A method and device for generating a load spectrum for a contact line locator test

Abstract

The present application relates to a method and device for generating a load spectrum for a contact network locator test, and relates to the technical field of computer data processing. The load data is extrapolated to obtain all loads that may occur during the entire life cycle of the component; the load amplitude extreme value obtained based on the cycle count is graded, and the multi-level cycle load is more in line with the actual fatigue characteristics of the locator. It includes: using the meta-node in the bow-net coupling system to simulate the physical effects on the contact network locator, coupling the meta-node with the dynamic equation, and calculating the initial displacement load vector of the meta-node; generating a supplementary displacement load vector that meets the probability density distribution at a preset position, and forming an extrapolated displacement load vector together with the initial displacement load vector; counting the cycle of the extrapolated displacement load vector to obtain the load amplitude, load mean and cycle frequency of the extrapolated displacement load vector cycle; grading the extrapolated displacement load vector to obtain a load spectrum.

Description

Technical Field

[0001] The present application relates to computer data processing, and in particular to a method and device for generating a load spectrum for a contact network locator test. Background Art

[0002] The overhead contact network is a special form of power transmission line erected above the railway line to supply power to electric locomotives. Electric traction locomotives obtain electrical energy from the overhead contact network and provide driving energy. The overhead contact network positioner is an important component connecting the contact line. When the train passes at high speed, the good working condition of the positioner is a necessary condition to ensure the smooth and stable operation of the high-speed railway locomotive. Therefore, it is important to accurately predict the fatigue life of the positioner.

[0003] Under the existing technology, the way to predict the fatigue life of the positioner is to conduct a fatigue life test of the positioner. However, the fatigue life test of the positioner is currently mostly carried out by a constant amplitude vibration fatigue test. For example, according to the simulation results of the bow-net, the maximum cyclic amplitude of the displacement during the vibration of the positioner is selected, and the main frequency of the positioner vibration is used as the loading frequency to determine the fatigue test plan of the contact network positioner.

[0004] However, the use of constant amplitude load spectrum for positioner fatigue testing simplifies the complex vibration process of the positioner, and the test results are relatively conservative. Since the test parameters are formulated according to the maximum vibration load of the positioner, a lot of fatigue load information during the vibration process of the positioner is ignored, which leads to low accuracy in predicting the fatigue life of the positioner. How to generate load test parameters that are more likely to represent the load data of the component under the entire life cycle and cover as much fatigue load information as possible has become an urgent problem to be solved in related fields. Summary of the invention

[0005] The embodiments of the present application propose a method and device for generating a load spectrum for a contact network locator test, which solves the deficiency of the load data in the current contact network locator test in covering the whole cycle.

[0006] In a first aspect, an embodiment provides a method for generating a load spectrum for a contact network locator test, the method comprising:

[0007] The meta-node in the bow-catenary coupling system is used to simulate the physical action on the contact network locator, and the meta-node is coupled with the dynamic equation to calculate the initial displacement load vector of the meta-node; the initial displacement load vector of the meta-node represents the sum of deformations caused by the physical action of the target load on the locator; the target load represents the sum of external forces that cause the locator structure or component to generate internal forces and deformations; a probability density distribution that conforms to the distribution of the initial displacement load vector is obtained, and a supplementary displacement load vector that meets the probability density distribution is generated at a preset position, which together with the initial displacement load vector constitutes an extrapolated displacement load vector; the rain flow counting method is used to count the cycles of the extrapolated displacement load vector to obtain the load amplitude, load mean and cycle frequency of the extrapolated displacement load vector cycle; the extrapolated displacement load vector is classified according to the load amplitude, the load mean and the cycle frequency to obtain a load spectrum for testing the contact network locator.

[0008] In one embodiment, the pantograph-catenary coupling model for coupling the dynamic equations of the meta-nodes is expressed as formula (1):

[0009] (1)

[0010] Among them, M represents the mass matrix of the pantograph-catenary coupling system, D represents the damping matrix of the pantograph-catenary coupling system, and K represents the stiffness matrix of the pantograph-catenary coupling system. is the target load corresponding to the physical action on the meta-node; is the acceleration vector of the pantograph-catenary coupling system, is the velocity vector of the pantograph-catenary coupling system, is the initial displacement load vector.

[0011] In one embodiment, obtaining the probability density distribution of the initial displacement load vector includes:

[0012] The initial displacement load vector is cycle counted by using a rain flow counting method to obtain multiple cycles of initial displacement load vectors;

[0013] Obtaining the cycle ratio of the number of cycles of each of the initial displacement load vectors to the number of cycles of all the initial displacement load vectors, and the cycle initial value and cycle termination value in the initial displacement load vectors of multiple cycles;

[0014] Setting an adaptive factor of a kernel density estimation algorithm model according to the cycle ratio;

[0015] According to the adaptive factor, a kernel function is placed at the preset position, and the loop initial value and the loop termination value are brought into the kernel function for calculation;

[0016] The probability density distribution is obtained by superimposing each calculated kernel function.

[0017] In one embodiment, the step of setting the adaptive factor of the kernel density estimation algorithm model according to the cycle ratio includes:

[0018] Substituting the cycle ratio into formula (2), we get the intermediate value;

[0019] (2)

[0020] in, is the middle value, Indicates that the logarithm of the intermediate value is calculated. Indicates The ratio of the number of initial displacement load vector cycles to the total number of cycles, Indicates The initial value of the initial displacement load vector, Indicates The loop termination value of the initial displacement load vector, is the number of initial displacement load vectors for multiple cycles;

[0021] Substituting the intermediate value into formula (3) to obtain the adaptive factor;

[0022] (3)

[0023] Represents the adaptive factor.

[0024] In one embodiment, the kernel function is expressed as formula (4);

[0025] (4)

[0026] in, Indicates The initial value of the initial displacement load vector, Indicates The loop termination value of the initial displacement load vector, represents the adaptive factor, represents the cyclic initial value of the extrapolated displacement load vector generated according to the probability density distribution, represents the loop termination value of the extrapolated displacement load vector generated according to the probability density distribution;

[0027] According to the adaptive factor, a kernel function is placed at the preset position, and the loop initial value and the loop termination value are brought into the kernel function for calculation, including:

[0028] The adaptive factor is brought into a kernel function, the kernel function with the adaptive factor is placed at the preset position, and the loop initial value and the loop termination value are brought into the kernel function with the adaptive factor for calculation.

[0029] In one embodiment, superimposing each calculated kernel function to obtain the probability density distribution includes:

[0030] Formula (5) is used to implement the superposition of the calculated kernel functions to obtain the probability density distribution satisfied by the extrapolated displacement load vector;

[0031] (5)

[0032] in, The probability density distribution that the extrapolated displacement load vector satisfies is, , , represents the standard deviation of the mean of the initial displacement load vector after rainflow counting, represents the standard deviation of the amplitude of the initial displacement load vector after rainflow counting, is the number of initial displacement load vectors for multiple cycles; represents the cyclic initial value of the extrapolated displacement load vector generated according to the probability density distribution, Represents the loop termination value of the extrapolated displacement load vector generated according to the probability density distribution.

[0033] Execute S21 to obtain the initial displacement load vector of multiple cycles after rain flow counting on the initial load vector.

[0034] In one embodiment, the extrapolated displacement load vector is graded according to the load amplitude, the load mean and the cycle frequency to obtain a load spectrum for testing the contact network locator, including:

[0035] Finding the maximum displacement load amplitude value among the load amplitudes;

[0036] Based on the condition that fatigue damage has equal damage, generating the ratio coefficient;

[0037] The ratio coefficient is multiplied by the maximum displacement load amplitude to obtain a load cycle amplitude node, a framework of the load spectrum is established based on the load cycle amplitude node and the load mean node, and the cycle frequency is filled in the framework of the load spectrum to obtain the load spectrum for testing the contact network locator.

[0038] In a second aspect, an embodiment provides a device for generating a load spectrum for a contact network positioner test, the device comprising:

[0039] A dynamic equation coupling module is used to simulate the physical effects on the contact network locator by using the meta-nodes in the bow-catenary coupling system, perform dynamic equation coupling on the meta-nodes, and calculate the initial displacement load vector of the meta-nodes; the initial displacement load vector of the meta-nodes represents the sum of deformations of the locator caused by the physical effects of the target load; the target load represents the sum of external forces that cause the locator structure or component to generate internal forces and deformations;

[0040] A load extrapolation module, used to obtain a probability density distribution that conforms to the distribution of the initial displacement load vector, generate a supplementary displacement load vector that satisfies the probability density distribution at a preset position, and form an extrapolated displacement load vector together with the initial displacement load vector;

[0041] A cycle counting module, used for performing cycle counting on the extrapolated displacement load vector by using a rain flow counting method, and obtaining a load amplitude, a load mean and a cycle frequency of the extrapolated displacement load vector cycle;

[0042] A grading module is used to grade the extrapolated displacement load vector according to the load amplitude, the load mean and the cycle frequency to obtain a load spectrum for testing the contact network locator.

[0043] In one embodiment, the load extrapolation module includes:

[0044] A cycle counting submodule is used to count the cycles of the initial displacement load vector using a rain flow counting method to obtain multiple cycles of the initial displacement load vector; obtain the cycle ratio of the number of cycles of each initial displacement load vector to the number of cycles of all initial displacement load vectors, and the cycle initial value and cycle termination value in the multiple cycles of the initial displacement load vector;

[0045] A calculation submodule, used for setting an adaptive factor of a kernel density estimation algorithm model according to the cycle ratio;

[0046] The superposition submodule is used to place a kernel function at the preset position according to the adaptive factor, bring the loop initial value and the loop termination value into the kernel function for calculation; and superimpose each calculated kernel function to obtain the probability density distribution.

[0047] In one embodiment, the grading module includes:

[0048] A search submodule, used for searching for a maximum displacement load amplitude value in the load amplitude values;

[0049] A coefficient generation submodule, for generating the ratio coefficient based on the condition that fatigue damage has equal damage;

[0050] The grading submodule is used to perform a product operation on the ratio coefficient and the maximum displacement load amplitude to obtain a load cycle amplitude node, establish a framework of the load spectrum based on the load cycle amplitude node and the load mean node, fill in the cycle frequency in the framework of the load spectrum, and obtain the load spectrum for testing the contact network locator.

[0051] The beneficial effects of this application are:

[0052] The method for generating a contact network locator test load spectrum proposed in the embodiment of the present application is based on a bow-net coupling simulation model under the condition of a train running at a speed of 400 km / h, simulates the load received by the contact network locator in a train running scenario at a speed of 400 km / h, obtains an initial displacement load vector representing the fatigue load information of the locator, obtains the probability distribution of the initial displacement load vector, and deduces a first probability distribution that the fatigue load information of the locator throughout its life cycle should conform to based on the initial displacement load vector, and then extrapolates the fatigue load information, and the supplemented fatigue load information satisfies the actual stress law of the locator throughout its life cycle; further, the extrapolated fatigue load information is cycle counted to obtain cyclic load information, and the repeated stress condition of the locator in the application scenario is further simulated, and finally the cyclic load information is graded according to the Conover coefficient, and the obtained eight-level load spectrum consists of block spectra of different amplitudes, which can approximately simulate the actual displacement of the structure, can well simulate the cumulative frequency curve of the fatigue load, and at the same time more realistically reflect the fatigue characteristics of the locator. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 It is a flowchart of the steps of the method for generating a load spectrum for a contact network locator test proposed in an embodiment of the present application;

[0054] Figure 2 This is a schematic diagram of the displacement change of a positioner in the X direction in an example pantograph-catenary coupling system of the present application;

[0055] Figure 3 This is a schematic diagram of the displacement change of a positioner in the Y direction in an example pantograph-catenary coupling system of the present application;

[0056] Figure 4 This is a schematic diagram of displacement change of a positioner in the Z direction in an example pantograph-catenary coupling system of the present application;

[0057] Figure 5 This is a schematic diagram of an initial displacement load vector cycle obtained by performing cycle counting on an initial displacement load vector in an example of the present application;

[0058] Figure 6 It is a functional module diagram of the overhead line locator test load spectrum generating device proposed in the embodiment of the present application. DETAILED DESCRIPTION

[0059] The present application is further described in detail below by specific embodiments in conjunction with the accompanying drawings. Wherein similar elements in different embodiments adopt associated similar element numbers. In the following embodiments, many detailed descriptions are intended to enable the present application to be better understood. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, and methods. In some cases, some operations related to the present application are not shown or described in the specification, in order to avoid the core part of the present application being overwhelmed by too much description, and for those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the description in the specification and the general technical knowledge in the art.

[0060] In addition, the features, operations or characteristics described in the specification can be combined in any appropriate manner to form various implementations. At the same time, the steps or actions in the method description can also be interchanged or adjusted in a manner that is obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for the purpose of clearly describing a certain embodiment and are not meant to be a required sequence, unless otherwise specified that a certain sequence must be followed.

[0061] The serial numbers assigned to the components herein, such as "first", "second", etc., are only used to distinguish the objects described and do not have any order or technical meaning. The "connection" and "coupling" mentioned in this application, unless otherwise specified, include direct and indirect connections (couplings).

[0062] The applicant currently uses a constant amplitude load spectrum to perform fatigue tests on positioners, which simplifies the complex vibration process of the positioner. However, since the test parameters are formulated according to the maximum vibration load of the positioner, a lot of fatigue load information during the vibration process of the positioner is ignored. In addition, due to the limitations of testing and simulation technology, the positioner fatigue test generally uses short-cycle loads, which are not enough to represent the load data under the full life cycle of the component.

[0063] In view of this, in order to overcome the problems existing in the load spectrum compilation process of the current positioner fatigue test program, such as the load data used in the current positioner fatigue test is based on over-simplified vibration collection, ignoring too much fatigue load data, etc., the embodiment of the present application proposes a method for generating a load spectrum for a contact network positioner test, which is applied to electronic equipment, simulates the physical effects on the positioner during the operation of the contact network, obtains initial load data, and extrapolates the load data to obtain all loads that may occur in the entire life cycle of the components, covering more fatigue load information; at the same time, the load data is cycle counted, and the load amplitude extreme values ​​obtained based on the cycle count are graded to obtain extreme load information that contributes more to fatigue damage, and the multi-stage cyclic loading load is more in line with the actual fatigue characteristics of the locator.

[0064] The method for generating a load spectrum for a contact network locator test proposed in the embodiment of the present application obtains initial load data by simulating the physical effects on the locator during the operation of the contact network, and extrapolates the load data to obtain all loads that may occur in the entire life cycle of the component, covering more fatigue load information; at the same time, the load data is cycle counted, and the load amplitude extreme values ​​obtained based on the cycle count are graded to obtain extreme load information that contributes more to fatigue damage. The multi-level cyclic load is more in line with the actual fatigue characteristics of the locator.

[0065] Figure 1 is a flowchart of the steps of the method for generating a load spectrum for a contact network locator test proposed in an embodiment of the present application, such as Figure 1 As shown, the method for generating a load spectrum for a contact line locator test includes the following steps:

[0066] Step S1: Use the meta-node in the bow-catenary coupling system to simulate the physical effects on the contact network locator, couple the meta-node with the dynamic equation, and calculate the initial displacement load vector of the meta-node; the initial displacement load vector of the meta-node represents the sum of deformations caused by the physical effects of the target load on the locator; the target load represents the sum of external forces that cause the locator structure or component to generate internal forces and deformations.

[0067] In one example of the present application, S1 is executed by the Newmark method in the finite element analysis software Ansys. The positioner is subjected to physical effects in the use scenario during a certain period of time, and the displacement of the element node under the simulated physical effects is calculated. Since the displacement can represent the total deformation of the positioner caused by the physical effects of the target load, the load applied to the element node can be represented by the displacement.

[0068] The bow-catenary coupling system is based on a full study of the structural characteristics of the contact network, selecting appropriate contact network suspension and compensation methods, establishing the contact network dynamic stiffness model and variable mass block model, and deriving a four-element model of the bow-catenary combination based on the existing three-element reduced mass model.

[0069] The embodiment of the present application uses the Newmark method in the finite element analysis software Ansys to simulate the dynamic equations of the bow-catenary coupling system to obtain the initial displacement load vector of the element node.

[0070] The embodiment of the present application also provides a specific method for coupling the dynamic equations of the meta-nodes to obtain the initial displacement load vector of the meta-nodes:

[0071] A pantograph-catenary coupling model is established to couple the dynamic equations of the meta-nodes. The calculation formula (1) of the pantograph-catenary coupling model is:

[0072] (1)

[0073] Among them, M represents the mass matrix of the pantograph-catenary coupling system, D represents the damping matrix of the pantograph-catenary coupling system, and K represents the stiffness matrix of the pantograph-catenary coupling system. is the target load corresponding to the physical action on the metanode structure, that is, the load vector of the structure formed by the metanode and the contact network; is the acceleration vector of the pantograph-catenary coupling system, is the velocity vector of the pantograph-catenary coupling system, is the initial displacement load vector.

[0074] The data collection cycle can be set, and loads can be applied to the meta-nodes multiple times during the data collection cycle to obtain multiple sets of data to input into the bow-net coupling model and calculate multiple , that is, the number of initial displacement load vectors is N, where N is an integer greater than or equal to 1.

[0075] In one example of the present application, the pantograph operating speed is set to 400km / h in the pantograph-network coupling system, and the pantograph-network coupling system obtains an initial displacement load vector. The multiple initial displacement load vectors obtained by applying loads to the meta-nodes at different time points are integrated to obtain the displacement change of the locator: the locator positioning point lifting information is extracted from the displacement vector of the meta-node. The information includes the coordinates of the three positioning points of the left, middle, and right of the locator. X represents the coordinate in the radial direction of the locator contact line, Y represents the coordinate in the vertical direction of the locator, and Z represents the coordinate direction of the axial direction of the locator contact line. Subtracting the initial coordinates corresponding to the three points from the coordinates of the three points can obtain the displacement changes of the three points in the X, Y, and Z directions. Taking point X as an example, after the target load is applied to the locator, X moves to X', and (X'-X) is calculated to obtain the displacement change in the X direction.

[0076] Figure 2 This is a schematic diagram of the displacement change of a locator in the X direction in an example bow-catenary coupling system of the present application. Figure 2 The horizontal axis corresponds to time, and the vertical axis corresponds to the displacement in the X direction, showing the different initial displacement load vectors corresponding to the element node within a period (0 seconds-14 seconds), forming the displacement change of the locator in the X direction within (0 seconds-14 seconds).

[0077] Figure 3 This is a schematic diagram of the displacement change of a locator in the Y direction in an example bow-catenary coupling system of the present application. Figure 3 The horizontal axis corresponds to time, and the vertical axis corresponds to the displacement in the Y direction, showing the different initial displacement load vectors corresponding to the element node within a period (0 seconds-14 seconds), forming the displacement change of the locator in the Y direction within (0 seconds-14 seconds).

[0078] Figure 4 This is a schematic diagram of the displacement change of a locator in the Z direction in an example bow-catenary coupling system of the present application. Figure 4 The horizontal axis corresponds to time, and the vertical axis corresponds to the displacement in the Z direction, showing the different initial displacement load vectors corresponding to the element node within a period (0 seconds-14 seconds), forming the displacement change of the locator in the Z direction within (0 seconds-14 seconds).

[0079] Step S2: Obtain a probability density distribution that meets the initial displacement load vector distribution, generate a supplementary displacement load vector that meets the probability density distribution at a preset position, and form an extrapolated displacement load vector together with the initial displacement load vector.

[0080] The probability density distribution is the probability distribution that the supplementary displacement load vector obtained after extrapolating the initial displacement load vector must follow. The supplementary displacement load vector can supplement the load data of the locator under the full life cycle on the basis of the initial displacement vector, and expand the displacement load vector of a specific period output by the bow-catenary coupling system to obtain all loads that may occur in the full life cycle of the components, and supplement the fatigue load information of the locator during vibration as much as possible, especially the extreme load that contributes more to fatigue damage, to overcome the problem of information loss caused by the simplified vibration process of the constant amplitude load spectrum used in the simulation of the bow-catenary coupling system, and improve the comprehensiveness of the load tested on the contact network locator, thereby improving the accuracy of the fatigue life test of the contact network locator.

[0081] In order to further obtain comprehensive load information over the entire life cycle, the embodiment of the present application also proposes a method of executing S2 to extrapolate the initial displacement load vector:

[0082] S21: The initial displacement load vector is cycle counted using the rain flow counting method to obtain multiple cycle initial displacement load vectors.

[0083] S22: Obtain the cycle ratio of each initial displacement load vector cycle number to all initial displacement load vector cycle numbers, and the cycle initial value and cycle termination value in the initial displacement load vector of multiple cycles.

[0084] An example of the present application also provides a method for realizing "obtaining the cycle ratio of each initial displacement load vector cycle number to all initial displacement load vector cycle numbers, and the cycle initial value and cycle termination value in the initial displacement load vector of multiple cycles":

[0085] The rain flow counting method starts to flow along the slope inside the peak position of the initial displacement load vector in a specific cycle, and stops flowing when encountering a peak value larger than its initial peak value. When the rain flow encounters the rain flow from the previous step, it stops flowing. After stopping the flow, it is recorded as a cycle of the initial displacement load vector. All full cycles are taken out and the amplitude of each cycle is recorded. Therefore, the rain flow counting method can convert the quantitative changes in the random load history into cyclic loads, and record the cyclic initial value of the initial displacement load vector. and the loop termination value of the initial displacement load vector , and count these cycles.

[0086] Figure 5 : is a schematic diagram of the initial displacement load vector cycle obtained by counting the initial displacement load vector in an example of the present application. The horizontal axis is the displacement cycle start value, the unit is mm, and the vertical axis is the displacement cycle end value, the unit is mm. Different color areas correspond to different cycle frequencies. Figure 5 As shown in the figure, after rain flow counting, multiple groups of initial displacement load vectors are successfully obtained. Taking area A as an example, the interval of the displacement cycle start value is (3,5), the interval of the displacement cycle end value is (3,5), and the corresponding cycle frequency is 3.

[0087] Substituting the initial value of the cycle and the end value of the cycle into the proportional calculation formula, we can get The ratio of the number of initial displacement load vector cycles to the total number of cycles, and then The ratio of the number of initial displacement load vector cycles to the total number of cycles is substituted into formula (2) to calculate the intermediate value. , substituting the intermediate value into formula (3) to obtain the adaptive factor of the kernel density estimation algorithm model.

[0088] S23: Setting the adaptive factor of the kernel density estimation algorithm model according to the cycle ratio.

[0089] The process of calculating the adaptive factor includes:

[0090] Substitute the cycle ratio into formula (2) to obtain the intermediate value;

[0091] (2)

[0092] is the middle value, Indicates that the logarithm of the intermediate value is calculated. It represents the first The ratio of the number of initial displacement load vector cycles to the total number of cycles, Indicates The initial value of the initial displacement load vector, Indicates The loop termination value of the initial displacement load vector, is the number of initial displacement load vectors for multiple cycles.

[0093] Substitute the intermediate value into formula (3) to obtain the adaptive factor;

[0094] (3)

[0095] Represents the adaptive factor.

[0096] S24: placing a kernel function at a preset position according to the adaptive factor, and bringing the loop initial value and the loop termination value into the kernel function for calculation.

[0097] The preset position can be set based on the initial displacement load vector. The kernel function is placed within the preset change value centered on the initial displacement load vector to generate a local density estimate. Then, by superimposing these local density estimates, an estimate of the overall probability density function is obtained, thereby obtaining a probability density distribution that conforms to the initial displacement load vector distribution and that the extrapolated load vector needs to follow.

[0098] The kernel function is expressed as formula (4);

[0099] (4)

[0100] Indicates The initial value of the initial displacement load vector, Indicates The loop termination value of the initial displacement load vector, represents the adaptive factor, represents the cyclic initial value of the extrapolated displacement load vector generated according to the probability density distribution, Represents the loop termination value of the extrapolated displacement load vector generated according to the probability density distribution.

[0101] Substitute the adaptive factor into the calculation formula (4) of the above kernel function as an independent variable, Indicates The initial value of the initial displacement load vector, Indicates The loop termination value of the initial displacement load vector is used as a subvariable, and the relationship between the loop initial value of the extrapolated displacement load vector and the loop termination value of the extrapolated displacement load vector and the kernel function can be obtained. Therefore, according to the placement of the kernel function, a local density estimate can be generated, and then by superimposing these local density estimates, an estimate of the overall probability density function is obtained.

[0102] S25: Superimpose each calculated kernel function to obtain a probability density distribution.

[0103] The specific methods of superimposing each calculated kernel function to obtain the probability density distribution include:

[0104] Formula (5) is used to realize the superposition of the calculated kernel functions and obtain the probability density distribution satisfied by the extrapolated displacement load vector;

[0105] (5)

[0106] in, is the probability density distribution that the extrapolated displacement load vector satisfies, , , and is the standard deviation of the two-dimensional data of the counting matrix (From-To matrix) in the rainflow counting method, is the number of initial displacement load vectors for multiple cycles. It means to find the minimum standard deviation of the two-dimensional data of the counting matrix in the rainflow counting method. represents the standard deviation of the mean of the initial displacement load vector after rainflow counting, Represents the standard deviation of the amplitude of the initial displacement load vector after rainflow counting.

[0107] After obtaining the probability density distribution, in a specific embodiment, by setting the extrapolation multiple to 10, based on the obtained displacement probability density distribution, Monte Carlo simulation can be used to obtain extrapolated displacement data that is highly fitted to the original data probability distribution, which serves as the data source for the subsequent eight-level two-dimensional load spectrum of displacement.

[0108] In one example of this application, Denoted as R, Note that O, kernel function The calculation process can be expressed as formula (6):

[0109] (6)

[0110] During the execution of step S2, the above S21 to S25 are executed to obtain a probability density distribution, and then the initial displacement load vector is extrapolated based on the probability density distribution to generate a supplementary displacement load vector outside a specific period. The supplementary displacement load vector and the initial displacement load vector together constitute an extrapolated displacement load vector.

[0111] In order to overcome the defect that the extrapolated displacement load vector has a large randomness, the embodiment of the present application further performs a cyclic counting on the extrapolated displacement load vector.

[0112] Step S3: Use the rain flow counting method to count the cycles of the extrapolated displacement load vector to obtain the load amplitude, load mean and cycle frequency of the extrapolated displacement load vector cycle.

[0113] Since the rainflow counting method can convert the quantity changes in the random load history into cyclic loads and count these cycles, and at the same time, the rainflow counting method takes into account the hysteresis effect in the displacement load time history, and can retain more load information, the rainflow counting method can simplify the extrapolated displacement data into several load cycles, and obtain the load amplitude, mean value and cycle frequency of the extrapolated displacement load vector cycle.

[0114] Step S4: The extrapolated displacement load vector is classified according to the load amplitude, load mean and cycle frequency to obtain a load spectrum for testing the contact network locator.

[0115] This application provides an example of a method for executing S4:

[0116] S41: Search for the maximum displacement load amplitude in the load amplitude.

[0117] S42: Generate a ratio coefficient based on the condition that fatigue damage has equal damage.

[0118] S43: Perform a product operation on the contrast coefficient and the maximum displacement load amplitude to obtain a load cycle amplitude node, establish a load spectrum framework based on the load cycle amplitude node and the load mean node, fill in the cycle frequency in the load spectrum framework, and obtain a load spectrum for testing the contact network locator.

[0119] The load mean obtained by taking the S4 load mean is used as the load mean node.

[0120] For example, after cyclic calculation of the extrapolated displacement load vector, the displacement load amplitudes obtained include: m1, m2, m3, ... m v v is an integer greater than 3, and the maximum displacement load amplitude m is found in the load amplitude. max =40.971.

[0121] According to the Conover method, based on the condition that fatigue damage has equal damage, the ratio coefficients are generated: 1.000, 0.950, 0.850, 0.725, 0.575, 0.425, 0.275, 0.125. The ratio coefficients are compared with the maximum displacement load amplitude m in turn. max Perform a multiplication operation to obtain the load cycle amplitude node. With the load cycle amplitude node as the first dimension and the load mean as the second dimension, establish the framework of the load spectrum, fill in the data according to the cycle frequency corresponding to different load cycle amplitude nodes and load mean values, and obtain the load spectrum for testing the contact network locator.

[0122] Table 1 is an eight-level load spectrum obtained by an example of this application. The load spectrum is divided into eight levels at equal intervals, which can well simulate the cumulative frequency curve of fatigue load and more realistically reflect the fatigue characteristics of parts. The unit of the load cycle amplitude node is millimeter (mm), and the unit of the load mean value is millimeter (mm).

[0123] Table 1

[0124] .

[0125] Based on Table 1, it can be found that the cycle frequency of the extrapolated displacement load vector that satisfies the load cycle amplitude node of 17.413 and the load mean node of -10.720 is 221 times. According to the above eight-level load spectrum, the fatigue life test of the contact network positioner can better simulate the load information of the contact network positioner in the whole life period, such as the number of specific external force influences, different external force cycle laws, changes in external force effects, etc., to overcome the problems existing in the current positioner fatigue test program load spectrum compilation process, such as over-simplification of the vibration process, neglect of too much fatigue load data, etc. The load spectrum is composed of block spectra of different amplitudes, which can approximate the actual displacement of the structure.

[0126] The method for generating a contact network locator test load spectrum proposed in the embodiment of the present application is based on a bow-net coupling simulation model under the condition of a train running at a speed of 400 km / h, simulates the load received by the contact network locator in a train running scenario at a speed of 400 km / h, obtains an initial displacement load vector representing the fatigue load information of the locator, obtains the probability distribution of the initial displacement load vector, and deduces a first probability distribution that the fatigue load information of the locator throughout its life cycle should conform to based on the initial displacement load vector, and then extrapolates the fatigue load information, and the supplemented fatigue load information satisfies the actual stress law of the locator throughout its life cycle; further, the extrapolated fatigue load information is cycle counted to obtain cyclic load information, and the repeated stress condition of the locator in the application scenario is further simulated, and finally the cyclic load information is graded according to the Conover coefficient, and the obtained eight-level load spectrum consists of block spectra of different amplitudes, which can approximately simulate the actual displacement of the structure, can well simulate the cumulative frequency curve of the fatigue load, and at the same time more realistically reflect the fatigue characteristics of the locator.

[0127] Figure 6 : is a functional module diagram of the overhead line locator test load spectrum generating device proposed in the embodiment of the present application, such as Figure 6 As shown, the overhead line locator test load spectrum generating device includes a dynamic equation coupling module 61, a load extrapolation module 62, a cycle counting module 63 and a grading module 64.

[0128] The dynamic equation coupling module 61 is used to simulate the physical effects on the contact network locator by using the meta-nodes in the bow-net coupling system, couple the meta-nodes with the dynamic equations, and calculate the initial displacement load vector of the meta-nodes. The initial displacement load vector of the meta-node represents the total deformation of the locator caused by the physical effects of the target load; the target load represents the total external force that causes the internal force and deformation of the locator structure or component.

[0129] The load extrapolation module 62 is used to obtain a probability density distribution that meets the initial displacement load vector distribution, generate a supplementary displacement load vector that meets the probability density distribution at a preset position, and form an extrapolated displacement load vector together with the initial displacement load vector.

[0130] The cycle counting module 63 is used to count the cycles of the extrapolated displacement load vector using the rain flow counting method to obtain the load amplitude, load mean and cycle frequency of the extrapolated displacement load vector cycle.

[0131] The classification module 64 is used to classify the extrapolated displacement load vector according to the load amplitude, load mean and cycle frequency to obtain a load spectrum for testing the contact network locator.

[0132] Figure 6The implementation principle and technical effects of the overhead line locator test load spectrum generation device provided in the illustrated embodiment may be further described with reference to the relevant description in the overhead line locator test load spectrum generation method embodiment.

[0133] Optionally, the bow-net coupling model for coupling the dynamic equations of the meta-nodes by the dynamic equation coupling module is expressed as formula (1):

[0134] (1)

[0135] Among them, M represents the mass matrix of the pantograph-catenary coupling system, D represents the damping matrix of the pantograph-catenary coupling system, and K represents the stiffness matrix of the pantograph-catenary coupling system. is the target load corresponding to the physical action on the meta-node; is the acceleration vector of the pantograph-catenary coupling system, is the velocity vector of the pantograph-catenary coupling system, is the initial displacement load vector.

[0136] Optionally, the load extrapolation module includes:

[0137] The cycle counting submodule is used to count the cycles of the initial displacement load vector using the rain flow counting method to obtain the initial displacement load vector of multiple cycles; obtain the cycle ratio of the number of cycles of each initial displacement load vector to the number of cycles of all initial displacement load vectors, and the cycle initial value and cycle termination value in the initial displacement load vector of multiple cycles;

[0138] A calculation submodule, used to set an adaptive factor of a kernel density estimation algorithm model according to a cycle ratio;

[0139] The superposition submodule is used to place the kernel function at a preset position according to the adaptive factor, bring the loop initial value and the loop termination value into the kernel function for calculation; and superimpose each calculated kernel function to obtain the probability density distribution.

[0140] Optionally, the calculation submodule is specifically used to substitute the cycle ratio into formula (2) to obtain an intermediate value;

[0141] (2)

[0142] in, is the middle value, Indicates that the logarithm of the intermediate value is calculated. Indicates The ratio of the number of initial displacement load vector cycles to the total number of cycles, Indicates The initial value of the initial displacement load vector, Indicates The loop termination value of the initial displacement load vector, is the number of initial displacement load vectors for multiple cycles;

[0143] Substitute the intermediate value into formula (3) to obtain the adaptive factor;

[0144] (3)

[0145] Represents the adaptive factor.

[0146] Optionally, the kernel function is expressed as formula (4);

[0147] (4)

[0148] in, Indicates The initial value of the initial displacement load vector, Indicates The loop termination value of the initial displacement load vector, represents the adaptive factor, represents the cyclic initial value of the extrapolated displacement load vector generated according to the probability density distribution, represents the loop termination value of the extrapolated displacement load vector generated according to the probability density distribution;

[0149] The superposition submodule is specifically used to bring the adaptive factor into the kernel function, place the kernel function with the adaptive factor at a preset position, and bring the loop initial value and the loop termination value into the kernel function of the adaptive factor for calculation.

[0150] Optionally, the superposition submodule is specifically used to implement the superposition of the calculated kernel functions using formula (5) to obtain the probability density distribution satisfied by the extrapolated displacement load vector;

[0151] (5)

[0152] in, is the probability density distribution that the extrapolated displacement load vector satisfies, , , represents the standard deviation of the mean of the initial displacement load vector after rainflow counting, represents the standard deviation of the amplitude of the initial displacement load vector after rainflow counting, is the number of initial displacement load vectors for multiple cycles.

[0153] Optionally, the grading module includes:

[0154] A search submodule is used to search for the maximum displacement load amplitude in the load amplitude;

[0155] A coefficient generation submodule is used to generate a ratio coefficient based on the condition that fatigue damage has equal damage;

[0156] The grading submodule is used to perform a product operation on the contrast coefficient and the maximum displacement load amplitude to obtain the load cycle amplitude node, establish the load spectrum framework based on the load cycle amplitude node and the load mean node, fill in the cycle frequency in the load spectrum framework, and obtain the load spectrum for testing the contact network locator.

[0157] Regarding the various modules / units included in the various devices described in the above embodiments, they can be software modules / units, or hardware modules / units, or they can be partially software modules / units and partially hardware modules / units. For example, for various devices applied to or integrated in a chip, the various modules / units included therein can all be implemented in the form of hardware such as circuits, or at least some of the modules / units can be implemented in the form of software programs, which run on a processor integrated inside the chip, and the remaining modules / units can be implemented in the form of hardware such as circuits; for various devices applied to or integrated in a chip module, the various modules / units included therein can all be implemented in the form of hardware such as circuits, and different modules / units can be located in the same component of the chip module (such as a chip, circuit module, etc.) or in different components, or at least some of the modules / units can be implemented in the form of software programs. The software program may be implemented in the form of a program, which runs on a processor integrated in the chip module, and the remaining modules / units may be implemented in the form of hardware such as circuits; for each device applied to or integrated in the electronic terminal device, each module / unit contained therein may be implemented in the form of hardware such as circuits, and different modules / units may be located in the same component (for example, a chip, a circuit module, etc.) or in different components in the electronic terminal device, or at least some modules / units may be implemented in the form of a software program, which runs on a processor integrated in the electronic terminal device, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits.

[0158] In one embodiment of the present application, a computer-readable storage medium is provided, on which a program is stored. The stored program includes a method that can be loaded by a processor and process any of the above embodiments.

[0159] Those skilled in the art will appreciate that all or part of the functions of the various methods in the above-mentioned embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can be stored in a computer-readable storage medium, and the storage medium can include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to implement the above-mentioned functions. For example, the program is stored in the memory of the device, and when the program in the memory is executed by the processor, all or part of the above-mentioned functions can be implemented. In addition, when all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can also be stored in a storage medium such as a server, another computer, disk, optical disk, flash disk or mobile hard disk, and can be downloaded or copied and saved in the memory of the local device, or the system of the local device is updated, and when the program in the memory is executed by the processor, all or part of the functions in the above-mentioned embodiments can be implemented.

[0160] The above specific examples are used to illustrate the present application, which is only used to help understand the present application and is not intended to limit the present application. For technicians in the technical field to which the present application belongs, they can also make some simple deductions, deformations or substitutions based on the ideas of the present application.

Claims

1. A method for generating a load spectrum for a contact network locator test, characterized in that: The method comprises: The meta-nodes in the bow-catenary coupling system are used to simulate the physical effects on the contact network locator, and the meta-nodes are coupled with dynamic equations to calculate the initial displacement load vectors of the meta-nodes; the initial displacement load vectors of the meta-nodes represent the sum of deformations of the locator caused by the physical effects of the target load; the target load represents the sum of external forces that cause the locator structure or component to generate internal forces and deformations; Obtaining a probability density distribution that meets the distribution of the initial displacement load vector, generating a supplementary displacement load vector that meets the probability density distribution at a preset position, and forming an extrapolated displacement load vector together with the initial displacement load vector; The extrapolated displacement load vector is cycle counted by using a rain flow counting method to obtain a load amplitude, a load mean, and a cycle frequency of the extrapolated displacement load vector cycle; According to the load amplitude, the load mean and the cycle frequency, the extrapolated displacement load vector is graded to obtain a load spectrum for testing the contact network locator; The generating of the supplementary displacement load vector satisfying the probability density distribution comprises: extrapolating the initial displacement load vector based on the probability density distribution to generate a supplementary displacement load vector; the supplementary displacement load vector satisfies the actual force law of the positioner throughout its entire life cycle.

2. The method for generating a load spectrum for a contact network locator test according to claim 1, characterized in that: The pantograph-catenary coupling model for coupling the dynamic equations of the meta-nodes is expressed as formula (1): （1） Among them, M represents the mass matrix of the pantograph-catenary coupling system, D represents the damping matrix of the pantograph-catenary coupling system, and K represents the stiffness matrix of the pantograph-catenary coupling system. is the target load corresponding to the physical action on the meta-node; is the acceleration vector of the pantograph-catenary coupling system, is the velocity vector of the pantograph-catenary coupling system, is the initial displacement load vector.

3. The method for generating a load spectrum for a contact network locator test according to claim 1, characterized in that: Obtaining the probability density distribution of the initial displacement load vector includes: The initial displacement load vector is cycle counted by using a rain flow counting method to obtain multiple cycles of initial displacement load vectors; Obtaining the cycle ratio of the number of cycles of each of the initial displacement load vectors to the number of cycles of all the initial displacement load vectors, and the cycle initial value and cycle termination value in the initial displacement load vectors of multiple cycles; Setting an adaptive factor of a kernel density estimation algorithm model according to the cycle ratio; According to the adaptive factor, a kernel function is placed at the preset position, and the loop initial value and the loop termination value are brought into the kernel function for calculation; The probability density distribution is obtained by superimposing each calculated kernel function.

4. The method for generating a load spectrum for a contact network locator test according to claim 3, characterized in that: The step of setting the adaptive factor of the kernel density estimation algorithm model according to the cycle ratio includes: Substituting the cycle ratio into formula (2), we get the intermediate value; （2） in, is the middle value, Indicates that the logarithm of the intermediate value is calculated. Indicates The ratio of the number of initial displacement load vector cycles to the total number of cycles, Indicates The initial value of the initial displacement load vector, Indicates The loop termination value of the initial displacement load vector, is the number of initial displacement load vectors for multiple cycles; Substituting the intermediate value into formula (3) to obtain the adaptive factor; （3） Represents the adaptive factor.

5. The method for generating a load spectrum for a contact network locator test according to claim 3, characterized in that: The kernel function is expressed as formula (4); （4） in, Indicates The initial value of the initial displacement load vector, Indicates The loop termination value of the initial displacement load vector, represents the adaptive factor, represents the cyclic initial value of the extrapolated displacement load vector generated according to the probability density distribution, represents the loop termination value of the extrapolated displacement load vector generated according to the probability density distribution; According to the adaptive factor, a kernel function is placed at the preset position, and the loop initial value and the loop termination value are brought into the kernel function for calculation, including: The adaptive factor is brought into a kernel function, the kernel function with the adaptive factor is placed at the preset position, and the loop initial value and the loop termination value are brought into the kernel function with the adaptive factor for calculation.

6. The method for generating a load spectrum for a contact network locator test according to claim 5, characterized in that: Superimposing each calculated kernel function to obtain the probability density distribution includes: Formula (5) is used to implement the superposition of the kernel functions after each calculation, so as to obtain the probability density distribution satisfied by the extrapolated displacement load vector; （5） in, The probability density distribution that the extrapolated displacement load vector satisfies is, (6), (7), represents the standard deviation of the mean of the initial displacement load vector after rainflow counting, represents the standard deviation of the amplitude of the initial displacement load vector after rainflow counting, is the number of initial displacement load vectors for the multiple cycles.

7. The method for generating a load spectrum for a contact network locator test according to claim 1, characterized in that: The extrapolated displacement load vector is classified according to the load amplitude, the load mean and the cycle frequency to obtain a load spectrum for testing the contact network locator, including: Finding the maximum displacement load amplitude value among the load amplitudes; Based on the condition that fatigue damage has equal damage, a ratio coefficient is generated; The ratio coefficient is multiplied by the maximum displacement load amplitude to obtain a load cycle amplitude node, a framework of the load spectrum is established based on the load cycle amplitude node and the load mean node, and the cycle frequency is filled in the framework of the load spectrum to obtain the load spectrum for testing the contact network locator.

8. A device for generating a load spectrum for a contact network positioner test, characterized in that: The overhead line locator test load spectrum generating device comprises: A dynamic equation coupling module is used to simulate the physical effects on the contact network locator by using the meta-nodes in the bow-catenary coupling system, perform dynamic equation coupling on the meta-nodes, and calculate the initial displacement load vector of the meta-nodes; the initial displacement load vector of the meta-nodes represents the sum of deformations of the locator caused by the physical effects of the target load; the target load represents the sum of external forces that cause the locator structure or component to generate internal forces and deformations; A load extrapolation module, used to obtain a probability density distribution that conforms to the distribution of the initial displacement load vector, generate a supplementary displacement load vector that satisfies the probability density distribution at a preset position, and form an extrapolated displacement load vector together with the initial displacement load vector; The generating of the supplementary displacement load vector satisfying the probability density distribution comprises: extrapolating the initial displacement load vector based on the probability density distribution to generate a supplementary displacement load vector; the supplementary displacement load vector satisfies the actual force law of the positioner in the entire life cycle; A cycle counting module, used for performing cycle counting on the extrapolated displacement load vector by using a rain flow counting method, and obtaining a load amplitude, a load mean and a cycle frequency of the extrapolated displacement load vector cycle; A grading module is used to grade the extrapolated displacement load vector according to the load amplitude, the load mean and the cycle frequency to obtain a load spectrum for testing the contact network locator.

9. The overhead line locator test load spectrum generating device according to claim 8, characterized in that: The load extrapolation module includes: A cycle counting submodule is used to count the cycles of the initial displacement load vector using a rain flow counting method to obtain multiple cycles of the initial displacement load vector; obtain the cycle ratio of the number of cycles of each initial displacement load vector to the number of cycles of all initial displacement load vectors, and the cycle initial value and cycle termination value in the multiple cycles of the initial displacement load vector; A calculation submodule, used for setting an adaptive factor of a kernel density estimation algorithm model according to the cycle ratio; The superposition submodule is used to place a kernel function at the preset position according to the adaptive factor, bring the loop initial value and the loop termination value into the kernel function for calculation; and superimpose each calculated kernel function to obtain the probability density distribution.

10. The overhead line locator test load spectrum generating device according to claim 8, characterized in that: The classification module comprises: A search submodule, used for searching for a maximum displacement load amplitude value in the load amplitude values; A coefficient generation submodule is used to generate a ratio coefficient based on the condition that fatigue damage has equal damage; The grading submodule is used to perform a product operation on the ratio coefficient and the maximum displacement load amplitude to obtain a load cycle amplitude node, establish a framework of the load spectrum based on the load cycle amplitude node and the load mean node, fill in the cycle frequency in the framework of the load spectrum, and obtain the load spectrum for testing the contact network locator.

Images