High-speed railway turnout service state evaluation method

Abstract

The invention discloses a high-speed railway turnout service state evaluation method. The method comprises the following steps: screening index types influencing turnout service performance; based on the action principles of the two types of evaluation indexes and the influence mechanism on the service performance of the high-speed railway turnout, classifying a driving performance influence class and a turnout structure performance retention class, and introducing historical maintenance influence evaluation indexes by considering the influence that the overall performance is possibly reduced after the turnout part is maintained; optimizing evaluation index parameters, performing static and dynamic index correlation analysis on a plurality of index item points of a driving performance influence class, a turnout structure performance retention class and a historical maintenance influence class, simplifying the index item points and avoiding repeated evaluation; weight coefficients of all indexes are formulated and used for overall scoring of the turnouts; an evaluation process is formulated, then a three-level evaluation system is constructed, an evaluation result is analyzed, specific item points of turnout deterioration can be directly positioned through three-level index analysis, and a basis is provided for maintenance and repair.

Description

Technical Field

[0001] This invention belongs to the field of railway turnout maintenance technology, specifically relating to a method for assessing the service status of high-speed railway turnouts. Background Technology

[0002] High-speed railway turnouts are one of the key pieces of equipment in railway engineering. Their complex structure, high performance requirements, and significant technical challenges make them the weakest link in the high-speed railway track structure. Due to inherent irregularities, wheel load transitions, and uneven stiffness in high-speed turnouts, the wheel-rail relationship in the turnout area is complex, and wheel-rail impacts are more severe. Damage and defects in the turnout area are more prominent than in sections of the track. Turnout defects can easily lead to serious consequences such as train swaying and derailment, threatening the safe operation of high-speed trains. Therefore, they have always been a key focus of high-speed railway line inspection and maintenance. As high-speed railway turnouts age, component deterioration and reduced smoothness are inevitable after long-term service. A reasonable turnout condition assessment method can provide a basis for developing targeted preventative measures, ensuring the safe operation of high-speed trains.

[0003] Currently, to ensure the safe operation of high-speed turnouts, the inspection and maintenance of high-speed railway turnouts are mainly carried out in accordance with the industry regulations, "Rules for the Maintenance of High-Speed ​​Railway Lines." These regulations stipulate aspects related to the management of dynamic irregularities, static geometric dimensions, vehicle dynamics indicators, and structural dimensions of high-speed turnouts. The inspection of high-speed turnouts mainly includes two parts: turnout condition and geometric dimensions, and turnout rail inspection. Turnout condition and geometric dimensions are mainly inspected using dynamic and static testing equipment, while rail inspection mainly includes rail flaw detection and visual inspection of surface damage.

[0004] In summary, while corresponding maintenance standards have been established for the operation and maintenance of high-speed turnouts, the existing turnout area management indicators are numerous and the quality evaluation system is complex, encompassing geometry, fit, longitudinal displacement, connecting components, ballastless track, markings, and more. The current management model involves managing multiple indicators in parallel, with over a hundred indicators in the turnout area. Each indicator has its own management limits, which are used as the basis for maintenance. This current maintenance model makes turnout evaluation challenging, as there are numerous inspection indicators. Furthermore, because the key parameters affecting turnout service performance have not yet been identified, the turnout inspection results obtained by referring to existing standards cannot directly reflect the service status of high-speed turnouts, failing to develop a joint analysis method for the service status and performance of high-speed turnouts.

[0005] To address the aforementioned pain points and difficulties, current technical solutions often employ turnout evaluation using data from high-speed integrated inspection vehicles or static ground inspection data, and utilize peak value management and mean value management standards. Peak value management involves controlling each indicator individually according to established standards; mean value management, on the other hand, manages a section by applying an average comprehensive score (such as kilometer deductions, unit or section quality indices, etc.). Based on the integrated inspection vehicle data, dynamic geometric irregularities of the turnout can be evaluated. 1) The literature (Evaluation Method of Track Geometric Irregularity in High-Speed ​​Railway Turnout Area Based on TQI-T [J]. Journal of Railway Science and Engineering, 2023, 20(8): 2785-2793) uses the Turnout Track Quality Index (TQI-T) as an indicator for diagnosing turnout defects in high-speed railways. Taking the turnout area and its 25m extension before and after it as an evaluation section, based on the data from the comprehensive inspection vehicle, the sum of the standard deviations of the left and right rail height, left and right rail orientation, level, triangular pit, and track gauge is obtained, and the TQI-T result is calculated. A control limit of 5mm is proposed. However, this method only uses the dynamic geometric data of high-speed dynamic inspection as the basis to obtain a sum of deviation dispersion, which represents the geometric state of the line. The geometric smoothness of the turnout area is only one element of the turnout's service status and cannot comprehensively evaluate the turnout performance. Currently, we can only perform a relatively rough analysis and evaluation of the track condition of turnouts and the track within a certain mileage range before and after them. We do not yet have the ability to accurately locate the problem to a specific structure, and we have not been able to fully combine the detection data with the train passing status for analysis. Therefore, we are still some distance from the precise analysis of turnout status.

[0006] 2) The literature (Research on Comprehensive Evaluation Method of High-Speed ​​Railway Turnout Operation Status [J]. Railway Technical Supervision, 2023(2):38-43.) and (Patent: A Method for Evaluating the Operation Status of Straight Rails of High-Speed ​​Turnouts CN113987755B) propose a comprehensive evaluation method for the operation status of high-speed railway turnouts. The comprehensive evaluation method of the comprehensive evaluation model for the operation status of high-speed railway turnouts evaluates the following items: the main ones are the grinding quality index (GQI), the consistency of the basic rail profile, the symmetry of the basic rail profile, the straightness of the weld, the smoothness, the rail wear, the reduction value of the switch area and frog area, the rail surface defects, and the vehicle stability, etc., and gives the weight coefficients of each indicator. The total score for each item is 100 points. The turnout comprehensive score is obtained by scoring each item separately and according to the weight coefficients. Based on the score, the turnout status is divided into four levels: A, B, C, and D. Scores between 100 and 85 (excluding 85) are classified as Grade A, 85 to 70 (excluding 70) as Grade B, 70 to 60 (excluding 60) as Grade C, and scores less than or equal to 60 as Grade D. However, this method has significant limitations: First, 90% of the evaluation indicators focus on the apparent quality or damage of the rails, failing to comprehensively reflect the overall condition of the turnout, such as localized gaps in the turnout or deterioration in the stiffness of the track pads. Second, the direct weighted average method used to reflect the overall quality of the turnout is insufficient for guiding maintenance and repair work, and offers no significant efficiency improvement compared to traditional single-indicator inspection and analysis.

[0007] 3) Literature (Comprehensive Assessment Method for Turnout Health Status [J]. Railway Construction, 2023, 63(02):27-31.) and (Patent: A Method for Assessing the Status of Turnouts in Conventional Railways CN114943399B) integrate various static detection data of turnouts and information on rail maintenance and replacement during turnout service to propose a comprehensive assessment method based on the Turnout Health Assessment Index (THI). Nine current status items for the entire turnout health status assessment are determined based on the turnout's structural characteristics and usage features, including static geometric dimensions, dynamic smoothness, rail wear, rail damage, fastener performance, switch rail reduction value, electrical interface, turnout sleeper status, and ballast status. The impact of maintenance deduction items such as turnout rail replacement and ballast tamping is also considered. The scoring rules for each item are clarified, and the weight coefficients of each current status item are determined using hierarchical analysis. After obtaining scores for each indicator through a single-item deduction method, a turnout health assessment index is calculated to comprehensively evaluate the overall health status of the turnout group. Based on the calculation results, the turnout status is divided into four levels: excellent, good, average, and unqualified. This method considers a large number of indicators and can comprehensively assess the turnout status, but it requires a significant amount of inspection, data processing, and analysis. Furthermore, this method uses an over-limit deduction method, meaning that a score change only occurs when only one indicator exceeds the standard limit. Therefore, the correlation between the final comprehensive turnout assessment result and the actual turnout status needs further improvement.

[0008] 4) The literature (Research on Health Status Diagnosis and Evaluation Technology of High-Speed ​​Turnouts Based on Multi-Source Digital Analog Dual Drive [D]. Beijing Jiaotong University, 2024) specifically scores the track geometry, short-wave condition, and vehicle throughput performance of the turnout area, and establishes a comprehensive evaluation model of turnout health status based on the Health Index of Turnout (HIT) to comprehensively evaluate the status of turnout equipment. Regarding the track geometry of the turnout area: the TQI-T index of each group of turnouts to be evaluated is calculated according to TQI-T. Regarding the short-wave condition, the wheel-rail force of each weld and turnout center is evaluated, and the short-wave condition is scored. Finally, the train ride smoothness is evaluated. The HIT index is then obtained, and the final results are divided into three levels: good, concerning, and critically concerning. This method evaluates based on the measurement results of a comprehensive inspection train; all data are onboard data, which can comprehensively reflect the train's ride quality, but cannot accurately identify the structural status of the turnout.

[0009] Currently, the evaluation methods for the service status of high-speed railway turnout systems are still in the early stages of research, with few relevant research results. Existing methods also have problems such as insufficient items, inaccurate indicators, and how to use the evaluation results to guide maintenance and repair.

[0010] Existing technical solutions reveal two main categories of methods for assessing the service status of high-speed turnouts: The first is a single-item limit management model based on standardized specifications. This method, currently used by on-site maintenance departments, involves controlling the test results of each turnout indicator to ensure all indicators remain within standard limits. The second is an average value management method. This method employs multiple indicators for comprehensive scoring. Examples include: ① using ground-based test data such as rail profile, straightness, and light band for comprehensive scoring; ② using comprehensive test train data, such as track gauge, level, triangular grooves, car body acceleration, and wheel-rail force for comprehensive scoring; ③ combining ground and onboard data for scoring, and using a single-item deduction method.

[0011] The first type of method has numerous indicators, making it impossible to characterize the overall quality status of high-speed turnouts. The second type of method suffers from incomplete indicators; for example, considering only the condition of the rails or the operating conditions of high-speed trains fails to comprehensively reflect turnout performance. Some scholars have integrated static and dynamic data from the turnout area for evaluation, but the method used is a one-way indicator deduction method. This method cannot accurately reflect the actual condition of the turnout, only showing two modes: exceeding limits and not exceeding limits, thus having certain evaluation defects. Furthermore, another shortcoming of existing technical solutions is the failure to integrate the static inspection indicators of high-speed turnouts with the dynamic detection indicators during high-speed train passage. The various indicators are intertwined, making it impossible to quickly and accurately assess the service status of high-speed turnouts and provide maintenance guidance.

[0012] Therefore, how to provide a method for assessing the service status of high-speed railway turnouts that can quickly evaluate and guide subsequent on-site maintenance is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0013] In view of this, the present invention provides a method for evaluating the service status of high-speed railway turnouts. By rapidly evaluating the performance and status of high-speed railway turnouts after long-term service, it ensures the safe and stable operation of high-speed trains passing through the turnouts. At the same time, the evaluation results will also directly guide on-site maintenance and repair work.

[0014] To achieve the above objectives, the present invention adopts the following technical solution: a method for evaluating the service status of high-speed railway turnouts, characterized by comprising the following steps: Step 1: Screen the types of indicators that affect the service performance of turnouts, including evaluation indicators that affect the smoothness and safety of high-speed train operation and evaluation indicators that affect the long-term service performance of the high-speed turnout structure itself. Step 2: Obtain static index parameters and dynamic train operation performance index parameters of the high-speed railway turnout area according to the existing operation and maintenance requirements. Link the static index parameters and dynamic train operation performance index parameters with the two evaluation indicators in Step 1. Based on the working principle and the impact mechanism on the service performance of high-speed railway turnouts, reclassify them into train operation performance impact category and turnout structure performance maintenance category. Consider the impact of turnout component maintenance on overall performance reduction and introduce historical maintenance impact evaluation index. Step 3: Optimize the evaluation index parameters in Step 2. Based on Step 2, screen key factors and simplify index items. Perform static and dynamic index correlation analysis on several index items related to the impact on train performance and the maintenance of turnout structural performance. Static index parameters and dynamic train performance index parameters are interrelated. The inspection data of some static index parameters directly affect the inspection data of dynamic train performance index parameters. Simplify index items and avoid duplicate evaluation. Step 4: Determine the weighting coefficients for each indicator, assigning weights of 0.45, 0.45, and 0.1 to indicators affecting train operation, indicators affecting turnout structural performance, and historical maintenance records, respectively, and use these weights to score the overall turnout. Step 5: Develop an evaluation process and construct a three-tiered evaluation system, then analyze the evaluation results. The first-tier score is the overall score of the turnout; the second-tier score includes indicators affecting train operation, indicators affecting turnout structural performance, and performance scores mapped from historical maintenance records for train operation, structural performance, and historical maintenance; the third-tier score includes indicators affecting train operation, indicators affecting turnout structural performance, and several detailed indicators from the next level of historical maintenance records. Through the analysis of these three-tiered indicators, the specific deterioration points of the turnout can be directly located, providing a basis for maintenance and repair.

[0015] The beneficial technical effects of this invention are as follows: The high-speed turnout evaluation method proposed in this invention provides guidance for various engineering departments to formulate inspection and maintenance plans for assessing the operational status of high-speed turnouts. It is worth noting that this method reclassifies and streamlines the indicators affecting turnout service performance into three main categories, significantly reducing the number of evaluation items. Based on these three categories—traffic performance impact, turnout structural performance maintenance, and historical maintenance impact—a three-level evaluation scheme is formed, from the item level to the performance level, and finally to the overall turnout evaluation. This three-level evaluation system can comprehensively identify the turnout status. The three-level evaluation system provides managers with rapid judgment and accurate maintenance guidance. When a single indicator exceeds the limit, timely maintenance should be carried out. A single indicator score below 60 points means the entire turnout group is unqualified and will no longer be scored.

[0016] Preferably, in step one, the indicators affecting train operation mainly include the geometric state of the static track, and the indicators affecting the long-term service of the turnout structure itself include the assembly state between track components and whether the rail components are severely corroded.

[0017] The resulting technical effect is that, for turnout structures, the main function is to ensure smooth and safe train operation, which is the ultimate goal. At the same time, the structure itself also needs to maintain durability. Therefore, the two major categories of influencing factors are defined first, and each category of influencing factors has multiple inspection items.

[0018] Preferably, in step two, the indicators affecting train performance include static geometric dimensions and dynamic irregularities; the indicators maintaining turnout structural performance include rail wear, rail damage, fastener performance, connecting components, tightness and gaps, electrical interface status, and turnout sleeper track bed status; and the indicators evaluating the impact of historical maintenance include replacing rail components, replacing connecting components, and repairing the substructure.

[0019] The resulting technical effect is that the indicators of train performance impact, turnout structural performance maintenance, and historical maintenance impact evaluation all contain multiple different items, and each item contains different inspection points. Through multi-level division, from the item to the performance level and then to the overall level, it is possible to quickly and accurately judge the over-limit items, and it is also convenient to assess the service status of the turnout area in the line as a whole.

[0020] Preferably, in step three, static and dynamic correlation analysis is first performed to construct a vehicle-refined turnout dynamic coupling model, analyze which indicators affect driving performance and which indicators affect structural performance, thereby classifying and linking these indicators, exploring the influence of static geometric parameters on the driving performance and structural safety performance of the turnout area, setting static geometric irregularities, and using orthogonal design methods to calculate the influence of different factors on driving dynamic performance. Then, key factors are screened, the calculated effect assessment values ​​are used as experimental results, and the effects of each analysis factor are obtained according to the variance calculation method of orthogonal experiment, and the key factors affecting dynamic driving performance are extracted. Further optimization of evaluation index parameters: Based on the static and dynamic analysis of high-speed turnout structure, the evaluation indexes are optimized, and various evaluation index parameters for turnout service performance are formulated, which are divided into two categories: Level I indicators and Level II indicators. Level I indicators include those affecting train performance, those maintaining the structural condition of turnout, and those affecting historical maintenance; Level II indicators are the detailed inspection items of each Level I indicator. Finally, all indicators and items are normalized and effectively evaluated.

[0021] The resulting technical effect is that by analyzing the correlation between static and dynamic indicators in the indicator system, the items can be simplified, duplicate evaluations can be avoided, and normalization processing can facilitate the unified description and representation of different parameters.

[0022] Preferably, when normalizing the various indicator items, a piecewise smoothing function based on the Sigmoid function is used as the normalization function;

[0023] in: The meanings of the various parameters are as follows: x : Index value (input); L p Planned maintenance limits; L t Temporary repair limits; A: This is the penalty weight for the first descent phase, controlling the magnitude of performance degradation starting from Lp; B: Penalty weight control for the second descent phase, representing the magnitude of the sharp performance drop starting from Lt.

[0024] The resulting technical effect is that, due to the different attributes of the various turnout index parameters obtained, such as geometric indicators in mm and vehicle acceleration in m / s², the technical effect is that the turnout indicators are different in nature. 2 Furthermore, the values ​​of each parameter vary considerably. To conduct an effective evaluation, the indicators are normalized. In the performance evaluation of railway turnout structures, unlike other evaluations with unlimited values, each indicator within the turnout has strict control limits. Once these limits are exceeded, each indicator requires immediate repair. Therefore, its normalization function should possess the following characteristics: within the planned maintenance limit range, the closer to the limit, the slightly lower the performance; when the planned maintenance limit is exceeded, the performance decreases rapidly; when the temporary repair limit is exceeded, the indicator fails. The above function is used to normalize each test indicator for easier subsequent evaluation and analysis.

[0025] Preferably, in step four, since the next level of detailed inspection items of each indicator have different impacts on the overall evaluation, it is necessary to divide the next level of detailed indicator items into weights, form a comparison matrix of the next level of detailed inspection items of each indicator, calculate the eigenvector corresponding to the largest eigenvalue of the judgment matrix, and normalize it as the weight, so as to obtain the weight coefficient of indicator Vi (i takes the value 1, 2, 3, ..., n), the weight corresponding to the i-th indicator is ki, the score is Pi, and the score of the corresponding indicator is calculated.

[0026] Based on this, the final evaluation results of three types of indicators were obtained, with the weights for driving performance, structural performance, and historical maintenance being 0.45, 0.45, and 0.1, respectively, resulting in the final evaluation result for the turnout. .

[0027] The resulting technical effect is that although three different performance indicators are used to evaluate the overall service status of high-speed railway turnouts, these three types of indicators have different impacts on the evaluation results. That is, the weight of each type of indicator should be reasonably divided to achieve a reasonable evaluation effect. Of course, the specific items in each type of indicator also need to be assigned reasonable weights according to the influence mechanism in order to ensure the accuracy of the overall evaluation.

[0028] Preferably, when the first-level score is below 90 points, attention should be paid; when the first-level score is below 80 points, the various indicators of the second-level score should be analyzed; determine which category of score is too low and needs to be repaired in a planned manner; when the score of a certain category of indicators in the second-level score is also below 80 points, the parameters of the specific third-level detailed items that affect the assessment results should be identified as exceeding the limits and repairs should be arranged.

[0029] The resulting technical effect is that the three-level evaluation system facilitates accurate assessment of the structural condition of high-speed railway turnouts by relevant personnel in the field, while also predicting the evolution of turnout quality and providing guidance for turnout maintenance.

[0030] Preferably, in step five, the evaluation results of the three-level indicators are recorded on a weekly or monthly basis, and the development and change patterns of each level of indicators are analyzed. If a sudden change in the evaluation score occurs, the cause is investigated immediately.

[0031] The resulting technical effect is that it can guide relevant personnel to predict and assess the service status of relevant turnouts, and provide guidance for related construction. Attached Figure Description

[0032] Fig. 1 This invention provides an index system for evaluating the service status of high-speed railway turnouts. Fig. 2 This is the normalized scoring curve under different static level deviation conditions of the present invention. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] See the appendix of this invention. Figs. 1-2 According to an embodiment of the present invention, a method for evaluating the service status of high-speed railway turnouts includes the following steps: Step 1: Screen the types of indicators affecting the service performance of turnouts, including evaluation indicators affecting the smoothness and safety of high-speed train operation, and evaluation indicators affecting the long-term service performance of the high-speed turnout structure itself. Since the primary function of a turnout structure is to ensure smooth and safe train operation—this is the ultimate goal—and it also needs to maintain durability, we first define two main categories of influencing factors. Indicators affecting train operation mainly include geometric condition (geometric condition includes items 1-4 in Table 1), while indicators affecting the service life of the turnout structure itself include the assembly condition between track components (component assembly condition includes items 5-19 in Table 1) and whether the rail components have severe corrosion (rail condition includes items 20-29 in Table 1). These two types of indicators need to be evaluated comprehensively because some static inspection indicators can directly affect the dynamic performance of high-speed trains, such as static geometric irregularities, while other static indicators will not affect train operation performance in the short term, such as railbed corrosion and poor local contact. These indicators will directly affect the long-term durability of the turnout structure itself.

[0035] The parameters that can be obtained using existing technologies in the turnout area include both static and dynamic indicators, as shown in Table 1. The dynamic driving performance indicators are shown in Table 2.

[0036] It is worth noting that Table 1 contains static inspection index parameters, while Table 2 contains dynamic inspection vehicle inspection index parameters (referred to as dynamic inspection data). The static inspection data and dynamic inspection data are interrelated, and some static inspection data can affect the dynamic inspection data.

[0037] Table 1. List of Static Indicators for Service Status of High-Speed ​​Railway Turnouts

[0038] Table 2 List of performance indicators for high-speed railway turnouts

[0039] Step Two: Based on the working principles and impact mechanisms of the two types of evaluation indicators from Step One on the service performance of high-speed railway turnouts, a reclassification was performed, dividing them into categories affecting train operation performance and maintaining turnout structural performance. The categories affecting train operation performance include static geometric dimensions and dynamic irregularities. The categories maintaining turnout structural performance include rail wear, rail damage, fastener performance, connecting components, tightness and clearance, electrical interface status, and turnout sleeper ballast condition. The impact of potential performance degradation after turnout component repairs was also considered, leading to the introduction of historical maintenance impact evaluation indicators; for example, the mismatch between old and new components after replacing a single component, or the reduced strength of ballast mortar after repair. The classification of high-speed railway turnout service performance evaluation indicators is shown in Table 3, and the constructed high-speed turnout service status assessment indicator system is as follows: Fig. 1 As shown.

[0040] Table 3 Classification of Service Performance Evaluation Indicators for High-Speed ​​Railway Turnouts

[0041] Step 3: Optimize the evaluation index parameters in Step 2. Based on Step 2, screen key factors and simplify index items. Perform static and dynamic index correlation analysis on several index items related to the impact on train performance, the maintenance of turnout structural performance, and the impact of historical maintenance, simplify index items and avoid duplicate evaluation. Step 3, the simplification and optimization of indicators, includes the following steps; ① Correlation analysis A refined dynamic coupling model of the vehicle and the turnout was constructed to investigate the impact of static geometric parameters on the train's performance and structural safety in the turnout area. Static geometric irregularities were introduced, including the following: An orthogonal design method was used to calculate the effects of different factors on the train's dynamic performance (including car body acceleration, wheel-rail force, and derailment coefficient).

[0042] Table 4. Screening of Key Parameters for High-Speed ​​Turnout Service Status

[0043] ② Screening of key factors The calculated effect assessment values ​​were used as the experimental results, and the effects of each analytical factor were obtained according to the variance calculation method of orthogonal experiments. Key factors affecting dynamic train performance were extracted. The calculated significant influencing factors included: 20mm and 35mm reduction values ​​of the cross-section of the tip and frog, triangular pits at the switch and fork, uneven welds, and unsupported track slabs.

[0044] ③ Optimization of evaluation index parameters Based on the static and dynamic analysis of the high-speed turnout structure, the evaluation indicators were optimized. The parameters for various evaluation indicators of the turnout's service performance were formulated, as shown in the table below.

[0045] Table 5. Service Status Assessment Indicators and Parameters for High-Speed ​​Turnouts

[0046] ④ Detailed inspection items were developed for each indicator, as shown in the table below. Based on system analysis, a total of 30 items were identified as indicators for evaluating the service status of high-speed turnouts. This significantly reduces the workload of data statistics compared to the hundreds of indicators in the maintenance specifications. The items are further divided into two categories: Level I and Level II indicators, providing a foundation for the development of the next step in the evaluation methodology.

[0047] Table 6. Service Status Assessment Indicators and Parameters for High-Speed ​​Turnouts

[0048] ⑤ Standardize various indicators. Because the 30 turnout indicator parameters have different attributes, such as geometric indicators in mm and vehicle acceleration in m / s², etc. 2 Furthermore, the values ​​of each parameter vary considerably. To conduct an effective evaluation, the indicators are normalized. In the performance evaluation of railway turnout structures, unlike other evaluations with unlimited values, each indicator within the turnout has strict control limits. Once these limits are exceeded, each indicator requires timely maintenance. Therefore, its normalization function should possess the following characteristics: within the planned maintenance limit range, the closer to the limit, the slightly lower the performance; when the planned maintenance limit is exceeded, the performance decreases rapidly; when the temporary repair limit is exceeded, the indicator fails. It is worth noting that static geometric deviation levels I and II employ planned maintenance and temporary repair; dynamic geometric deviation levels I and II employ routine maintenance and planned maintenance.

[0049] A piecewise smoothing function based on the Sigmoid function is used as the normalization function:

[0050] in:

[0051] Meaning of each parameter: x : Index value (input); L p Planned maintenance limits; L t Temporary repair limits; A: This refers to the penalty weight for the first descent phase, controlling the transition from... L p The extent of the initial performance degradation; B: For the penalty weight control in the second descent phase, from L t The magnitude of the initial sharp performance drop; Taking static level deviation as an example, its Level I and Level II indicators are 4mm and 6mm, respectively. The normalized scoring curves under different deviation conditions are shown in the attached figure. Fig. 2 As shown, when the deviation is close to the Level I limit, a score of 90 can be obtained. When the deviation exceeds Level I, the score drops rapidly, and when the deviation reaches Level II, the score is only 60. Once Level II is exceeded, immediate repair is required, therefore no further scoring is performed.

[0052] The above function is used to normalize the various test indicators. Taking a 350km / h speed-class high-speed turnout as an example, the planned maintenance and temporary repair limits for each indicator are shown in the table below.

[0053] Table 7. Evaluation Indicators and Parameters for the Service Status of High-Speed ​​Turnouts

[0054] It is worth noting that not all indicators have graded limits. For example, rail damage can be evaluated based on the condition of the rails inspected on-site, combined with flaw detection, using a direct deduction method: no points are deducted for minor damage, -20 points for minor damage, and -40 points for serious damage. In historical maintenance data, the direct deduction method is used for evaluation: for example, replacing a single main rail results in -10 points.

[0055] Step 4: Determine the weighting coefficients for each indicator, assigning weights of 0.45, 0.45, and 0.1 to indicators affecting train operation, indicators affecting turnout structural performance, and historical maintenance records, respectively, and use these weights to score the overall turnout. First, the indicators affecting train operation, the indicators affecting turnout structure, and the historical maintenance records are evaluated separately. Train operation performance and turnout structure performance have the same weight, while the historical maintenance records have the lowest weight, and are directly assigned weights of 0.45, 0.45, and 0.1.

[0056] Secondly, the Level II indicators are weighted. Based on the key indicator parameters calculated in step 3, and combined with the weighting coefficients, the weighting can be determined using the conventional analytic hierarchy process (AHP). There are 17 items in total, including static and dynamic geometric deviations, encompassing long-wave irregularities and short-wave impacts. Therefore, indicators 1-15 are compared, while indicators 16 and 17, representing short-wave impacts, are scored separately. Indicators 1-15 form a comparison matrix; the data in the table represents the relative importance of two indicators, with a higher ratio indicating greater importance.

[0057] Table 8. Indicator Comparison Matrix

[0058] Calculate the eigenvector corresponding to the largest eigenvalue of the judgment matrix, and normalize it as the weight. This yields the weight coefficients for indicators 1 to 15. The weight for the i-th indicator is ki, and its score is Pi. Therefore, the long-wave geometric irregularity score is... .

[0059] The shortwave impact assessment consists of two indicators, 16 and 17, both with an equal weight of 0.5. The calculated shortwave irregularity score is: .

[0060] The rail performance evaluation consists of two indicators, 18 and 22. The weights of each indicator are calculated using an analytic hierarchy process (AHP) matrix. The point score for each indicator is... Similarly, the evaluation score for connecting parts and the lower foundation is S. 22 and S 23 The evaluation score for the connecting parts and the lower foundation was... All indicators in the historical maintenance records have the same weight, 1 / 3, resulting in a score of S3 for this evaluation item.

[0061] Based on this, the final evaluation results of three types of indicators are obtained. The weights of the three items, namely, driving performance, structural performance, and historical maintenance, are 0.45, 0.45, and 0.1, respectively, resulting in the final evaluation structure of the turnout. .

[0062] Step 5: Develop an assessment process and construct a three-tiered evaluation system. Analyze the assessment results to provide guidance for the comprehensive maintenance and repair of turnouts. The first-level score is the overall turnout score; the second-level score includes indicators affecting train operation, indicators affecting turnout structural performance, and three major categories mapped from historical maintenance records: train operation performance, structural performance, and historical maintenance. The third-level score includes indicators affecting train operation, indicators affecting turnout structural performance, and several detailed indicators from the next level of historical maintenance records. Through the analysis of these three levels of indicators, specific points of turnout deterioration can be directly identified, providing a basis for maintenance and repair.

[0063] It should be noted that if a single indicator exceeds the limit, it should be repaired in time. If a single indicator score is below 60 points, it means that the entire turnout is unqualified and will no longer be scored.

[0064] The first-level rating is the highest level, rating all turnouts within a track section. This rating guides management in planning inspections, prioritizing those with poor ratings (e.g., below 90 points). The second-level rating has three indicators: geometric smoothness, turnout structural condition, and maintenance history. When a group of turnouts in the first-level rating is low (below 80 points), the second-level indicators need to be analyzed to determine which category of items is low and requires planned maintenance. When a second-level indicator is also below 80 points, it can be found that a specific tertiary indicator may be exceeding limits, and maintenance should be arranged.

[0065] Understandably, the first-level score is the total score of a set of turnouts, the second-level score includes three categories (major items) of indicators (geometric category includes 17 parameters, structural performance category includes 10 parameters, and historical maintenance category includes 3 parameters), and the third-level score is the specific 30 item parameters.

[0066] This invention comprehensively considers static inspection indicators, dynamic inspection indicators, historical maintenance records, and the correlation between static parameters and dynamic responses, and proposes a service performance indicator parameter system that integrates static and dynamic aspects of turnouts, significantly reducing the number of evaluation items.

[0067] A multi-level turnout evaluation scheme is proposed. From the item level to the performance level, and finally to the overall turnout evaluation, the three-level scheme can comprehensively identify the turnout status. Traditional evaluation methods directly provide the final result, making it difficult to analyze the factors affecting the final result.

[0068] The design logic of this invention is as follows: For turnout structures, their main function is to ensure the smoothness and safety of train operation, which is the ultimate goal. At the same time, they also need to maintain durability. Therefore, we first define two major categories of influencing factors: evaluation indicators that affect the smoothness and safety of high-speed train operation and evaluation indicators that affect the long-term service performance of the high-speed turnout structure itself.

[0069] Secondly, the parameters obtainable using existing technologies in the turnout area include both static and dynamic indicators. The challenge lies in linking these static and dynamic indicators with the two most fundamental influencing factors: employing static and dynamic performance correlation analysis, constructing a vehicle-refined turnout dynamic coupling model, and analyzing which static indicators affect train performance and which affect structural durability, thereby classifying and linking these indicators.

[0070] Static / dynamic indicators and their impact on driving performance / structural durability require establishing causal relationships: the various static and dynamic indicators are the causes, and the impacts on driving performance and structural durability are the effects. Nearly one hundred static or dynamic indicator data points can be obtained through on-site inspection and testing. To clarify which data are necessary and affect driving performance or structural durability, correlation analysis and key factor screening yielded the evaluation indicator table in Table 5. Further clarification of the specific inspection items for each indicator resulted in the operational evaluation table in Table 6. It can be seen that both static and dynamic geometric irregularities affect driving performance, while indicators such as rails and connecting parts affect structural durability. Therefore, these two types of influencing indicators are transformed into 30 detailed and operational items.

[0071] During on-site execution, only 30 data points need to be collected and entered. According to this evaluation method, the 30 data points are first normalized, and then combined with the weighting coefficients to obtain static, dynamic and historical scores, and finally the total score is obtained.

[0072] During final management, the turnouts are managed in a hierarchical manner based on their total score. If a group of turnouts scores well, it does not need to be monitored. If a turnout scores low, inspection and maintenance can be arranged, and its corresponding three categories (operation, structure, and historical maintenance) can be further analyzed to formulate relevant maintenance strategies.

[0073] Compared with existing technologies, this invention has the following advantages: First, the indicators are more comprehensive, taking into account static, dynamic, and historical data; second, the indicators are more accurate, taking into account the interrelationships and influences of various indicators, eliminating redundant evaluation indicators, and formulating more reasonable evaluation weights; third, the evaluation of indicators is more targeted and hierarchical, and can identify specific indicators from the overall status of the turnout to performance evaluation, making it easier to judge turnout problems and helping to guide on-site maintenance and repair.

[0074] The solution was applied to a high-speed railway turnout. The results showed that the turnouts with good on-site feedback could achieve scores of over 90. When the evaluation score was 80-90, the turnouts showed some defects such as poor fit and foundation gaps. The evaluation results were consistent with the on-site conditions.

[0075] The apparatus and methods disclosed in the embodiments are described simply because they correspond to the methods disclosed in the embodiments. For relevant details, please refer to the method section.

[0076] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for evaluating the service status of high-speed railway turnouts, characterized in that, Includes the following steps: Step 1: Screen the types of indicators that affect the service performance of turnouts, including evaluation indicators that affect the smoothness and safety of high-speed train operation and evaluation indicators that affect the long-term service performance of the high-speed turnout structure itself. Step 2: Obtain static index parameters and dynamic train operation performance index parameters of the high-speed railway turnout area according to the existing operation and maintenance requirements. Link the static index parameters and dynamic train operation performance index parameters with the two evaluation indicators in Step 1. Based on the working principle and the impact mechanism on the service performance of high-speed railway turnouts, reclassify them into train operation performance impact category and turnout structure performance maintenance category. Consider the impact of turnout component maintenance on overall performance reduction and introduce historical maintenance impact evaluation index. Step 3: Optimize the evaluation index parameters in Step 2. Based on Step 2, screen key factors and simplify index items. Perform static and dynamic index correlation analysis on several index items related to the impact on train performance and the maintenance of turnout structural performance. Static index parameters and dynamic train performance index parameters are interrelated. The inspection data of some static index parameters directly affect the inspection data of dynamic train performance index parameters. Simplify index items and avoid duplicate evaluation. Step 4: Determine the weighting coefficients for each indicator, assigning weights of 0.45, 0.45, and 0.1 to indicators affecting train operation, indicators affecting turnout structural performance, and historical maintenance records, respectively, and use these weights to score the overall turnout. Step 5: Develop an evaluation process and construct a three-tiered evaluation system, then analyze the evaluation results. The first-tier score is the overall score of the turnout; the second-tier score includes indicators affecting train operation, indicators affecting turnout structural performance, and performance scores mapped from historical maintenance records for train operation, structural performance, and historical maintenance; the third-tier score includes indicators affecting train operation, indicators affecting turnout structural performance, and several detailed indicators from the next level of historical maintenance records. Through the analysis of these three-tiered indicators, the specific deterioration points of the turnout can be directly located, providing a basis for maintenance and repair.

2. The method for evaluating the service status of high-speed railway turnouts according to claim 1, characterized in that, In step one, the indicators affecting train operation mainly include the geometric state of the static track, while the indicators affecting the long-term service of the turnout structure itself include the assembly state between track components and whether the rail components are severely corroded.

3. The method for evaluating the service status of high-speed railway turnouts according to claim 1, characterized in that, In step two, the indicators affecting train performance include static geometric dimensions and dynamic irregularities; the indicators for maintaining turnout structural performance include rail wear, rail damage, fastener performance, connecting components, tightness and gaps, electrical interface status, and turnout sleeper track bed status; and the indicators for evaluating the impact of historical maintenance include replacing rail components, replacing connecting components, and repairing the substructure.

4. The method for evaluating the service status of high-speed railway turnouts according to claim 1, characterized in that, In step three, static and dynamic correlation analysis is first performed to construct a vehicle-refined turnout dynamic coupling model. This model analyzes which indicators affect driving performance and which affect structural performance, thereby classifying and linking these indicators to explore the impact of static geometric parameters on the driving performance and structural safety performance of the turnout area. Static geometric irregularities are set up, and orthogonal design methods are used to calculate the impact of different factors on driving dynamic performance. Then, key factors are screened, the calculated effect assessment values ​​are used as experimental results, and the effects of each analysis factor are obtained according to the variance calculation method of orthogonal experiment, and the key factors affecting dynamic driving performance are extracted. Further optimization of evaluation index parameters: Based on the static and dynamic analysis of high-speed turnout structure, the evaluation indexes are optimized, and various evaluation index parameters for turnout service performance are formulated, which are divided into two categories: Level I indicators and Level II indicators. Level I indicators include those affecting train performance, those maintaining the structural condition of turnout, and those affecting historical maintenance; Level II indicators are the detailed inspection items of each Level I indicator. Finally, all indicators and items are normalized and effectively evaluated.

5. The method for evaluating the service status of high-speed railway turnouts according to claim 4, characterized in that, When normalizing the various indicator items, a piecewise smoothing function based on the Sigmoid function is used as the normalization function; in: The meanings of the various parameters are as follows: x : Index value (input); L p Planned maintenance limits; L t Temporary repair limits; A: This is the penalty weight for the first descent phase, controlling the magnitude of performance degradation starting from Lp; B: Penalty weight control for the second descent phase, representing the magnitude of the sharp performance drop starting from Lt.

6. The method for evaluating the service status of high-speed railway turnouts according to claim 1, characterized in that, In step four, since the next level of detailed inspection items of each indicator have different impacts on the overall evaluation, it is necessary to divide the next level of detailed indicator items into weights, form a comparison matrix of the next level of detailed inspection items of each indicator, calculate the eigenvector corresponding to the largest eigenvalue of the judgment matrix, and normalize it as the weight. Then the weight coefficient of indicator Vi (i takes the value 1, 2, 3, ... n) can be obtained. The weight corresponding to the i-th indicator is ki, the score is Pi, and the score of the corresponding indicator is calculated. Based on this, the final evaluation results of three types of indicators were obtained, with the weights for driving performance, structural performance, and historical maintenance being 0.45, 0.45, and 0.1, respectively, resulting in the final evaluation result for the turnout. .

7. The method for evaluating the service status of high-speed railway turnouts according to claim 1, characterized in that, When the Level 1 score is below 90, attention should be paid to it; when the Level 1 score is below 80, the various indicators of the Level 2 score should be analyzed; determine which category of score is too low and make planned repairs; when the score of a certain category of indicators in the Level 2 score is also below 80, identify the specific Level 3 detailed item indicator parameters that are exceeding the limits and should arrange repairs.

8. The method for evaluating the service status of high-speed railway turnouts according to claim 1, characterized in that, In step five, the evaluation results of the three-level indicators are recorded on a weekly or monthly basis. The development and change patterns of each level of indicators are analyzed. If a sudden change in the evaluation score occurs, the cause is investigated immediately.

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