Method and device for identifying diseases of dirty ballast bed in spring melting period

Abstract

The invention provides a disease identification method and device for a dirty ballast bed in a spring melting period, and relates to the technical field of ballast bed disease identification, and the method specifically comprises the steps: building a discontinuous ligand cementation contact model based on a discrete element simulation method, and introducing a temperature-rigidity coupling factor and a temperature-strength coupling factor into the model; the method comprises the following steps: acquiring mechanical response data of a dirty ballast under the action of different temperature gradients, dirty contents and dynamic loads through a partition cascade temperature control large triaxial experimental device, and constructing a critical dynamic strain calculation model by using the mechanical response data based on a plastic stability theory; a ballast bed structure simulation model is established by combining the cemented contact model and the critical dynamic strain calculation model, a ballast bed microscopic contact behavior under the dynamic-melting coupling effect in the spring melting period is simulated, and simulation data are obtained; according to the method, correlation analysis is carried out on simulation data to generate a disease assessment index of the ballast bed, so that the disease occurrence risk is assessed, and the risk dynamic assessment of the dirty ballast bed in the spring melting period is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of roadbed disease identification, and in particular to a method and device for identifying dirty roadbed diseases during the spring thaw period. Background Art

[0002] During the spring thaw period, with the increase in temperature and the infiltration of snowmelt water, the mechanical properties of the dirty roadbed will be significantly affected. Roadbed materials, especially ballast, as the foundation of railways and highways, are subject to constantly changing dynamic loads. However, the accumulation of fine particles in the dirty roadbed will have a negative impact on the internal bonding structure of the roadbed, resulting in a decrease in the stiffness and strength of the bonding bonds. Traditional roadbed disease identification methods mostly rely on static monitoring and empirical judgment, and cannot fully consider temperature changes and their effects on material properties, especially under dynamic loads. This method often ignores the dynamic changes in the microscopic contact behavior inside the roadbed, resulting in the failure to promptly and effectively identify and treat the mud and mud diseases that occur during the spring thaw period, thereby increasing the risk of roadbed failure.

[0003] In addition, existing technologies have certain limitations in the acquisition and analysis of mechanical response data. Most methods fail to effectively integrate the combined effects of multiple factors such as temperature gradient, dirt content and dynamic load on the performance of the roadbed. Therefore, the lack of dynamic evaluation indicators under specific environmental conditions has led to an incomplete and scientific evaluation of the roadbed state. The current evaluation system is often based on fixed thresholds and fails to adapt to changes in the roadbed state under different temperature and moisture conditions. More importantly, traditional methods fail to provide real-time feedback on the microscopic contact behavior and physical changes of the roadbed, resulting in a delayed response in practical applications and an inability to take timely measures to prevent the aggravation of the disease. Therefore, it is particularly important to develop a technical means that can comprehensively consider the effects of temperature, dirt and dynamic loads on roadbed diseases and provide real-time and dynamic evaluation.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The object of the present invention is to provide a method and device for identifying dirty roadbed diseases during the spring thaw period to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions: A method for identifying dirty roadbed diseases during spring thaw period, the specific steps comprising: S1, based on the discrete element simulation method, a discontinuous graded ligand bond contact model is established, and the temperature-stiffness coupling factor and temperature-strength coupling factor are introduced into the model. The temperature-stiffness coupling factor and temperature-strength coupling factor are used to characterize the dynamic effects of melting on the bond stiffness and bond strength respectively; S2, obtain the mechanical response data of dirty ballast under different temperature gradients, dirt content and dynamic loads through a zoned stepped temperature-controlled large triaxial experimental device, and use the mechanical response data to build a critical dynamic strain calculation model based on the plastic shakedown theory; S3, a simulation model of the ballast structure is established by combining the cementation contact model and the critical dynamic strain calculation model, simulating the microscopic contact behavior of the ballast under the dynamic-melting coupling during the spring thaw period, and obtaining simulation data including the cementation bond fracture rate, force chain non-uniformity and settlement rate; S4, by conducting correlation analysis on the cement bond fracture rate, force chain non-uniformity and settlement rate, a roadbed disease assessment index is generated, and the disease assessment index is compared with the preset threshold value. Based on the comparison result, the risk of roadbed mud and slurry disease is assessed.

[0007] Furthermore, the establishment of the discontinuous graded bonding contact model is specifically as follows: based on the discrete element method, the ballast particles are modeled as polyhedral units, and the bonding bonds between the dirty fine particles and the ballast are characterized by a parallel bonding model; The temperature-stiffness coupling factor and temperature-strength coupling factor are introduced, and the specific expressions are as follows: ; In the formula, is the temperature-stiffness coupling factor, is the real-time temperature of the environment where the track bed is located. is the reference temperature, is the reference temperature The initial stiffness under is a natural constant, is the first temperature attenuation coefficient, which is used to characterize the attenuation rate of the adhesive bond stiffness with increasing temperature and is calibrated through experiments; is the temperature-intensity coupling factor, is the reference temperature The initial strength under is the second temperature attenuation coefficient, which is used to characterize the attenuation rate of the bonding strength with increasing temperature and is calibrated through experiments; and The calibration method is: using a high-precision bidirectional loading tester, shear test is performed on dirty ballast samples with fixed dirt content in the range of -10℃ to 20℃, at intervals of 5℃, to measure the bond stiffness when the bond is destroyed. and bond strength , and through nonlinear regression fitting, determine and ; The contact force between particles is expressed as follows: ; In the formula, is the contact force between particles, is the relative displacement between particles, i.e., the overlapping displacement, Represents the contact area.

[0008] Furthermore, a large triaxial experimental device with zoned stepped temperature control is used to obtain the mechanical response data of dirty ballast samples under different temperature gradients, dirt contents and dynamic loads. The mechanical response data include dynamic stress amplitude, cumulative energy dissipation, and failure stress, temperature and moisture content when the sample is destroyed. The temperature gradient ranges from [-10°C, 20°C], the dirt content ranges from 5% to 20%, specifically the mass ratio of dirt fine particles to the dirty ballast sample, the frequency range of the dynamic load is 1-5 Hz, and the amplitude range is 50-200 kPa; Based on the plastic shakedown theory, the critical dynamic strain calculation model is constructed using mechanical response data. The formula is as follows: ; In the formula, is the critical dynamic strain, that is, the dynamic strain recorded when the sample is destroyed. is the dynamic stress amplitude, is the reference stress, is the moisture content, is the temperature, is the reference temperature, is the cumulative energy dissipation, As the reference energy consumption, through test calibration, , , , and are the fitting coefficients, determined by nonlinear regression; The cumulative energy dissipation The calculation formula is as follows: ; In the formula, is the strain rate, i.e. the time derivative of strain, Indicates loading time, is the function of strain changing with time, represents a sinusoidal oscillating load, is a sine function, is the dynamic stress amplitude, and The range is 50-200kPa, is the circumference of a circle, is the frequency, and , unit is Hz.

[0009] Furthermore, combining the bonding contact model and the critical dynamic strain calculation model, a roadbed structure simulation model is established based on the discrete element method. The ballast particles are modeled as polyhedral units, and the dirty fine particles are simplified as small spheres, which are filled in the ballast gaps according to the preset gradation. A bonding bond is generated at the particle contact point, and its stiffness is and strength According to real-time temperature Dynamic update, applying sinusoidal fluctuating loads on the top of the model, setting the temperature gradient field to simulate the melting process during the spring thaw, monitoring the cementation bond fracture rate, force chain non-uniformity and settlement rate; The preset gradation refers to a mass ratio of fine dirt particles to ballast particles ranging from 5% to 20%; The temperature gradient field is [-10℃, 20℃]; The sinusoidal undulating load The expression is as follows: ; In the formula, is a sine function, is the dynamic stress amplitude, and The range is 50-200kPa, is the circumference of a circle, is the frequency, and , in Hz, Indicates loading time.

[0010] Furthermore, the specific logic of monitoring the cement bond fracture rate, force chain non-uniformity and sedimentation rate is as follows: during the simulation process, the number of cement bonds that are broken in each calculation step is counted, and the ratio is calculated with the total number of initial cement bonds as the cement bond fracture rate, that is: ; In the formula, is the cementation bond breakage rate, is the number of fracture bonds, when the sinusoidal load Exceeding contact force When the fracture is determined, is the total number of cementation bonds generated when the model is initialized; the calculation step is the time increment of each iteration; The force chain non-uniformity is calculated according to the following formula: : ; In the formula, is the average contact force, is the total number of bonding bonds generated when the model is initialized. For the The contact force at each contact point, is the index of the contact point, is the standard deviation of the contact force, which is used to characterize the degree of discreteness of the force chain distribution. is the force chain non-uniformity; Select the center area at the top of the model. The particle array is used as a representative particle, the sedimentation rate of each particle is calculated, and the sedimentation rate of all representative particles is averaged to characterize the overall sedimentation rate; The formula for calculating the sedimentation rate is as follows: ; In the formula, is the sedimentation rate, is the dynamic stress amplitude, is the critical dynamic strain, is the proportionality factor, determined according to the material properties, and .

[0011] Furthermore, the correlation analysis of the cement bond fracture rate, force chain non-uniformity and settlement rate was carried out to generate a disease assessment index for characterizing the risk of mud and mud oozing disease in the roadbed. The formula is as follows: ; In the formula, is the disease assessment index, is the cementation bond breakage rate, is the force chain non-uniformity, is the sedimentation rate, is a natural constant, , and are preset weights, determined according to the analytic hierarchy process.

[0012] Furthermore, according to the analytic hierarchy process, , and The specific logic is: The three indicators of cement bond fracture rate, force chain non-uniformity and sedimentation rate are marked, and the relative importance values ​​between them are determined by the nine-scale method to construct a judgment matrix, in which the cement bond fracture rate is marked as 1, the force chain non-uniformity is marked as 2, and the sedimentation rate is marked as 3. The constructed judgment matrix is: ; in, , denotes the index of the index, and , , Indicates that the index is The index relative to the index is The index importance of , the importance is scaled from 1 to 9, and The larger the value, the higher the index. The index is compared to the index The greater the importance of the index, , ; Each element value in the judgment matrix is ​​divided by the sum of its columns to obtain the normalized normalized judgment matrix. The mean of the element values ​​in each row of the normalized judgment matrix is ​​calculated, and the mean of the element values ​​in the first row is used as the weight of the cementation bond fracture rate, the mean of the element values ​​in the second row is used as the weight of the force chain non-uniformity, and the mean of the element values ​​in the third row is used as the weight of the sedimentation rate. With the constraint that the sum of the scaled values ​​is equal to 1, the three weights are scaled in equal proportions, and the scaled weights are used as the proportional coefficients of the corresponding exponents.

[0013] Furthermore, the disease assessment index With preset threshold The specific logic for comparison is as follows: when When , it is judged as a low risk level, indicating that the current roadbed condition is relatively good, and the cementation bond fracture rate, force chain non-uniformity and settlement rate are all within an acceptable range; when When the risk level is medium, it means that the roadbed has a certain degree of disease risk. Monitoring and evaluation measures should be taken and maintenance should be carried out when necessary. when It is judged as a high-risk level, indicating that the current roadbed has a high risk of mud and mud disease, and the bond fracture rate, force chain non-uniformity and settlement rate have reached dangerous levels. It is necessary to conduct an immediate on-site assessment and inspection and take emergency maintenance measures.

[0014] Furthermore, the preset threshold The calibration method is: ; In the formula, is the basic risk threshold, determined by expert assessment method, is the real-time temperature of the environment where the track bed is located. is the moisture content; and is a step function, hour, ,otherwise ,exist hour, ,otherwise .

[0015] The present invention further provides a device for identifying dirty roadbed diseases during the spring thaw period, wherein the device for identifying dirty roadbed diseases during the spring thaw period is used to execute the above-mentioned method for identifying dirty roadbed diseases during the spring thaw period, and comprises: The discontinuous graded ligand bonding contact model construction module is based on the discrete element simulation method to establish the discontinuous graded ligand bonding contact model, and introduce the temperature-stiffness coupling factor and the temperature-strength coupling factor into the model. The temperature-stiffness coupling factor and the temperature-strength coupling factor are used to characterize the dynamic effects of melting on the bonding bond stiffness and bonding bond strength respectively. The critical dynamic strain calculation model construction module is used to obtain the mechanical response data of dirty ballast under different temperature gradients, dirt content and dynamic loads through a zoned stepped temperature control large triaxial experimental device, and to construct a critical dynamic strain calculation model based on the plastic shakedown theory using the mechanical response data; The module for building a simulation model of the roadbed structure is used to build a simulation model of the roadbed structure by combining the cementation contact model and the critical dynamic strain calculation model, simulate the microscopic contact behavior of the roadbed under the dynamic-melting coupling during the spring thaw period, and obtain simulation data including the cementation bond fracture rate, force chain non-uniformity and settlement rate; The disease risk assessment module is used to generate a roadbed disease assessment index by performing correlation analysis on the cement bond fracture rate, force chain non-uniformity and settlement rate, compare the disease assessment index with a preset threshold, and assess the risk of roadbed mud and slurry disease based on the comparison results.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a scientific and systematic evaluation mechanism by introducing discrete element simulation and zoned stepped temperature-controlled large triaxial experiments. Specifically, based on the dynamic model of temperature-stiffness coupling factor and temperature-strength coupling factor, the stiffness and strength of the cementing bond can reflect the changes in ambient temperature in real time, thereby effectively capturing the microscopic contact behavior of the ballast under different conditions. This dynamic monitoring method can timely identify the fracture rate and force chain non-uniformity of the cementing bond inside the ballast, revealing the potential risk of mud and mud oozing.

[0017] By comparing the generation of the disease assessment index with the preset threshold, the roadbed status can be subdivided into low, medium and high risk levels. This clear risk classification provides a practical basis for subsequent maintenance and management, ensuring that preventive measures are taken in time before potential risks occur, reducing the possibility of roadbed failure. In addition, the flexibility and adaptability of this method make the assessment results more realistic and provide strong technical support for the safe operation of the roadbed. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the overall method flow of the present invention; Figure 2 It is a schematic diagram of the overall device module of the present invention. DETAILED DESCRIPTION

[0019] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0020] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0021] Example: See also Figure 1 , the present invention provides a technical solution: A method for identifying dirty roadbed diseases during spring thaw period, the specific steps comprising: S1, based on the discrete element simulation method, a discontinuous graded ligand bond contact model is established, and the temperature-stiffness coupling factor and temperature-strength coupling factor are introduced into the model. The temperature-stiffness coupling factor and temperature-strength coupling factor are used to characterize the dynamic effects of melting on the bond stiffness and bond strength respectively; In this embodiment, the discontinuous graded bond contact model is established by: based on the discrete element method, the ballast particles are modeled as polyhedral units, and the bonding bonds between the dirty fine particles and the ballast are characterized by a parallel bonding model; The temperature-stiffness coupling factor and temperature-strength coupling factor are introduced, and the specific expressions are as follows: ; In the formula, is the temperature-stiffness coupling factor, is the real-time temperature of the environment where the ballast bed is located, and The range is from -10℃ to 20℃, which is used to simulate the temperature changes during the spring thaw period; The reference temperature is 0°C, the freezing point in this embodiment. is the reference temperature The initial stiffness under is a natural constant, is the first temperature attenuation coefficient, which is used to characterize the attenuation rate of the adhesive bond stiffness with increasing temperature and is calibrated through experiments; is the temperature-intensity coupling factor, is the reference temperature The initial strength under is the second temperature attenuation coefficient, which is used to characterize the attenuation rate of the bonding strength with increasing temperature and is calibrated through experiments; Temperature-stiffness coupling factor and the temperature-intensity coupling factor It is used to quantify the dynamic effect of temperature changes on the mechanical properties of the bond, and to characterize the effect of temperature changes on the stiffness and strength of the bond. When the temperature rises, the material will undergo thermal expansion, causing changes in its microstructure. The molecular motion of the bonding material is enhanced, resulting in an increase in the microscopic contact surface of the bond, which in turn reduces the overall stiffness and strength. Exponential functions are often used in physics and engineering to describe material properties that change with time or temperature. This form can effectively capture the rapid changes in material stiffness and strength within a specific temperature range. By introducing a reference temperature , the formula can compare the temperature change relative to a known benchmark. This method helps to determine the mechanical properties of the cementitious bond under specific temperature conditions, so the stiffness and strength of the cementitious bond decay exponentially with increasing temperature. The exponential decay function is used to simulate the nonlinear decay of the cementitious bond performance with increasing temperature, which more realistically reflects the weakening effect of temperature fluctuations during the spring thaw on the microstructure of the ballast.

[0022] and The calibration method is: using a high-precision bidirectional loading tester, shear test is performed on dirty ballast samples with fixed dirt content in the range of -10℃ to 20℃, at intervals of 5℃, to measure the bond stiffness when the bond is destroyed. and bond strength , and through nonlinear regression fitting, determine and ; The contact force between particles is expressed as follows: ; In the formula, is the contact force between particles, is the relative displacement between particles, i.e., the overlapping displacement, Represents the contact area.

[0023] The advantage of step S1 is that the introduction of temperature-stiffness coupling factor and temperature-strength coupling factor enables the stiffness and strength of the cementitious bond to dynamically reflect changes in ambient temperature. This method effectively overcomes the defect of traditional disease identification technology that is insufficiently responsive to environmental changes, and can more realistically simulate the actual mechanical behavior of dirty roadbeds during the spring thaw period, greatly improving the accuracy and reliability of disease identification. In this scheme, the use of this step can provide a scientific and dynamic evaluation basis for the overall scheme, making the subsequent acquisition of mechanical response data and the construction of critical dynamic strain calculation models more in line with actual conditions. By accurately simulating the microscopic contact behavior of the roadbed, key data support can be provided for the subsequent generation of disease assessment indexes, thereby comprehensively improving the scientificity and effectiveness of roadbed disease risk assessment and ensuring that maintenance measures can be taken in time before potential risks arise.

[0024] S2, obtain the mechanical response data of dirty ballast under different temperature gradients, dirt content and dynamic loads through a zoned stepped temperature-controlled large triaxial experimental device, and use the mechanical response data to build a critical dynamic strain calculation model based on the plastic shakedown theory; In this embodiment, a large triaxial experimental device with zoned stepped temperature control is used to obtain mechanical response data of dirty ballast samples under different temperature gradients, dirt contents and dynamic loads. The mechanical response data includes dynamic stress amplitude, cumulative energy dissipation, and failure stress, temperature and moisture content when the sample is destroyed. The temperature gradient ranges from [-10°C, 20°C], and a temperature test point is set every 5°C. The specific temperature test points include: -10°C, -5°C, 0°C, 5°C, 0°C, 15°C, and 20°C; The dirt content ranges from 5% to 20%, specifically the mass ratio of dirt fine particles to the dirty ballast sample. The specific dirt content test points include: 5%, 10%, 15%, and 20%; The moisture content ranges from 5% to 20%, and the specific moisture content test points include: 5%, 10%, 15%, and 20%; The frequency range of dynamic load is 1-5Hz, the amplitude range is 50-200kPa, and an amplitude point is set every 50kPa. The specific amplitude points include: 50kPa, 100kPa, 150kPa, 200kPa; The different dirt content and temperature test points were randomly combined to produce multiple groups of dirty ballast specimens. The temperature of the experimental device was adjusted to the required experimental gradient and kept stable. The preset dynamic load was applied and the stress and strain data under different amplitudes, frequencies and moisture contents were recorded. Under each experimental condition, the dynamic stress amplitude, cumulative energy dissipation, failure stress, temperature and moisture content were recorded in real time. Multiple experiments were carried out under different temperatures and dirt content conditions to obtain mechanical response data to construct a critical dynamic strain calculation model.

[0025] Based on the plastic shakedown theory, the critical dynamic strain calculation model is constructed using mechanical response data. The formula is as follows: ; In the formula, is the critical dynamic strain, that is, the dynamic strain recorded when the sample is destroyed. is the dynamic stress amplitude, which refers to the amplitude of the instantaneous maximum stress applied to the structure; is the reference stress, is the moisture content, is the temperature, that is, the temperature at which the sample is destroyed, is the reference temperature, is the cumulative energy dissipation, As the reference energy consumption, through test calibration, , , , and are the fitting coefficients, determined by nonlinear regression, and , , , , .

[0026] In this formula, the critical dynamic strain It is used to characterize the threshold strain of dirty ballast transitioning from stable deformation to accelerated damage under the coupling of cyclic dynamic load and temperature. It is considered that the soil has entered the unstable deformation stage and the risk of mud and slurry has increased significantly. Used to characterize the effect of dynamic load on critical strain, index Reflects the nonlinear effect of dynamic stress, where , which is consistent with the law of "stress increase leads to critical strain decrease" in the plastic shakedown theory; The term is used to quantify the softening effect of moisture content on ballast, where , indicating that the increase of water content will reduce the critical strain, which is consistent with the experimental phenomenon of strength attenuation of saturated ballast; Item describes the weakening effect of increased temperature on cementitious bonds during the spring thaw period; The term reflects the amplification effect of the cumulative damage on the critical strain, and the cumulative energy dissipation The formula directly characterizes the plastic work under cyclic loading. This formula is used to predict the failure threshold strain of ballast under dynamic loading, integrating dynamic stress amplitude, moisture content, temperature and cumulative energy dissipation, and quantifying the impact of the complex environment during the spring thaw on the stability of the roadbed.

[0027] The cumulative energy dissipation The calculation formula is as follows: ; In the formula, is the strain rate, i.e. the time derivative of strain, Indicates loading time, is the function of strain changing with time, represents a sinusoidal oscillating load, is a sine function, is the dynamic stress amplitude, and The range is 50-200kPa, is the circumference of a circle, is the frequency, and , unit is Hz.

[0028] The advantage of step S2 is that by using a large triaxial test device with zoned stepped temperature control, the mechanical response data of dirty ballast under different temperature gradients, dirt content and dynamic loads can be obtained, so that the mechanical behavior of the roadbed can be accurately analyzed. This method provides a more detailed dynamic performance evaluation than traditional static testing, making the response of the roadbed material under actual working conditions more realistic, and can effectively reveal the causes of roadbed diseases during the spring thaw period.

[0029] In this solution, this step can provide key experimental data support for the overall solution, making the construction of the critical dynamic strain calculation model more scientific and reasonable. The acquisition of this experimental data not only improves the accuracy of the subsequent simulation model, but also ensures the comprehensiveness and reliability of the roadbed disease assessment. By combining the changes in dynamic loads and environmental conditions, this step provides an empirical basis for disease assessment, so that the risk of roadbed mud and mud can be more effectively predicted and assessed, ensuring the safe operation of railways and highways.

[0030] S3, a simulation model of the ballast structure is established by combining the cementation contact model and the critical dynamic strain calculation model, simulating the microscopic contact behavior of the ballast under the dynamic-melting coupling during the spring thaw period, and obtaining simulation data including the cementation bond fracture rate, force chain non-uniformity and settlement rate; In this embodiment, the bond contact model and the critical dynamic strain calculation model are combined to establish a roadbed structure simulation model based on the discrete element method. The ballast particles are modeled as polyhedral units, and the dirty fine particles are simplified as small spheres, which are filled in the ballast gaps according to the preset gradation. The bond bonds are generated at the particle contact points, and their stiffness is and strength According to real-time temperature Dynamic update, applying sinusoidal fluctuating loads on the top of the model, setting the temperature gradient field to simulate the melting process during the spring thaw, monitoring the cementation bond fracture rate, force chain non-uniformity and settlement rate; The preset gradation refers to a mass ratio of fine dirt particles to ballast particles ranging from 5% to 20%; The temperature gradient field is [-10℃, 20℃]; The sinusoidal undulating load The expression is as follows: ; In the formula, is a sine function, is the dynamic stress amplitude, and The range is 50-200kPa, is the circumference of a circle, is the frequency, and , in Hz, Indicates loading time.

[0031] The specific logic of monitoring the cement bond fracture rate, force chain non-uniformity and sedimentation rate is as follows: during the simulation process, the number of cement bonds that are broken in each calculation step is counted, and the ratio is calculated with the total number of initial cement bonds as the cement bond fracture rate, that is: ; In the formula, is the cementation bond fracture rate, is the number of fracture bonds, when the sinusoidal load Exceeding contact force When the fracture is determined, is the total number of bonding bonds generated when the model is initialized; the calculation step size is the time increment of each iteration.

[0032] Bond breakage rate It directly reflects the degree of damage to the connection structure between ballast particles. When the fracture rate increases, the mechanical transmission capacity between particles decreases significantly, resulting in a decrease in the overall stiffness of the roadbed. This process will cause two key problems: first, the roadbed's ability to resist deformation is weakened, and it is more likely to accumulate plastic deformation under the dynamic load of the train; second, the microcracks formed by the fracture provide channels for water penetration and fine particle migration, significantly increasing the risk of mud spillage. Existing experimental data show that when the cement bond fracture rate exceeds 30%, the elastic modulus of the roadbed may drop by more than 50%.

[0033] The force chain non-uniformity is calculated according to the following formula: : ; In the formula, is the average contact force, is the total number of bonding bonds generated when the model is initialized. For the The contact force at each contact point, is the index of the contact point, is the standard deviation of the contact force, which is used to characterize the degree of discreteness of the force chain distribution. is the force chain non-uniformity.

[0034] Force chain non-uniformity Characterizes the degree of balance of contact force distribution between ballast particles. Increased non-uniformity means obvious stress concentration in the force chain network. This uneven distribution will bring about three effects: particles in the stress concentration area are more likely to break or slip, accelerating local settlement; the discontinuous distribution of force chains weakens the overall stability of the roadbed and may cause sudden deformation; under long-term action, high non-uniformity will lead to anisotropy of the roadbed structure, manifested as rapid deterioration of track geometry. Monitoring data show that when the non-uniformity exceeds 0.4, the service performance of the roadbed will drop sharply. Force chain non-uniformity The calculation of is based on the statistical standard deviation concept, is the standard deviation of the contact force, indicating the degree of discreteness of the contact force, is the average contact force, and the ratio eliminates the dimension effect and facilitates comparison across models.

[0035] Select the center area at the top of the model. The particle array is used as a representative particle, the sedimentation rate of each particle is calculated, and the sedimentation rate of all representative particles is averaged to characterize the overall sedimentation rate; The formula for calculating the sedimentation rate is as follows: ; In the formula, is the sedimentation rate, is the dynamic stress amplitude, is the critical dynamic strain, is the proportionality factor, determined according to the material properties, and .

[0036] Dynamic stress amplitude It is the amplitude of the instantaneous maximum stress applied to the ballast structure. When the structure is subjected to greater dynamic stress, the internal stress state will intensify, promoting the sliding and displacement between particles, thereby accelerating the sedimentation process. As the sedimentation rate increases, will increase accordingly; when the critical dynamic strain increases, it means that the structure's resistance to deformation is enhanced, and the structure can continue to settle under higher stress, resulting in an increase in the settlement rate; that is, , and sedimentation rate There is a positive correlation.

[0037] Sedimentation rate It is the most intuitive macroscopic indicator for evaluating the status of the ballast bed. It refers to the sinking speed of particles under dynamic loads, reflecting the settlement behavior of particles under specific conditions. This rate is an important indicator for evaluating the stability and safety of ballast bed materials during the spring thaw period. An increase in the rate often indicates three potential problems: the fracture of cementation bonds and the reconstruction of force chains have developed to a macroscopically visible stage; the foundation below the ballast layer may soften or erode; the failure of the drainage system leads to an increase in pore water pressure. These problems will significantly increase the risk of mud bubbling.

[0038] The advantage of step S3 is that, by combining the bonding contact model and the critical dynamic strain calculation model, the simulation model of the ballast structure is established based on the discrete element method, which can more realistically simulate the microscopic contact behavior of the ballast during the spring thaw period. This method effectively integrates the physical model with the experimental data, improves the accuracy of the simulation results, and makes the evaluation of the internal mechanical state of the ballast more comprehensive. This dynamic simulation can not only capture important parameters such as the fracture rate of the bonding bond, the non-uniformity of the force chain, and the sedimentation rate, but also better understand the response characteristics of the ballast under different environmental conditions. In this scheme, the use of this step can provide key simulation data support for the overall scheme, so that the accuracy and effectiveness of disease identification are comprehensively improved. By deeply analyzing the dynamic behavior of the ballast during the spring thaw period, the potential risks of mud and mud diseases can be better predicted and identified. This process not only helps to formulate more effective maintenance strategies, but also provides a solid theoretical basis for subsequent risk assessment and management, thereby ensuring the safe operation of railways and highways in practical applications.

[0039] S4, by conducting correlation analysis on the cement bond fracture rate, force chain non-uniformity and settlement rate, a roadbed disease assessment index is generated, the disease assessment index is compared with a preset threshold, and based on the comparison result, the risk of roadbed mud and mud disease is assessed; In this embodiment, a correlation analysis is performed on the cement bond fracture rate, the force chain non-uniformity and the settlement rate to generate a disease assessment index for characterizing the risk of mud swell and mud swell in the ballast bed. The formula is as follows: ; In the formula, It is a disease assessment index used to quantify the risk of mud and mud on the roadbed. The index comprehensively considers multiple influencing factors such as the cement bond fracture rate, force chain non-uniformity and settlement rate to evaluate the health status of the entire roadbed. is the cementation bond fracture rate, is the force chain non-uniformity, is the sedimentation rate, is a natural constant, , and are preset weights, determined according to the analytic hierarchy process.

[0040] Disease Assessment Index It is used to characterize the risk of muddy roadbed. The larger the value, the higher the risk of muddy roadbed. , which can effectively predict the possible diseases of the roadbed and help engineers and maintenance personnel formulate corresponding maintenance and reinforcement measures to improve the safety and service life of the roadbed. In addition, the quantitative form of the evaluation index is also conducive to comparison between different construction or maintenance schemes. The three parameters of the bond fracture rate, force chain non-uniformity and settlement rate in the formula characterize the damage state of the roadbed from different scales: the bond fracture rate directly reflects the integrity of the microscopic connection structure. The higher the bond fracture rate, the worse the connectivity of the roadbed material, which may lead to a higher risk of disease. The force chain non-uniformity characterizes the balance of microscopic mechanical transmission. The force chain non-uniformity reflects the distribution of internal forces in the material. The higher the non-uniformity, the worse the bearing capacity and stability of the material, which increases the possibility of disease. The settlement rate reflects the development trend of macroscopic deformation. The settlement rate directly affects the stability of the roadbed material. The higher the settlement rate, the more unstable the material may be, further increasing the risk of disease. This combination of multi-scale parameters can fully capture the whole process of the roadbed from microscopic damage to macroscopic failure. The cement bond fracture rate adopts a linear term to reflect its direct proportional relationship with the risk of the disease; the force chain non-uniformity adopts a square term to highlight the nonlinear influence of its stress concentration effect; the settlement rate adopts an exponential term to accurately capture the mutation characteristics of the settlement acceleration stage. This design not only conforms to the physical meaning of each parameter, but also can amplify the sensitivity of high-risk signals. Since it has been explained in the previous article that the increase of the cement bond fracture rate, force chain non-uniformity or settlement rate will lead to an increase in the risk of mud and mud on the roadbed, it will not be repeated here.

[0041] According to the analytic hierarchy process , and The specific logic is: The three indicators of cement bond fracture rate, force chain non-uniformity and sedimentation rate are marked, and the relative importance values ​​between them are determined by the nine-scale method to construct a judgment matrix, in which the cement bond fracture rate is marked as 1, the force chain non-uniformity is marked as 2, and the sedimentation rate is marked as 3. The constructed judgment matrix is: ; in, , denotes the index of the index, and , , Indicates that the index is The index relative to the index is The index importance of , the importance is scaled from 1 to 9, and The larger the value, the higher the index. The index is compared to the index The greater the importance of the index, , ; Each element value in the judgment matrix is ​​divided by the sum of its columns to obtain the normalized normalized judgment matrix. The mean of the element values ​​in each row of the normalized judgment matrix is ​​calculated, and the mean of the element values ​​in the first row is used as the weight of the cementation bond fracture rate, the mean of the element values ​​in the second row is used as the weight of the force chain non-uniformity, and the mean of the element values ​​in the third row is used as the weight of the sedimentation rate. With the constraint that the sum of the scaled values ​​is equal to 1, the three weights are scaled in equal proportions, and the scaled weights are used as the proportional coefficients of the corresponding exponents.

[0042] Disease Assessment Index With preset threshold The specific logic for comparison is as follows: when When , it is judged as a low risk level, indicating that the current roadbed condition is relatively good, and the cementation bond fracture rate, force chain non-uniformity and settlement rate are all within an acceptable range; when When the risk level is medium, it means that the roadbed has a certain degree of disease risk. Monitoring and evaluation measures should be taken and maintenance should be carried out when necessary. when It is judged as a high-risk level, indicating that the current roadbed has a high risk of mud and mud disease, and the bond fracture rate, force chain non-uniformity and settlement rate have reached dangerous levels. It is necessary to conduct an immediate on-site assessment and inspection and take emergency maintenance measures.

[0043] Preset Threshold The calibration method is: ; In the formula, is the basic risk threshold, determined by expert assessment method, is the real-time temperature of the environment where the track bed is located. is the moisture content; and is a step function, hour, ,otherwise ,exist hour, ,otherwise .

[0044] set up The correction item is because: 10℃ is the phase change critical point of typical ballast bonding materials. After exceeding this temperature, the bonding strength will decay rapidly. The coefficient 0.2 corresponds to the threshold value that needs to be lowered by 20% when the temperature rises from 10 degrees Celsius to 20 degrees Celsius. Set The correction term is because: 10% moisture content is the critical moisture content of ballast performance. When this value is exceeded, the lubrication effect of water significantly reduces the friction coefficient between particles, forming a synergistic effect with the temperature correction; and the form of the step function simplifies the calculation and meets the needs of engineering applications.

[0045] The advantage of step S4 is that by performing correlation analysis on the cement bond fracture rate, force chain non-uniformity and sedimentation rate, a disease assessment index of the roadbed can be generated. Compared with the prior art, this method can comprehensively consider multiple mechanical indicators to form a unified evaluation index, thereby improving the accuracy and effectiveness of disease identification. This comprehensive analysis makes the performance evaluation of the roadbed not only rely on a single indicator, avoids the one-sidedness that may appear in traditional methods, and provides a more comprehensive and scientific basis for subsequent maintenance decisions. In this scheme, the use of this step can provide a key risk assessment tool for the overall scheme, ensuring that the potential disease risks of the roadbed can be identified and assessed in time during the spring thaw period. By comparing the disease assessment index with the preset threshold, the health status of the roadbed can be quickly judged, and corresponding monitoring and maintenance measures can be taken according to the risk level. This decision support mechanism can effectively reduce maintenance costs, improve the safety and reliability of the roadbed, and thus ensure the safe operation of railways and highways in practical applications.

[0046] See also Figure 2 , a device for identifying dirty roadbed diseases during spring thaw period, comprising: The discontinuous graded ligand bonding contact model construction module is based on the discrete element simulation method to establish the discontinuous graded ligand bonding contact model, and introduce the temperature-stiffness coupling factor and the temperature-strength coupling factor into the model. The temperature-stiffness coupling factor and the temperature-strength coupling factor are used to characterize the dynamic effects of melting on the bonding bond stiffness and bonding bond strength respectively. The critical dynamic strain calculation model construction module is used to obtain the mechanical response data of dirty ballast under different temperature gradients, dirt content and dynamic loads through a zoned stepped temperature control large triaxial experimental device, and to construct a critical dynamic strain calculation model based on the plastic shakedown theory using the mechanical response data; The module for building a simulation model of the roadbed structure is used to build a simulation model of the roadbed structure by combining the cementation contact model and the critical dynamic strain calculation model, simulate the microscopic contact behavior of the roadbed under the dynamic-melting coupling during the spring thaw period, and obtain simulation data including the cementation bond fracture rate, force chain non-uniformity and settlement rate; The disease risk assessment module is used to generate a roadbed disease assessment index by performing correlation analysis on the cement bond fracture rate, force chain non-uniformity and settlement rate, compare the disease assessment index with a preset threshold, and assess the risk of roadbed mud and slurry disease based on the comparison results.

[0047] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0048] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0049] 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, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0050] The above description is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application.

Claims

1. A method for identifying dirty roadbed diseases during spring thaw, characterized in that: The specific steps include: S1: Based on the discrete element simulation method, a discontinuous graded ligand bond contact model is established, and the temperature-stiffness coupling factor and temperature-strength coupling factor are introduced into the model. The temperature-stiffness coupling factor and temperature-strength coupling factor are used to characterize the dynamic effects of melting on the bond stiffness and bond strength respectively; S2: The mechanical response data of dirty ballast under different temperature gradients, dirt content and dynamic loads are obtained through a zoned stepped temperature-controlled large triaxial test device, and the critical dynamic strain calculation model is constructed based on the plastic shakedown theory using the mechanical response data; S3: A simulation model of the ballast structure is established by combining the cementation contact model and the critical dynamic strain calculation model to simulate the microscopic contact behavior of the ballast under the dynamic-melting coupling during the spring thaw period, and obtain simulation data including the cementation bond fracture rate, force chain non-uniformity and settlement rate; S4: Generate a ballast bed disease assessment index by performing correlation analysis on the cement bond fracture rate, force chain non-uniformity and settlement rate. Compare the disease assessment index with the preset threshold value and evaluate the risk of ballast bed mud and slurry disease based on the comparison result.

2. A method for identifying dirty roadbed diseases during spring thaw period according to claim 1, characterized in that: The discontinuous graded bonding contact model is established by: based on the discrete element method, the ballast particles are modeled as polyhedral units, and the bonding bonds between the dirty fine particles and the ballast are characterized by a parallel bonding model; The temperature-stiffness coupling factor and temperature-strength coupling factor are introduced, and the specific expressions are as follows: ； In the formula, is the temperature-stiffness coupling factor, is the real-time temperature of the environment where the track bed is located. is the reference temperature, is the reference temperature The initial stiffness under is a natural constant, is the first temperature attenuation coefficient, which is used to characterize the attenuation rate of the adhesive bond stiffness with increasing temperature and is calibrated through experiments; is the temperature-intensity coupling factor, is the reference temperature The initial strength under is the second temperature attenuation coefficient, which is used to characterize the attenuation rate of the bonding strength with increasing temperature and is calibrated through experiments; and The calibration method is: using a high-precision bidirectional loading tester, shear test is performed on dirty ballast samples with fixed dirt content in the range of -10℃ to 20℃, at intervals of 5℃, to measure the bond stiffness when the bond is destroyed. and bond strength , and through nonlinear regression fitting, determine and ; The contact force between particles is expressed as follows: ； In the formula, is the contact force between particles, is the relative displacement between particles, i.e., the overlapping displacement, Represents the contact area.

3. A method for identifying dirty roadbed diseases during spring thaw period according to claim 1, characterized in that: A zoned stepped temperature-controlled large triaxial test device is used to obtain the mechanical response data of dirty ballast samples under different temperature gradients, dirt contents and dynamic loads. The mechanical response data include dynamic stress amplitude, cumulative energy dissipation, and failure stress, temperature and moisture content when the sample is destroyed. The temperature gradient ranges from [-10°C, 20°C], the dirt content ranges from 5% to 20%, specifically the mass ratio of dirt fine particles to the dirty ballast sample, the frequency range of the dynamic load is 1-5 Hz, and the amplitude range is 50-200 kPa; Based on the plastic shakedown theory, the critical dynamic strain calculation model is constructed using mechanical response data. The formula is as follows: ； In the formula, is the critical dynamic strain, that is, the dynamic strain recorded when the sample is destroyed. is the dynamic stress amplitude, is the reference stress, is the moisture content, is the temperature, is the reference temperature, is the cumulative energy dissipation, As the reference energy consumption, through test calibration, , , , and are the fitting coefficients, determined by nonlinear regression; The cumulative energy dissipation The calculation formula is as follows: ； In the formula, is the strain rate, i.e. the time derivative of strain, Indicates loading time, is the function of strain changing with time, represents a sinusoidal oscillating load, is a sine function, is the dynamic stress amplitude, and The range is 50-200kPa, is the circumference of a circle, is the frequency, and , unit is Hz.

4. A method for identifying dirty roadbed diseases during spring thaw period according to claim 1, characterized in that: Combining the bonding contact model and the critical dynamic strain calculation model, a roadbed structure simulation model was established based on the discrete element method to simulate the microscopic contact behavior of the roadbed under the dynamic-melting coupling during the spring thaw period, and obtain simulation data including the bonding bond fracture rate, force chain non-uniformity and settlement rate. The ballast particles are modeled as polyhedral units, and the fine dirt particles are simplified as small spheres, which are filled into the ballast gaps according to the preset gradation; a bonding bond is generated at the particle contact point, and its stiffness and strength According to real-time temperature Dynamic update, applying sinusoidal fluctuating loads on the top of the model, setting the temperature gradient field to simulate the melting process during the spring thaw, monitoring the cementation bond fracture rate, force chain non-uniformity and settlement rate; The preset gradation refers to a mass ratio of fine dirt particles to ballast particles ranging from 5% to 20%; The temperature gradient field is [-10℃, 20℃]; The sinusoidal undulating load The expression is as follows: ； In the formula, is a sine function, is the dynamic stress amplitude, and The range is 50-200kPa, is the circumference of a circle, is the frequency, and , in Hz, Indicates loading time.

5. A method for identifying dirty roadbed diseases during spring thaw period according to claim 4, characterized in that: The specific logic of monitoring the cement bond fracture rate, force chain non-uniformity and sedimentation rate is as follows: during the simulation process, the number of cement bonds that are broken in each calculation step is counted, and the ratio is calculated with the total number of initial cement bonds as the cement bond fracture rate, that is: ； In the formula, is the cementation bond breakage rate, is the number of fracture bonds, when the sinusoidal load Exceeding contact force When the fracture is determined, is the total number of cementation bonds generated when the model is initialized; the calculation step is the time increment of each iteration; The force chain non-uniformity is calculated according to the following formula: : ； In the formula, is the average contact force, is the total number of bonding bonds generated when the model is initialized. For the The contact force at each contact point, is the index of the contact point, is the standard deviation of the contact force, which is used to characterize the degree of discreteness of the force chain distribution. is the force chain non-uniformity; Select the center area at the top of the model. The particle array is used as a representative particle, the sedimentation rate of each particle is calculated, and the sedimentation rate of all representative particles is averaged to characterize the overall sedimentation rate; The formula for calculating the sedimentation rate is as follows: ； In the formula, is the sedimentation rate, is the dynamic stress amplitude, is the critical dynamic strain, is the proportionality factor, determined according to the material properties, and .

6. A method for identifying dirty roadbed diseases during spring thaw period according to claim 1, characterized in that: The correlation analysis of the cement bond fracture rate, force chain non-uniformity and settlement rate was carried out to generate a disease assessment index for characterizing the risk of ballast mud overflow disease. The formula is as follows: ； In the formula, is the disease assessment index, is the cementation bond fracture rate, is the force chain non-uniformity, is the sedimentation rate, is a natural constant, , and are preset weights, determined according to the analytic hierarchy process.

7. A method for identifying dirty roadbed diseases during spring thaw period according to claim 6, characterized in that: According to the analytic hierarchy process , and The specific logic is: The three indicators of cement bond fracture rate, force chain non-uniformity and sedimentation rate are marked, and the relative importance values ​​between them are determined by the nine-scale method to construct a judgment matrix, in which the cement bond fracture rate is marked as 1, the force chain non-uniformity is marked as 2, and the sedimentation rate is marked as 3. The constructed judgment matrix is: ； in, , denotes the index of the index, and , , Indicates that the index is The index relative to the index is The index importance of , the importance is scaled from 1 to 9, and The larger the value, the higher the index. The index is compared to the index The greater the importance of the index, , ; Each element value in the judgment matrix is ​​divided by the sum of its columns to obtain the normalized normalized judgment matrix. The mean of the element values ​​in each row of the normalized judgment matrix is ​​calculated, and the mean of the element values ​​in the first row is used as the weight of the cementation bond fracture rate, the mean of the element values ​​in the second row is used as the weight of the force chain non-uniformity, and the mean of the element values ​​in the third row is used as the weight of the sedimentation rate. With the constraint that the sum of the scaled values ​​is equal to 1, the three weights are scaled in equal proportions, and the scaled weights are used as the proportional coefficients of the corresponding exponents.

8. The method for identifying dirty roadbed diseases during spring thaw period according to claim 1, characterized in that: Disease Assessment Index With preset threshold The specific logic for comparison is as follows: when When , it is judged as a low risk level, indicating that the current roadbed condition is relatively good, and the cementation bond fracture rate, force chain non-uniformity and settlement rate are all within an acceptable range; when When the risk level is medium, it means that the roadbed has a certain degree of disease risk. Monitoring and evaluation measures should be taken and maintenance should be carried out when necessary. when It is judged as a high-risk level, indicating that the current roadbed has a high risk of mud and mud disease, and the bond fracture rate, force chain non-uniformity and settlement rate have reached dangerous levels. It is necessary to conduct an immediate on-site assessment and inspection and take emergency maintenance measures.

9. A method for identifying dirty roadbed diseases during spring thaw period according to claim 8, characterized in that: Preset Threshold The calibration method is: ； In the formula, is the basic risk threshold, determined by expert assessment method, is the real-time temperature of the environment where the track bed is located. is the moisture content; and is a step function, hour, ,otherwise ,exist hour, ,otherwise .

10. A device for identifying dirty roadbed diseases during spring thaw, characterized in that: The device for identifying dirty roadbed damage during spring thaw is used to execute the method for identifying dirty roadbed damage during spring thaw as claimed in any one of claims 1 to 9, comprising: The discontinuous graded ligand bonding contact model construction module is based on the discrete element simulation method to establish the discontinuous graded ligand bonding contact model, and introduce the temperature-stiffness coupling factor and the temperature-strength coupling factor into the model. The temperature-stiffness coupling factor and the temperature-strength coupling factor are used to characterize the dynamic effects of melting on the bonding bond stiffness and bonding bond strength respectively. The critical dynamic strain calculation model construction module is used to obtain the mechanical response data of dirty ballast under different temperature gradients, dirt content and dynamic loads through a zoned stepped temperature control large triaxial experimental device, and to construct a critical dynamic strain calculation model based on the plastic shakedown theory using the mechanical response data; The module for building a simulation model of the roadbed structure is used to build a simulation model of the roadbed structure by combining the cementation contact model and the critical dynamic strain calculation model, simulate the microscopic contact behavior of the roadbed under the dynamic-melting coupling during the spring thaw period, and obtain simulation data including the cementation bond fracture rate, force chain non-uniformity and settlement rate; The disease risk assessment module is used to generate a roadbed disease assessment index by performing correlation analysis on the cement bond fracture rate, force chain non-uniformity and settlement rate, compare the disease assessment index with a preset threshold, and assess the risk of roadbed mud and slurry disease based on the comparison results.

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