Service state evaluation method for large-ramp seamless track fastener system

Abstract

The invention provides a service state evaluation method for a large-ramp seamless track fastener system. The method comprises the following steps: determining an evaluation object of the large-ramp seamless track fastener system, collecting evaluation parameters representing the service state of the fastener system, and establishing a dimensionless evaluation decision matrix according to the evaluation parameters representing the service state of the fastener system; performing weight assignment on dimensionless evaluation parameters in the dimensionless evaluation decision matrix based on a deviation maximization objective weighting multi-parameter fusion algorithm, and performing normalization processing to obtain an abnormal service state evaluation value of each component of the fastener system; based on the abnormal service state evaluation value of each component of the fastener system, obtaining different service state evaluation scores of the fastener system through a relative difference method; and obtaining an overall service state comprehensive evaluation index of the fastener system through an accumulation method based on the evaluation scores of the different service states of the fastener system. According to the method, the operation and maintenance strategy of the seamless track design in the hard mountainous area can be perfected, and quantitative evaluation of the service state of the fastener system is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of railway line fastener systems, and in particular to a service status evaluation method for a seamless line fastener system on a steep slope. Background Art

[0002] Rail fasteners, as an important component of the track structure, are used to connect the rails and the supporting structure under the rails. They have the functions of fixing the position of the rails, providing elastic support for the rails, and dispersing and transmitting the vertical and lateral forces between the wheels and rails. By effectively transferring the load, the fasteners enable the rails, sleepers, roadbed and other track components to form an integrated structural system. They are key components to ensure the stable, safe and smooth operation of seamless lines, and play a vital role in ensuring the safety, stability and smoothness of train operations.

[0003] Therefore, a correct evaluation of the service status and service performance of the fastener system is of great significance for timely and accurate understanding of the health status of the fasteners, ensuring the safe operation of railway lines, and extending the service life of the fasteners and the entire line. However, the current existing methods for evaluating the service status of seamless line fastener systems lack versatility and universality when applied to lines with different operating environments and different speed levels, and are difficult to meet the needs of the service environment operation of seamless lines with large slopes in the western mountainous areas. Therefore, there is an urgent need for a method for evaluating the service status of seamless line fastener systems under large slope conditions to improve the design and operation and maintenance strategies of seamless lines in difficult mountainous areas and provide solid theoretical and technical support for ensuring the safe and reliable service of seamless lines in complex operating environments. Summary of the Invention

[0004] The present invention provides a service status evaluation method for a steep slope seamless line fastener system, so as to realize a comprehensive and quantitative evaluation of the service status of the fastener system in a steep slope section of a railway track.

[0005] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions.

[0006] A service status evaluation method for a seamless track fastener system on a steep slope, comprising:

[0007] Determine the evaluation object of the fastener system of the steep slope seamless railway and collect evaluation parameters representing the service status of the fastener system;

[0008] Performing dimensionless processing on various evaluation parameters characterizing the service status of the fastener system to establish a dimensionless evaluation decision matrix;

[0009] The dimensionless evaluation parameters in the dimensionless evaluation decision matrix are weighted and normalized based on an objective weighted multi-parameter fusion algorithm with maximum deviation to obtain the abnormal service status evaluation value of each component of the fastener system;

[0010] Obtaining evaluation scores for different service states of the fastener system by a relative difference method based on the evaluation values of abnormal service states of each component of the fastener system;

[0011] Based on the evaluation scores of different service states of the fastener system, a comprehensive evaluation index of the overall service state of the fastener system is obtained by a cumulative method.

[0012] Preferably, the determination of the evaluation object of the steep slope seamless railway fastener system and the collection of evaluation parameters characterizing the service status of the fastener system include:

[0013] The evaluation objects of the fastener system for seamless railway tracks with large slopes include the normal service status of the fastener system, the protrusion of the rubber pad under the rail, the reduction of the friction coefficient between the rubber pad under the rail and the rail layer, the increase of the elastic modulus of the rubber pad under the rail, the reduction of the friction coefficient between the elastic pad under the iron pad and the iron pad layer, the increase of the elastic modulus of the elastic pad under the iron pad, the insufficient pressure of the spring clip, the fracture of the spiral spike, and the reduction of the friction coefficient between the insulating gauge block and the rail;

[0014] Construct a refined finite element model of the seamless railway fastener system, including ω-shaped fastener spring bars, rubber pads under rails, iron pads, insulating gauge blocks, gauge baffles, elastic pads under iron pads, spiral spikes, flat washers, height adjustment pads under iron pads, rails, and sleeper components;

[0015] Applying multiple cyclic loads to the seamless railway fastener system on the steep slope, and using a refined finite element model of the seamless railway fastener system to collect evaluation parameters that can characterize the service status of the fastener system, the evaluation parameters that characterize the service status of the fastener system include rail creep, spring clip pressure decay rate, and degradation coefficients of various fastener system components;

[0016] The rail creep is the cumulative rail creep after multiple cyclic loads are applied to the fastener system. The spring clip pressure decay rate is the ratio of the difference between the spring clip pressure and the initial normal installation pressure after multiple cyclic loads are applied to the fastener system to the initial normal installation pressure. The degradation coefficient of each component of the fastener system is the ratio of the Mises stress of each component after multiple cyclic loads are applied to the fastener system to the corresponding allowable tensile strength.

[0017] Preferably, the dimensionless processing of the evaluation parameters characterizing the service status of the fastener system to establish a dimensionless evaluation decision matrix includes:

[0018] The various evaluation parameters that characterize the service status of the fastener system are divided into positive indicators and negative indicators. A positive indicator means that the larger the evaluation parameter value, the better the final evaluation result, while a negative indicator means that the smaller the evaluation parameter value, the better the final evaluation result. The following formula can be used for calculation:

[0019] Positive indicators:

[0020] Negative indicators:

[0021] Among them, x ij represents the evaluation value of the evaluation parameter G under the evaluation object A; r ij Indicates the normalized evaluation index value; It represents the maximum value of the evaluation object set A under the evaluation parameter G;

[0022] The dimensionless evaluation parameter values after dimensionless processing are used as column vectors, and the evaluation objects are used as row vectors to construct the dimensionless evaluation decision matrix R of the fastener system service status.

[0023] Preferably, the objective weighted multi-parameter fusion algorithm based on maximization of deviation assigns weights to the dimensionless evaluation parameters in the dimensionless evaluation decision matrix and performs normalization processing to obtain the abnormal service status evaluation value of each component of the fastener system, including:

[0024] The weight vector of each evaluation parameter in the dimensionless evaluation decision matrix R is set to:

[0025]

[0026] Among them, ω is the weight vector of the evaluation parameter, m is the number of evaluation parameters, j is the index of the evaluation parameter, ω j Indicates the weight of the evaluation parameter;

[0027] According to the idea of maximizing deviation, if the evaluation parameter G j If the differences in the evaluation values of all evaluation objects are large, it is considered that this evaluation parameter has a greater impact on the evaluation results of the evaluation object, and a larger weight coefficient is assigned. The objective function is constructed as follows:

[0028]

[0029] Among them, maxF(ω) represents the maximum value in the weight vector, m is the number of evaluation parameters, n is the number of evaluation objects, i and k are the indexes of evaluation objects, j is the index of evaluation parameters, and r ij 、r kj All represent the normalized evaluation parameter values, and st is the constraint condition of the objective function;

[0030] Construct a Lagrangian function to solve the objective function, and the solution of the function is:

[0031]

[0032] Among them, ω jIndicates the weight of the evaluation parameter, m is the number of evaluation parameters, n is the number of evaluation objects, i and k are the indexes of the evaluation objects, j is the index of the evaluation parameter, and r ij 、r kj All represent the normalized evaluation parameter values;

[0033] Normalize the weight vector ω to obtain the weight coefficient of each evaluation parameter:

[0034]

[0035] Among them, ω j * represents the normalized evaluation parameter weight, m is the number of evaluation parameters, n is the number of evaluation objects, i and k are the indexes of evaluation objects, j is the index of evaluation parameters, and r ij 、r kj All represent the normalized evaluation parameter values;

[0036] Get the standardized evaluation decision matrix R = (r ij ) n*m , calculate the multi-parameter fusion evaluation value Q of the fastener system in different service states i :

[0037]

[0038] Among them, Q i represents the multi-index fusion evaluation value, ω j * represents the normalized evaluation parameter weight, j is the index of the evaluation parameter, n is the number of evaluation objects, r ij Indicates the normalized evaluation parameter value.

[0039] Preferably, the step of obtaining evaluation scores of different service states of the fastener system by a relative difference method based on the evaluation values of abnormal service states of various components of the fastener system includes:

[0040] The evaluation scores of different service states of the fastener system are calculated using the following formula:

[0041]

[0042] Among them, C i Indicates the service status evaluation score of the fastener system, Q 正常 It represents the evaluation score of the fastener system under normal service conditions, Q 异常 Indicates the evaluation score of the fastener system under abnormal service conditions.

[0043] Preferably, the method of obtaining the comprehensive evaluation index of the overall service status of the fastener system by accumulating the evaluation scores of different service statuses of the fastener system includes:

[0044] Based on the evaluation scores of different service states of the fastener system, the overall service state comprehensive evaluation index FQI of the fastener system is calculated by the accumulation method:

[0045]

[0046] Among them, FQI represents the comprehensive evaluation index of the overall service status of the fastener system;

[0047] The higher the FQI score of the overall service status comprehensive evaluation index of the fastener system, the more serious the deterioration of the service status of the fastener system.

[0048] It can be seen from the technical solutions provided by the above-mentioned embodiments of the present invention that the method of the present invention can improve the design and operation and maintenance strategy of seamless lines in difficult mountainous areas, ensure the safe and reliable service of seamless lines in complex operating environments, and thus realize the quantitative evaluation of the service status of the fastener system.

[0049] Additional aspects and advantages of the present invention will be set forth in part in the following description, will become apparent from the following description, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0051] Figure 1 A processing flow chart of a service status evaluation method for a steep slope seamless railway fastener system provided by an embodiment of the present invention;

[0052] Figure 2 A refined finite element model of the seamless railway fastener system provided in an embodiment of the present invention; Figure 2 In the figure, 1 is the rail, 2 is the spiral spike, 3 is the flat washer, 4 is the ω-shaped spring bar, 5 is the insulating gauge block, 6 is the gauge baffle, 7 is the rubber pad under the rail, 8 is the iron pad, 9 is the elastic pad under the iron pad, 10 is the height adjustment pad under the iron pad, and 11 is the sleeper.

[0053] Figure 3 This is an example diagram of rail creep under different service conditions of the fastener system collected in the finite element simulation model provided in an embodiment of the present invention.

[0054] Figure 4This is an example diagram of the pressure attenuation rate of the spring clip under different service states of the fastener system collected in the finite element simulation model provided in an embodiment of the present invention.

[0055] Figure 5 This is an example diagram of degradation coefficients of various components of the fastener system under different service conditions collected in the finite element simulation model provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0056] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limiting the present invention.

[0057] It will be understood by those skilled in the art that, unless expressly stated otherwise, the singular forms "a", "an", "said" and "the" used herein may also include the plural forms. It should be further understood that the term "comprising" used in the description of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, "connected" or "coupled" as used herein may include wireless connections or couplings. The term "and / or" used herein includes any unit and all combinations of one or more associated listed items.

[0058] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art in the art to which the present invention pertains. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art and, unless defined as such herein, will not be interpreted in an idealized or overly formal sense.

[0059] To facilitate understanding of the embodiments of the present invention, several specific embodiments will be further explained below with reference to the accompanying drawings, and each embodiment does not constitute a limitation on the embodiments of the present invention.

[0060] In order to simultaneously consider the abnormal service status of different components of the fastener system and realize the quantitative and comprehensive evaluation of the overall service status of the fastener system, the processing flow of a service status evaluation method for a large slope seamless railway fastener system provided in an embodiment of the present invention is as follows: Figure 1 As shown, the processing steps include the following:

[0061] Step S1: Determine the evaluation object of the fastener system, collect evaluation parameters that characterize the service status of the fastener system, and construct an evaluation decision matrix based on various evaluation parameters.

[0062] The evaluation objects of the fastener system for a seamless railway track on a steep slope selected in the embodiment of the present invention include, but are not limited to, the normal service status of the fastener system, the protrusion of the rubber pad under the rail, the reduction of the friction coefficient between the rubber pad under the rail and the rail layer, the increase of the elastic modulus of the rubber pad under the rail, the reduction of the friction coefficient between the elastic pad under the iron pad and the iron pad layer, the increase of the elastic modulus of the elastic pad under the iron pad, insufficient pressure of the spring clip, broken spiral spikes, and the reduction of the friction coefficient between the insulating gauge block and the rail.

[0063] The embodiment of the present invention establishes a refined finite element model of a seamless railway fastener system including components such as ω-shaped fastener spring bars, rubber pads under rails, iron pads, insulating gauge blocks, gauge baffles, elastic pads under iron pads, spiral spikes, flat washers, height adjustment pads under iron pads, rails, and sleepers. Figure 2 A refined finite element model of the seamless line fastener system provided in an embodiment of the present invention, Figure 2 In the figure, 1 is the rail, 2 is the spiral spike, 3 is the flat washer, 4 is the ω-shaped spring bar, 5 is the insulating gauge block, 6 is the gauge baffle, 7 is the rubber pad under the rail, 8 is the iron pad, 9 is the elastic pad under the iron pad, 10 is the height adjustment pad under the iron pad, and 11 is the sleeper.

[0064] The parameters of the refined finite element model of the seamless railway fastener system are shown in Table 1. All components are simulated using solid elements.

[0065] Table 1 Parameters of the refined finite element model of the seamless railway fastener system

[0066]

[0067] Each component of the seamless railway fastener system is designed based on the actual design material properties. Fastener systems are assembled structures consisting of multiple components. Accurately modeling the constraints between component connections is a key challenge in fastener system analysis, requiring the establishment of appropriate constraints to simulate the force transfer between components. To ensure the relevance of the simulation analysis and the accuracy of the results, nonlinear contact elements are used at component connections based on nonlinear contact theory. Specific boundary conditions are then applied to the refined model based on actual research findings.

[0068] The braking load acting on the fastener system on the ramp has a component of the train load in the direction of the ramp, so the ramp component of the train load should also be added when calculating the braking load. The train braking load can be calculated using the following method:

[0069] Pz=Q×sinα+Q×cosα×μ

[0070] Where Pz is the train braking load, Q is the train load, α is the slope inclination, and μ is the braking adhesion coefficient.

[0071] In this embodiment of the present invention, five cyclic loads are applied to the fastener system. A refined finite element model of the seamless railway fastener system is used to collect evaluation parameters that can characterize the service status of the fastener system. These evaluation parameters include, but are not limited to, rail creep, spring clip pressure decay rate, and degradation coefficients of various fastener system components. Rail creep is the cumulative amount of rail creep after five cyclic loads are applied to the fastener system. Figure 3 This is an example diagram of rail creep at different service states of the fastener system collected in the finite element simulation model provided in the embodiment of the present invention, as shown in FIG. Figure 3 As shown in the figure; the spring clip buckle pressure attenuation rate is the ratio of the difference between the spring clip buckle pressure and the initial normal installation buckle pressure after 5 cyclic loads are applied to the fastener system to the initial normal installation buckle pressure. Figure 4 This is an example diagram of the pressure decay rate of the spring clip when the fastener system is in different service states, collected from the finite element simulation model provided in the embodiment of the present invention. Figure 4 As shown in the figure; the degradation coefficient of each component of the fastener system is the ratio of the Mises stress of each component to the corresponding allowable tensile strength after 5 cyclic loads are applied to the fastener system. Figure 5 This is an example diagram of degradation coefficients of various components of the fastener system at different service states collected from the finite element simulation model provided in the embodiment of the present invention, such as Figure 5 shown.

[0072] The evaluation decision matrix X constructed by the embodiment of the present invention using various evaluation parameters that characterize the service status of the fastener system is shown in Table 2.

[0073] Table 2 Fastener system service status evaluation decision matrix

[0074]

[0075]

[0076] Step S2: Perform dimensionless processing on the collected characterization parameters and establish a dimensionless evaluation decision matrix R.

[0077] Since the evaluation parameters may have different dimensions, orders of magnitude, and units, the original evaluation indicators need to be dimensionless in order to obtain correct evaluation results. Considering the different directions of influence of each evaluation parameter on the evaluation results, the evaluation indicators can be divided into positive indicators and negative indicators; positive indicators mean that the larger the evaluation parameter value, the better the final evaluation result, while negative indicators mean that the smaller the evaluation parameter value, the better the final evaluation result. The following formula can be used for calculation:

[0078] Positive indicators:

[0079] Negative indicators:

[0080] Among them, x ij represents the evaluation value of the evaluation parameter G under the evaluation object A; r ij Indicates the normalized evaluation index value; It represents the maximum value of the evaluation object set A under the evaluation parameter G.

[0081] The dimensionless evaluation parameter values after dimensionless processing are used as column vectors, and the evaluation objects are used as row vectors to construct a dimensionless evaluation decision matrix for the service status of the fastener system.

[0082] Illustratively, the dimensionless evaluation decision matrix R constructed in this embodiment of the present invention is shown in Table 3.

[0083] Table 3 Dimensionless evaluation decision matrix for fastener system service status

[0084]

[0085]

[0086] Step S3: weight the evaluation parameters based on the multi-parameter fusion algorithm of maximizing the deviation, and perform normalization processing to obtain evaluation values of different service states of the fastener system.

[0087] The principle of maximizing the deviation is to reflect the differences between evaluation parameters by assigning greater weights to evaluation parameters that have a greater impact on the evaluation results.

[0088] The weight assignment of the dimensionless evaluation parameters in the dimensionless evaluation decision matrix R can be calculated using the following formula:

[0089] The weight vector of each evaluation parameter is set as:

[0090]

[0091] Among them, ω is the weight vector of the evaluation parameter, m is the number of evaluation parameters, j is the index of the evaluation parameter, ω j Represents the weight of the evaluation parameter.

[0092] According to the idea of maximizing deviation, if the evaluation parameter G j If the difference in the evaluation values of all evaluation objects is large, it is considered that this evaluation parameter has a greater impact on the evaluation results of the evaluation object and should be given a larger weight coefficient. Therefore, the objective function is constructed as follows:

[0093]

[0094] Among them, maxF(ω) represents the maximum value in the weight vector, m is the number of evaluation parameters, n is the number of evaluation objects, i and k are the indexes of evaluation objects, j is the index of evaluation parameters, and r ij 、r kj Both represent the normalized evaluation parameter values, ω j represents the weight of the evaluation parameter, and st is the constraint condition of the objective function.

[0095] The objective function is solved by using the Lagrangian function, and the Lagrangian multiplier λ is introduced to construct the Lagrangian function Respectively for ω j and λ to find the partial derivative, set the partial derivative to zero, and solve for ω j and λ, and according to the constraint ω j ≥0 Check the solved ω j The value meets the requirements. If not, the weight that does not meet the conditions is projected into the feasible region according to the projection method to obtain the weight value that meets the requirements. That is, the solution of the objective function is:

[0096]

[0097] Among them, ω j Indicates the weight of the evaluation parameter, m is the number of evaluation parameters, n is the number of evaluation objects, i and k are the indexes of the evaluation objects, j is the index of the evaluation parameter, and r ij 、r kj All represent the normalized evaluation parameter values.

[0098] Then, the calculated weight vector ω is normalized to finally obtain the weight coefficients of each evaluation parameter:

[0099]

[0100] Among them, ω j * represents the normalized evaluation parameter weight, m is the number of evaluation parameters, n is the number of evaluation objects, i and k are the indexes of evaluation objects, j is the index of evaluation parameters, and r ij 、r kj All represent the normalized evaluation parameter values.

[0101] The weight coefficients of the evaluation parameters of different service states of the fastener system obtained in the embodiment of the present invention are shown in Table 4.

[0102] Table 4

[0103]

[0104] According to the above normalized evaluation decision matrix R=(r ij ) n*m and the weight vector ω * , perform multi-parameter fusion evaluation value Q i Calculation:

[0105]

[0106] Among them, Q i represents the multi-index fusion evaluation value, ω j * represents the normalized evaluation parameter weight, n represents the number of evaluation objects, r ij Indicates the normalized evaluation parameter value.

[0107] Among them, Q i Represents the multi-index fusion evaluation value.

[0108] The multi-parameter fusion evaluation values of the fastener system in different service states obtained in the embodiment of the present invention are shown in Table 5.

[0109] Table 5 Multi-parameter fusion evaluation values of fastener system service status

[0110]

[0111]

[0112] Step S4: Processing the service status evaluation value of the fastener system based on the relative difference method to determine the evaluation scores of different service statuses of the fastener system.

[0113] The evaluation scores of different service conditions of the fastener system can be calculated using the following formula:

[0114]

[0115] Among them, C i Indicates the service status evaluation score of the fastener system, Q 正常 It represents the evaluation score of the fastener system under normal service conditions, Q 异常 Indicates the evaluation score of the fastener system under abnormal service conditions.

[0116] The evaluation scores of the fastener systems in different service states obtained in the embodiments of the present invention are shown in Table 6.

[0117] Table 6 Fastener system service status evaluation scores

[0118]

[0119] The higher the evaluation score, the more serious the deterioration of the fastener system's service condition.

[0120] Step S5: Based on the accumulation method, a comprehensive evaluation index FQI of the overall service status of the fastener system is proposed to quantitatively evaluate the service status of the fastener system.

[0121] In a fastener system's complex service environment, the abnormal service state that may occur is no longer a single case, nor is it a superposition of abnormal service states of different components. The comprehensive evaluation index FQI of the fastener system's overall service state can be calculated using the following formula:

[0122]

[0123] Among them, FQI represents the comprehensive evaluation index of the overall service status of the fastener system.

[0124] The above formula and the service status evaluation score of the fastener system can be used to comprehensively and quantitatively evaluate the overall service status of the fastener system. The higher the FQI score of the comprehensive evaluation index of the overall service status of the fastener system, the more serious the deterioration of the service status of the fastener system.

[0125] For example, when the fastener system has two service degradation conditions: the rail pad protrudes 10 mm and the friction coefficient between the rail rubber pad and the rail layer decreases to 0.25; and the rail pad protrudes 30 mm and the friction coefficient between the rail rubber pad and the rail layer decreases to 0.30. The FQI values under these two service degradation conditions are shown in Table 7.

[0126] Table 7 FQI score of the overall service status comprehensive index of the fastener system

[0127]

[0128] It can be seen from Table 7 that the FQI value of the overall service status of the second fastener system is higher than that of the first fastener system, indicating that the overall service status of the second fastener system is worse than that of the first fastener system.

[0129] In summary, this invention integrates evaluation parameters that characterize the service condition of a fastener system and proposes a comprehensive evaluation index (FQI) for the overall service condition of the fastener system based on an objectively weighted multi-parameter fusion algorithm that maximizes deviations. This allows for a quantitative assessment of the service condition of the fastener system. This invention, the first to propose a comprehensive evaluation method for the service condition of a fastener system, provides a reference basis and theoretical support for evaluating the service condition of fastener systems and has significant engineering value and significance for the condition monitoring and maintenance of railway track fastener systems.

[0130] Those skilled in the art will appreciate that the accompanying drawings are merely schematic diagrams of an embodiment, and the modules or processes in the accompanying drawings are not necessarily required to implement the present invention.

[0131] From the above description of the embodiments, it can be seen that those skilled in the art can clearly understand that the present invention can be implemented by means of software plus the necessary general-purpose hardware platform. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present invention or certain parts of the embodiments.

[0132] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device or system embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, refer to the partial description of the method embodiments. The device and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. A person of ordinary skill in the art can understand and implement it without making any creative efforts.

[0133] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for evaluating the service status of a seamless railway fastener system on a steep slope, characterized in that: include: Determine the evaluation object of the fastener system of the steep slope seamless railway and collect evaluation parameters representing the service status of the fastener system; Performing dimensionless processing on various evaluation parameters characterizing the service status of the fastener system to establish a dimensionless evaluation decision matrix; The dimensionless evaluation parameters in the dimensionless evaluation decision matrix are weighted and normalized based on an objective weighted multi-parameter fusion algorithm with maximum deviation to obtain the abnormal service status evaluation value of each component of the fastener system; Obtaining evaluation scores for different service states of the fastener system by a relative difference method based on the evaluation values of abnormal service states of each component of the fastener system; Based on the evaluation scores of different service states of the fastener system, a comprehensive evaluation index of the overall service state of the fastener system is obtained by a cumulative method.

2. The method according to claim 1, characterized in that The determination of the evaluation object of the steep slope seamless railway fastener system and the collection of evaluation parameters representing the service status of the fastener system include: The evaluation objects of the fastener system for seamless railway tracks with large slopes include the normal service status of the fastener system, the protrusion of the rubber pad under the rail, the reduction of the friction coefficient between the rubber pad under the rail and the rail layer, the increase of the elastic modulus of the rubber pad under the rail, the reduction of the friction coefficient between the elastic pad under the iron pad and the iron pad layer, the increase of the elastic modulus of the elastic pad under the iron pad, the insufficient pressure of the spring clip, the fracture of the spiral spike, and the reduction of the friction coefficient between the insulating gauge block and the rail; Construct a refined finite element model of the seamless railway fastener system, including ω-shaped fastener spring bars, rubber pads under rails, iron pads, insulating gauge blocks, gauge baffles, elastic pads under iron pads, spiral spikes, flat washers, height adjustment pads under iron pads, rails, and sleeper components; Applying multiple cyclic loads to the seamless railway fastener system on the steep slope, and using a refined finite element model of the seamless railway fastener system to collect evaluation parameters that can characterize the service status of the fastener system, the evaluation parameters that characterize the service status of the fastener system include rail creep, spring clip pressure decay rate, and degradation coefficients of various fastener system components; The rail creep is the cumulative rail creep after multiple cyclic loads are applied to the fastener system. The spring clip pressure decay rate is the ratio of the difference between the spring clip pressure and the initial normal installation pressure after multiple cyclic loads are applied to the fastener system to the initial normal installation pressure. The degradation coefficient of each component of the fastener system is the ratio of the Mises stress of each component after multiple cyclic loads are applied to the fastener system to the corresponding allowable tensile strength.

3. The method according to claim 2, characterized in that The dimensionless processing of the evaluation parameters characterizing the service status of the fastener system to establish a dimensionless evaluation decision matrix includes: The evaluation parameters characterizing the service status of the fastener system are divided into positive indicators and negative indicators. A positive indicator means that the larger the evaluation parameter value, the better the final evaluation result; a negative indicator means that the smaller the evaluation parameter value, the better the final evaluation result. The following formula can be used for calculation: Positive indicators: Negative indicators: Among them, x ij represents the evaluation value of the evaluation parameter G under the evaluation object A; r ij Indicates the normalized evaluation index value; It represents the maximum value of the evaluation object set A under the evaluation parameter G; The dimensionless evaluation parameter values after dimensionless processing are used as column vectors, and the evaluation objects are used as row vectors to construct the dimensionless evaluation decision matrix R of the fastener system service status.

4. The method according to claim 3, characterized in that The objective weighted multi-parameter fusion algorithm based on maximization of deviation assigns weights to the dimensionless evaluation parameters in the dimensionless evaluation decision matrix and performs normalization processing to obtain the abnormal service status evaluation value of each component of the fastener system, including: The weight vector of each evaluation parameter in the dimensionless evaluation decision matrix R is set to: Among them, ω is the weight vector of the evaluation parameter, m is the number of evaluation parameters, j is the index of the evaluation parameter, ω j Indicates the weight of the evaluation parameter; According to the idea of maximizing deviation, if the evaluation parameter G j If the differences in the evaluation values of all evaluation objects are large, it is considered that this evaluation parameter has a greater impact on the evaluation results of the evaluation object, and a larger weight coefficient is assigned. The objective function is constructed as follows: Among them, maxF(ω) represents the maximum value in the weight vector, m is the number of evaluation parameters, n is the number of evaluation objects, i and k are the indexes of evaluation objects, j is the index of evaluation parameters, and r ij 、r kj All represent the normalized evaluation parameter values, and st is the constraint condition of the objective function; Construct a Lagrangian function to solve the objective function, and the solution of the function is: Among them, ω j Indicates the weight of the evaluation parameter, m is the number of evaluation parameters, n is the number of evaluation objects, i and k are the indexes of the evaluation objects, j is the index of the evaluation parameter, and r ij 、r kj All represent the normalized evaluation parameter values; Normalize the weight vector ω to obtain the weight coefficient of each evaluation parameter: Among them, ω j * represents the normalized evaluation parameter weight, m is the number of evaluation parameters, n is the number of evaluation objects, i and k are the indexes of evaluation objects, j is the index of evaluation parameters, and r ij 、r kj All represent the normalized evaluation parameter values; Get the standardized evaluation decision matrix R = (r ij ) n*m , calculate the multi-parameter fusion evaluation value Q of the fastener system in different service states i : Among them, Q i represents the multi-index fusion evaluation value, ω j * represents the normalized evaluation parameter weight, j is the index of the evaluation parameter, n is the number of evaluation objects, r ij Indicates the normalized evaluation parameter value.

5. The method according to claim 4, characterized in that The method of obtaining evaluation scores of different service states of the fastener system by a relative difference method based on the abnormal service state evaluation values of each component of the fastener system includes: The evaluation scores of different service states of the fastener system are calculated using the following formula: Among them, C i Indicates the service status evaluation score of the fastener system, Q 正常 It represents the evaluation score of the fastener system under normal service conditions, Q 异常 Indicates the evaluation score of the fastener system under abnormal service conditions.

6. The method according to claim 5, characterized in that The method of obtaining the comprehensive evaluation index of the overall service status of the fastener system by accumulating the evaluation scores of different service status of the fastener system includes: Based on the evaluation scores of different service states of the fastener system, the overall service state comprehensive evaluation index FQI of the fastener system is calculated by the accumulation method: Among them, FQI represents the comprehensive evaluation index of the overall service status of the fastener system; The higher the FQI score of the overall service status comprehensive evaluation index of the fastener system, the more serious the deterioration of the service status of the fastener system.

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