A method for making a decision on treatment of a ballast disconnection disease

Abstract

A kind of track bed off-joint disease management decision method, it is related to track traffic disease management technical field, including obtaining the quantization data of track bed off-joint disease in morphological dimension, functional dimension and environmental risk dimension;According to the quantization data of morphological dimension and functional dimension, determine the core risk level of disease by the preset core level determination matrix;According to the quantization data of environmental risk dimension, determine the environmental risk level of disease by the preset environmental risk determination matrix;Based on the combination of core risk level and environmental risk level, generate comprehensive early warning level;According to comprehensive early warning level, output final management scheme;It is used to solve the more general judgment of the harm degree of traditional disease, and the mapping relationship between disease diagnosis result and actual management scheme cannot be determined.

Description

Technical Field

[0001] This invention relates to the field of rail transit defect management technology, specifically to a decision-making method for managing track bed gap defects. Background Technology

[0002] Track bed separation is a common and typical defect in ballastless track structures (including high-speed railways, subways, and urban rail transit). It mainly manifests as gaps or voids between the track bed slab and the underlying supporting structure (such as bridge beams, tunnel arches, and roadbed subgrade). This defect weakens the overall integrity of the track structure and affects the stability of its geometry. Under the combined effects of train loads and environmental factors, it may further develop into mud pumping, track bed damage, or even structural instability, seriously threatening train operation safety.

[0003] Currently, existing technologies for the detection and treatment of track bed gap defects mainly focus on the following aspects: Firstly, in terms of defect detection and assessment, methods such as feeler gauges, ground-penetrating radar, and hammer impact are commonly used to measure the width, depth, and extent of joints. Based on the measurement results, qualitative or semi-quantitative classifications are made in accordance with relevant maintenance rules. However, these assessment methods are often limited to the geometric morphology of the defect itself, lacking a comprehensive consideration of functional impacts (such as deterioration of track geometry and abnormal dynamic response of the train body) and environmental risks (such as track location characteristics and groundwater seepage). This leads to one-sided assessment results that fail to accurately reflect the actual severity and development trend of the defect. Furthermore, on-site assessments often rely on the personal experience of inspection personnel, lacking standardized and quantitative judgment procedures, resulting in poor consistency of assessment results.

[0004] Secondly, in terms of treatment decisions, existing technologies typically employ relatively fixed process solutions, such as universally grouting to fill detected cracks. This "one-size-fits-all" approach fails to differentiate based on the cause, location, severity, and environmental conditions of the defects, resulting in treatment measures that are sometimes excessive (causing unnecessary cost waste for minor defects) and sometimes insufficient (treating the symptoms but not the root cause for severe or complex conditions). More importantly, current practices lack a systematic correlation between defect diagnosis and treatment selection: diagnostic results often only provide a general level (such as mild, moderate, or severe) without establishing a standardized mapping logic from diagnostic level to specific process combinations. The decision-making process heavily relies on the subjective judgment of engineers, making it difficult to guarantee the targetedness and effectiveness of treatment.

[0005] Therefore, we propose a method that can quantify the severity of disease damage and clarify the mapping relationship between disease diagnosis results and actual treatment plans. Summary of the Invention

[0006] The purpose of this invention is to provide a decision-making method for the treatment of track bed gap defects, which solves the problems of the traditional method of judging the degree of damage of defects being too general and the inability to clearly define the mapping relationship between the defect diagnosis results and the actual treatment plan.

[0007] This invention is achieved through the following technical solution: A decision-making method for the treatment of track bed gap defects includes: Obtain quantitative data on track bed gap defects in terms of morphology, function, and environmental risk. Based on quantitative data in morphological and functional dimensions, the core risk level of the disease is determined through a preset core level judgment matrix. Based on the quantitative data of environmental risk dimension, the environmental risk level of the disease is determined through a preset environmental risk judgment matrix; A comprehensive early warning level is generated based on a combination of core risk level and environmental risk level. Based on the comprehensive early warning level, the final governance plan will be output.

[0008] Furthermore, the quantitative data for the morphological dimension includes at least one of the following: joint width, joint depth, and grouting length: The quantitative data for the functional dimensions include at least one of the track static geometric parameters and the vehicle dynamic response parameters; The quantitative data for the environmental risk dimension includes location characteristics and water seepage status.

[0009] Furthermore, based on the quantitative data of morphological and functional dimensions, the core risk level of the disease is determined through a preset core level judgment matrix. The specific steps are as follows: The quantified data of the morphological dimension are compared with the preset morphological thresholds to obtain the morphological sub-levels; Each quantitative data point of the functional dimension is compared with a preset functional threshold to obtain a functional sub-level; Take the highest level from the morphological sub-level and the highest level from the functional sub-level, input them into the core level determination matrix, and output the core risk level; The core level determination matrix is ​​configured with the following priority rule: the higher the functional sub-level, the higher the output core risk level.

[0010] Furthermore, based on the quantitative data of the environmental risk dimension, the environmental risk level of the disease is determined through a preset environmental risk judgment matrix. The specific steps are as follows: Input the location characteristics and seepage status into the environmental risk assessment matrix, and output the environmental risk level; The environmental risk assessment matrix is ​​configured to output a high-risk level when the location features are special sections and the seepage status is severe. Special sections include elevated sections with a curve radius ≤ 400m, sections with a slope ≥ 30‰, the junction of open and closed tunnels, or structural deformation joints.

[0011] Furthermore, the process of generating a comprehensive early warning level based on a combination of core risk level and environmental risk level involves the following steps: Based on the core risk level and environmental risk level, query the preset comprehensive early warning response table to determine the comprehensive early warning level and the corresponding operation and maintenance strategy; The operation and maintenance strategy includes one or more of the following: routine observation, key observation, planned maintenance, priority maintenance, or emergency measures.

[0012] Furthermore, the treatment solution is composed of one or more basic process units; The basic process unit includes at least one of the following: surface sealing, pressure grouting, rebar anchoring, backfill grouting and water plugging, base dredging, and installation of lateral limiting device.

[0013] Furthermore, based on the comprehensive early warning level, the final governance plan is output, and the specific steps include: When the overall early warning level is observation level, a treatment plan centered on surface sealing will be output. When the comprehensive early warning level is maintenance level or emergency level, a treatment plan with pressure grouting as the core is output; When the defect is located in the tunnel section and is accompanied by water seepage or mud pumping, the treatment plan also includes back wall grouting to plug water and foundation dredging, which are carried out in sequence before pressure grouting.

[0014] Furthermore, the step of outputting a governance plan based on the comprehensive early warning level also includes: When the defect is located on an elevated section, the treatment plan also includes rebar anchoring performed after pressure grouting; When the defect is located on an elevated section and belongs to a special section, or when the defect is located on an elevated section and abnormal lateral displacement is detected, the treatment plan also includes installing a lateral limiting device.

[0015] Furthermore, after implementing the governance plan, the governance effect is quantitatively evaluated, and closed-loop feedback is executed based on the evaluation results; The quantitative assessment includes: conducting assessments with different cycles and contents for diseases of different core risk levels, and setting quantitative standards for compliance. The evaluation includes at least one of the following: appearance quality, grouting fullness, track geometry, and dynamic response data.

[0016] Furthermore, the closed-loop feedback includes: When the quantitative assessment of governance effectiveness fails to meet the quantitative standards, data-driven cause diagnosis is conducted. Based on the diagnostic results, output model optimization suggestions or revised governance solutions, and implement re-governance accordingly.

[0017] The technical solution of the present invention has at least the following advantages and beneficial effects: This invention discloses a decision-making method for the treatment of track bed gap defects. By simultaneously collecting quantitative data from three dimensions—morphology, function, and environmental risk—it can accurately quantify the severity of the defects from multiple angles and comprehensively, significantly improving the ability to identify the true state of the defects. Based on this, the core risk judgment matrix and environmental risk judgment matrix are used to determine the core risk level and environmental risk level, respectively, thereby generating a comprehensive early warning level that integrates the current state and the risk of deterioration. This achieves a shift from fuzzy grading to refined and standardized grading. Finally, a matching treatment plan is directly output based on the comprehensive early warning level, opening up the decision-making link between the diagnostic results and specific processes. This ensures that the selection of treatment measures accurately corresponds to the actual risk of the defects, effectively avoiding insufficient or excessive treatment, and improving the scientific and economical nature of maintenance decisions.

[0018] Furthermore, by flexibly selecting various morphological parameters such as joint width, depth, and grouting length, as well as various functional parameters such as track static geometry and vehicle dynamic response, the method can adapt to different detection conditions and data acquisition scenarios, thus enhancing its practicality.

[0019] In addition, the core risk level determination adopts the rule of prioritizing functional sub-levels to ensure that driving safety has the highest weight in decision-making. In the environmental risk determination, location characteristics and water seepage status are integrated, and the risk level of defects located in special sections such as small radius curves, steep slopes, and structural junctions and accompanied by water seepage is automatically upgraded, so that the decision-making system can fully adapt to complex operating environments.

[0020] It is worth noting that the comprehensive early warning level corresponds to a full range of operation and maintenance strategies, from routine observation to emergency measures, providing clear operational guidance for on-site work. The treatment plan adopts a modular combination of basic process units such as surface sealing, pressure grouting, rebar anchoring, backfill grouting and water plugging, foundation dredging, and lateral limiting devices. This allows for the rapid generation of standardized process sequences for different scenarios, such as mud pumping in tunnel sections and structural reinforcement in elevated sections. The introduction of lateral limiting devices effectively constrains the lateral displacement of the elevated curved sections, enhancing the long-term stability of the structure.

[0021] Furthermore, the quantitative assessment and closed-loop feedback mechanism after governance can track and verify the governance effect at different cycles, and automatically trigger cause diagnosis and solution correction when the standards are not met, forming a virtuous cycle of continuous optimization of the decision-making model, thus ensuring the long-term reliability of the system. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of a decision-making process for the treatment of track bed gap defects according to the present invention; Figure 2 This is a schematic diagram of the decision-making system for the treatment of track bed gap defects according to the present invention; Figure 3 This is a schematic diagram of a storage device structure according to the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0024] Example 1 like Figure 1 The method for decision-making regarding the treatment of track bed gap defects, as shown, includes: S1. Obtain quantitative data on track bed gap defects in terms of morphology, function, and environmental risk. Furthermore, the quantitative data for the morphological dimension includes at least one of the following: joint width, joint depth, and grouting length: The quantitative data for the functional dimensions include at least one of the track static geometric parameters and the vehicle dynamic response parameters; The quantitative data for the environmental risk dimension includes location characteristics and water seepage status.

[0025] By constructing a three-dimensional quantitative data collection system of morphology, function, and environmental risk, the morphology dimension focuses on the static physical damage characteristics of the defects, which intuitively reflects the degree of damage to the track bed structure; the function dimension focuses on the dynamic impact of the defects on the safety of track operation, which is in line with the core requirements of rail transit safety; and the environmental risk dimension focuses on the working conditions and hydrological conditions of the defects, which predicts the subsequent deterioration trend of the defects. This standardizes and digitizes the characteristics of track bed gap defects, transforming vague qualitative judgments into measurable, comparable, and traceable quantitative parameters. This avoids biases caused by human experience-based judgments and provides accurate and unified data support for subsequent risk classification, early warning determination, and matching of treatment plans, significantly improving the accuracy and consistency of subsequent decision-making.

[0026] Furthermore, the specific collection standards and grading thresholds for quantitative data in each dimension are as follows, providing a unified basis for quantitative judgment: The morphological dimension quantification data grading thresholds are as follows: Joint width W is divided into three levels: W1 ≤ 1.5mm, 1.5mm < W2 ≤ 3mm, W3 > 3mm; Joint depth D is divided into three levels: D1 ≤ distance from the edge of the track bed to the edge of the sleeper, D2 ≤ 1 / 2 track bed width, D3 > 1 / 2 track bed width; Grouting length L is divided into three levels: L1 ≤ half the length of the track bed on one side, L2 < the total length of the track bed, L3 ≥ complete on both sides. Each parameter is measured on-site using feeler gauges, steel rulers, steel tape measures, or ground-penetrating radar, and the average value of multiple measurements is taken as the final quantified data to ensure data accuracy.

[0027] Furthermore, this embodiment proposes to use the entropy weight method to achieve adaptive calculation of the morphological dimension weights, specifically as follows: Suppose that m samples were collected from a diseased section, and each sample has n indicators (including crack width, crack depth, and grouting length). Construct the original data matrix. First, the data is normalized:

[0028] Calculate the information entropy of the j-th indicator:

[0029] This leads to the weight of the j-th indicator:

[0030] Based on the above calculations, the system automatically assigns weights to the joint width, depth, and grout seepage length, forming a weighted morphological composite value. Similarly, the entropy weight method is used to calculate the weights for the track static geometric parameters and vehicle dynamic response parameters in the functional dimension, thus obtaining the comprehensive functional value. This algorithm allows the weights for each evaluation to be dynamically updated based on the sample data, avoiding the limitations of fixed thresholds.

[0031] The functional dimensions quantify the data classification thresholds: the track static geometric parameters are classified into F1 (not exceeding the maintenance standard), F2 (exceeding the maintenance standard but not exceeding the temporary compensation standard), and F3 (exceeding the temporary compensation standard) according to the "High-speed Railway Line Maintenance Rules"; the vehicle dynamic response parameters are classified into F1 (no level II or above exceeding limits), F2 (exceeding level II limits), and F3 (exceeding level III limits) according to the on-board vibration measurement data, which accurately correspond to the track operation safety exceeding limit levels.

[0032] The environmental risk dimension quantitative data classification standard: location characteristics are divided into 1 (General Section) 2 (Special Sections); the seepage state is divided into S1 (surface wet), S2 (continuous seepage or local water accumulation), and S3 (large-area water surge or mud pumping), which is suitable for all working conditions such as rail transit tunnels and elevated roads.

[0033] S2. Based on the quantitative data of morphological and functional dimensions, the core risk level of the disease is determined through a preset core level judgment matrix. The specific steps are as follows: The quantified data of the morphological dimension are compared with the preset morphological thresholds to obtain the morphological sub-levels; Each quantitative data point of the functional dimension is compared with a preset functional threshold to obtain a functional sub-level; Take the highest level from the morphological sub-level and the highest level from the functional sub-level, input them into the core level determination matrix, and output the core risk level; The core level determination matrix is ​​configured with the following priority rule: the higher the functional sub-level, the higher the output core risk level.

[0034] Since the core bottom line of rail transit operation is train safety, the threat of track function abnormalities to operational safety is far greater than simple structural damage. Therefore, a priority rule for functional sub-levels is set, while the highest value of the morphological sub-level is combined to take into account both the current structural damage status of the defect and the actual operational hazards. The core level determination matrix used in this step is shown in Table 1, achieving standardized and quantitative determination: Table 1 Core Level Determination Matrix

[0035] This establishes a dual assessment system of "morphological damage + functional safety," firmly safeguarding the bottom line of driving safety through the function priority rule, achieving accurate and standardized classification of the core risk level of defects, effectively avoiding safety hazards caused by neglecting dynamic operational risks, and unifying the standard of defect classification across the entire line to solve the problem of inconsistent assessment results in different sections and by different personnel.

[0036] Furthermore, in this embodiment, the fuzzy comprehensive evaluation method can be used to determine the core level, specifically as follows: First, establish the factor set. and a collection of comments A fuzzy relation matrix is ​​constructed using trapezoidal membership functions. , of which elements This represents the membership degree of the i-th factor to the j-th rating level.

[0037] The membership function is as follows: For low risk (L1):

[0038] For medium-risk (L2) and high-risk (L3) cases, triangular or trapezoidal membership functions are used, with parameters... The calibration is based on historical statistical data and the "Rules for Maintenance of High-Speed ​​Railway Lines".

[0039] Then, the weight vector obtained using the entropy weight method Perform fuzzy synthesis operation:

[0040] in To adopt a weighted average type fuzzy operator ,Right now Finally, the core risk level is determined according to the principle of maximum membership. Simultaneously, the membership vectors for each level are output, which can be used for subsequent fine-tuning of the comprehensive early warning level.

[0041] S3. Based on the quantitative data of the environmental risk dimension, determine the environmental risk level of the disease through a preset environmental risk assessment matrix. The specific steps are as follows: Input the location characteristics and seepage status into the environmental risk assessment matrix, and output the environmental risk level; The environmental risk assessment matrix is ​​configured to output a high-risk level when the location features are special sections and the seepage status is severe. Special sections include elevated sections with a curve radius ≤ 400m, sections with a slope ≥ 30‰, the junction of open and closed tunnels, or structural deformation joints.

[0042] This step is based on the core principle of rail transit engineering—that special stress sections combined with water erosion accelerate the deterioration of track defects—and constructs an environmental risk assessment model that couples location and seepage factors. While defects develop slowly in conventional sections, special sections with small-radius curves and steep slopes experience complex stresses. The addition of seepage and water accumulation significantly exacerbates track bed separation, voids, and mud pumping. Therefore, this two-dimensional coupling approach to assess environmental risk enables early prediction of potential defects. The environmental risk assessment matrix used is shown in Table 2. Table 2 Environmental Risk Matrix Determination Table

[0043] It enables a comprehensive assessment of both current and potential risks of defects, significantly improving adaptability to the complex geology and working conditions of urban rail transit in mountainous areas. It can identify high-risk defects in advance, providing a basis for differentiated operation and maintenance and tiered management, and effectively reducing the probability of safety accidents caused by sudden deterioration of defects.

[0044] In addition, this embodiment introduces a grey Markov chain model to perform time-series prediction of the seepage state S, specifically as follows: First, collect a sequence of seepage status data for n consecutive sky windows. ,in This represents the seepage level of the k-th observation (1, 2, and 3 correspond to slight dampness, significant seepage / water accumulation, and large-area leakage / water accumulation, respectively). The original sequence is generated by a single accumulation:

[0045] Establish the discrete form of the grey differential equation:

[0046] in For background values, For development coefficient, Let be the gray action quantity. Solve for the parameters using the least squares method. and This allows us to obtain the predicted value for the next moment. .

[0047] Then, the relative values ​​of the predicted residuals are divided into several states (e.g., negative large, negative small, zero, positive small, positive large), the state transition probability matrix is ​​calculated, and the gray predicted values ​​are corrected based on the current residual states to finally obtain the final predicted seepage level. The predicted value is used to replace the current measured value in the environmental risk assessment matrix, enabling "early warning one maintenance cycle in advance." If the predicted seepage level is higher than the current measured level, the environmental risk level is automatically adjusted upwards.

[0048] This algorithm enables dynamic prediction of environmental risks, and is particularly suitable for mountainous cities with frequent rainy seasons and sudden hydrological changes.

[0049] S4. Based on the combination of core risk level and environmental risk level, a comprehensive early warning level is generated. The specific steps are as follows: Based on the core risk level and environmental risk level, query the preset comprehensive early warning response table to determine the comprehensive early warning level and the corresponding operation and maintenance strategy; The operation and maintenance strategy includes one or more of the following: routine observation, key observation, planned maintenance, priority maintenance, or emergency measures.

[0050] By adopting a dual-level coupled early warning logic of current core risks and potential environmental risks, the static damage level of diseases is combined with the dynamic environmental deterioration risk, and a gradient-based comprehensive early warning level is divided. The corresponding operation and maintenance strategies are matched to achieve an upgrade from "single disease classification" to "precise operation and maintenance decision-making", which can adapt to the management and control needs of different risk diseases.

[0051] The specific comprehensive early warning response rules for this step are shown in Table 3: Table 3 Comprehensive Disease Assessment and Graded Response

[0052] This will enable the construction of a comprehensive maintenance system covering "prevention and observation - planned maintenance - emergency response", thoroughly solving the problems of indiscriminate maintenance, over-treatment of minor defects, and untimely handling of serious defects, achieving precise allocation of maintenance resources, and balancing track operation safety and maintenance economy.

[0053] S5. Based on the comprehensive early warning level, output the final governance plan.

[0054] In addition, the treatment solution is composed of one or more basic process units; The basic process unit includes at least one of the following: surface sealing, pressure grouting, rebar anchoring, backfill grouting and water plugging, base dredging, and installation of lateral limiting device.

[0055] The modular process unit combination design breaks down various mature treatment processes into independent basic units, and recombines them in a modular manner according to the disease warning level, occurrence scenario and disease characteristics, replacing the fixed single treatment solution and adapting to the personalized treatment needs of different working conditions and different levels of diseases. In addition, the core functions and applicable scenarios of the basic process unit are clearly defined as follows, providing a standardized basis for solution combination: Surface sealing: The core function is preventative waterproofing and delaying the development of defects, suitable for all observation-level defects and surface protection after various treatments; Pressure grouting: The core function is to fill gaps and voids, restore interlayer bonding and bearing capacity of the track bed, and is the core process for all maintenance-level and emergency-level defects; Back wall grouting and water plugging: The core function is to seal external water sources and reinforce weak foundations, suitable for pre-treatment of water-rich defects in tunnels; Foundation dredging: The core function is to remove muddy and weak media from the foundation and clean the construction interface, suitable for the treatment of mudslide and siltation defects; Rebar anchoring: The core function is to enhance the overall mechanical connection between the track bed and the foundation, suitable for the reinforcement of defects in elevated sections; Lateral limiting device installation: The core function is to restrain the lateral displacement of the track bed and improve structural stability, suitable for special sections of elevated sections and defects with abnormal displacement.

[0056] It enables the transformation of treatment solutions from "fixed one-size-fits-all" to "modular and precise adaptation". The process combination is flexible and highly standardized, and it can be quickly adapted to all scenarios such as tunnels, elevated roads, general sections and special sections. It avoids the waste of resources caused by over-treatment of minor defects, and also eliminates the problem of insufficient treatment of serious defects and treating the symptoms but not the root cause, which greatly improves the pertinence and long-term effectiveness of treatment.

[0057] The specific steps for outputting the final governance plan based on the comprehensive early warning level include: When the overall early warning level is observation level, a treatment plan centered on surface sealing will be output. When the comprehensive early warning level is maintenance level or emergency level, a treatment plan with pressure grouting as the core is output; When the defect is located in the tunnel section and is accompanied by water seepage or mud pumping, the treatment plan also includes back wall grouting to plug water and foundation dredging, which are carried out in sequence before pressure grouting.

[0058] By matching core processes based on the severity of tunnel defects, and following the treatment logic of "prevention first for minor defects, reinforcement and repair first for severe defects," this approach also incorporates pre-treatment water blocking and dredging processes to address typical conditions such as water-rich and frost-prone tunnel sections. Traditional tunnel defect treatment methods often involve simple grouting without addressing the water source and weak foundation, leading to repeated recurrences. This step, through pre-treatment water control and dredging, addresses the root causes of complex tunnel joint defects. Furthermore, the treatment process is optimized to address the core pain points of tunnel defects, forming a closed-loop treatment logic of "water blocking → dredging → grouting → protection." This thoroughly solves the industry problem of incomplete treatment and secondary recurrence of tunnel seepage, frost heave, and mudslide defects, significantly improving the long-term effectiveness of treating tunnel track bed joint defects.

[0059] In addition, the steps for outputting a governance plan based on the comprehensive early warning level also include: When the defect is located on an elevated section, the treatment plan also includes rebar anchoring performed after pressure grouting; When the defect is located on an elevated section and belongs to a special section, or when the defect is located on an elevated section and abnormal lateral displacement is detected, the treatment plan also includes installing a lateral limiting device.

[0060] By designing a dedicated reinforcement logic based on the stress characteristics of the elevated track section, the elevated track bed, which has no roadbed support, is more affected by train loads, wind loads, and centrifugal forces, and the interlayer bonding is prone to failure. Therefore, after grouting, rebar anchoring is added to strengthen the mechanical connection between layers. For special sections such as small radius curves and abnormal displacement defects, lateral limiting devices are added to specifically constrain lateral displacement and adapt to the complex stress conditions of the elevated section.

[0061] By employing a graded reinforcement scheme of "grouting filling + rebar reinforcement + lateral restraint", the overall integrity and displacement resistance of the elevated section track bed structure are significantly improved, effectively solving the problems of easy spread of joint defects and poor structural stability in the elevated section.

[0062] The characteristics of each basic process unit and its role in a typical scheme are shown in Tables 4 and 5: Table 4. Overview of Basic Process Units

[0063] Table 5 Guidelines for Typical Comprehensive Governance Plans

[0064] Example 2 As one embodiment, after implementing the governance scheme according to the method in Embodiment 1, the governance effect is quantitatively evaluated, and closed-loop feedback is executed based on the evaluation results; The quantitative assessment includes: conducting assessments with different cycles and contents for diseases of different core risk levels, and setting quantitative standards for compliance. The evaluation includes at least one of the following: appearance quality, grouting fullness, track geometry, and dynamic response data.

[0065] This step establishes a tiered and quantitative assessment system. The core logic is "matching the severity of the disease with the intensity of the assessment," meaning that the higher the risk level of the disease, the greater its impact on structural safety after treatment. This necessitates a more comprehensive and long-term assessment approach, while clearly defining quantitative standards to ensure the objectivity and traceability of the assessment results, providing accurate data support for closed-loop feedback.

[0066] This enables standardized and quantitative acceptance of treatment effects, completely solving the problems of unclear judgment standards and subjective and arbitrary acceptance of traditional technical treatment effects. By grading the assessment, it takes into account both acceptance efficiency and assessment accuracy, avoiding the waste of resources caused by over-assessment of minor diseases, and ensuring that the treatment quality of serious diseases meets the standards. This provides a reliable basis for subsequent closed-loop optimization and ensures the long-term effectiveness of the treatment.

[0067] Furthermore, based on the actual needs of track bed joint treatment, the quantitative assessment standards, cycles, and methods for different core risk levels of the defects are shown in Table 6, thus standardizing the assessment process: Table 6. Evaluation Contents for the Grading of Track Bed Joint Treatment

[0068] In addition, the short-term evaluation criteria are shown in Table 7 (applicable to short-term acceptance of all levels of diseases). Table 7 Short-term evaluation criteria and methods for the treatment of track bed gaps

[0069] The medium- and long-term evaluation criteria are shown in Table 8 (applicable to L2 and L3 level disease tracking). Table 8. Medium- and Long-Term Evaluation Standards for the Treatment of Track Bed Joints

[0070] Furthermore, the closed-loop feedback includes: When the quantitative assessment of governance effectiveness fails to meet the quantitative standards, data-driven cause diagnosis is conducted. Based on the diagnostic results, output model optimization suggestions or revised governance solutions, and implement re-governance accordingly.

[0071] This step constructs a closed-loop logic of "diagnosis-governance-assessment-optimization". The core is to transform the problem of non-compliance in the assessment into a data-driven problem that can be analyzed and solved. By tracing back the data throughout the process, the root cause of the failure can be located, and then the decision-making model or governance solution can be optimized in a targeted manner to achieve continuous iteration of the technical system.

[0072] The specific closed-loop handling process is shown in Table 9, ensuring that feedback optimization is implementable and traceable:

[0073] It can form a virtuous cycle of governance system, realize "one-time governance and continuous optimization", not only solve the current governance failure problem, but also improve the accuracy of subsequent disease classification, decision-making and governance through model optimization, effectively reduce the disease recurrence rate, and accumulate engineering data, so that the method can be continuously adapted to complex working conditions, and greatly improve the long-term reliability and practicality of the entire governance decision-making system.

[0074] Example 3 As one example, such as Figure 2 The system shown is a decision-making system for the treatment of track bed gap defects, including: The data acquisition module is used to acquire quantitative data on track bed gap defects in terms of morphology, function, and environmental risk. The core risk level determination module determines the core risk level of the disease based on quantitative data from the morphological and functional dimensions and through a preset core level judgment matrix. The environmental risk level determination module determines the environmental risk level of the disease based on quantitative data of the environmental risk dimension and through a preset environmental risk judgment matrix. The early warning level generation module generates a comprehensive early warning level based on a combination of core risk level and environmental risk level. The governance solution output module outputs the final governance solution based on the comprehensive early warning level. Example 4 As attached Figure 3 An electronic device shown includes: Processor, memory, communication interface; The memory is used to store the executable instructions of the processor; The processor is configured to execute the aforementioned method for managing track bed gap defects by executing the executable instructions.

[0075] A readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned method for managing track bed gap defects.

[0076] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A decision-making method for the treatment of track bed gap defects, characterized in that, include: Obtain quantitative data on track bed gap defects in terms of morphology, function, and environmental risk. Based on quantitative data in morphological and functional dimensions, the core risk level of the disease is determined through a preset core level judgment matrix. Based on the quantitative data of environmental risk dimension, the environmental risk level of the disease is determined through a preset environmental risk judgment matrix; A comprehensive early warning level is generated based on a combination of core risk level and environmental risk level. Based on the comprehensive early warning level, the final governance plan will be output.

2. The decision-making method for treating track bed gap defects according to claim 1, characterized in that: The quantitative data for the morphological dimension includes at least one of the following: joint width, joint depth, and grouting length: The quantitative data for the functional dimensions include at least one of the track static geometric parameters and the vehicle dynamic response parameters; The quantitative data for the environmental risk dimension includes location characteristics and water seepage status.

3. The decision-making method for treating track bed gap defects according to claim 2, characterized in that: The core risk level of the disease is determined based on quantitative data from morphological and functional dimensions using a preset core level judgment matrix. The specific steps are as follows: The quantified data of the morphological dimension are compared with the preset morphological thresholds to obtain the morphological sub-levels; Each quantitative data point of the functional dimension is compared with a preset functional threshold to obtain a functional sub-level; Take the highest level from the morphological sub-level and the highest level from the functional sub-level, input them into the core level determination matrix, and output the core risk level; The core level determination matrix is ​​configured with the following priority rule: the higher the functional sub-level, the higher the output core risk level.

4. The decision-making method for treating track bed gap defects according to claim 2, characterized in that: The step of determining the environmental risk level of a disease based on quantitative data from the environmental risk dimension and through a preset environmental risk assessment matrix is ​​as follows: Input the location characteristics and seepage status into the environmental risk assessment matrix, and output the environmental risk level; The environmental risk assessment matrix is ​​configured to output a high-risk level when the location features are special sections and the seepage status is severe. Special sections include elevated sections with a curve radius ≤ 400m, sections with a slope ≥ 30‰, the junction of open and closed tunnels, or structural deformation joints.

5. The decision-making method for treating track bed gap defects according to claim 4, characterized in that: The process of generating a comprehensive early warning level based on a combination of core risk level and environmental risk level is as follows: Based on the core risk level and environmental risk level, query the preset comprehensive early warning response table to determine the comprehensive early warning level and the corresponding operation and maintenance strategy; The operation and maintenance strategy includes one or more of the following: routine observation, key observation, planned maintenance, priority maintenance, or emergency measures.

6. The decision-making method for treating track bed gap defects according to claim 5, characterized in that: The treatment scheme is composed of one or more basic process units; The basic process unit includes at least one of the following: surface sealing, pressure grouting, rebar anchoring, backfill grouting and water plugging, base dredging, and installation of lateral limiting device.

7. The decision-making method for treating track bed gap defects according to claim 6, characterized in that: The final governance plan is output based on the comprehensive early warning level, and the specific steps include: When the overall early warning level is observation level, a treatment plan centered on surface sealing will be output. When the comprehensive early warning level is maintenance level or emergency level, a treatment plan with pressure grouting as the core is output; When the defect is located in the tunnel section and is accompanied by water seepage or mud pumping, the treatment plan also includes back wall grouting to plug water and foundation dredging, which are carried out in sequence before pressure grouting.

8. The decision-making method for treating track bed gap defects according to claim 6, characterized in that: The steps for outputting a governance plan based on the comprehensive early warning level also include: When the defect is located on an elevated section, the treatment plan also includes rebar anchoring performed after pressure grouting; When the defect is located on an elevated section and belongs to a special section, or when the defect is located on an elevated section and abnormal lateral displacement is detected, the treatment plan also includes installing a lateral limiting device.

9. The decision-making method for treating track bed gap defects according to claim 1, characterized in that: After implementing the governance plan, the governance effect is quantitatively evaluated, and closed-loop feedback is executed based on the evaluation results. The quantitative assessment includes: conducting assessments with different cycles and contents for diseases of different core risk levels, and setting quantitative standards for compliance. The evaluation includes at least one of the following: appearance quality, grouting fullness, track geometry, and dynamic response data.

10. The decision-making method for treating track bed gap defects according to claim 9, characterized in that: The closed-loop feedback includes: When the quantitative assessment of governance effectiveness fails to meet the quantitative standards, data-driven cause diagnosis is conducted. Based on the diagnostic results, output model optimization suggestions or revised governance solutions, and implement re-governance accordingly.

Images