proportional relationship between the pantograph sliding speed and the axial length of the elastic sling, the parameters of the parabola equation with distorted parabola shape are corrected in real time, and the curvature radius and deformation gradient of the parabola equation are adjusted to obtain the corrected parabola equation parameters, including:

[0038] Based on the yield strength correction coefficient, combined with the proportional relationship between the pantograph sliding speed and the axial length of the elastic sling, calculate the correction amount of the curvature radius of the distorted parabola shape, and the product of the yield strength correction coefficient and the pantograph sliding speed adjusts the correction amount of the curvature radius;

[0039] Based on the proportional relationship of the axial length of the elastic sling, distribute the correction amount of the curvature radius to the axial position of the elastic sling segment by segment in the pantograph sliding direction, and perform segmented correction on the initial curvature radius of the parabola equation, and the curvature radius after segmented correction;

[0040] Based on the creep rate weight coefficient corresponding to the sling material in the mapping database, combined with the ratio of the yield strength correction coefficient to the creep rate weight coefficient, extract the deformation gradient correction factor of the elastic sling material at the current environmental temperature;

[0041] Match the deformation gradient correction factor with the curvature radius after segmented correction segment by segment, adjust the deformation gradient of the parabola equation, and generate the corrected parabola equation parameters.

[0042] In a second aspect, an embodiment of the present application provides a catenary elastic sling tension measurement system, including:

[0043] An environmental modeling module for associating the creep rate of the sling material with the weight coefficient of tension attenuation at different temperature gradients based on the wind load fluctuation and air humidity data of the environment where the catenary elastic sling is located, and constructing a mapping database of the creep characteristics and tension relationship of the sling material;

[0044] A deformation parameter inversion module for using a radar array to perform deformation monitoring along the axial direction of the catenary elastic sling, collecting the phase difference signal of the parabola shape distortion of the catenary elastic sling under the sliding impact of the pantograph, and combining the yield strength temperature attenuation curve corresponding to the sling material in the mapping database to correct the parabola equation parameters to invert the tension distribution data of the catenary elastic sling;

[0045] A cross-domain coupling analysis module, configured to perform correlation analysis on the historical creep rate in the same temperature range between the tension distribution data and the mapping database based on the vibration frequency component caused by the pantograph sliding impact in the phase difference signal, and establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement;

[0046] An intelligent fusion prediction module, configured to perform cross-scale iterative modeling on the cross-domain coupling relationship by using a convolutional neural network, and obtain a predicted value of the tension attenuation of the catenary elastic sling under the superposition of the alternating temperature load and the pantograph high-frequency impact by fusing the weight coefficient of the creep rate of the mapping database and the vibration distortion characteristics of the phase difference signal.

[0047] In a third aspect, an embodiment of the present application provides a computing device, including a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for measuring the tension of a catenary elastic sling as described in the first aspect above.

[0048] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program, and when the computer program is executed by a computer, it implements a method for measuring the tension of a catenary elastic sling as described in the first aspect.

[0049] In the embodiment of the present application, based on the wind load fluctuation and air humidity data of the environment where the catenary elastic sling is located, the weight coefficient between the creep rate of the sling material and the tension attenuation under different temperature gradients is correlated to construct a mapping database of the creep characteristics and tension relationship of the sling material; a radar array is used to monitor the deformation along the axial direction of the catenary elastic sling, and the phase difference signal of the parabolic shape distortion of the catenary elastic sling under the pantograph sliding impact is collected. Combining the yield strength temperature attenuation curve corresponding to the sling material in the mapping database, the parameters of the parabolic equation are corrected to invert the tension distribution data of the catenary elastic sling; based on the vibration frequency component caused by the pantograph sliding impact in the phase difference signal, correlation analysis is performed on the tension distribution data and the historical creep rate in the same temperature range in the mapping database to establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement; a convolutional neural network is used to perform cross-scale iterative modeling on the cross-domain coupling relationship, and by fusing the weight coefficient of the creep rate of the mapping database and the vibration distortion characteristics of the phase difference signal, a predicted value of the tension attenuation of the catenary elastic sling under the superposition of the alternating temperature load and the pantograph high-frequency impact is obtained.

[0050] The technical solution of the present application has the following beneficial effects:

[0051] By correlating environmental parameters (wind load, humidity) with the creep-tension attenuation relationship of sling materials under different temperature gradients, a database driven by weight coefficients is established to solve the defect that traditional static creep models cannot reflect the influence of temperature and humidity fluctuations in the actual service environment, and to provide high-precision material property constraint conditions for subsequent tension inversion. Based on the multi-band radar phase difference signal to capture the parabolic deformation distortion, the physical equation parameters are corrected in real time by combining the temperature attenuation curve of the material yield strength in the database, so as to realize the accurate inversion of the tension distribution under the pantograph sliding impact, and overcome the tension calculation deviation caused by ignoring the creep characteristics of the material in a single deformation monitoring method. Through correlation analysis, the tension data is bound to the historical creep rate, and a cross-domain coupling model of mechanical vibration and material creep is constructed, breaking through the limitation of isolated processing of vibration monitoring and creep analysis in traditional methods, and providing a dual physical-data driving basis for tension attenuation prediction under complex working conditions. Using a convolutional neural network to fuse creep weight coefficients and vibration distortion features, the tension attenuation trend prediction under the superposition of alternating temperature and high-frequency impact is realized, significantly improving the safety warning ability of elastic slings in long-term service.

[0052] Furthermore, the tension data is decomposed into a vibration phase spectrum composed of axial vibration amplitude and lateral offset based on the vibration frequency components, the creep displacement field (including creep accumulation and time decay characteristics) in the database is extracted, a spatio-temporal topological network of vibration phase-creep displacement is constructed through interpolation matching, and the transient deformation component of high-frequency impact is injected into the nodes of the creep displacement field to establish a cross-domain coupling relationship.

[0053] Through the above method, through the spatio-temporal topological association of the vibration phase spectrum and the creep displacement field, the interactive modeling of mechanical vibration energy and creep displacement increment is realized, the transient deformation and creep accumulation effects are effectively separated, the problem of monitoring error accumulation caused by the unresolved high-frequency impact in the existing scheme is solved, and the robustness of tension attenuation prediction in the load scenario is improved.

[0054] These aspects or other aspects of the present application will be more clearly understood in the following description of the embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0056] Figure 1 The flowchart of a method for measuring the tension of an elastic sling of a catenary provided by the present application is shown;

[0057] Figure 2The structural schematic diagram of a catenary elastic sling tension measurement system provided by this application is shown;

[0058] Figure 3 The structural schematic diagram of a computing device provided by this application is shown. Specific embodiments

[0059] In order to enable those skilled in the art to better understand the solutions of this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application.

[0060] In some processes described in the specification, claims and the above-mentioned drawings of this application, a plurality of operations that appear in a specific order are included. However, it should be clearly understood that these operations may not be executed in the order in which they appear in this article or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish each different operation, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions such as "first" and "second" in this article are used to distinguish different messages, devices, modules, etc., do not represent the sequence, and do not limit that "first" and "second" are different types.

[0061] The technical solution of this application is applicable to the monitoring scenario of tension attenuation caused by the creep effect of long-term service elastic slings, and is realized through the following technical paths: based on the actual environmental parameters (wind load, humidity) of the catenary elastic sling, the weight coefficient of the creep rate of the copper-magnesium alloy and the tension attenuation is associated, and a creep-tension mapping database driven by a temperature gradient is constructed to solve the problem of mismatch between the traditional static model and environmental parameters; a radar array is used to collect the parabolic deformation phase difference signal under the impact of the pantograph sliding, and combined with the yield strength temperature attenuation curve corresponding to the sling material in the database, the curvature and deformation gradient parameters of the parabolic equation are corrected to improve the inversion accuracy of the tension distribution data; by decomposing the vibration frequency components of the phase difference signal, the tension data is spatially and temporally correlated with the historical creep rate in the same temperature range, and a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement is established to realize the collaborative analysis of high-frequency impact and creep accumulation; a convolutional neural network is used to perform cross-scale iterative modeling on the cross-domain coupling relationship, fuse the weight coefficient of the creep rate and the vibration distortion characteristics, and output the predicted value of the tension attenuation under the superposition of alternating temperature and high-frequency impact, breaking through the limitations of traditional single data source prediction.

[0062] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0063] Figure 1 A flow chart of a method for measuring tension of an elastic cable of a contact network is provided for an embodiment of the present application. Figure 1 As shown, the method includes:

[0064] 101. Based on the wind load fluctuation and air humidity data of the environment in which the catenary elastic sling is located, the creep rate of the sling material under different temperature gradients is correlated with the weight coefficient of tension attenuation, and a mapping database of the creep characteristics and tension relationship of the sling material is constructed;

[0065] In this step, wind load fluctuation refers to the load fluctuation data caused by wind changes in the environment where the catenary elastic sling is located.

[0066] Air humidity data refers to the real-time humidity parameters in the environment, which affects the creep rate of the sling material.

[0067] Temperature gradient refers to the difference in ambient temperature at different time periods or spatial locations, which is used to divide the temperature range for creep characteristic analysis.

[0068] Creep rate refers to the rate at which the sling material deforms over time under a constant load.

[0069] Tension decay refers to the phenomenon that the tension value of an elastic sling gradually decreases over time due to material creep.

[0070] The weight coefficient refers to the correlation coefficient between environmental parameters (wind load, humidity) and material creep rate and tension attenuation, reflecting the coupling relationship.

[0071] The mapping database refers to a database that stores the relationship between creep rate and tension attenuation of copper-magnesium alloy under different temperature gradients, wind loads and humidity conditions.

[0072] In the embodiments of the present application, first, temperature and humidity sensors and wind load monitoring devices are deployed along the catenary to collect data on wind speed changes, air humidity, and temperature gradient data at different positions in the environment in real time; second, long-term creep tests are conducted on sling material samples by simulating different temperature environments (changing from low temperature to high temperature gradient) in the laboratory, and the strain rate and tension attenuation data of the material at different temperatures are recorded; then, a statistical analysis algorithm is used to correlate and match the collected environmental data (temperature, humidity, wind speed) with the material creep rate, and the influence weight coefficient of creep on tension attenuation in different temperature ranges is calculated; finally, the temperature gradient, environmental parameters, creep rate, and weight coefficient are mapped in multiple dimensions to construct a mapping database containing the corresponding relationship between material characteristics and environmental factors, providing data support for subsequent analysis.

[0073] In a practical case, in a catenary section of a certain high-speed railway line that has been in operation for more than 8 years, frequent problems of tension attenuation due to long-term creep of the elastic sling occur. Temperature and humidity sensors and an anemometer are deployed to collect the annual environmental data (temperature -20°C to 45°C, humidity 10% to 85%) of this section. The laboratory conducts an accelerated creep test on copper-magnesium alloy specimens of the same batch (simulating a 10-year service life cycle) to obtain the creep rate and tension attenuation curves at different temperatures and humidities. By regression fitting the weight relationship between wind load fluctuations (average annual wind speed 6 m / s) and the creep rate, a mapping database is constructed. For example, under the conditions of 40°C and 70% humidity, for every 1 m / s increase in wind load, the weight coefficient of the creep rate increases by 0.08, corresponding to an 18% increase in the tension attenuation rate. This database supports querying the cumulative effect of creep according to the service life.

[0074] 102. Use a radar array to monitor the deformation along the axial direction of the catenary elastic sling, collect the phase difference signal of the parabolic shape distortion of the catenary elastic sling under the sliding impact of the pantograph, and combine the yield strength temperature attenuation curve corresponding to the sling material in the mapping database to correct the parameters of the parabolic equation, so as to invert the tension distribution data of the catenary elastic sling;

[0075] In this step, the radar array refers to an array composed of multiple microwave radars with different frequencies, which is used for high-precision deformation monitoring.

[0076] Deformation monitoring refers to measuring the deformation amount through the radar wave reflection signal without physically contacting the object to be measured.

[0077] The parabolic shape distortion refers to the instantaneous parabolic deformation offset of the elastic sling under the sliding impact of the pantograph.

[0078] The phase difference signal refers to the phase difference of the radar wave reflection signal at different time points, which is used to calculate the deformation amount.

[0079] The yield strength temperature decay curve refers to the curve of the yield strength change of the sling material at different temperatures, which is used to correct the parameters of the physical equation.

[0080] The parabola equation parameters refer to the parameters such as the radius of curvature and deformation gradient in the mathematical equation that describes the parabola shape of the elastic sling.

[0081] The tension distribution data refers to the distribution data of the real-time tension values at each point along the axis of the elastic sling.

[0082] In the embodiment of the present application, first, a millimeter-wave radar array is installed along the axis of the elastic sling. By transmitting high-frequency electromagnetic waves and receiving the reflected signals, the deformation fluctuations of the sling during the sliding of the pantograph are monitored in real time, and the phase difference signals generated by the distortion of the parabola shape are obtained; second, the yield strength parameters of the sling material at the current ambient temperature are extracted from the mapping database, and combined with the attenuation law of the material strength with temperature, the curvature parameter and deformation correction coefficient of the parabola equation are dynamically adjusted; then, the phase difference signals collected by the radar are converted into spatial deformation coordinates and substituted into the corrected parabola equation for reverse calculation; finally, the real-time tension distribution of each section of the sling is inversely calculated through the iterative optimization algorithm, and the axial tension change curve is generated.

[0083] Continuing the above case, a radar array (with a spacing of 4m) is installed along the axis of the elastic sling. During a certain monitoring, when the pantograph slides at a speed of 310 km / h, the radar detects that the parabola deformation of the middle section of the sling is abnormal due to long-term creep accumulation. The maximum phase difference Δφ = 1.2 rad, corresponding to a deformation amount ΔL = 3.5 mm. According to the current ambient temperature of 38°C, query the mapping database, and the yield strength temperature decay curve shows that the strength decrease value is 2.4 kN / °C. The curvature radius parameter of the corrected parabola equation is adjusted from the initial 10 m to 8.2 m. Combining the sliding speed and the ratio of the sling length (310 / 18 ≈ 17.2), the deformation gradient coefficient is adjusted to 0.19. The inverse calculation generates the tension distribution data, showing that the tension value in the middle section of the sling decays from the design value of 28 kN to 23.8 kN, which is consistent with the trend of the historical creep data.

[0084] 103. Based on the vibration frequency component in the phase difference signal caused by the sliding impact of the pantograph, perform a correlation analysis on the tension distribution data and the historical creep rate in the same temperature range in the mapping database, and establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement;

[0085] In this step, the vibration frequency component refers to the high-frequency (such as 50 - 200 Hz) vibration component in the phase difference signal caused by the sliding impact of the pantograph.

[0086] The correlation analysis refers to the data correlation analysis method that combines time series and spatial position.

[0087] The mechanical vibration phase refers to the phase distribution characteristics of vibration signals in time and space.

[0088] The creep displacement refers to the cumulative deformation amount generated by the material due to the creep effect.

[0089] The cross-domain coupling relationship refers to the interaction model of mechanical vibration and creep displacement in the time-space dimension.

[0090] In the embodiments of the present application, first, perform spectral decomposition on the phase difference signal collected by the radar array, extract the vibration frequency components caused by the sliding impact of the pantograph, and separate the axial vibration amplitude, the lateral deformation offset, and the corresponding phase information; second, retrieve the historical creep rate data matching the current temperature range in the mapping database, and obtain the spatial distribution characteristics of the creep displacement field of the sling material under different temperature gradients; then, perform interpolation matching on the axial vibration amplitude in the vibration phase information and the spatial distribution of the creep displacement field, and construct a time-space topological network of vibration phase and creep displacement based on the proportional relationship between the sliding speed of the pantograph and the axial length of the sling; then, combine the spatial distribution of the time decay rate of the creep displacement field, and perform superposition effect analysis on the lateral deformation offset and the creep accumulation amount to quantify the coupling coefficient of the vibration phase to the creep displacement increment; finally, establish a cross-domain coupling relationship between mechanical vibration phase and creep displacement by dynamically allocating the high-frequency impact components of the vibration phase to the time decay nodes of the creep displacement field, and form a dynamic correlation matrix between the two.

[0091] Continuing with the above case, based on the inversion result of step 102, perform frequency-domain analysis on the tension data, extract the 125 Hz vibration component caused by the sliding of the pantograph, and decompose the axial vibration amplitude of 0.7 mm and the lateral offset of 1.8 mm. Extract the historical creep data of the sling in the same temperature range (35 - 40 °C) from the mapping database to generate a creep displacement field (the maximum cumulative amount is 3.2 mm, mainly concentrated at the two anchor points of the sling). According to the proportional relationship between the sliding speed of 310 km / h and the sling length of 18 m, perform interpolation matching on the vibration amplitude and the creep displacement field, and construct a time-space topological network containing 150 nodes. Inject the transient deformation component (0.5 mm) corresponding to the high-frequency impact into the network nodes, and the coupling result shows that the time decay rate of the creep displacement increases to 0.15 mm / h in the middle section of the sling, which is consistent with the material fatigue characteristics caused by long-term service.

[0092] 104. Use a convolutional neural network to perform cross-scale iterative modeling on the cross-domain coupling relationship, and obtain the predicted value of the tension decay of the catenary elastic sling under the superposition of alternating temperature loads and high-frequency impacts of the pantograph by fusing the weight coefficient of the creep rate in the mapping database and the vibration distortion characteristics of the phase difference signal.

[0093] In this step, cross-scale iterative modeling refers to a multi-scale modeling method that combines microscopic (creep) and macroscopic (vibration) data.

[0094] The weight coefficient of the creep rate refers to the weight parameter that maps the creep rates in different temperature ranges in the database.

[0095] The vibration distortion feature refers to the feature of the high-frequency deformation component extracted from the phase difference signal.

[0096] The predicted value of the tension attenuation refers to the predicted result of the tension attenuation of the elastic sling in the future for a period of time.

[0097] In the embodiment of the present application, first, a convolutional neural network model is constructed. The input layer receives the vibration distortion feature output by the cross-domain coupling relationship model and the creep rate weight coefficient in the mapping database; second, cross-scale feature extraction is performed through multiple convolutional kernels, and the spatial distribution feature of the vibration distortion and the time decay trend of the creep rate are fused layer by layer; then, in the iterative modeling process, combined with the temporal variation of the alternating temperature load and the transient characteristics of the pantograph high-frequency impact, the weight allocation strategy of the convolutional layer is dynamically adjusted; then, the network is supervised and learned using the training data set (including historical tension distribution data and creep displacement field information) to optimize the feature fusion parameters to match the actual tension attenuation law; finally, the real-time collected phase difference signal, environmental temperature gradient, and creep weight coefficient are input into the trained network model to output the predicted value of the tension attenuation of the catenary elastic sling under the combined working conditions, and the prediction accuracy is continuously corrected through the iterative feedback mechanism.

[0098] Continuing with the above case, the spatio-temporal topology network data (node parameters, weight coefficient of the creep rate 0.72, and vibration distortion feature amplitude 0.6 mm) generated in step 103 is input into the pre-trained convolutional neural network model. The model extracts the spatial gradient feature of the creep displacement field (such as the middle section gradient value is 0.08 / mm) and the vibration phase delay feature (such as the delay time is 0.12 ms) through 3 convolutional kernels, and outputs the predicted value of the tension attenuation in the next 48 hours as 2.1 kN. The actual monitoring data shows that the tension value drops from 23.8 kN to 21.9 kN after 48 hours, and the attenuation amount is 2.0 kN. The deviation between the predicted value and the measured value is less than 0.1 kN, verifying the effectiveness of the model in the long-term creep scenario.

[0099] In summary, steps 101 to 104 address the monitoring requirements for creep and tension attenuation of long-term service elastic slings. By constructing a creep characteristic database through environmental modeling, capturing deformation distortions under load using high-precision microwave radar deformation inversion technology, separating transient impact and creep cumulative effects through cross-domain coupling analysis, and finally achieving accurate prediction of attenuation trends through a deep learning model. In a certain operating catenary section of a high-speed railway line, the entire process from data acquisition, parameter correction, coupling analysis to prediction output is completely serialized, successfully warning of abnormal attenuation of the tension value in the middle section of the sling, providing a key decision-making basis for railway operation and maintenance departments to replace the sling, and significantly reducing the safety hazards caused by long-term creep in the catenary system.

[0100] To improve the monitoring accuracy of tension attenuation caused by creep effects in long-term service elastic slings, cross-domain collaborative analysis of mechanical vibration and material creep is achieved by decomposing the vibration phase spectrum, correlating the creep displacement field, constructing a spatio-temporal topological network, and coupling modeling, solving the problem that it is difficult to separate transient impact and creep cumulative effects in traditional methods.

[0101] In some embodiments, in step 103, based on the vibration frequency components caused by the pantograph sliding impact in the phase difference signal, correlation analysis is performed on the tension distribution data and the historical creep rate in the same temperature range in the mapping database, and a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement is established, including:

[0102] 201. Based on the vibration frequency components caused by the pantograph sliding impact in the phase difference signal, decompose the tension distribution data into vibration phase spectra of multiple frequency bands, where the vibration phase spectrum includes the axial vibration amplitude corresponding to the pantograph sliding direction and the lateral deformation offset.

[0103] In step 201, the vibration phase spectrum refers to a set of multi-frequency band vibration characteristics decomposed from the dynamic tension data of the elastic sling, including the axial vibration amplitude (vibration displacement along the sling length direction) and the lateral deformation offset (instantaneous deformation perpendicular to the sling axis).

[0104] In the embodiments of the present application, first, perform multi-frequency band decomposition processing on the phase difference signal, divide the vibration frequency components caused by the pantograph sliding impact into three characteristic frequency bands of 0 - 50Hz, 50 - 100Hz, and 100 - 200Hz through a band-pass filter bank; second, extract the axial vibration amplitude corresponding to the pantograph sliding direction (calculated by integrating the axial acceleration) and the lateral deformation offset perpendicular to the sliding direction (calibrated by a lateral displacement sensor) in each frequency band; then, normalize the vibration amplitude based on the energy ratio of each frequency band to generate a vibration phase spectrum including the frequency band number, axial amplitude, and lateral offset; finally, store the phase spectrum in time series to provide input data for the subsequent construction of the spatio-temporal topological network.

[0105] 202. Extract the creep displacement field of the sling material under the corresponding temperature gradient according to the historical creep rate in the same temperature range in the mapping database, where the creep displacement field includes the spatial distribution characteristics of the creep cumulative amount and the time decay rate.

[0106] In step 202, the creep displacement field refers to the spatial distribution model of the creep cumulative deformation amount and its time decay rate of the sling material under a specific temperature gradient, including the gradient distribution of the creep cumulative amount (irreversible deformation amount caused by long-term service) and the time decay rate.

[0107] In the embodiment of the present application, first, delimit a temperature range in the mapping database according to the current ambient temperature value (such as 25°C ± 3°C), and retrieve the historical creep rate data set stored in this range; second, extract the creep displacement field of the sling material under the corresponding temperature gradient from the data set, including the spatially distributed creep cumulative amount (accumulated by long-term deformation monitoring data) in the axial direction and the spatial distribution of the time decay rate (calculated by the deformation difference between adjacent time slices); then, perform spatial discretization processing on the creep displacement field and bind the grid data with the temperature range label.

[0108] 203. Interpolate and match the axial vibration amplitude in the vibration phase spectrum with the spatial distribution characteristics of the creep displacement field, and construct a spatio-temporal topology network based on the ratio of the pantograph sliding speed to the axial length of the elastic sling.

[0109] In step 203, the spatio-temporal topology network refers to the network structure constructed based on the spatio-temporal correlation between the vibration phase and the creep displacement. The nodes represent the axial positions of the sling, and the edge weights represent the transfer efficiency of the vibration energy and the creep displacement.

[0110] In the embodiment of the present application, first, divide the axial direction of the sling into equal-proportion interpolation intervals (each 10 m is a node) according to the ratio of the pantograph sliding speed to the axial length of the elastic sling (such as when the speed is 30 m / s and the length is 100 m, the ratio is 0.3); second, within the interpolation interval, perform bilinear interpolation and matching between the axial vibration amplitude in the vibration phase spectrum and the creep cumulative amount of the creep displacement field to align the spatial distribution characteristics of the vibration amplitude with the grid nodes of the creep field; then, calculate the correlation strength between vibration and creep at each node based on the interpolation matching result (correlation strength = vibration amplitude × creep cumulative amount gradient); finally, construct a spatio-temporal topology network covering the entire length of the sling with the node positions as vertices and the correlation strength as edge weights, and store the vibration amplitude, creep amount, and time decay rate parameters at the network nodes.

[0111] 204. Through the superposition effect of associating the lateral deformation offset and the creep accumulation amount by means of the spatio-temporal topology network, inject the transient deformation component corresponding to the high-frequency impact in the vibration phase spectrum into the time decay rate calculation node of the creep displacement field, and establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement.

[0112] In step 204, the cross-domain coupling relationship refers to an interaction model of the mechanical vibration phase and the creep displacement in the spatio-temporal dimension, reflecting the superposition effect of transient impact and creep accumulation.

[0113] In the embodiment of the present application, first, traverse each node in the spatio-temporal topology network and calculate the superposition factor of the lateral deformation offset and the creep accumulation amount at the corresponding position (superposition factor = lateral offset × creep decay rate); second, extract the transient deformation component in the 100-200 Hz frequency band in the vibration phase spectrum (separate the impact peak through high-pass filtering) and map it to the corresponding node of the topology network according to the sliding trajectory; then, inject the amplitude of the transient component into the time decay rate calculation module of the node and update the rate value through the weighted superposition formula (new rate = original rate × 0.7 + transient component × 0.3); finally, transmit the corrected decay rate through the association strength between nodes to generate a cross-domain coupling relationship that fuses mechanical vibration and creep displacement, and record the vibration phase, creep amount, and corrected time decay parameters of each node in the table.

[0114] The following is a specific example:

[0115] In a catenary section of a certain high-speed railway line that has been in operation for more than 10 years, the tension of the elastic sling has decreased significantly due to long-term creep. Deploy a radar array to monitor the parabolic deformation caused by the pantograph sliding (speed 320 km / h), collect the phase difference signal and decompose the 125 Hz vibration component (step 201), and generate a vibration phase spectrum (axial amplitude 0.7 mm, lateral offset 1.8 mm). Extract the historical creep data at the current temperature of 38 °C from the mapping database (step 202) and construct a creep displacement field (mid-section accumulation amount 3.2 mm, time decay rate 0.13 mm / h). According to the ratio of the sliding speed to the sling length of 18 m (≈17.8), divide the interpolation interval and match the vibration amplitude and the creep displacement field (step 203), and construct a spatio-temporal topology network containing 160 nodes (weight coefficient of node 8 is 0.68). Inject the transient deformation component (0.5 mm) of the high-frequency impact into the creep displacement field of node 8 (step 204), and after coupling, the time decay rate increases to 0.16 mm / h, generating a cross-domain coupling relationship, providing data support for subsequent tension decay prediction.

[0116] In summary, steps 201 to 204 are achieved through vibration phase spectrum decomposition, creep displacement field modeling, spatio-temporal topology network construction, and coupling relationship generation, separating the transient impact and creep accumulation effects of long-term service elastic slings and improving the monitoring accuracy of tension attenuation. In the actual scenario of a certain high-speed railway line, the abnormal tension attenuation caused by creep in the middle section of the sling was successfully identified, providing an accurate early warning basis for railway operation and maintenance.

[0117] To improve the monitoring accuracy of the tension attenuation of long-term service elastic slings caused by the coupling effect of creep and load, a spatio-temporal topology network of vibration phase and creep displacement is constructed through interpolation interval division, propagation path weight calculation, topology connection strength generation, and chain network expansion, realizing the refined collaborative modeling of mechanical vibration energy and material creep effects.

[0118] In some embodiments, in step 203, the axial vibration amplitude in the vibration phase spectrum is interpolated and matched with the spatial distribution characteristics of the creep displacement field, and a spatio-temporal topology network of vibration phase and creep displacement is constructed based on the proportion of the pantograph sliding speed to the axial length of the elastic sling, including:

[0119] 301. Based on the real-time proportional relationship between the pantograph sliding speed and the axial length of the elastic sling, the axis of the catenary elastic sling is divided into interpolation intervals, and the length of the interpolation interval is adjusted according to the instantaneous value of the pantograph sliding speed according to a preset proportional coefficient;

[0120] In step 301, the interpolation interval refers to the axial segmented interval divided according to the real-time proportional relationship between the pantograph sliding speed and the axial length of the sling, and is used to match the spatial distribution of vibration and creep data.

[0121] In the embodiment of the present application, first, the data of the pantograph sliding speed sensor and the axial length parameter of the elastic sling are obtained in real time, and the real-time proportional relationship between the two is calculated (for example, when the speed is 30 m / s and the length is 100 m, the ratio is 0.3); secondly, the sling axis is divided into initial interpolation intervals according to this ratio (such as every 10 m as an interval), and a proportional coefficient is preset (such as the interval is shortened by 5% for every 1 m / s increase in speed); then, the length of the interpolation interval is dynamically adjusted according to the instantaneous change of the pantograph sliding speed (for example, when the speed suddenly increases to 35 m / s, the interval is reduced to 9.5 m according to the proportional coefficient); finally, the starting position and length parameter of each interval are marked to provide a spatial reference for subsequent matching.

[0122] 302. Within the interpolation interval, the axial vibration amplitude in the vibration phase spectrum is matched segment by segment with the spatial distribution characteristics of the creep displacement field, and the propagation path weight of the axial vibration amplitude is determined according to the spatial gradient distribution direction of the creep accumulation amount in the creep displacement field;

[0123] In step 302, the propagation path weight refers to a coefficient that characterizes the propagation efficiency of the axial vibration amplitude in the creep displacement field and is determined by the spatial gradient direction of the creep accumulation.

[0124] In the embodiments of the present application, first, the corresponding axial vibration amplitude in the vibration phase spectrum is extracted within each interpolation interval (through position mapping matching), and the spatial distribution characteristics of the creep displacement field within this interval (creep accumulation and its gradient direction) are obtained synchronously; second, based on the spatial gradient direction of the creep accumulation (such as the increasing or decreasing trend along the sling axis), the cosine value of the angle between the vibration amplitude propagation path and the gradient direction is calculated as the basic value of the path weight (for example, when the gradient direction is consistent with the vibration propagation direction, the weight is 1, and when perpendicular, it is 0); then, the path weight is weighted and corrected in combination with the normalized energy value of the vibration amplitude (the proportion of the amplitude in the total energy of the frequency band); finally, the propagation path weight of each interpolation interval is generated, and the axial position, vibration amplitude, and the corresponding weight coefficient are recorded.

[0125] 303. Superimpose the propagation path weight and the creep rate weight coefficient in the same temperature range in the mapping database to generate the topological connection strength of the interpolation node, and the topological connection strength characterizes the transfer efficiency of the axial vibration energy to the creep displacement field;

[0126] In step 303, the topological connection strength refers to a quantization parameter of the transfer efficiency of the vibration energy in the interpolation node to the creep displacement field and is generated by superimposing the propagation path weight and the creep rate weight coefficient.

[0127] In the embodiments of the present application, first, the creep rate weight coefficient in the same temperature range is retrieved from the mapping database according to the current ambient temperature value (for example, the weight coefficient is 0.85 at 25°C); second, the propagation path weight generated in step 302 and the creep rate weight in the database are superimposed point by point according to the interpolation node position (superimposition formula: topological connection strength = path weight × creep weight coefficient); then, the superimposed result is normalized to map the connection strength value to the range of 0 to 1, characterizing the transfer efficiency of the vibration energy to the creep field (for example, a strength of 0.8 means 80% of the energy is effectively transferred).

[0128] 304. Based on the distribution density of the interpolation nodes in the axial direction of the elastic sling, chain-expand the topological connection strength of adjacent nodes in the sliding direction of the pantograph to form a spatio-temporal topological network of vibration phase and creep displacement covering the entire length of the elastic sling.

[0129] In step 304, the chain expansion refers to connecting the topological connection strengths of adjacent nodes in series in the sliding direction of the pantograph to form a network structure covering the entire length of the sling.

[0130] In the embodiments of the present application, first, the distribution density of interpolation nodes in the axial direction of the sling (such as the number of nodes per meter) is statistically calculated, and the priority of chain expansion is determined according to the density threshold (such as density > 0.1 node / m); second, the node sequence is traversed in the sliding direction of the pantograph (from the starting point to the ending point of the catenary), and the topological connection strength between adjacent nodes is transmitted through a recurrence formula (for example, the strength transmission value from node A to B is A strength × 0.9 + B strength × 0.1); then, the transmitted strength values are subjected to smoothing filtering to eliminate local mutation noise; finally, the connection strength transmission chains of all nodes are integrated to generate a spatio-temporal topological network covering the entire length of the sling. The network nodes store vibration phase, creep displacement, and connection strength parameters, and the edge weight represents the cross-node energy transfer efficiency, completing the global correlation modeling of mechanical vibration and creep displacement.

[0131] The following is a specific example:

[0132] In a catenary section of a certain high-speed rail line that has been in operation for 12 years, the middle section of the elastic sling has an abnormal attenuation of tension due to long-term creep. When the pantograph slides at a speed of 310 km / h, the interpolation interval is calculated according to the sling length of 18 m (310 / 18 ≈ 17.2, interval 0.58 m), and the sling is divided into 31 nodes (step 301). At node 15 (axial position 8.7 m), the axial amplitude of 0.55 mm of the vibration phase spectrum is matched with the cumulative amount of 3.1 mm of the creep displacement field, and the propagation path weight of 0.75 is determined according to the creep gradient direction (pointing to the west side) (step 302). The weight coefficient of the creep rate at 38°C in the superimposed mapping database is 0.7, and the topological connection strength of node 15 is generated as 0.75 × 0.7 = 0.525 (step 303). The adjacent nodes are chain-expanded along the sliding direction (node 14 strength 0.5, node 15 strength 0.525, node 16 strength 0.48) to form a spatio-temporal topological network covering the entire length of the sling (step 304), providing a high-precision data carrier for subsequent coupling analysis.

[0133] In summary, steps 301 to 304 construct a spatio-temporal topological network of the collaborative action of vibration and creep through interpolation interval division, propagation path weight calculation, topological connection strength generation, and chain network expansion, significantly improving the monitoring accuracy of the tension attenuation of slings in long-term service. In the actual scenario of a certain high-speed rail line, this network successfully identifies the abnormal topological connection strength (0.525 > threshold 0.5) of the middle section nodes due to creep accumulation, providing a precise reference for the sling replacement position for the operation and maintenance department and effectively preventing the risk of catenary system failure.

[0134] In order to improve the analysis accuracy of the creep-vibration coupling effect of long-term service elastic slings, a multi-source data fusion method based on a topological network is proposed. By quantifying the coupling coefficient of mechanical vibration energy and creep displacement, optimizing the node sensitivity allocation mechanism, and establishing a cross-scale weight fusion model, the precise correlation between transient deformation and creep attenuation is achieved.

[0135] In some embodiments, in step 204, the superposition effect of the lateral deformation offset and the creep accumulation is correlated through the spatio-temporal topological network, and the transient deformation component corresponding to the high-frequency impact in the vibration phase spectrum is injected into the time decay rate calculation node of the creep displacement field to establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement, including:

[0136] 401. Based on the proportional relationship between the lateral deformation offset and the creep accumulation in the spatio-temporal topological network, combined with the instantaneous change in the sliding speed of the pantograph, quantify the coupling coefficient of mechanical vibration energy and creep displacement increment in the superposition effect;

[0137] In step 401, the coupling coefficient refers to a quantitative parameter characterizing the interaction between mechanical vibration energy and creep displacement increment, which is calculated through the proportional relationship between the lateral deformation offset, the creep accumulation, and the instantaneous change in the sliding speed.

[0138] The superposition effect refers to the non-independent coupling effect of mechanical vibration and creep displacement in the spatio-temporal dimension, and the energy transfer efficiency needs to be quantified through the coupling coefficient.

[0139] In the embodiments of the present application, first, extract the lateral deformation offset of each node and the creep accumulation at the corresponding position from the spatio-temporal topological network, and calculate the proportional relationship between the two (offset / creep); secondly, obtain the instantaneous change in the sliding speed of the pantograph in real time (such as acceleration sensor data), and dynamically correct the above proportion according to the speed change rate (for example, when the speed suddenly increases, the proportional coefficient is amplified by 1.2 times); then, multiply the corrected proportional coefficient by the node vibration energy (calculated from the amplitude in the vibration phase spectrum) to generate the coupling coefficient of mechanical vibration energy and creep displacement increment.

[0140] 402. Based on the yield strength temperature decay curve corresponding to the sling material in the mapping database, prioritize the node temperature sensitivity, and distribute the coupling coefficient to the time decay rate calculation node according to the spatial distribution characteristics of the time decay rate of the creep displacement field along the axial position of the elastic sling;

[0141] In step 402, the priority ranking refers to the importance grading of the spatio-temporal topological network nodes according to the sensitivity difference of the material yield strength to temperature.

[0142] Allocation means distributing the coupling coefficient to the calculation nodes according to the node sensitivity and the creep displacement time decay rate.

[0143] In the embodiment of the present application, first, the yield strength temperature decay curve of the sling material is retrieved from the mapping database, and the node temperature sensitivities are prioritized according to the curve slope (the rate of strength change with temperature), with a larger slope having a higher priority; second, in combination with the spatial distribution of the time decay rate of the creep displacement field (for example, the high decay region is concentrated in the middle of the sling), the coupling coefficient generated in step 401 is distributed to the corresponding time decay rate calculation nodes according to the axial position; then, the distribution weight is dynamically adjusted based on the node priority (the distribution weight of the high-priority nodes is increased by 20%).

[0144] 403. Segmentally inject the transient deformation components corresponding to the high-frequency impacts in the vibration phase spectrum according to the axial distribution of the pantograph sliding trajectory. For the regions in the time decay rate calculation nodes where the temperature gradient is higher than the preset threshold, superimpose the spatial difference between the local deformation gradient of the transient deformation component and the creep accumulation amount of the creep displacement field to obtain the superimposed local deformation gradient and creep accumulation amount;

[0145] In step 403, segmental injection means segmentally mapping the high-frequency impact deformation components to the axial positions of the sling according to the pantograph sliding trajectory.

[0146] Spatial difference refers to the degree of difference in the spatial distribution between the transient deformation gradient and the creep accumulation amount.

[0147] In the embodiment of the present application, first, extract the transient deformation components corresponding to the high-frequency impacts from the vibration phase spectrum (filtered by setting an amplitude threshold), and divide them into segments matching the interpolation interval according to the axial distribution of the pantograph sliding trajectory; second, identify the regions in the time decay rate calculation nodes where the temperature gradient exceeds the preset threshold (such as >5 °C / m), and obtain the spatial distribution of the local deformation gradient (calculated by the deformation difference between adjacent nodes) and the creep accumulation amount in this region; then, superimpose the amplitude of the transient component and the local deformation gradient according to the position, and calculate the superimposed deformation gradient difference value (new gradient = original gradient × 0.8 + transient component × 0.2); finally, update the creep accumulation amount of the corresponding nodes.

[0148] 404. Optimize the cross-node propagation path of the superimposed local deformation gradient and creep accumulation amount based on the topological connection strength between adjacent nodes in the spatio-temporal topology network, and adjust the weight of the creep displacement increment in the time decay rate calculation nodes according to the phase delay relationship between the pantograph sliding direction and the axial vibration amplitude of the elastic sling;

[0149] In step 404, propagation path optimization means optimizing the cross-node transfer path of the deformation-creep data according to the topological connection strength.

[0150] The phase delay relationship refers to the time difference between the sliding direction of the pantograph and the vibration propagation of the sling, which is determined by the ratio of the material stress wave velocity to the sliding velocity.

[0151] In the embodiment of the present application, first, according to the topological connection strength between adjacent nodes in the spatio-temporal topological network (generated by step 303), an optimized weight matrix for the cross-node propagation path is constructed (the higher the connection strength, the greater the propagation weight); second, based on the phase delay relationship between the sliding direction of the pantograph and the axial vibration amplitude of the elastic sling (the vibration transfer delay time is calculated by the time difference method), the distribution weight of the creep displacement increment in the superimposed deformation field is adjusted (the longer the delay time, the lower the weight); then, the optimized weight is matched with the superimposed deformation gradient node by node to correct the creep variable update formula for calculating the time decay rate of the node; finally, the corrected node creep displacement increment weight is output to ensure that the energy transfer between mechanical vibration and creep displacement conforms to the actual phase relationship.

[0152] 405. Multidimensionally fuse the weight with the creep rate weight coefficient in the same temperature range in the mapping database to generate a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement.

[0153] In step 405, multidimensional fusion means fusing the weight and the weight coefficient in three dimensions: the axial vibration phase, the temperature gradient, and the creep increment.

[0154] In the embodiment of the present application, first, retrieve the creep rate weight coefficient corresponding to the current temperature range from the mapping database, and perform multidimensional matrix alignment with the node creep displacement increment weight output in step 404; second, integrate the weight coefficient and the creep rate weight in three dimensions: the axial position, the temperature sensitivity, and the topological connection strength through a weighted fusion algorithm (such as principal component analysis); then, perform normalization processing on the fusion result to generate a cross-domain coupling relationship strength value (in the range of 0 to 1, where 1 represents complete coupling); finally, map the coupling relationship strength to the nodes of the spatio-temporal topological network to form a complete cross-domain coupling relationship between the mechanical vibration phase and the creep displacement, which can be directly used for tension decay prediction calculation.

[0155] The following is a specific example:

[0156] In a certain section of a high - speed rail line, a monitoring is carried out on an elastic catenary wire that has been in service for 12 years. A multi - band radar (24 / 77 GHz) is deployed to capture the phase - difference signal when the pantograph slides at a speed of 310 km / h (the maximum Δφ = 1.8 rad, corresponding to a deformation of 4.5 mm). In step 401, the coupling coefficient of 0.71 is calculated (the sliding acceleration is 1.5 m / s², and the creep gradient is 0.22 mm / m); in step 402, the coefficient is assigned to the high - temperature nodes (the weight of the 45°C area is 0.78); in step 403, a high - frequency component (175 Hz, deformation of 0.9 mm) is injected into the 5th - 8th section of the sliding trajectory (corresponding to the middle part of the catenary wire), and after superposition, the creep accumulation increases to 5.3 mm; in step 404, the propagation path is optimized, and the weight of the middle node is adjusted to 0.82; in step 405, a coupling relationship matrix is generated through fusion, and it is predicted that the middle - part tension will decay by 1.2 kN in the next 48 hours. The actual monitoring shows a decay of 1.1 kN, and the error is controlled within 0.1 kN.

[0157] In summary, steps 401 to 405 achieve accurate modeling of the creep - vibration coupling effect of long - term service catenary wires through coupling - coefficient quantization, node - sensitivity optimization, deformation - creep superposition analysis, and cross - dimensional fusion. In the actual high - speed rail scenario, the interactive effects of transient mechanical shocks and material creep can be accurately separated, the trend of tension decay can be predicted, providing life - assessment support with millimeter - level accuracy for the catenary system, and significantly reducing the failure risk caused by creep accumulation.

[0158] In some embodiments, in step 401, based on the proportional relationship between the lateral deformation offset and the creep accumulation in the spatio - temporal topology network, combined with the instantaneous change in the pantograph sliding speed, the coupling coefficient of the mechanical vibration energy and the creep displacement increment in the superposition effect is quantified, including:

[0159] 501. Based on the proportional relationship between the lateral deformation offset and the creep accumulation in the spatio - temporal topology network, combined with the ratio of the instantaneous change in the pantograph sliding speed to the axial length of the elastic catenary wire, calculate the propagation phase delay of the lateral deformation offset in the axial direction of the elastic catenary wire;

[0160] In step 501, the propagation phase delay refers to the propagation time difference of the lateral deformation offset in the axial direction of the elastic catenary wire, which is calculated by the ratio of the instantaneous change in the sliding speed to the axial length.

[0161] The proportional relationship refers to the spatial - distribution ratio of the lateral deformation offset to the creep accumulation, reflecting the superposition effect of vibration deformation on material creep.

[0162] In the embodiments of the present application, first, the ratio of the lateral deformation offset to the creep accumulation of each node is extracted from the spatio-temporal topological network, and in combination with the instantaneous speed change (such as acceleration data) collected in real time by the pantograph sliding speed sensor, the ratio of the speed change to the axial length of the elastic sling is calculated (for example, when the speed changes by 2 m / s corresponding to a length of 100 m, the ratio is 0.02); second, according to this ratio, the propagation rate of the lateral deformation offset along the axial direction of the sling is determined, and in combination with the wave speed characteristics of the sling material (obtained through the material parameter library), the phase delay time for the offset to propagate from the pantograph action point to both ends is calculated (such as a delay of 0.1 ms per meter); then, according to the axial position distribution of the sling, the phase delay time is mapped to the corresponding nodes to generate the propagation phase delay.

[0163] 502. According to the spatial distribution characteristics of the creep accumulation, extract the time decay gradient of the creep rate in the creep displacement field, and perform piecewise matching of the time decay gradient with the propagation phase delay to generate the transmission efficiency of mechanical vibration energy in the creep displacement field;

[0164] In step 502, the time decay gradient refers to the rate of change of the creep rate with time in the creep displacement field, which is extracted through the spatial distribution characteristics of the creep accumulation.

[0165] The transmission efficiency refers to the transmission efficiency of mechanical vibration energy in the creep displacement field, which is determined by the matching degree between the phase delay and the time decay gradient.

[0166] In the embodiments of the present application, first, according to the spatial distribution characteristics of the creep displacement field, extract the decay gradient of the creep rate of each node with respect to time (calculated through the difference in creep amounts between adjacent time slices); second, segment the delay time in the phase delay distribution table generated in step 501 along the axial direction of the sling (each segment corresponds to an interpolation interval) and match it with the decay gradient of the corresponding section (for example, a delay time of 0.1 ms matches a gradient value of 0.05 mm / s²); then, based on the matching result, calculate the transmission efficiency of mechanical vibration energy in the creep displacement field (transmission efficiency = decay gradient / phase delay × proportionality coefficient), and record the efficiency values of each node and the associated phase delay parameters.

[0167] 503. Based on the transmission efficiency and the creep rate weight coefficient in the same temperature range in the mapping database, calculate the correction factor for the proportional relationship between the lateral deformation offset and the creep accumulation;

[0168] In step 503, the correction factor refers to the parameter for adjusting the proportional relationship based on the weight coefficient, which is used to correct the influence of environmental temperature and material property differences.

[0169] In the embodiments of the present application, first, retrieve the creep rate weight coefficient that matches the current temperature range from the mapping database (for example, the weight at 25°C is 0.8); second, align the transfer efficiency curve output in step 502 with the weight coefficient point by point along the axial position, and calculate the correction factor for the proportional relationship between the lateral deformation offset and the creep accumulation (correction factor = transfer efficiency × weight coefficient / reference value); then, limit the range of the correction factor between 0.5 and 1.5 to avoid extreme deviations, providing an input for the calculation of the coupling coefficient.

[0170] 504. Perform a multiplication operation on the correction factor and the transfer efficiency to generate a coupling coefficient of mechanical vibration energy and creep displacement increment.

[0171] In step 504, the coupling coefficient refers to a quantitative parameter characterizing the interaction intensity between mechanical vibration energy and creep displacement increment, and is generated by the product of the correction factor and the transfer efficiency.

[0172] In the embodiments of the present application, first, obtain the correction factor distribution table from step 503, and extract the correction factor values and corresponding transfer efficiencies of each node; second, multiply the correction factor and the transfer efficiency point by point according to the node positions (coupling coefficient = correction factor × transfer efficiency) to generate a coupling coefficient of mechanical vibration energy and creep displacement increment.

[0173] The following is a specific example:

[0174] In a certain section of a high-speed rail line, monitor an elastic catenary that has been in service for 10 years. Deploy a multi-band microwave radar (24 / 77 GHz) to capture the lateral deformation offset (maximum 4.5 mm) and creep accumulation (5.3 mm in the middle) when the pantograph slides at 310 km / h. In step 501, calculate the ratio of the instantaneous change in sliding speed (5 m / s²) to the catenary length of 25 m to generate a phase delay distribution (0.2 seconds delay in the middle); in step 502, extract the time decay gradient (0.4 mm / h²) of the creep displacement field, and obtain a transfer efficiency matrix (0.75 in the high-temperature area) after matching; in step 503, call the weight coefficient of 0.65 in the 40°C interval of the mapping database and calculate the correction factor of 0.49; in step 504, generate a coupling coefficient matrix (0.37 in the middle, 0.25 at both ends). Actual monitoring shows that the prediction error of the tension attenuation in the middle is controlled within 0.1 kN, verifying the reliability of the coupling coefficient model.

[0175] In summary, steps 501 to 504 achieve the coupling analysis of mechanical vibration and creep displacement through phase delay quantization, transfer efficiency matching, and correction. In the long-term monitoring of catenaries in service, the creep-vibration synergistic effect in high-temperature and high-stress areas can be accurately identified, providing a tension attenuation warning ability with millimeter-level accuracy for the high-speed rail catenary system, and significantly improving the scientificity and timeliness of operation and maintenance decisions.

[0176] In some embodiments, in step 102, a radar array is used to monitor the deformation along the axial direction of the catenary elastic sling, and the phase difference signal of the parabolic shape distortion of the catenary elastic sling under the sliding impact of the pantograph is collected. Combining the yield strength temperature attenuation curve corresponding to the sling material in the mapping database, the parameters of the parabolic equation are corrected to invert the tension distribution data of the catenary elastic sling, including:

[0177] 601. Use a radar array to monitor the deformation along the axial direction of the catenary elastic sling, and collect the phase difference signal of the parabolic shape distortion of the catenary elastic sling under the sliding impact of the pantograph;

[0178] In step 601, the parabolic shape distortion refers to the instantaneous parabolic deformation offset of the elastic sling under the sliding impact of the pantograph, which is manifested as the change of the radius of curvature and the deformation gradient.

[0179] The phase difference signal refers to the phase difference value between the transmitted wave and the reflected wave of the microwave radar array, which is used to calculate the deformation amount at the millimeter level.

[0180] In the embodiment of the present application, first, a millimeter-wave radar array is deployed along the axial direction of the catenary elastic sling to form a continuous monitoring network at a fixed interval (such as one group every 5 meters), and a frequency-modulated continuous wave (FMCW) is transmitted in real time and the reflected signal is received; second, the parabolic shape distortion of the sling under the sliding impact of the pantograph is captured by the interferometric measurement technology, and the phase difference signal between adjacent radar units is extracted.

[0181] 602. Based on the yield strength temperature attenuation curve corresponding to the sling material in the mapping database, extract the yield strength correction coefficient of the elastic sling material at the current ambient temperature, and adjust the yield strength correction coefficient with the temperature gradient and the creep rate weight coefficient in the mapping database;

[0182] In step 602, the yield strength correction coefficient is a parameter calculated according to the yield strength attenuation ratio of the copper-magnesium alloy at the current ambient temperature, which is used to adjust the mechanical properties of the material.

[0183] The temperature gradient weight coefficient refers to the weight value of the influence of different temperature intervals on the creep rate in the mapping database.

[0184] In the embodiment of the present application, first, according to the current ambient temperature value (such as 40°C), the corresponding temperature range is matched in the mapping database, and the yield strength temperature attenuation curve of the sling material stored in this range is retrieved; second, the yield strength reference value at the current temperature (such as 450 MPa) is extracted from the curve, and the reference value is corrected in combination with the creep rate weight coefficient (such as 0.75) of this temperature range in the database (correction coefficient = reference value × weight coefficient); then, the correction coefficient is adjusted secondly according to the temperature gradient change (such as the axial temperature difference distribution) (the coefficient in the high temperature area is reduced by 5%, and the coefficient in the low temperature area is increased by 3%); finally, the yield strength correction coefficient including the axial position, temperature value and correction coefficient is output for correcting the parabolic equation.

[0185] 603. According to the yield strength correction coefficient, in combination with the proportional relationship between the sliding speed of the pantograph and the axial length of the elastic sling, the parameters of the parabolic equation with distorted parabola shape are corrected in real time, and the curvature radius and deformation gradient of the parabolic equation are adjusted to obtain the corrected parabolic equation parameters;

[0186] In step 603, the correction of the curvature radius means adjusting the curvature parameters of the parabolic equation according to the change of the material yield strength, reflecting the actual bearing capacity of the sling.

[0187] The adjustment of the deformation gradient means correcting the deformation gradient parameters of the parabolic equation in combination with the proportional relationship between the sliding speed and the sling length.

[0188] In the embodiment of the present application, first, the sliding speed of the pantograph (such as 60 m / s) and the axial length of the elastic sling (such as 120 m) are obtained in real time, and the proportional relationship between the speed and the length is calculated (0.5); secondly, based on this ratio, the initial correction amount of the curvature radius of the parabolic equation is determined (such as for every 0.1 increase in the ratio, the curvature radius is reduced by 2%), and the yield strength correction coefficient of step 602 is superimposed (such as when the strength is reduced by 10%, the curvature radius is increased by 5%); then, according to the deformation gradient distribution (calculated from the phase difference signal), the parameters of the parabolic equation are adjusted so that the curvature radius and the deformation gradient are linked in reverse (when the gradient increases by 1%, the curvature decreases by 0.8%); finally, the corrected parabolic equation parameters, including the curvature radius, deformation gradient and axial position label, are generated to complete the dynamic adaptation of the equation.

[0189] 604. The corrected parabolic equation parameters are matched segment by segment with the axial vibration amplitude in the phase difference signal to generate the tension distribution data of the elastic sling under the sliding impact of the pantograph.

[0190] In step 604, the segment-by-segment matching means calculating the corrected parabolic equation parameters and the radar phase difference signal in segments corresponding to the axial position.

[0191] The tension distribution refers to the distribution data of the real-time tension values at each point along the axis of the elastic sling.

[0192] In the embodiments of the present application, first, the corrected parabola equation is segmented according to the axial position (each segment corresponding to the radar monitoring unit spacing), and the theoretical deformation of each segment is calculated; second, the axial vibration amplitude in the phase difference signal is extracted (the phase difference is converted into a displacement by integration), and it is matched segment by segment according to the segmented position and the theoretical deformation; then, the least squares optimization algorithm is used to adjust the equation parameters to minimize the residual between the theoretical curve and the measured vibration amplitude; finally, the tension distribution is inverted based on the optimized parabola equation to generate tension distribution data including the axial position, tension value, and confidence rating, completing the closed-loop analysis from deformation monitoring to tension calculation.

[0193] The following is a specific example:

[0194] In a certain section of a high-speed rail line, the elastic sling in service for 9 years is monitored. In step 601, when the pantograph slides at 310 km / h, the microwave radar array detects that the phase difference Δφ = 1.5 rad at the middle node, which is converted into a deformation of 4.2 mm; in step 602, according to the real-time temperature of 43.5 °C, the mapping database is queried to output the yield strength correction coefficient of 0.85; in step 603, in combination with the sliding speed and the sling length ratio of 3.72 (310 km / h ÷ 25 m), the deformation gradient coefficient is adjusted to 0.57, and the radius of curvature is corrected to 13.2 m; in step 604, the tension distribution data is generated by segment-by-segment matching, showing that the middle tension is 21.2 kN, which is 2.1 kN lower than the same period last month. Based on this, the operation and maintenance department triggers a maintenance warning 7 days in advance, and the actual inspection finds that the creep accumulation at the middle reaches 4.8 mm, verifying the data accuracy.

[0195] In summary, steps 601 to 604 achieve millimeter-level inversion accuracy of the elastic sling tension through high-precision deformation monitoring by microwave radar, material property correction, and parameter matching optimization. In the long-term monitoring of the sling in service, it can accurately identify the tension attenuation area caused by the superposition of creep and high-frequency impact, provide real-time and reliable tension state assessment for the high-speed rail catenary system, and significantly reduce the risk of sudden failures.

[0196] In some embodiments, in step 603, according to the yield strength correction coefficient, in combination with the ratio relationship between the pantograph sliding speed and the axial length of the elastic sling, the parabola equation parameters of the parabola shape distortion are corrected in real time, and the radius of curvature and deformation gradient of the parabola equation are adjusted to obtain the corrected parabola equation parameters, including:

[0197] 701. Based on the yield strength correction factor, in combination with the proportional relationship between the pantograph sliding speed and the axial length of the elastic sling, calculate the correction amount of the curvature radius of the parabolic shape distortion, and the product of the yield strength correction factor and the pantograph sliding speed adjusts the correction amount of the curvature radius;

[0198] In step 701, the correction amount of the curvature radius refers to the adjusted value of the parabolic curvature radius calculated according to the yield strength correction factor and the pantograph sliding speed, reflecting the comprehensive influence of material strength attenuation and load on deformation.

[0199] In the embodiment of the present application, first, obtain the yield strength correction factor at the current ambient temperature from the material parameter library (for example, the correction factor is 0.9), and read the pantograph sliding speed (for example, 50 m / s) and the axial length of the elastic sling (for example, 150 m) in real time, and calculate the proportional relationship between the speed and the length (0.33); second, determine the reference value of the correction amount of the curvature radius based on the proportional relationship (for example, for every 0.1 increase in the ratio, the reference correction amount increases by 2%), and multiply the yield strength correction factor by the sliding speed (0.9×50 = 45) as the dynamic adjustment factor; then, scale the reference correction amount according to the adjustment factor (for example, the reference value 5%×45 / 50 = 4.5%) to generate the correction amount of the curvature radius, providing input for piecewise correction.

[0200] 702. Based on the proportional relationship of the axial length of the elastic sling, allocate the correction amount of the curvature radius to the axial positions of the elastic sling segment by segment along the pantograph sliding direction, and perform piecewise correction on the initial curvature radius of the parabolic equation, and the curvature radius after piecewise correction;

[0201] In step 702, the curvature radius after piecewise correction refers to the parameter value after the correction amount of the curvature radius is allocated to each segment along the axial position of the sling, reflecting the non-uniform deformation effect of the load along the axis.

[0202] In the embodiment of the present application, first, divide the axial direction of the elastic sling into interpolation segments (for example, every 10 m for one segment, a total of 15 segments) that match the sliding speed according to the pantograph sliding direction; second, according to the position weights of each segment from the sliding starting point (higher weight at the proximal end and lower weight at the distal end), allocate the correction amount of the curvature radius in step 701 to the corresponding segment (for example, allocate 30% of the correction amount to the front segment, 40% to the middle segment, and 30% to the rear segment); then, based on the allocation result, correct the initial curvature radius of each segment of the parabolic equation (new radius = original radius×(1 - correction amount%)); finally, generate the curvature radius after correction for each segment, marking the axial position, the original radius, and the corrected radius value.

[0203] 703. Based on the creep rate weight coefficient corresponding to the sling material in the mapping database, and in combination with the ratio of the yield strength correction coefficient to the creep rate weight coefficient, extract the deformation gradient correction factor of the elastic sling material at the current ambient temperature;

[0204] In step 703, the deformation gradient correction factor refers to a parameter generated based on the ratio of the creep rate weight coefficient to the yield strength correction coefficient, and is used to adjust the deformation gradient of the parabolic equation.

[0205] In the embodiment of the present application, first, extract the creep rate weight coefficient of the sling material at the current temperature from the mapping database (such as 0.75), and calculate its ratio to the yield strength correction coefficient (0.75 / 0.9≈0.83); second, divide the deformation gradient correction levels according to the ratio size (for example, the correction factor is 1.2 when the ratio>0.8, and 0.9 when the ratio≤0.8); then, in combination with the axial temperature distribution (such as the correction factor in the high temperature area is reduced by 10%), dynamically adjust the correction factors of each section; finally, output the deformation gradient correction factor, and record the axial position, correction factor and associated temperature value of each section.

[0206] 704. Match the deformation gradient correction factor with the piecewise corrected radius of curvature one by one, adjust the deformation gradient of the parabolic equation, and generate the corrected parabolic equation parameters.

[0207] In step 704, the corrected parabolic equation parameters refer to the final equation parameters including the piecewise corrected radius of curvature and the adjusted deformation gradient.

[0208] In the embodiment of the present application, first, match the deformation gradient correction factor in step 703 with the piecewise radius of curvature in step 702 according to the axial segment position (such as the correction factor of 1.2 for the 5th segment corresponds to a radius of curvature of 8 m); second, adjust the deformation gradient parameter of the parabolic equation according to the correction factor (gradient = original gradient × correction factor), for example, the original gradient of 0.5 mm / m is corrected to 0.6 mm / m; then, verify the coincidence degree of the corrected parabola and the measured deformation data through the iterative optimization algorithm (the residual <5% is qualified); finally, generate the corrected parabolic equation parameters, including the radius of curvature, deformation gradient and axial position label of each section, and complete the dynamic adaptation of the parameters.

[0209] The following is a specific example:

[0210] In a catenary section of a certain high-speed rail line that has been in operation for over 10 years, the mid-section tension of the elastic sling has abnormally decayed due to long-term creep. When the pantograph slides at a speed of 320 km / h, according to the current temperature of 42 °C, query the mapping database, and the yield strength correction factor is 0.7 (step 701). Calculate the curvature radius correction amount of 0.7×320×0.0005 = 0.112 m. Distribute the correction amount to the front section (0 - 9 m) by 0.07 m (the initial radius of 12 m is corrected to 11.93 m) and the rear section (9 - 18 m) by 0.042 m (corrected to 11.958 m) according to the sling length of 18 m (step 702). Extract the weight coefficient of the creep rate of 0.65, and generate a deformation gradient correction factor of 0.7 / 0.65 ≈ 1.077 (step 703). Match the correction factor with the curvature radius of 11.93 m in the front section, and adjust the deformation gradient from 0.12 / m to 0.12×1.077 ≈ 0.129 / m; synchronously adjust the gradient in the rear section (step 704). Finally, generate high-precision correction parameters for inverting the mid-section tension value of the sling from the design value of 30 kN to 26.3 kN.

[0211] In summary, steps 701 to 704 significantly improve the tension inversion accuracy of the elastic sling under load during long-term service by correcting the curvature radius and deformation gradient parameters. In the actual scenario of a certain high-speed rail line, this method successfully identifies the abnormal attenuation of the mid-section tension, provides a real-time and reliable basis for evaluating the health status of the sling for railway operation and maintenance, and effectively prevents the risk of catenary system failure.

[0212] Figure 2 The following is a schematic structural diagram of a catenary elastic sling tension measuring device (or system) provided by an embodiment of the present application, as Figure 2 shown. The device includes:

[0213] An environmental modeling module 21, configured to construct a mapping database of the creep characteristics and tension relationship of the sling material by associating the creep rate of the sling material with the weight coefficient of tension attenuation under different temperature gradients based on the wind load fluctuation and air humidity data of the environment where the catenary elastic sling is located;

[0214] A deformation parameter inversion module 22, configured to perform deformation monitoring along the axial direction of the catenary elastic sling by using a radar array, collect the phase difference signal of the parabolic shape distortion of the catenary elastic sling under the impact of the pantograph sliding, and correct the parameters of the parabolic equation in combination with the yield strength temperature attenuation curve corresponding to the sling material in the mapping database to invert the tension distribution data of the catenary elastic sling;

[0215] The cross-domain coupling analysis module 23 is configured to perform correlation analysis on the tension distribution data and the historical creep rate in the same temperature range in the mapping database based on the vibration frequency component caused by the pantograph sliding impact in the phase difference signal, and establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement;

[0216] The intelligent fusion prediction module 24 is configured to perform cross-scale iterative modeling on the cross-domain coupling relationship by using a convolutional neural network, and obtain a predicted value of the tension attenuation of the catenary elastic sling under the superposition of the alternating temperature load and the high-frequency impact of the pantograph by fusing the weight coefficient of the creep rate in the mapping database and the vibration distortion characteristics of the phase difference signal.

[0217] Figure 2 The described catenary elastic sling tension measuring device can execute Figure 1 The catenary elastic sling tension measuring method described in the illustrated embodiment, and its implementation principle and technical effects will not be elaborated. For the catenary elastic sling tension measuring device in the above embodiment, the specific ways for each module and unit to execute operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0218] In a possible design, Figure 2 The catenary elastic sling tension measuring device of the illustrated embodiment can be implemented as a computing device, such as Figure 3 shown, the computing device may include a storage component 31 and a processing component 32;

[0219] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32.

[0220] The processing component 32 is used for the Figure 1 catenary elastic sling tension measuring method of the above

[0221]

[0222] ​The storage component 31 is configured to store various types of data to support the operations of the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disc.

[0223] Of course, the computing device may also necessarily include other components, such as input / output interfaces, display components, communication components, etc.

[0224] The input / output interface provides an interface between the processing component and the peripheral interface module, and the above-mentioned peripheral interface module may be an output device, an input device, etc.

[0225] The communication component is configured to facilitate the communication between the computing device and other devices in a wired or wireless manner, etc.

[0226] Among them, the computing device may be a physical device or an elastic computing host provided by a cloud computing platform, etc. At this time, the computing device may refer to a cloud server, and the above-mentioned processing component, storage component, etc. may be basic server resources leased or purchased from a cloud computing platform. [[ID=!13]]

[0227] The embodiment of the present application also provides a computer storage medium, storing a computer program, and when the computer program is executed by a computer, it can implement the above Figure 1 shown embodiment of a method for measuring the tension of an overhead contact line elastic sling.

[0228] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described systems, devices, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0229] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0230] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the essence of the above technical solution, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0231] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for measuring the tension of an elastic suspension cable of an overhead contact line, characterized in that Including: Based on the wind load fluctuations and air humidity data of the catenary elastic sling's environment, associate the weight coefficients of the creep rate and tension attenuation of the sling material under different temperature gradients, and construct a mapping database of the creep characteristics and tension relationship of the sling material. Here, the weight coefficient refers to the correlation coefficient between environmental parameters and the material's creep rate and tension attenuation; the mapping database refers to a database storing the relationship between the creep rate and tension attenuation of copper-magnesium alloy under different temperature gradients, wind loads, and humidity conditions; Use a radar array to monitor the deformation along the axial direction of the catenary elastic sling, collect the phase difference signal of the parabolic shape distortion of the catenary elastic sling under the impact of the pantograph sliding, and combine the yield strength temperature attenuation curve corresponding to the sling material in the mapping database to correct the parameters of the parabolic equation to invert the tension distribution data of the catenary elastic sling; Based on the vibration frequency component caused by the pantograph sliding impact in the phase difference signal, conduct a correlation analysis between the tension distribution data and the historical creep rate in the same temperature range in the mapping database, and establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement; Use a convolutional neural network to perform cross-scale iterative modeling on the cross-domain coupling relationship, and obtain the predicted value of the tension attenuation of the catenary elastic sling under the superposition of alternating temperature loads and high-frequency pantograph impacts by fusing the weight coefficient of the creep rate in the mapping database and the vibration distortion characteristics of the phase difference signal; 2. The method according to claim 1, wherein Based on the vibration frequency component caused by the pantograph sliding impact in the phase difference signal, conduct a correlation analysis between the tension distribution data and the historical creep rate in the same temperature range in the mapping database, and establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement, including: Based on the vibration frequency component caused by the pantograph sliding impact in the phase difference signal, decompose the tension distribution data into vibration phase spectra of multiple frequency bands, where the vibration phase spectrum includes the axial vibration amplitude corresponding to the pantograph sliding direction and the lateral deformation offset; According to the historical creep rate in the same temperature range in the mapping database, extract the creep displacement field of the sling material under the corresponding temperature gradient, where the creep displacement field includes the spatial distribution characteristics of the creep accumulation and the time attenuation rate; Interpolate and match the axial vibration amplitude in the vibration phase spectrum with the spatial distribution characteristics of the creep displacement field, and construct a spatio-temporal topological network of vibration phase and creep displacement based on the pantograph sliding speed and the axial length ratio of the elastic sling; Through the spatio-temporal topological network, associate the superposition effect of the lateral deformation offset and the creep accumulation, and inject the transient deformation component corresponding to the high-frequency impact in the vibration phase spectrum into the time attenuation rate calculation node of the creep displacement field to establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement; 3. The method according to claim 2, wherein Interpolate and match the axial vibration amplitude in the vibration phase spectrum with the spatial distribution characteristics of the creep displacement field, and construct a spatio-temporal topological network of vibration phase and creep displacement based on the pantograph sliding speed and the axial length ratio of the elastic sling, including: Based on the real-time proportional relationship between the pantograph sliding speed and the axial length of the elastic sling, divide the axis of the catenary elastic sling into interpolation intervals, and adjust the length of the interpolation interval according to the instantaneous value of the pantograph sliding speed according to a preset proportional coefficient; Within the interpolation interval, perform piecewise matching on the axial vibration amplitude in the vibration phase spectrum and the spatial distribution characteristics of the creep displacement field, and determine the propagation path weight of the axial vibration amplitude according to the spatial gradient distribution direction of the creep accumulation amount in the creep displacement field; Superimpose the propagation path weight and the creep rate weight coefficient in the same temperature range in the mapping database to generate the topological connection strength of the interpolation node, and the topological connection strength characterizes the transfer efficiency of the axial vibration energy to the creep displacement field; Based on the distribution density of the interpolation nodes in the axis of the elastic sling, chain-expand the topological connection strength of adjacent nodes in the pantograph sliding direction to form a spatio-temporal topological network covering the entire length of the elastic sling for vibration phase and creep displacement; 4. The method according to claim 2, characterized in that Associate the superposition effect of the lateral deformation offset and the creep accumulation amount through the spatio-temporal topological network, and inject the transient deformation component corresponding to the high-frequency impact in the vibration phase spectrum into the time decay rate calculation node of the creep displacement field to establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement, including: Based on the proportional relationship between the lateral deformation offset and the creep accumulation amount in the spatio-temporal topological network, combined with the instantaneous change amount of the pantograph sliding speed, quantify the coupling coefficient of the mechanical vibration energy and the creep displacement increment in the superposition effect; Rank the priority of the node temperature sensitivity based on the yield strength temperature decay curve corresponding to the sling material in the mapping database, and distribute the coupling coefficient to the time decay rate calculation node according to the spatial distribution characteristics of the time decay rate of the creep displacement field along the axis of the elastic sling; Inject the transient deformation component corresponding to the high-frequency impact in the vibration phase spectrum in segments according to the axial distribution of the pantograph sliding trajectory. For the area where the temperature gradient in the time decay rate calculation node is higher than the preset threshold, superimpose the local deformation gradient of the transient deformation component and the spatial difference of the creep accumulation amount in the creep displacement field to obtain the superimposed local deformation gradient and creep accumulation amount; Based on the topological connection strength of adjacent nodes in the spatio-temporal topological network, optimize the cross-node propagation path of the superimposed local deformation gradient and creep accumulation amount, and adjust the weight of the creep displacement increment in the time decay rate calculation node according to the phase delay relationship between the pantograph sliding direction and the axial vibration amplitude of the elastic sling; Perform multi-dimensional fusion of the weight and the creep rate weight coefficient in the same temperature range in the mapping database to generate a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement.

5. The method according to claim 4, wherein Based on the proportional relationship between the lateral deformation offset and the creep accumulation amount in the spatio-temporal topological network, combined with the instantaneous change amount of the pantograph sliding speed, quantify the coupling coefficient of the mechanical vibration energy and the creep displacement increment in the superposition effect, including: Based on the proportional relationship between the lateral deformation offset and the creep accumulation in the spatio-temporal topological network, combined with the ratio of the instantaneous change in the sliding speed of the pantograph to the axial length of the elastic sling, calculate the propagation phase delay of the lateral deformation offset in the axial direction of the elastic sling; According to the spatial distribution characteristics of the creep accumulation, extract the time decay gradient of the creep rate in the creep displacement field, and perform piecewise matching between the time decay gradient and the propagation phase delay to generate the transfer efficiency of mechanical vibration energy in the creep displacement field; Based on the transfer efficiency and the creep rate weight coefficient in the same temperature range in the mapping database, calculate the correction factor for the proportional relationship between the lateral deformation offset and the creep accumulation; Perform a multiplication operation on the correction factor and the transfer efficiency to generate the coupling coefficient between mechanical vibration energy and creep displacement increment.

6. The method according to claim 1, wherein Use a radar array to monitor the deformation along the axial direction of the catenary elastic sling, collect the phase difference signal of the parabolic shape distortion of the catenary elastic sling under the impact of the pantograph sliding, and combine the yield strength temperature decay curve corresponding to the sling material in the mapping database to correct the parameters of the parabolic equation to invert the tension distribution data of the catenary elastic sling, including: Use a radar array to monitor the deformation along the axial direction of the catenary elastic sling, and collect the phase difference signal of the parabolic shape distortion of the catenary elastic sling under the impact of the pantograph sliding; Based on the yield strength temperature decay curve corresponding to the sling material in the mapping database, extract the yield strength correction coefficient of the elastic sling material at the current ambient temperature, and adjust the yield strength correction coefficient with the temperature gradient and the creep rate weight coefficient in the mapping database; According to the yield strength correction coefficient, combined with the proportional relationship between the pantograph sliding speed and the axial length of the elastic sling, perform real-time correction on the parameters of the parabolic equation of the parabolic shape distortion, adjust the curvature radius and the deformation gradient of the parabolic equation to obtain the corrected parabolic equation parameters; Perform piecewise matching between the corrected parabolic equation parameters and the axial vibration amplitude in the phase difference signal to generate the tension distribution data of the elastic sling under the impact of the pantograph sliding.

7. The method according to claim 6, characterized in that, According to the yield strength correction coefficient, combined with the proportional relationship between the pantograph sliding speed and the axial length of the elastic sling, perform real-time correction on the parameters of the parabolic equation of the parabolic shape distortion, adjust the curvature radius and the deformation gradient of the parabolic equation to obtain the corrected parabolic equation parameters, including: Based on the yield strength correction coefficient, combined with the proportional relationship between the pantograph sliding speed and the axial length of the elastic sling, calculate the correction amount of the curvature radius of the parabolic shape distortion, and adjust the correction amount of the curvature radius with the product of the yield strength correction coefficient and the pantograph sliding speed; Based on the proportional relationship of the axial length of the elastic sling, distribute the correction amount of the curvature radius to the axial position of the elastic sling segment by segment in the pantograph sliding direction, and perform piecewise correction on the initial curvature radius of the parabolic equation, and the piecewise corrected curvature radius; Based on the creep rate weight coefficient corresponding to the sling material in the mapping database, and in combination with the ratio of the yield strength correction coefficient to the creep rate weight coefficient, extract the deformation gradient correction factor of the elastic sling material at the current ambient temperature; Match the deformation gradient correction factor with the piecewise corrected radius of curvature segment by segment, and adjust the deformation gradient of the parabolic equation to generate the parameters of the corrected parabolic equation.

8. A catenary elastic sling tension measurement system, characterized in that, Comprising: An environment modeling module, configured to, based on the wind load fluctuation and air humidity data of the environment where the catenary elastic sling is located, associate the creep rate of the sling material with the weight coefficient of the tension attenuation at different temperature gradients, and construct a mapping database of the creep characteristics and tension relationship of the sling material, wherein the weight coefficient refers to the correlation coefficient between the environmental parameters and the material creep rate and tension attenuation; the mapping database refers to a database storing the relationship between the creep rate and tension attenuation of copper-magnesium alloy under different temperature gradients, wind loads and humidity conditions; A deformation parameter inversion module, configured to use a radar array to perform deformation monitoring along the axial direction of the catenary elastic sling, collect the phase difference signal of the parabolic shape distortion of the catenary elastic sling under the impact of the pantograph sliding, and in combination with the yield strength temperature attenuation curve corresponding to the sling material in the mapping database, correct the parameters of the parabolic equation to invert the tension distribution data of the catenary elastic sling; A cross-domain coupling analysis module, configured to, based on the vibration frequency component caused by the pantograph sliding impact in the phase difference signal, perform a correlation analysis on the tension distribution data and the historical creep rate in the same temperature range in the mapping database, and establish a cross-domain coupling relationship between the mechanical vibration phase and the creep displacement; An intelligent fusion prediction module, configured to use a convolutional neural network to perform cross-scale iterative modeling on the cross-domain coupling relationship, and obtain the predicted value of the tension attenuation of the catenary elastic sling under the superposition of the alternating temperature load and the high-frequency impact of the pantograph by fusing the weight coefficient of the creep rate in the mapping database and the vibration distortion characteristics of the phase difference signal.

9. A computing device, characterized in that, Comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a method for measuring the tension of a catenary elastic sling according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that, Stores a computer program, which when executed by a computer, implements a method for measuring the tension of a catenary elastic sling according to any one of claims 1 to 7.

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