A method and system for vehicle body service life safety assessment

Abstract

The present invention provides a method and system for safety assessment of vehicle body service life, which relates to the field of rail transit technology. The method comprises constructing a stress distribution finite element model of a vehicle body structure in service to obtain stress distribution at key locations of the vehicle body structure; extracting load characteristics of key vehicle body structures under real service conditions; obtaining stress-time histories at each key location; iteratively calculating the stress-time histories according to the rain flow counting method to deduce the probability distribution of stress spectra for equivalent service mileage; and calculating the remaining life of the vehicle body structure based on the actual vehicle body conditions and the probability distribution of stress spectra for equivalent service mileage, in combination with P-S-N curves and fracture mechanics parameters obtained from fatigue performance tests of key materials, thereby completing the assessment of vehicle body life. The present invention has the beneficial effect of being able to more realistically reflect the service damage of key vehicle structures, thereby providing support for the transition of vehicle structures from scheduled maintenance to condition-based maintenance.

Description

Technical Field

[0001] The present invention relates to the field of rail transportation technology, and in particular to a method and system for safety assessment of vehicle body service life. Background Art

[0002] As a key component of the vehicle's load-bearing structure, the aluminum alloy body of a rail vehicle undergoes significant service life, subject to changes in the route, passenger flow, and environment, as well as fatigue and alternating loads and degradation of the structural material properties. These intertwined factors severely impact the safe operation and maintenance of the vehicle, posing new challenges for structural integrity assessment. For example, a subway train developed macrocracks nearing the middle and late stages of its designed service life. Comprehensive consideration of the structural service conditions, the reality of the environment, the timeliness of service, and the evolution of these conditions is crucial for predicting the probability that the structure will maintain structural integrity until the next inspection interval. This approach ensures the safety of the load-bearing structure and ultimately facilitates service life assessment and life extension decisions. The primary load-bearing structure of the vehicle body is designed for a standard 30-year service life to ensure service safety. However, actual vehicle service conditions are complex, and the vehicle's structural state evolves over time. The design variations make it difficult to fully apply random loads to life assessments based on standard loads, resulting in conservative and incomplete predictions.

[0003] However, in the existing technology, the service safety assessment risks and life prediction maintenance thresholds of key structures of in-service vehicles are unclear. When damage is found in the current vehicle body service structure during the inspection and maintenance process, repair measures are taken for maintenance. There is a lack of a basis for safety risk assessment of the vehicle's main load-bearing structure and a lack of life prediction analysis to guide status maintenance strategies during dynamic state changes. A set of structural integrity safety assessment and remaining life prediction methods have not yet been formed for the key welded structures of dynamically in-service rail vehicles to ensure safe operation and guide status maintenance. To this end, the present invention provides a complete set of safety evaluation and life assessment methods for in-service rail vehicle structures to provide support for rail vehicle maintenance and life extension decisions. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and system for vehicle life safety assessment to improve the above-mentioned problems. To achieve the above-mentioned purpose, the technical solutions adopted by the present invention are as follows:

[0005] In a first aspect, the present application provides a method for assessing vehicle service life safety, including:

[0006] Based on the vehicle body structure, a finite element model of the stress distribution of the vehicle body structure in service is constructed, and the stress distribution of key locations of the vehicle body structure is obtained, where the key locations include the coupler and the traction rod;

[0007] Based on the stress distribution, the load characteristics of key vehicle body structures under real service conditions are extracted. This includes static vehicle body testing using strain gauge electrical measurement, and the extraction of test load spectra for couplers and traction rods through strain inverse load identification technology combined with vehicle body circuit testing.

[0008] Based on the load characteristics and stress distribution, the test load spectrum of the coupler and traction rod is input into the stress distribution finite element model to obtain the stress time history of each key position;

[0009] According to the rain flow counting method, the stress time history is iteratively calculated to obtain the short-term stress time history, and the stress spectrum probability distribution of equivalent service mileage is deduced based on the short-term stress time history;

[0010] Based on the actual situation of the vehicle body and the probability distribution of the stress spectrum of the equivalent service mileage, the remaining life of the vehicle body structure is calculated in combination with the PSN curve and fracture mechanics parameters obtained from fatigue performance tests of key materials, thereby completing the assessment of the vehicle body life.

[0011] Preferably, the method includes performing a static test on the vehicle body using a strain gauge electrical measurement method, and extracting the test load spectrum of the coupler and the traction rod by using a strain inverse load identification technology in combination with a vehicle body circuit test, which includes:

[0012] According to the principle of force decomposition, the load force can be decomposed into the first load, the second load and the third load. During the test, each load is maintained for 10-15 seconds to determine the relationship matrix between load and strain;

[0013] The dynamic strain signals of the components during vehicle operation are obtained through testing. Combined with the load-strain relationship matrix, the load spectrum curve of the components is solved. The strain response of the components under each step load is recorded to obtain the relationship matrix, and then the service load characteristics are extracted.

[0014] Based on the service load characteristics, the force results of the coupler and the traction rod are calculated to obtain the test load spectrum of the coupler and the traction rod. The calculation formula is as follows:

[0015]

[0016] Where ε is the strain, Δl is the tensile length, L is the original length of the rod, F is the external load, and EA is the tensile stiffness.

[0017] Preferably, the stress time history is iteratively calculated according to the rain flow counting method to obtain a short-term stress time history, and the stress spectrum probability distribution of the equivalent service mileage is deduced based on the short-term stress time history, which includes:

[0018] Determine the daily average equivalent stress amplitude and the daily average stress cycle loading number corresponding to the daily average equivalent stress amplitude according to the rain flow counting method;

[0019] Based on the daily average equivalent stress amplitude and the daily average number of stress cycle loading, and considering the randomness of the finite service load, the stress time history of the key measuring points of the vehicle body is extrapolated by dynamic stress using the stress intensity factor extrapolation method to obtain the short-term stress time history of the key measuring points.

[0020] Based on the short-term stress time history of key measuring points, the stress spectrum probability distribution of the equivalent service mileage throughout the entire life cycle is deduced.

[0021] Preferably, the stress spectrum probability distribution of the equivalent service mileage of the entire life cycle is deduced based on the short-term stress time history of the key measuring points, which includes:

[0022] Based on the stress distribution of key measuring points, the Gauss function is selected as the kernel function for probability density estimation. The calculation formula is as follows:

[0023]

[0024] Where u is the expectation, which determines the central symmetry axis of the normal distribution. Based on the probability density estimation, the optimal bandwidth coefficient is calculated by the principle of minimizing the mean square integral error. The calculation formula is as follows:

[0025]

[0026] Where, is the optimal bandwidth, and σ is the standard deviation of the sample data.

[0027] The optimal bandwidth is selected, and non-parametric kernel density fitting is performed on the short-term stress time history of key measuring points to obtain the fitting results. The chi-square test is used to evaluate the fitting results, and then the probability distribution of the stress spectrum of equivalent service mileage is obtained.

[0028] In a second aspect, the present application further provides a vehicle service life safety assessment system, comprising an acquisition module, an extraction module, an input module, a first calculation module, and a second calculation module, wherein:

[0029] Acquisition module: used to build a finite element model of the stress distribution of the vehicle body structure in service based on the vehicle body structure, and obtain the stress distribution of key positions of the vehicle body structure, where the key positions include the positions of the coupler and the traction rod;

[0030] Extraction module: This module is used to extract the load characteristics of key vehicle body structures under real service conditions based on stress distribution. This module uses strain gauge electrical measurement to conduct static vehicle body tests, and uses strain inverse load identification technology combined with vehicle body circuit tests to extract the test load spectra of the coupler and traction rod.

[0031] Input module: used to input the test load spectrum of the coupler and traction rod into the stress distribution finite element model based on load characteristics and stress distribution, and obtain the stress time history of each key position;

[0032] The first calculation module is used to iteratively calculate the stress time history based on the rain flow counting method to obtain the short-term stress time history, and to deduce the stress spectrum probability distribution of equivalent service mileage based on the short-term stress time history;

[0033] The second calculation module is used to calculate the remaining life of the vehicle body structure based on the stress spectrum probability distribution of the actual vehicle body and equivalent service mileage, combined with the PSN curve and fracture mechanics parameters obtained from fatigue performance tests of key materials, thereby completing the assessment of the vehicle body life.

[0034] In a third aspect, the present application further provides a vehicle body service life safety assessment device, comprising:

[0035] memory for storing computer programs;

[0036] A processor is used to implement the steps of the vehicle body service life safety assessment method when executing the computer program.

[0037] In a fourth aspect, the present application also provides a readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the above-mentioned method for safety assessment of vehicle service life are implemented.

[0038] The beneficial effects of the present invention are:

[0039] The present invention obtains the damage status of the vehicle body structure under the current service status based on the mechanical properties of the vehicle's key structural materials, modeling and simulation analysis of the vehicle structure, non-destructive defect detection and line testing, conducts real line testing to obtain the load and stress characteristics of the key structures under the service environment, and evaluates the life of the structure with or without cracks based on simulation and test data. It can more realistically reflect the service damage of the vehicle's key structures, thereby providing support for the transition of vehicle structures from periodic maintenance to condition-based maintenance.

[0040] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or understood by practicing the embodiments of the present invention. The purposes and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0042] Figure 1 This is a flow chart of a vehicle body service life safety assessment method according to an embodiment of the present invention;

[0043] Figure 2 This is a schematic structural diagram of a vehicle service life safety assessment system according to an embodiment of the present invention;

[0044] Figure 3 This is a schematic structural diagram of a vehicle body service life safety assessment device according to an embodiment of the present invention;

[0045] Figure 4 Schematic diagram of the evolution process of service load characteristics of a vehicle body service life safety assessment method described in an embodiment of the present invention.

[0046] In the figure: 701, acquisition module; 702, extraction module; 7021, first determination unit; 7022, solution unit; 7023, first calculation unit; 703, input module; 704, first calculation module; 7041, second determination unit; 7042, deduction unit; 7043, probability distribution unit; 70431, selection unit; 70432, second calculation unit; 70433, evaluation unit; 705, second calculation module; 800, vehicle body service life safety assessment equipment; 801, processor; 802, memory; 803, multimedia component; 804, I / O interface; 805, communication component. DETAILED DESCRIPTION

[0047] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0048] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are used only to distinguish the description and should not be understood as indicating or implying relative importance.

[0049] Example 1:

[0050] This embodiment provides a method for safety assessment of the service life of a vehicle body.

[0051] See also Figure 1 , the figure shows that the method includes step S100, step S200, step S300, step S400 and step S500.

[0052] S100: Construct a stress distribution finite element model of the in-service vehicle body structure based on the vehicle body structure, and obtain stress distribution at key positions of the vehicle body structure, wherein the key positions include positions of a coupler and a traction rod.

[0053] It can be understood that this step includes two steps. The first is to construct a three-dimensional model of the vehicle body structure and a stress distribution model. Among them, based on the structure of the vehicle body, such as the connection relationship between components, the positioning relationship, etc., the relationship between important components, such as connection holes and welding relationships, etc., is measured; the structural information of each component is mapped, such as transition arc, thickness, stiffener plate size, thickness and distribution, etc. Detailed mapping is carried out for the connection relationship and profile thickness of the main structures of the vehicle body (such as the chassis, side walls, end walls and roof, etc.), and a vehicle body model that conforms to reality is established to provide key input for subsequent simulation analysis. The aluminum alloy lightweight profile bears the entire body, and the three-dimensional modeling process is from line to surface. After operations such as stretching, rotating, and cutting the surface, the three-dimensional structure of each component of the vehicle body is obtained. The established three-dimensional structure includes all the appearance features of the components except small fillets and welds, which is sufficient to ensure the accuracy of the subsequent finite element model establishment. Multiple components are assembled to obtain a substructure, and the substructure is assembled to obtain a three-dimensional model of the entire vehicle.

[0054] The second is to obtain the stress distribution of key weak points of the vehicle structure based on the standard load; among them, based on the three-dimensional model and in accordance with the basic theoretical method of finite element, by combining the plate and shell with the solid unit, a finite element model equivalent to the actual structure is established, the vehicle finite element simulation method (boundary conditions, etc.) is determined, and relevant standards are selected for simulation analysis. The specific process is as follows: (1) Combining the three-dimensional model of the vehicle body, the mechanical properties of the corresponding material grade and the finite element modeling method, the vehicle body structure is discretized, and based on the finite element unit type, a finite element model consistent with the actual mechanical structure is established; the standard load is input at the position of the coupler and traction rod to obtain the fatigue and damage details stress distribution, and the transfer relationship between the unit load and the stress distribution is established.

[0055] S200, based on stress distribution, extracts the load characteristics of key vehicle body structures under real service conditions. This includes static vehicle body testing using strain gauge electrical measurement, and extracting the test load spectra of the coupler and traction rod through strain inverse load identification technology combined with vehicle body circuit testing.

[0056] It can be understood that the step S200 includes S201, S202 and S203, wherein:

[0057] S201. According to the force decomposition principle, the load force can be decomposed into a first load, a second load, and a third load. During the test, each load is maintained for 10-15 seconds to determine the load-strain relationship matrix.

[0058] Among them, it is necessary to conduct static calibration tests on the vehicle body and reasonably design the test fixture structure of the vehicle coupler and traction pin so that it can accurately simulate the force transmission path of the test piece. Usually, the components are subjected to multi-axis loads in the working state. According to the principle of force decomposition, the load force F can be decomposed into F in the three directions of X, Y and Z. X 、F Y 、F Z Three loads are applied. During the test, a stepped load spectrum is given to the specimen. Each load is maintained for 10-15 seconds. The average strain value of the strain gauge response at the step position is taken. The relationship matrix K between the load and strain is determined by the relationship between the two. The calculation formula is as follows:

[0059]

[0060] S202. Dynamic strain signals of components during vehicle operation are obtained through testing. The load spectrum curve of the components is solved by combining the load-strain relationship matrix. The strain response of the components under each step load is recorded to obtain the relationship matrix, thereby extracting service load characteristics.

[0061] It should be noted that the dynamic strain signal of the component during vehicle operation is obtained through testing. The load spectrum curve of the specimen can be inversely calculated by combining the above formula with the relationship matrix obtained from the calibration test. By recording the strain response of the component under each step load, a straight line can be approximated. The slope of the straight line is found, which is the corresponding coefficient in the relationship matrix. By finding the total strain-load linear slope of the component response under the load, the relationship matrix can be obtained, and the service load characteristics can be extracted.

[0062] S203. Based on the service load characteristics, the force results of the coupler and the traction rod are calculated to obtain the test load spectrum of the coupler and the traction rod. The calculation formula is as follows:

[0063]

[0064] Where ε is the strain, Δl is the tensile length, L is the original length of the rod, F is the external load, and EA is the tensile stiffness.

[0065] It should be noted that when the vehicle is running, the coupler mainly bears the longitudinal load. It can be regarded as a two-force rod structure. When an external load F is applied to the structure, the rod will produce a certain deformation, which can be calculated by the above formula based on material mechanics.

[0066] From the above formula, it can be seen that when the tensile (compressive) stiffness of the structure is known, the load F can be derived from the strain ε, as shown in the following formula. For the coupler, it is only necessary to test its longitudinal strain response to obtain the coupler service characteristic load, as shown in the following formula:

[0067] F X =(k xx ) -1 ε x

[0068] The synchronous characteristics of the service loads of the integrated coupler and the traction rod can be used as the service effective load of the vehicle body. Since the key structure mainly bears the longitudinal load, the present invention mainly revolves around the longitudinal load.

[0069] S300. Based on the load characteristics and stress distribution, the test load spectrum of the coupler and the traction rod is input into the stress distribution finite element model to obtain the stress time history of each key position.

[0070] It can be understood that in this step S300, the load spectrum of the car body coupler and traction rod established in step S200 is applied to the car body finite element model constructed in step S100, and the stress time history of the stress influence surface of each vulnerable detail is obtained based on the finite time service load characteristics and the unit load and stress distribution transfer relationship obtained in the above steps.

[0071] S400. According to the rain flow counting method, the stress time history is iteratively calculated to obtain the short-term stress time history, and the stress spectrum probability distribution of the equivalent service mileage is deduced based on the short-term stress time history.

[0072] It can be understood that the step S400 includes S401, S402 and S403, wherein:

[0073] S401. Determine the daily average equivalent stress amplitude and the daily average stress cycle loading number corresponding to the daily average equivalent stress amplitude according to the rain flow counting method;

[0074] S402. Based on the daily average equivalent stress amplitude and the daily average stress cycle loading number, the randomness of the finite service load is considered;

[0075] S403. Based on the short-term stress-time history of key measuring points, dynamic stress extrapolation is performed on the stress-time history of key measuring points of the vehicle body through the stress rain flow technology matrix time domain extrapolation method, and then the stress spectrum probability distribution of the equivalent service mileage of the entire life cycle is deduced.

[0076] It should be noted that the stress time history of the vulnerable position is calculated based on the rain flow counting method, and its daily average equivalent stress amplitude and the corresponding daily average stress cycle loading number are determined. Taking into account the randomness of the finite service load, and based on the service load characteristics, the effective amplitude information is extracted. A non-parametric kernel density estimation method is proposed to perform dynamic stress extrapolation on the stress time history of the key measuring points of the vehicle body, and the probability distribution of the full life cycle stress spectrum of the key measuring points is obtained through the extrapolation method.

[0077] S403. Based on the short-term stress time history of key measuring points, the stress spectrum probability distribution of the equivalent service mileage of the entire life cycle is deduced.

[0078] It should be noted that if Figure 4 As shown in the figure, the complex environment in which the vehicle is located during operation leads to a strong randomness in the measured data of the line, making it difficult to directly use a single function to describe the distribution law of the dynamic stress spectrum of the vehicle body. Therefore, the non-parametric estimation method overcomes the shortcomings of the traditional parameter estimation method, that is, there is no need to assume a distribution function, and the distribution characteristics of the sample itself are studied entirely based on its own data. The purpose of stress spectrum fitting is to obtain the probabilistic law of the test stress spectrum, to infer the extreme values ​​of stress and stress distribution at all levels under the entire life cycle as much as possible, and to further extrapolate the stress spectrum. This realizes the safety evaluation and life assessment of the cracked and non-cracked states of the in-service rail vehicle structure, which is of great significance to the maintenance and life extension decision-making of key vehicle structures.

[0079] It should be noted that step S403 includes S4031, S4032, and S4033, wherein:

[0080] S4031. Based on the stress distribution of key measuring points, the Gauss function is selected as the kernel function for probability density estimation. The calculation formula is as follows:

[0081]

[0082] Where u is the expectation, which determines the central symmetry axis of the normal distribution.

[0083] In order to perform kernel density estimation more accurately, the calculation is based on the principle of minimizing the mean square integral error (MISE). The mean square integral error is used to measure the difference between the fitted probability density function and the actual probability density function. The optimal bandwidth coefficient h is solved by minimizing the asymptotic MISE. Its expression is:

[0084]

[0085] Where E(g) is the mean function, μ2(K)=∫x 2 K(x)dx,R(K)=∫K 2 (x)dx, K is the Gauss kernel function, n is the sample size, h is the bandwidth coefficient, μ2(K) is the central area, and R(K) is the neighboring area;

[0086] Taking the kernel function as Gauss function, according to the classic thumb rule, the optimal choice expression of the bandwidth coefficient h is

[0087]

[0088] Where d is the dimension of the kernel density estimation, σ is the standard deviation of the sample data, and for one-dimensional kernel density estimation, if d = 1, the optimal bandwidth is obtained.

[0089] S4032. Based on the probability density estimation, the optimal bandwidth coefficient is calculated by the principle of minimizing the mean square integral error. The calculation formula is as follows:

[0090]

[0091] Where, is the optimal bandwidth, and σ is the standard deviation of the sample data.

[0092] S4033. Select the optimal bandwidth and perform non-parametric kernel density fitting estimation on the short-term stress time history of key measuring points to obtain the fitting results. Use the chi-square test to evaluate the fitting results and then obtain the probability distribution of the stress spectrum of equivalent service mileage.

[0093] S500, based on the actual situation of the vehicle body and the probability distribution of the stress spectrum of equivalent service mileage, combined with the PSN curve obtained from fatigue performance tests of key materials and fracture mechanics parameters, calculates the remaining life of the vehicle body structure, thereby completing the assessment of the vehicle body life.

[0094] It can be understood that in this step, the nominal stress cumulative damage is integrated with the crack-free state of the key areas of the vehicle body to evaluate the damage of the key parts. The fracture mechanics, crack propagation threshold, crack propagation rate, fracture toughness and other input parameters are integrated with the crack structure. The probabilistic service load characteristics in the above steps are used to calculate the remaining life of the vehicle body structure. The above steps are combined to realize the comprehensive evaluation of the fatigue life of the vehicle body structure and the maintenance strategy based on the remaining life.

[0095] The specific assessment method is to conduct life safety assessment of key structures of in-service vehicles according to the following three types. The first type is high-stress areas without cracks (mainly weld toes and structural arc transitions); the second type is small-sized macro cracks; and the third type is visible and obvious cracks.

[0096] For the first type: conduct fatigue property tests on the material and carry out fatigue life assessment based on the fatigue life damage PSN curve; since the life of this area is relatively long, the aforementioned nominal stress method is combined to assess the damage in this area and achieve health evaluation.

[0097] For the second type, fracture mechanics testing of the material is conducted to obtain relevant parameters. Damage tolerance methods are then used to assess the remaining life and crack evolution patterns. For the second type, although cracks are observed, they are very small, likely just past the initiation stage and in the early stages of crack propagation. Repairing these cracks is ineffective and uneconomical. However, a well-planned repair process can allow for appropriate repairs.

[0098] The general steps of the remaining life assessment method based on linear elastic fracture mechanics are:

[0099] (1) Determine the initial crack length, which can be measured by non-destructive testing. The safety of the structure is evaluated by comparing the calculated stress intensity factor with the fracture value obtained by the test.

[0100] (2) Based on the service evolution characteristic load spectrum in the third part, the stress intensity factor amplitude at the key position is obtained, and the crack propagation zone is simulated based on the sub-model technology.

[0101] (3) Determine the crack growth increment Δa, calculate the stress intensity factor amplitude ΔK when the crack grows to (a+Δa), and calculate the number of load cycles of the component under the condition of the crack growth increment Δa by integrating the Paris formula;

[0102] (4) Repeat the above process until the stress intensity factor at the crack front reaches the fracture toughness of the material, and finally obtain the remaining life of the structure when it expands from the initial crack to the critical crack.

[0103] Through crack propagation simulation analysis, the crack propagation morphology is evolved, which can not only calculate the remaining life under the crack, but also further guide the maintenance strategy, avoid blind repairs, and thus achieve precise repairs.

[0104] Example 2:

[0105] like Figure 2 As shown, this embodiment provides a vehicle body service life safety assessment system, see Figure 2 The system includes an acquisition module 701, an extraction module 702, an input module 703, a first calculation module 704 and a second calculation module 705, wherein:

[0106] Acquisition module 701: used to construct a stress distribution finite element model of the in-service vehicle body structure based on the vehicle body structure, and obtain the stress distribution of key positions of the vehicle body structure, wherein the key positions include positions of the coupler and the traction rod;

[0107] Extraction module 702: is used to extract the load characteristics of key vehicle body structures under real service conditions based on stress distribution. This includes performing static vehicle body tests using strain gauge electrical measurement methods, and extracting the test load spectra of the coupler and traction rod using strain inverse load identification technology combined with vehicle body circuit tests.

[0108] Input module 703: used to input the test load spectrum of the coupler and traction rod into the stress distribution finite element model based on the load characteristics and stress distribution, and obtain the stress time history of each key position;

[0109] The first calculation module 704 is used to iteratively calculate the stress time history according to the rain flow counting method to obtain a short-term stress time history, and to deduce the stress spectrum probability distribution of equivalent service mileage based on the short-term stress time history;

[0110] Second calculation module 705: Based on the actual condition of the vehicle body and the probability distribution of the stress spectrum of the equivalent service mileage, combined with the PSN curve and fracture mechanics parameters obtained from fatigue performance tests of key materials, the remaining life of the vehicle body structure is calculated, thereby completing the vehicle body life assessment.

[0111] Specifically, the extraction module 702 includes a first determination unit 7021, a solution unit 7022, and a first calculation unit 7023, wherein:

[0112] The first determination unit 7021 is used to decompose the load force into a first load, a second load, and a third load according to the force decomposition principle, maintain each load for 10-15 seconds during the test, and determine the load-strain relationship matrix;

[0113] Solving unit 7022: used to obtain dynamic strain signals of components during vehicle operation through testing, and solve the load spectrum curve of the component by combining the load-strain relationship matrix. The strain response of the component under each step load is recorded to obtain the relationship matrix, and then the service load characteristics are extracted.

[0114] The first calculation unit 7023 is used to calculate the force results of the coupler and the traction rod based on the service load characteristics, and obtain the test load spectrum of the coupler and the traction rod. The calculation formula is as follows:

[0115]

[0116] Where ε is the strain, Δl is the tensile length, L is the original length of the rod, F is the external load, and EA is the tensile stiffness.

[0117] Specifically, the first calculation module 704 includes a second determination unit 7041, a deduction unit 7042, and a probability distribution unit 7043, wherein:

[0118] The second determining unit 7041 is configured to determine the daily average equivalent stress amplitude and the daily average stress cycle loading number corresponding to the daily average equivalent stress amplitude according to the rain flow counting method;

[0119] Deduction unit 7042: used to consider the randomness of finite service loads based on the daily average equivalent stress amplitude and the daily average stress cycle loading number; based on the short-term stress time history of key measuring points, the matrix distribution of stress range and cycle number is obtained through the stress rain flow technology matrix time domain.

[0120] Probability distribution unit 7043: used to deduce the stress spectrum probability distribution of equivalent service mileage over the entire life cycle based on the short-term stress time history and matrix distribution of key measurement points.

[0121] Specifically, the deduction unit 7043 includes a selection unit 70431, a second calculation unit 70432, and an evaluation unit 70433, wherein:

[0122] Selection unit 70431: used to select Gauss function as kernel function for probability density estimation based on stress distribution of key measuring points. The calculation formula is as follows:

[0123]

[0124] Where u is the expectation, which determines the central symmetry axis of the normal distribution.

[0125] The second calculation unit 70432 is used to calculate the optimal bandwidth coefficient based on the probability density estimation and the principle of minimizing the mean square integral error. The calculation formula is as follows:

[0126]

[0127] Where, is the optimal bandwidth, and σ is the standard deviation of the sample data.

[0128] Evaluation unit 70433: used to select the optimal bandwidth, perform non-parametric kernel density fitting estimation on the short-term stress time history of key measuring points, obtain fitting results, evaluate the fitting results using the chi-square test, and then obtain the stress spectrum probability distribution of equivalent service mileage.

[0129] It should be noted that, regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated on here.

[0130] Example 3:

[0131] Corresponding to the above method embodiment, this embodiment also provides a vehicle body service life safety assessment device. The vehicle body service life safety assessment device described below and the vehicle body service life safety assessment method described above can be referenced to each other.

[0132] Figure 3 FIG. 8 is a block diagram of a vehicle body service life safety assessment device 800 according to an exemplary embodiment. Figure 3 As shown, the vehicle body service life safety assessment device 800 includes: a processor 801 and a memory 802. The vehicle body service life safety assessment device 800 also includes one or more of a multimedia component 803, an I / O interface 804, and a communication component 805.

[0133] The processor 801 is used to control the overall operation of the vehicle life safety assessment device 800 to complete all or part of the steps in the vehicle life safety assessment method described above. The memory 802 is used to store various types of data to support the operation of the vehicle life safety assessment device 800. This data may include, for example, instructions for any application or method operating on the vehicle life safety assessment device 800, as well as application-related data such as contact information, sent and received messages, images, audio, and video. The memory 802 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The multimedia component 803 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 802 or transmitted via the communication component 805. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 804 provides an interface between the processor 801 and other interface modules, and the above-mentioned other interface modules can be a keyboard, a mouse or buttons, etc. These buttons can be virtual buttons or physical buttons. The communication component 805 is used for wired or wireless communication between the vehicle body service life safety assessment device 800 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G or 4G, or a combination of one or more of them, so the corresponding communication component 805 may include: a Wi-Fi module, a Bluetooth module or an NFC module.

[0134] In an exemplary embodiment, the vehicle body service life safety assessment device 800 can be implemented by one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to execute the above-mentioned vehicle body service life safety assessment method.

[0135] In another exemplary embodiment, a computer-readable storage medium containing program instructions is also provided. When executed by a processor, the program instructions implement the steps of the above-described vehicle life safety assessment method. For example, the computer-readable storage medium may be the aforementioned memory 802 containing the program instructions. The program instructions may be executed by the processor 801 of the vehicle life safety assessment device 800 to perform the above-described vehicle life safety assessment method.

[0136] Example 4:

[0137] Corresponding to the above method embodiment, this embodiment further provides a readable storage medium. The readable storage medium described below and the vehicle body service life safety assessment method described above can refer to each other.

[0138] A computer program is stored on the readable storage medium, and when the computer program is executed by the processor, the steps of the vehicle body service life safety assessment method of the above method embodiment are implemented.

[0139] The readable storage medium may specifically be any readable storage medium that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0140] In summary, the present invention establishes a comprehensive assessment method and implements a system for assessing the safety status and lifespan of in-service vehicle structures. This method is used to guide the inspection, maintenance, and life extension decision-making of key in-service vehicle structures. The present invention's lifespan assessment method for in-service rail vehicle structures, based on the structural state and service load characteristics during service, enables safety evaluation and lifespan assessment of in-service rail vehicle structures in both cracked and crack-free states. This has significant implications for decision-making regarding the maintenance and life extension of key vehicle structures.

[0141] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

[0142] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A method for assessing vehicle service life safety, characterized in that: include: Based on the vehicle body structure, a finite element model of the stress distribution of the vehicle body structure in service is constructed, and the stress distribution of key locations of the vehicle body structure is obtained, where the key locations include the coupler and the traction rod; Based on the stress distribution, the load characteristics of key vehicle body structures under real service conditions are extracted. This includes static vehicle body testing using strain gauge electrical measurement, and the extraction of test load spectra for couplers and traction rods through strain inverse load identification technology combined with vehicle body circuit testing. Based on the load characteristics and stress distribution, the test load spectrum of the coupler and traction rod is input into the stress distribution finite element model to obtain the stress time history of each key position; According to the rain flow counting method, the stress time history is iteratively calculated to obtain the short-term stress time history, and the stress spectrum probability distribution of equivalent service mileage is deduced based on the short-term stress time history; Based on the actual conditions of the vehicle body and the probability distribution of stress spectra of equivalent service mileage, fatigue performance tests of key materials are conducted to obtain PSN curves and fracture mechanics parameters, and the remaining life of the vehicle body structure is calculated, thus completing the vehicle body life assessment; The method includes using a strain gauge electrical measurement method to conduct a static test on the vehicle body, and extracting the test load spectrum of the coupler and traction rod by using the strain inverse load identification technology combined with the vehicle body circuit test, including: According to the principle of force decomposition, the load force can be decomposed into the first load, the second load and the third load. During the test, each load is maintained for 10-15 seconds to determine the relationship matrix between load and strain; The dynamic strain signals of the components during vehicle operation are obtained through testing. Combined with the load-strain relationship matrix, the load spectrum curve of the components is solved. The strain response of the components under each step load is recorded to obtain the relationship matrix, and then the service load characteristics are extracted. Based on the service load characteristics, the force results of the coupler and the traction rod are calculated to obtain the test load spectrum of the coupler and the traction rod. The calculation formula is as follows: Where ε is the strain, Δl is the tensile length, L is the original length of the rod, F is the external load, and EA is the tensile stiffness.

2. The vehicle body service life safety assessment method according to claim 1, characterized in that: According to the rain flow counting method, the stress time history is iteratively calculated to obtain the short-term stress time history, and the stress spectrum probability distribution of the equivalent service mileage is deduced based on the short-term stress time history, which includes: Determine the daily average equivalent stress amplitude and the daily average stress cycle loading number corresponding to the daily average equivalent stress amplitude according to the rain flow counting method; Based on the daily average equivalent stress amplitude and the daily average stress cycle loading number, the randomness of the finite service load is considered; Based on the short-term stress time history of key measuring points, the stress time history of key measuring points of the vehicle body is dynamic stress extrapolated by the stress rain flow technology matrix time domain extrapolation method, and then the stress spectrum probability distribution of the equivalent service mileage of the entire life cycle is deduced.

3. The vehicle body service life safety assessment method according to claim 2, characterized in that: The short-term stress time history based on the key measuring points is used to deduce the stress spectrum probability distribution of the equivalent service mileage of the entire life cycle, including: Based on the stress distribution of key measuring points, the Gauss function is selected as the kernel function for probability density estimation. The calculation formula is as follows: Where u is the expectation, which determines the central symmetry axis of the normal distribution; Based on probability density estimation, the optimal bandwidth coefficient is calculated by the principle of minimizing the mean square integral error. The calculation formula is as follows: Where, is the optimal bandwidth, σ is the standard deviation of sample data; The optimal bandwidth is selected, and non-parametric kernel density fitting is performed on the short-term stress time history of key measuring points to obtain the fitting results. The chi-square test is used to evaluate the fitting results, and then the probability distribution of the stress spectrum of equivalent service mileage is obtained.

4. A vehicle service life safety assessment system, characterized in that: include: Acquisition module: used to build a finite element model of the stress distribution of the vehicle body structure in service based on the vehicle body structure, and obtain the stress distribution of key positions of the vehicle body structure, where the key positions include the positions of the coupler and the traction rod; Extraction module: This module is used to extract the load characteristics of key vehicle body structures under real service conditions based on stress distribution. This module uses strain gauge electrical measurement to conduct static vehicle body tests, and uses strain inverse load identification technology combined with vehicle body circuit tests to extract the test load spectra of the coupler and traction rod. Input module: used to input the test load spectrum of the coupler and traction rod into the stress distribution finite element model based on load characteristics and stress distribution, and obtain the stress time history of each key position; The first calculation module is used to iteratively calculate the stress time history based on the rain flow counting method to obtain the short-term stress time history, and to deduce the stress spectrum probability distribution of equivalent service mileage based on the short-term stress time history; The second calculation module is used to calculate the remaining life of the vehicle structure based on the stress spectrum probability distribution of the actual vehicle body and equivalent service mileage, combined with the PSN curve and fracture mechanics parameters obtained from fatigue performance tests of key materials, thereby completing the vehicle body life assessment; The extraction module includes: The first determination unit is used to decompose the load force into the first load, the second load and the third load according to the force decomposition principle, and maintain each load for 10-15 seconds during the test to determine the load-strain relationship matrix; Solving unit: used to obtain the dynamic strain signal of the vehicle body components during operation through testing, and solve the load spectrum curve of the components by combining the load-strain relationship matrix. It also records the strain response of the components under each step load to obtain the relationship matrix, and then extracts the service load characteristics; The first calculation unit is used to calculate the force results of the coupler and the traction rod based on the service load characteristics, and obtain the test load spectrum of the coupler and the traction rod. The calculation formula is as follows: Where ε is the strain, Δl is the tensile length, L is the original length of the rod, F is the external load, and EA is the tensile stiffness.

5. The vehicle service life safety assessment system according to claim 4, characterized in that: The first computing module includes: The second determining unit is used to determine the daily average equivalent stress amplitude and the daily average stress cycle loading number corresponding to the daily average equivalent stress amplitude according to the rain flow counting method; Deduction unit: used to consider the randomness of finite service loads based on the daily average equivalent stress amplitude and the daily average stress cycle loading number; Probability distribution unit: It is used to perform dynamic stress extrapolation on the stress time history of key measuring points of the vehicle body based on the short-term stress time history of key measuring points through the stress rain flow technology matrix time domain extrapolation method, and then deduce the stress spectrum probability distribution of the equivalent service mileage of the entire life cycle.

6. The vehicle service life safety assessment system according to claim 5, characterized in that: The deduction unit includes: Selection unit: It is used to estimate the probability density based on the stress distribution of key measuring points and select the Gauss function as the kernel function. The calculation formula is as follows: Where u is the expectation, which determines the central symmetry axis of the normal distribution; The second calculation unit is used to calculate the optimal bandwidth coefficient based on the probability density estimation and the principle of minimum mean square integral error. The calculation formula is as follows: Where, is the optimal bandwidth, σ is the standard deviation of sample data; Evaluation unit: used to select the optimal bandwidth, perform non-parametric kernel density fitting estimation on the short-term stress time history of key measuring points, obtain fitting results, evaluate the fitting results using chi-square test, and then obtain the stress spectrum probability distribution of equivalent service mileage.

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