Rail resonator design method and system based on sensitive frequency bands of actual railway operation

Abstract

The present invention discloses a rail resonator design method and system based on the actual railway operation sensitive frequency band, belonging to the railway design technology field; including testing the disease characteristics of the operating track according to the operating conditions of the railway site, obtaining the vibration signals corresponding to different operating track diseases under the actual operating state; inputting the vibration signals into the frequency domain feature recognition algorithm respectively, obtaining the vibration main frequency information corresponding to different operating track diseases; optimizing the vibration main frequency information corresponding to different operating track diseases through the fixed point theory to obtain the initial values ​​corresponding to different operating track diseases; inputting the resonator design theory, the initial value corresponding to the operating track disease, and the minimum amplitude in the vibration main frequency information into the multi-objective optimization algorithm to calculate the rail resonator design parameters. The present invention can propose the corresponding rail dynamic resonator dynamic parameters according to the main track dynamic damage characteristics on site, and simultaneously achieve the vibration reduction effect on multiple track disease main vibration frequency bands.

Description

Technical Field

[0001] The present invention belongs to the technical field of railway design, and in particular relates to a rail resonator design method and system based on a sensitive frequency band of actual railway operation. Background Art

[0002] With the rapid development of rail transit in major and medium-sized cities in my country, the vibration damage problem caused by its high operating speed and intensive operating frequency has become increasingly prominent. Figure 1 The wavy wear damage on the rail surface is shown, which will aggravate the high-frequency vibration of the wheel and rail, and further cause problems such as excessive noise and fracture of track structures. Figure 2 The problem of spring clip breakage caused by high-frequency wheel-rail vibration is demonstrated.

[0003] In order to deal with the problem of track vibration damage, rail resonator is currently one of the more commonly used means to control vibration damage.

[0004] Although dynamic resonators have been widely used in the treatment of dynamic diseases in urban rail transit, there are still certain problems that affect their actual use effect:

[0005] (1) At present, rail resonators are often "pre-designed", that is, mature products are first formed during the research and development process, and the vibration reduction frequency band and effect requirements of the corresponding products are obtained during the research and development test process. In actual application, suitable products are selected by matching the resonance frequency characteristics of the phenomenon in the existing product library. However, considering that the actual wheel-rail vibration on site is generally broadband (1-5000Hz) and random vibration, in the actual treatment process, the rail resonator in the existing product library may not match the main frequency of the wheel-rail vibration disease on site.

[0006] (2) In actual engineering projects, wheel-rail vibration diseases often occur simultaneously with multiple resonance disease problems. Each disease corresponds to one or more resonance frequency ranges. However, existing resonator products often find it difficult to achieve simultaneous vibration reduction of multiple resonance frequency bands on site.

[0007] Therefore, it is urgent to develop a rail resonator design method based on the actual on-site operation characteristics. On the basis of mastering the main dynamic damage frequency bands of the on-site rail system, the corresponding resonator design parameters can have a certain vibration reduction effect for multiple resonance frequency bands on site. Summary of the invention

[0008] The purpose of the present invention is to meet actual needs and provide a rail resonator design method and system based on the actual railway operation sensitive frequency band. According to the main track dynamic damage characteristics on site, the corresponding rail dynamic resonator dynamic parameters can be proposed, and the vibration reduction effect of multiple track disease main vibration frequency bands can be achieved at the same time, ensuring targeted treatment of track vibration diseases on site and better guiding the on-site track operation disease treatment work.

[0009] In the first aspect, in order to achieve the above-mentioned invention object, the first object of the present invention is to provide a rail resonator design method based on the actual railway operation sensitive frequency band, comprising:

[0010] S1. According to the operating conditions of the railway site, the disease characteristics of the operating track are tested to obtain the vibration signals corresponding to different operating track diseases under the actual operating conditions;

[0011] S2. Input the vibration signals into the frequency domain feature recognition algorithm to obtain the vibration main frequency information corresponding to different operating track diseases;

[0012] S3, optimizing the vibration main frequency information corresponding to different operating track diseases through fixed point theory to obtain initial values ​​corresponding to different operating track diseases;

[0013] S4. The resonator design formula is used as the function to be optimized, the initial value corresponding to the operating track disease is used as the input value of the function to be optimized, and the minimum amplitude in the vibration main frequency information corresponding to the operating track disease is used as the constraint condition. The design parameters of the rail resonator are calculated using a multi-objective optimization algorithm.

[0014] In the above-mentioned scheme of the rail resonator design method based on the actual railway operation sensitive frequency band, the disease characteristic test includes rail corrugation characteristic test, fastener system natural frequency test, rail vibration main frequency test and wheel-rail operation noise test.

[0015] In the above-mentioned scheme of the rail resonator design method based on the sensitive frequency band of actual railway operation, the test method of the disease characteristic test includes a wheel-rail dynamic characteristic test and an in-situ excitation test.

[0016] In the above-mentioned scheme of the rail resonator design method based on the actual railway operation sensitive frequency band, the frequency domain feature recognition algorithm includes the following steps:

[0017] The frequency domain feature recognition algorithm comprises the following steps:

[0018] S21, performing wavelet transform on the vibration signal to obtain a time-frequency domain characteristic relationship;

[0019] S22, determining the main frequency band of vibration and the corresponding intensity characteristics according to the time-frequency domain characteristics, and performing time partition processing on the vibration signal;

[0020] S23, respectively process the vibration signals in each time partition by short-time Fourier transform, extract the frequency information in each time partition according to the signal strength, and take the frequency information with the largest signal strength as the main vibration frequency information.

[0021] In the above-mentioned scheme of the rail resonator design method based on the sensitive frequency band of actual railway operation, the time-frequency domain characteristic relationship includes the intensity and frequency domain distribution characteristics of the vibration signal at each moment.

[0022] In the above scheme of the rail resonator design method based on the actual railway operation sensitive frequency band, the initial values ​​are the mass, damping and stiffness of the resonator.

[0023] In the above scheme of the rail resonator design method based on the actual railway operation sensitive frequency band, the multi-objective optimization algorithm includes the following steps:

[0024] S41, randomly generate the position and velocity of the particle swarm for initialization;

[0025] S42, calculating the fitness value according to the position of each particle, and updating the position of each particle;

[0026] S43, updating the speed of each particle according to the updated position;

[0027] S44, repeat S42 and S43 until the preset maximum number of iterations is reached or the fitness value converges stably.

[0028] In a second aspect, a second object of the present invention is to provide a rail resonator design system based on a sensitive frequency band of actual railway operation, comprising:

[0029] Data processing module: According to the operating conditions of the railway site, the disease characteristics of the operating track are tested to obtain the vibration signals corresponding to different operating track diseases under the actual operating conditions;

[0030] Data initialization module: input the vibration signals into the frequency domain feature recognition algorithm respectively to obtain the vibration main frequency information corresponding to different operating track diseases; optimize the vibration main frequency information corresponding to different operating track diseases through fixed point theory to obtain the initial values ​​corresponding to different operating track diseases;

[0031] Data design module: The resonator design formula is used as the function to be optimized, the initial value corresponding to the operating track disease is used as the input value of the function to be optimized, and the minimum amplitude in the vibration main frequency information corresponding to the operating track disease is used as the constraint condition. The design parameters of the rail resonator are calculated using a multi-objective optimization algorithm.

[0032] In a third aspect, a third object of the present invention is to provide an electronic device, comprising: a memory, a processor and a computer program; wherein the computer program is stored in the memory and is configured to be executed by the processor to implement the method described in the first aspect.

[0033] In a fourth aspect, a fourth object of the present invention is to provide a computer-readable storage medium, wherein the storage medium stores a computer program; the computer program is executed by a processor to implement the method described in the first aspect.

[0034] The advantages and positive effects of this application are:

[0035] 1. This application conducts operational disease characteristic tests based on the on-site operation characteristics of the railway to obtain the vibration data of the wheel-rail system under actual operation conditions; incorporates the obtained vibration data into the frequency domain feature recognition algorithm based on vibration-noise fusion, and obtains the sensitive frequency band characteristics corresponding to various track diseases respectively, and optimizes it based on the Den Hartog fixed point theory as the basic optimization theory, and adopts a multi-objective optimization algorithm to design the mechanical parameters and structural parameters of the resonator, thereby realizing the resonator dynamic parameter design that matches the on-site operation conditions.

[0036] 2. In order to clarify the main frequency characteristics of track vibration diseases in actual railway sites, this application first uses the wheel-rail vibration signal obtained from on-site tests to obtain the time-frequency domain characteristics of the signal at each moment through wavelet transform, and then divides the time into segments based on factors such as vibration intensity and frequency characteristics. Then, short-time Fourier transform is performed on each time period to obtain the main frequency of vibration in each time period.

[0037] 3. The resonator design parameters proposed in this application can better match the actual dynamic disease damage characteristics on site, avoiding the problem that there is no corresponding resonator product in certain specific frequency bands that may exist in existing products.

[0038] 4. This application uses a multi-objective optimization algorithm to design the rail resonator parameters using the frequency band to be damped as a constraint condition for calculation, thereby achieving a balanced design of multiple resonant frequency bands. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0040] Figure 1 A schematic diagram showing the wavy wear damage on the surface of the rail provided by the present invention;

[0041] Figure 2 A schematic diagram showing the fracture of the spring bar provided by the present invention is shown;

[0042] Figure 3 A flow chart showing a rail resonator design method based on a sensitive frequency band of actual railway operation provided by an embodiment of the present invention;

[0043] Figure 4 The roadmap of the rail resonator design method based on the actual railway operation sensitive frequency band provided by the embodiment of the present invention is shown;

[0044] Figure 5 It shows a schematic diagram of a multi-point position repetition test of a multi-point input multi-point output technology provided by an embodiment of the present invention;

[0045] Figure 6 The multi-degree-of-freedom dynamics model provided by the embodiment of the present invention is shown;

[0046] Figure 7 A schematic diagram of a rail vibration acceleration test provided by a third embodiment of the present invention is shown;

[0047] Figure 8 A schematic diagram of a trackside noise test provided by a third embodiment of the present invention is shown;

[0048] Fig. 9 A schematic diagram showing the main frequency vibration information results obtained by the rail corrugation characteristic test provided by the third embodiment of the present invention;

[0049] Fig.10 A schematic diagram showing the main frequency information of vibration obtained from the rail running noise test provided by the third embodiment of the present invention is shown;

[0050] Fig.11 A schematic diagram showing a comparison of the vibration reduction effects before and after optimization provided by the third embodiment of the present invention; DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0053] All numerical designations, such as temperatures, lengths, flows, including ranges, are approximate. It is to be understood, although not always expressly stated, that all numerical designations are preceded by the term "about".

[0054] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside" and "outside" etc., indicating directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as a limitation on the present invention.

[0055] See also Figures 1 to 11 ;

[0056] When the vibration is transmitted longitudinally from the wheel and the track to the resonator position, the vibration energy is transferred to the inside of the resonator through the resonator's own dynamic action, and the vibration energy is consumed by the polymer material wrapped around itself, thereby achieving the effect of reducing wheel-rail vibration.

[0057] First embodiment

[0058] The present invention provides a rail resonator design method based on the actual railway operation sensitive frequency band, such as Figure 3 and Figure 4 As shown, including:

[0059] S1. According to the operating conditions of the railway site, the disease characteristics of the operating track are tested to obtain the vibration signals corresponding to different operating track diseases under the actual operating conditions.

[0060] In order to match the design of the rail dynamic resonator with the on-site operating conditions, it is first necessary to clarify the actual vibration disease characteristic state of the rail under the actual on-site operating conditions.

[0061] The disease characteristic test includes rail corrugation characteristic test, fastener system natural frequency test, rail vibration main frequency test and wheel-rail operation noise test. According to relevant data, the existing track diseases on site mainly include dynamic damage conditions such as rail corrugation wear, high-frequency damage and fracture of fasteners (components), and wheel-rail operation noise.

[0062] The tests of on-site track operation dynamic damage and diseases can be divided into two categories according to their test methods and data types: wheel-rail dynamic characteristics tests and in-situ vibration tests. Among them, the natural frequency test of the fastener system is carried out by in-situ vibration test, and the rest are on-site wheel-rail dynamic characteristics tests.

[0063] (1) In-situ vibration test

[0064] In-situ vibration test can be carried out by vibration excitation, force hammer vibration, etc., which belongs to the fixed-point test method. Here, the impact test of force hammer vibration is used as an example to illustrate. This test method is often used to detect the natural frequency and modal characteristics of the object to be tested. The natural frequency test of the fastener spring bar is as follows: Figure 5 As shown, in order to eliminate the randomness in the test process, multi-point input multi-point output (MIMO) technology is generally used to perform multi-point repeated tests. The letter arrows are the knocking points. The vibration signal is collected by the deployed vibration acceleration sensor and transmitted to the data acquisition instrument.

[0065] (2) Wheel-rail dynamic characteristics test

[0066] On-site wheel-rail dynamic characteristic test includes rail corrugation characteristic test at skylight point and rail vibration main frequency test under vehicle operation status. Rail corrugation characteristic test mainly uses corrugation trolley, ruler and other means to determine the main wavelength of rail corrugation under track operation status and convert the corresponding vehicle speed into excitation frequency characteristics; rail vibration main frequency test collects vibration signals of vehicles and tracks under actual operation to determine the main frequency information of track diseases such as rail vibration main frequency and wheel-rail operation noise. The test indicators are generally rail vibration acceleration, in-vehicle noise, etc.

[0067] Therefore, the wheel-rail dynamic characteristics test can be used to obtain the results of three tests, namely, the rail corrugation characteristics test, the rail vibration main frequency test and the wheel-rail running noise test, that is, the vibration signal.

[0068] S2. Input the vibration signal into the frequency domain feature recognition algorithm to obtain the vibration main frequency information corresponding to various operating track diseases.

[0069] When analyzing the main frequency information of vibration of dynamic damage of rail system, Fourier transform (FFT) and wavelet transform technology are often used for time-frequency domain analysis. The FFT analysis results have high spectral data analysis accuracy, but because the entire time domain signal is required in the transformation process, it cannot reflect the process of vibration energy spectrum characteristics changing with time; wavelet transform technology realizes the time-frequency domain characteristic analysis of time signals by introducing wavelet basis function w(x), but its analysis effect depends on the selection of wavelet basis function, and its calculation accuracy cannot meet the requirements for the identification of main frequency information of vibration.

[0070] Based on the above situation, this application performs time-frequency domain extraction through the following algorithm:

[0071] S21. Perform wavelet transform on the vibration signal to obtain the time-frequency domain characteristic relationship; the time-frequency domain characteristic relationship includes the intensity of the vibration signal at each moment and the frequency domain distribution characteristics. The calculated result has low accuracy, and the obtained vibration main frequency range is relatively wide, so it is impossible to further extract accurate vibration frequency domain characteristics, and further processing is required.

[0072] S22. Performing time partition processing on the vibration signal according to the time-frequency domain characteristic relationship; the partition basis includes the vibration main frequency band and its intensity characteristics varying with time.

[0073] Rail transit trains are often composed of multiple vehicles. Each wheel passing through a measuring point will cause a vibration. Therefore, the vibration signal needs to be partitioned according to the periodic characteristics. First, the main frequency band of the vibration when the wheel passes through the measuring point is determined. The time point when the wheel passes the measuring point is determined based on the time-frequency domain characteristics and the main frequency band of the signal. The time period when the vehicle passes is determined based on the intensity characteristics that change over time and analyzed.

[0074] S23, respectively process the vibration signals in each time partition by short-time Fourier transform, extract the frequency information in each time partition according to the signal strength, and take the frequency information with the largest signal strength as the main vibration frequency information.

[0075] The vibration signal in each time period is processed by short-time Fourier transform, and the first frequency information f1 and the second frequency information f2 in each interval are extracted according to the signal strength, that is, the frequency domain amplitude; further, the frequency information with the largest peak value is selected as the first vibration main frequency and the second vibration main frequency, and two frequencies are taken into consideration to further enhance the vibration reduction effect.

[0076] Compared with the traditional Fourier transform, the short-time Fourier transform further divides the vibration signal into time periods for processing, and also reduces the energy leakage problem in each analysis period by introducing a window function, thereby ensuring the range of the vibration main frequency information obtained after processing and the accuracy of the analysis results.

[0077] Therefore, by performing the above analysis process on the vibration signal, the main vibration frequency information for different disease characteristics of the operating track can be obtained, that is, the vibration frequency band to be optimized.

[0078] S3. Optimizing the vibration main frequency information through fixed-point theory to obtain an initial value.

[0079] After obtaining the vibration main frequency information of the existing track dynamic diseases at the railway site, the mechanical parameters of the rail resonator can be designed.

[0080] The vibration reduction principle of the rail resonator can be adopted as follows Figure 6 The two-degree-of-freedom dynamic model shown in the figure is used for simulation. The part in the dashed box is the mechanical equipment to be damped (i.e., the wheels and rails in the wheel-rail system), hereinafter referred to as the main system, with a mass parameter of m1; the part in the solid box is the resonator dynamic model (i.e., the rail resonator), with a mass parameter of m2, and a single (or multiple) mass block and the corresponding spring damper are connected to the main system.

[0081] Here we take the two-degree-of-freedom vibration model as an example. The external load acts on the main system, and the vibration equation of the two-degree-of-freedom system is as follows:

[0082] ,

[0083] in, , k 1. c 1 are the vibration displacement, stiffness and damping of the main system respectively, x 2. k 2. c 2 are the vibration displacement, stiffness and damping of the resonator, F 0 is the excitation load, w is the excitation circular frequency corresponding to the main vibration frequency, w Substitute the corresponding vibration main frequency information, t For time.

[0084] According to the above vibration equation, the vibration amplitude of the main system and the rail resonator under the excitation of specific vibration main frequency information can be calculated:

[0085] ,

[0086] Among them, X1 is the vibration amplitude of the main system, X2 is the vibration amplitude of the rail resonator, is the imaginary part. For a vibration system without a resonator (i.e., only the main system exists), the corresponding vibration amplitude is:

[0087] ,

[0088] Wherein, F represents the exciting load.

[0089] To solve the rail resonator system, it is necessary to reduce the vibration of the main system as much as possible, transfer the vibration energy from the main system to the rail resonator, and dissipate part of the energy through the resonator damping c2.

[0090] In the classical resonator design theory, Den Hartog fixed point theory is used to describe the optimal design of the resonator. The optimal design of the resonator set by this method should satisfy the following two formulas, namely the two-degree-of-freedom resonator design formula:

[0091] ,

[0092] in, is the ratio of resonator damping to critical damping, is the ratio of the resonator mass to the main system mass, is the natural frequency of the resonator, is the natural frequency of the main system.

[0093] Combining the above formulas, we can get the optimal resonator mass, stiffness and damping, which can be used as the initial value for subsequent calculations. It should be noted that different operating track defects correspond to different initial values.

[0094] In summary, the vibration amplitude of the rail resonator at the system's natural frequency can be minimized through the above process. However, for track defect characteristics with multiple sensitive frequency bands, this method cannot reduce the forced vibration amplitude of multiple vibration frequency bands at the same time. Therefore, it is necessary to further combine the multi-objective optimization algorithm on this basis to achieve comprehensive control of vibrations in multiple frequency bands.

[0095] S4. The resonator design formula is used as the function to be optimized, the initial value corresponding to the operating track disease is used as the input value of the function to be optimized, and the minimum amplitude in the vibration main frequency information corresponding to the operating track disease is used as the constraint condition. The design parameters of the rail resonator are calculated using a multi-objective optimization algorithm.

[0096] The multi-objective algorithm calculates the optimal value of the objective function under a series of constraints. Commonly used multi-objective parameter optimization methods include Bayesian optimization method, particle swarm algorithm, genetic algorithm, etc. Exemplarily, the above-mentioned two-degree-of-freedom resonator design formula is used as the function to be optimized. Other formulas in S3 will also be involved in the specific calculation. The initial value corresponding to the operating track disease is used as the input value of the function to be optimized, and the output is the corresponding vibration main frequency information; the minimum amplitude in the vibration main frequency information is used as a constraint condition, that is, based on the function to be optimized, the resonator dynamic parameter design is performed using a multi-objective optimization algorithm, so that the corresponding vibration main frequency information is reduced to the lowest amplitude in the vibration main frequency information, corresponding to the two-degree-of-freedom resonator design formula and related formulas, then X1 needs to be reduced, and the corresponding resonator parameter design value at this time, that is, the value of the resonator mass, stiffness and damping, is what this application seeks.

[0097] This application does not specifically limit the multi-objective algorithm used. Here, the particle swarm algorithm is used as an example for introduction:

[0098] Particle swarm optimization is an optimization algorithm developed based on the behavior of groups such as bird flocks and fish schools. Particle swarm optimization simulates the behavior of individuals (particles) in a group to find the optimal solution. Its basic idea is to find the optimal solution in the solution space through cooperation and competition between individuals. Its core is to regard each particle as a potential solution in the search space. The particle updates its position and velocity based on its own experience and the experience of the group in the hope of finding the optimal solution.

[0099] The specific steps when using the particle swarm algorithm are as follows:

[0100] S41. Randomly generate the position and velocity of the particle swarm for initialization.

[0101] S42. Calculate the fitness value according to the position of each particle and update the position of each particle.

[0102] S43. Update the speed of each particle according to the updated position.

[0103] S44, repeat S42 and S43 until the preset maximum number of iterations is reached or the fitness value converges stably. The fitness is used to evaluate the quality of each particle as a solution. The particle swarm algorithm is a prior art and will not be described in detail in this application.

[0104] It should be noted that if the track has only one defect, it is only necessary to input the vibration main frequency information corresponding to the defect, the minimum amplitude in the vibration main frequency information and the initial value into the multi-objective optimization algorithm. If the track has multiple defects, it is necessary to input the relevant parameters of each disease into the algorithm for calculation.

[0105] Based on the above technical scheme, the corresponding dynamic parameters of the rail dynamic resonator can be proposed according to the main track dynamic damage characteristics on site, and the vibration reduction effect of multiple main vibration frequency bands of track diseases can be achieved at the same time, ensuring targeted treatment of track vibration diseases on site and better guiding the on-site track operation disease treatment work.

[0106] Second embodiment

[0107] Based on the content of the first embodiment, the present application provides a rail resonator design system based on the actual railway operation sensitive frequency band, including:

[0108] Data processing module: According to the operating conditions of the railway site, the disease characteristics of the operating track are tested to obtain the vibration signals corresponding to different operating track diseases under the actual operating conditions;

[0109] Data initialization module: input the vibration signals into the frequency domain feature recognition algorithm respectively to obtain the vibration main frequency information corresponding to different operating track diseases; optimize the vibration main frequency information corresponding to different operating track diseases through fixed point theory to obtain the initial values ​​corresponding to different operating track diseases;

[0110] Data design module: The resonator design formula is used as the function to be optimized, the initial value corresponding to the operating track disease is used as the input value of the function to be optimized, and the minimum amplitude in the vibration main frequency information corresponding to the operating track disease is used as the constraint condition. The design parameters of the rail resonator are calculated using a multi-objective optimization algorithm.

[0111] For other contents, please refer to the first embodiment and this application will not elaborate on them.

[0112] It should be noted that the division of the above-mentioned functional modules is only used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0113] Third embodiment

[0114] Based on the content of the first embodiment, this embodiment is described by taking a certain project as an example:

[0115] (1) Project Overview

[0116] This project is a subway line in a certain place, with a maximum operating speed of 120km / h. During the operation of the line, high-frequency noise disease occurred in a certain curve section, which caused a large number of complaints, so it is planned to use damping rails to treat it.

[0117] The curve radius of this section is 800m and the operating speed is 120km / h. Through on-site exploration, it was found that short-wavelength corrugation characteristics appeared on the surface of the rails. On this basis, it is necessary to further identify the main vibration frequency information corresponding to track diseases such as line noise and corrugation, and then determine the corresponding damping rail design parameters.

[0118] (2) Identification of characteristic frequencies of track defects

[0119] On-site rail vibration acceleration test and trackside noise test are used to clarify the main frequency information of track vibration disease on site. The test process is as follows: Figure 7 and Figure 8 As shown in the figure, the collected acceleration and noise time domain signals are processed according to the frequency domain feature recognition algorithm to obtain the vibration main frequency information of rail corrugation and high-frequency noise, respectively, as shown in Fig. 9 and Fig.10 As shown, Figure 7 , Figure 8 The dotted box in the figure is the collection point.

[0120] It can be seen that the first main frequency of the rail corrugation and high-frequency noise in this embodiment is concentrated at 630 Hz, and the second main frequency is located near 1500 Hz. Therefore, this frequency is the main frequency to be controlled by the damping rail.

[0121] (3) Multi-objective parameter optimization process of damping rail

[0122] After clarifying the main frequency information of vibration targeted by the damping rail, the optimization design of the dynamic parameters of the damping rail is further carried out to guide the actual product production and application. For the convenience of understanding, the two-degree-of-freedom resonator dynamic model is used for design. The basic design parameters are mainly the mass of the damping rail and the stiffness damping parameters of the connection mechanism. In the calculation process, considering the actual use conditions of the damping rail, the initial value set here not only satisfies the Den Hartog fixed point theory, but also satisfies the design parameter range of the general damping rail. On this basis, it is used as the initial value of the multi-objective optimization design, and the parameter optimization process is carried out. The design parameters and the main frequency of vibration reduction of the rail resonator before and after optimization are shown in Table 1.

[0123] Table 1 Comparison of resonator design parameters before and after optimization

[0124]

[0125] The multi-objective optimization process is carried out using the particle swarm algorithm. In a set characteristic frequency band of one-third octave, the first vibration main frequency is taken as the most important vibration reduction frequency, and its weight coefficient is 0.7, and the weight coefficient of the second vibration main frequency is 0.3. Fig.11 The vibration reduction effect of the damping rail before and after optimization is demonstrated. From the part circled by the dotted circle, it can be seen that the optimized damping rail parameters not only ensure the vibration reduction effect at the first main frequency, but also improve the vibration reduction effect at the second main frequency, thus achieving a better vibration reduction effect.

[0126] Fourth embodiment

[0127] The present application provides an electronic device, the electronic device comprising a processor and a memory for storing instructions executable by the processor; when the processor is configured to execute the instructions, the electronic device implements the method in the first embodiment. The electronic device can be a tablet computer, a handheld computer, a personal computer PC and other electronic devices. The electronic device can directly display the design results, which is convenient for operators to directly view.

[0128] Fifth embodiment

[0129] The present application provides a computer-readable storage medium, wherein the storage medium stores a computer program; the computer program is executed by a processor to implement the method in the first embodiment.

[0130] The above is only a preferred embodiment of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A rail resonator design method based on the actual railway operation sensitive frequency band, characterized in that: The following steps are involved: S1. According to the operating conditions of the railway site, the disease characteristics of the operating track are tested to obtain the vibration signals corresponding to different operating track diseases under the actual operating conditions; S2. Input the vibration signals into the frequency domain feature recognition algorithm to obtain the vibration main frequency information corresponding to different operating track diseases; S3, optimizing the vibration main frequency information corresponding to different operating track diseases through fixed point theory to obtain initial values ​​corresponding to different operating track diseases; S4. The resonator design formula is used as the function to be optimized, the initial value corresponding to the operating track disease is used as the input value of the function to be optimized, and the minimum amplitude in the vibration main frequency information corresponding to the operating track disease is used as the constraint condition. The design parameters of the rail resonator are calculated using a multi-objective optimization algorithm.

2. The rail resonator design method based on the actual railway operation sensitive frequency band according to claim 1 is characterized in that: The disease characteristic tests include rail corrugation characteristic tests, fastener system natural frequency tests, rail vibration main frequency tests and wheel-rail operation noise tests.

3. The rail resonator design method based on the actual railway operation sensitive frequency band according to claim 2 is characterized in that: The testing method of the disease characteristic test includes a wheel-rail dynamic characteristic test and an in-situ vibration test.

4. The rail resonator design method based on the actual railway operation sensitive frequency band according to claim 1 is characterized in that: The frequency domain feature recognition algorithm comprises the following steps: S21, performing wavelet transform on the vibration signal to obtain a time-frequency domain characteristic relationship; S22, determining the main frequency band of vibration and the corresponding intensity characteristics according to the time-frequency domain characteristics, and performing time partition processing on the vibration signal; S23, respectively process the vibration signals in each time partition by short-time Fourier transform, extract the frequency information in each time partition according to the signal strength, and take the frequency information with the largest signal strength as the main vibration frequency information.

5. The rail resonator design method based on the actual railway operation sensitive frequency band according to claim 4 is characterized in that: The time-frequency domain characteristic relationship includes the intensity and frequency domain distribution characteristics of the vibration signal at each moment.

6. The rail resonator design method based on the actual railway operation sensitive frequency band according to claim 1 is characterized in that: The initial values ​​are the mass, damping and stiffness of the resonator.

7. The rail resonator design method based on the actual railway operation sensitive frequency band according to claim 1 is characterized in that: The multi-objective optimization algorithm comprises the following steps: S41, randomly generate the position and velocity of the particle swarm for initialization; S42, calculating the fitness value according to the position of each particle, and updating the position of each particle; S43, updating the speed of each particle according to the updated position; S44, repeat S42 and S43 until the preset maximum number of iterations is reached or the fitness value converges stably.

8. A rail resonator design system based on the actual railway operation sensitive frequency band, characterized in that: include: Data processing module: According to the operating conditions of the railway site, the disease characteristics of the operating track are tested to obtain the vibration signals corresponding to different operating track diseases under the actual operating conditions; Data initialization module: input the vibration signals into the frequency domain feature recognition algorithm respectively to obtain the vibration main frequency information corresponding to different operating track diseases; optimize the vibration main frequency information corresponding to different operating track diseases through fixed point theory to obtain the initial values ​​corresponding to different operating track diseases; Data design module: The resonator design formula is used as the function to be optimized, the initial value corresponding to the operating track disease is used as the input value of the function to be optimized, and the minimum amplitude in the vibration main frequency information corresponding to the operating track disease is used as the constraint condition. The design parameters of the rail resonator are calculated using a multi-objective optimization algorithm.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program; wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program; the computer program is executed by a processor to implement the method according to any one of claims 1 to 7.

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