A fatigue life analysis method for chassis frame of combine harvester

Abstract

The present invention discloses a fatigue life analysis method for a chassis frame of a combine harvester, and relates to the technical field of harvesters, and comprises the following steps: obtaining load data, and preprocessing the load data, and compiling a load spectrum at the same time, constructing a chassis frame finite element model based on the preprocessed load data, and conducting strength verification analysis on the front axle, rear axle, and body of the chassis frame, and analyzing the deformation position and stress distribution of the chassis frame under different working conditions at the same time, and outputting a stress analysis report, and extracting the strain time history of the dangerous point of the chassis frame based on the stress analysis report and the chassis frame finite element model, and obtaining its stress time history according to the relationship between stress and strain. The present invention can accurately predict the fatigue life of each part, predict the possible failure position and fatigue life in advance, and take corresponding improvement measures in the design and manufacturing stage through the combination of finite element analysis and actual load spectrum.

Description

Technical Field

[0001] The invention relates to the technical field of harvesters, and in particular to a fatigue life analysis method for a chassis frame of a combine harvester. Background Art

[0002] With the advancement of agricultural modernization, combine harvesters, as important agricultural machinery, are playing an increasingly important role in agricultural production. The chassis frame is the main supporting component of the combine harvester, and its performance directly affects the stability and reliability of the whole machine. The chassis frame needs to withstand loads from the engine, transmission system, working parts, etc. during operation. Therefore, fatigue life analysis is an important part of ensuring the performance of the whole machine. By performing fatigue life analysis on the chassis frame, it is possible to predict fatigue damage that may occur during its service life, so as to take measures in advance to improve and optimize it. Combine harvesters usually operate in complex and changeable working environments, such as fields, rural roads, etc. Improving the performance and reliability of combine harvesters is of great significance to ensuring the smooth progress of agricultural production.

[0003] In the prior art, the loads borne by the chassis frame in actual operation are complex and changeable, including static loads, dynamic loads, and random loads. The size, direction, and frequency of these loads are often difficult to accurately measure and predict, resulting in inaccurate load spectrum data required for fatigue life analysis. Therefore, how to predict the load condition of the chassis frame and improve the accuracy of the load spectrum data is the problem we need to solve. A fatigue life analysis method for the chassis frame of a combine harvester is proposed. Summary of the invention

[0004] The present invention aims to provide a method for analyzing the fatigue life of a chassis frame of a combine harvester to solve the problems raised in the above-mentioned background technology.

[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0006] A fatigue life analysis method for a chassis frame of a combine harvester comprises the following steps: step 1, obtaining load data, preprocessing the load data, and compiling a load spectrum; step 2, constructing a finite element model of the chassis frame based on the preprocessed load data, performing strength verification analysis on a front axle, a rear axle, and a body of the chassis frame, analyzing the deformation position and stress distribution of the chassis frame under different working conditions, and outputting a stress analysis report, including a stress distribution diagram, a deformation diagram, stress values ​​of key parts, etc.;

[0007] Step 3: Based on the stress analysis report and the chassis frame finite element model, extract the strain time history of the chassis frame danger point, obtain its stress time history according to the relationship between stress and strain, and predict the fatigue life of the chassis frame under constant amplitude load, random load and mixed load, and output the fatigue prediction results. The prediction results should include information such as the fatigue life of the chassis frame, fatigue failure location and fatigue damage degree;

[0008] Step 4: According to the stress analysis report and fatigue prediction results, the fatigue life of the chassis frame is predicted and analyzed, and the fatigue evaluation coefficient is calculated to perform reliability evaluation on the fatigue life analysis of the chassis frame;

[0009] Step 5: predict the existing problems of the chassis frame, such as stress concentration, fatigue cracks, etc., based on the results of fatigue life analysis and reliability evaluation, and determine the warning level of the current chassis frame fatigue situation, and generate corresponding warning information according to the corresponding warning level;

[0010] Step 6: Based on the warning information, formulate corresponding improvement measures, such as adjusting the structural design, replacing materials or improving the manufacturing process, so as to improve the fatigue life of the chassis frame and the reliability of the whole machine.

[0011] A further improvement of the technical solution of the present invention is that in step 1, the process of compiling the load spectrum is:

[0012] Step 101, deploy sensors on the chassis frame of the combine harvester to collect load data borne by the chassis frame in real time, including the size and direction changes of static load and dynamic load, such as installing various sensors including strain gauges, acceleration sensors, force sensors, etc. at engine mounting points, transmission system connections, working component suspension points, and locations connected to wheels;

[0013] Step 102, synchronously recording the operating parameters of the combine harvester, including driving speed, operating gear, operating depth and steering angle;

[0014] Step 103, performing data cleaning, data smoothing, data standardization and data segmentation on the collected load data to remove abnormal values ​​and erroneous data;

[0015] Step 104, sort and count the pre-processed load data, analyze the distribution characteristics and change trends of the load data, determine the load change range, mean, standard deviation and other statistical characteristic parameters, for example, count the maximum value, minimum value, average value and force change frequency of the vertical force borne by the chassis frame in a complete operation cycle, and compile a load spectrum, which usually includes parameters such as load size, load direction, and load action time. The load spectrum can be further subdivided into time history load spectrum, rain flow counting load spectrum, extreme value load spectrum and other types. Select the appropriate load spectrum type according to actual needs.

[0016] A further improvement of the technical solution of the present invention is that in step 2, the analysis process of the deformation position and stress distribution of the chassis frame under different working conditions is as follows:

[0017] Step 201, according to the actual design size and structural shape of the chassis frame of the combine harvester, use the geometric modeling function of finite element analysis software, such as ANSYS, Abaqus, etc., to create a geometric model of the front axle, rear axle, and body parts of the chassis frame. In the modeling process, attention should be paid to capturing the detailed features of the structure, such as reinforcing ribs, holes, welded joints, etc., and assigning material properties to each component in the geometric model, such as density, elastic modulus, Poisson's ratio, etc., and dividing the geometric model mesh into discrete units and nodes;

[0018] Step 202, according to the pre-processed load data, static loads and dynamic loads are applied to the geometric model, and boundary conditions are set; for example: setting fixed constraints: applying fixed constraints at the support points of the chassis frame to simulate the support conditions under actual working conditions, specifically: fixing the support points of the front axle and the rear axle; sliding constraints: applying sliding constraints at certain locations to simulate the relative movement between components;

[0019] Step 203, in finite element analysis software, static analysis and dynamic analysis are performed on the chassis frame to calculate the stress value, deformation value, strain and displacement under static load, and evaluate the performance of the chassis frame under dynamic load, including modal analysis, transient response analysis or spectrum analysis, etc.;

[0020] Step 204, analyzing the stress distribution of the chassis frame under different working conditions according to the analysis results of the static analysis, identifying the stress concentration area, and comparing the calculated stress value with the allowable stress of the chassis frame material to determine the strength requirement of the chassis frame, and predicting the high stress area and low stress area of ​​the chassis frame;

[0021] Step 205, based on the analysis results of the static analysis, analyze the deformation distribution of the chassis frame under different working conditions, compare the calculated deformation value with the allowable deformation value of the chassis frame, determine whether the deformation requirements are met, and predict the deformation position and deformation amount. If the deformation value exceeds the allowable value, structural optimization or material improvement is required, and a stress analysis report is prepared.

[0022] A further improvement of the technical solution of the present invention is that in step 3, the process of obtaining the fatigue prediction result is:

[0023] Step 301, determining the position of the dangerous point of the chassis frame according to the stress analysis report, and extracting the strain time history of the dangerous point in the finite element analysis software;

[0024] Step 302, based on the material properties of the geometric model, analyzing the stress-strain relationship, and using the extracted strain-time history and strain relationship, calculating the stress-time history of the dangerous point, and obtaining the stress-time history index;

[0025] Step 303, according to the load types of constant amplitude load, random load and mixed load of the chassis frame and the working environment, the fatigue parameters of the material properties of the chassis frame are determined by using the geometric model, and the fatigue life analysis index is obtained in combination with the stress time history to predict the fatigue life of the chassis frame;

[0026] Step 304 , compare the fatigue life prediction results under constant amplitude load, random load and mixed load, analyze the influence of different load types on the fatigue life of the chassis frame, and output the fatigue prediction results.

[0027] A further improvement of the technical solution of the present invention is that the calculation formula of the stress time history index is:

[0028]

[0029] Where STH is the stress time history index, σ max,i is the maximum stress in the i-th stress cycle, σ min,i is the minimum stress in the ith stress cycle, σ f is the fatigue strength of the material, that is, the stress amplitude that causes material failure under infinite cycles, t i is the duration of the ith stress cycle, f i is the frequency of the ith stress cycle, α, β and γ are exponential parameters related to material properties and stress time history, and n is the total number of stress cycles;

[0030] The calculation formula of stress time history is:

[0031]

[0032] Where σ(t) is the stress at time t, E is the elastic modulus of the material, ε(t) is the strain at time t, a, b, c are coefficients related to the nonlinear behavior of the material, d is the coefficient related to the strain history effect, ω is the angular frequency of the strain history effect function, is the phase angle of the strain history influence function, τ is the integral variable, representing time;

[0033] The calculation formula of fatigue life analysis index is:

[0034]

[0035] Among them, N f is the fatigue life analysis index, D is the cumulative damage value, C,m,j is the fatigue parameter of the material, σ(t) is the stress at time t, σ a is the stress amplitude, i.e., the fluctuation of stress relative to its mean value, σ mean is the average value of stress, and T is a complete load cycle.

[0036] A further improvement of the technical solution of the present invention is that in step 4, the process of obtaining the fatigue assessment coefficient is:

[0037] Step 401, applying a load spectrum to the chassis frame, calculating the stress distribution of the frame through a finite element model of the chassis frame, and calculating the fatigue life of each part of the chassis frame respectively;

[0038] Step 402, based on the fatigue life of each part of the chassis frame, analyzing and accumulating the fatigue damage of each part to obtain the overall fatigue life of the chassis frame;

[0039] Step 403, based on the fatigue damage of each part of the chassis frame, analyzing the correlation between the overall fatigue life and the fatigue damage of each part of each part, and calculating the fatigue assessment coefficient in combination with the load spectrum;

[0040] Step 404 , based on the obtained fatigue evaluation coefficient, quantify the performance of the chassis frame under fatigue load, evaluate the fatigue life reliability of the chassis frame, and the influence of uncertainty on the chassis frame fatigue life prediction result.

[0041] A further improvement of the technical solution of the present invention is that the calculation formula of the fatigue evaluation coefficient is:

[0042]

[0043] Where FEC is the fatigue evaluation coefficient, δ max,i is the maximum stress value at the mth position, δ basei is the reference stress value, δ f,ois the fatigue strength of the oth part, that is, the stress level when the expected life of the component reaches a certain value under this stress, p is the power exponent of stress influence, which is used to adjust the contribution of stress to fatigue damage, f(μ o ) is the time history function, considering the influence of stress change over time on fatigue damage, μ o is the stress-time history of the Oth position, g(L o ) is the life influence function, considering the contribution of component life to fatigue damage, L o is the fatigue life of the oth part, that is, the number of cycles or time required for the component to reach fatigue failure under a given stress, and m is the number of parts considered in the chassis frame.

[0044] A further improvement of the technical solution of the present invention is that in step 5, the process of early warning information is:

[0045] Step 501, based on the fatigue evaluation coefficient, identifying the parts of the chassis frame with low fatigue life reliability, and comparing the fatigue life under different working conditions;

[0046] Step 502, combining the reliability evaluation results, determining high stress and high strain areas of the chassis frame, and predicting problems existing in the chassis frame, including fatigue damage accumulation, insufficient structural strength, material performance degradation, and connector failure;

[0047] Step 503, according to the fatigue life and reliability evaluation results of the chassis frame, different warning levels are set, namely, a low risk warning level, a medium risk warning level, and a high risk warning level;

[0048] Step 504, matching the determined different warning levels with the result of the fatigue assessment coefficient, setting corresponding warning assessment thresholds for different warning levels, and generating corresponding warning information.

[0049] A further improvement of the technical solution of the present invention is that: the multiple warning levels correspond to the multiple warning assessment thresholds, wherein the warning assessment thresholds include an upper threshold and a lower threshold;

[0050] The multiple warning levels and the multiple warning assessment thresholds satisfy the following relationship:

[0051] Low risk warning level FEC <S1;

[0052] Medium risk warning level S1≤FEC <S2;

[0053] High risk warning level FEC>S2;

[0054] Among them, FEC is the fatigue assessment coefficient, S1 is the upper threshold corresponding to the low risk warning level and the lower threshold corresponding to the medium risk warning level, and S2 is the upper threshold corresponding to the medium risk warning level and the lower threshold corresponding to the high risk warning level.

[0055] A further improvement of the technical solution of the present invention is that in step 6, the process of formulating corresponding improvement measures is:

[0056] Step 601, based on the early warning information, formulate corresponding improvement measures for stress concentration areas and fatigue damage parts, including optimizing structural design, selecting high-performance materials, strengthening fatigue life prediction and monitoring, and improving manufacturing processes;

[0057] Step 602, according to the formulated improvement measures, the chassis frame is actually modified and optimized, and the finite element analysis is re-performed, and the improved results are compared with the previous analysis results to evaluate the expected effects of the improvement measures.

[0058] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0059] 1. The present invention provides a fatigue life analysis method for a chassis frame of a combine harvester. By combining finite element analysis with actual load spectrum, the fatigue life of each part can be accurately predicted, possible failure positions and fatigue life can be predicted in advance, and corresponding improvement measures can be taken in the design and manufacturing stages. At the same time, combined with the damage accumulation calculation under various working conditions and the analysis of the overall fatigue evaluation coefficient of the chassis frame, the reliability of the chassis frame can be grasped as a whole, providing quantitative protection for the safe operation of the combine harvester.

[0060] 2. The present invention provides a fatigue life analysis method for a chassis frame of a combine harvester. Through finite element analysis technology and a finite element model of the chassis frame, the stress distribution and fatigue damage of the chassis frame under various working conditions are accurately evaluated, which is beneficial to the optimization design of the frame structure to reduce stress concentration and fatigue damage, thereby improving the overall strength and durability of the chassis frame, which not only extends the service life of the combine harvester, but also reduces the economic losses caused by downtime due to malfunctions.

[0061] 3. The present invention provides a fatigue life analysis method for a chassis frame of a combine harvester. By analyzing the detailed stress and deformation data of the chassis frame under different working conditions, stress concentration problems and other problems at the connection between the front axle and the vehicle body can be discovered in time, so as to optimize them and improve the fatigue life of the corresponding parts. In addition, by analyzing the fatigue life under different load spectra, the overall layout of the chassis frame can be adjusted in time to make the support structure of the frame more reasonable and the load distribution more uniform.

[0062] 4. The present invention provides a fatigue life analysis method for a chassis frame of a combine harvester. By dynamically predicting the stress-strain data of the chassis frame during operation, an early warning message is issued when the fatigue life is about to reach a limit, reminding the operator to take timely measures for maintenance or replacement. This not only improves the safety and reliability of the chassis frame, but also avoids major accidents and economic losses caused by fatigue fracture. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0064] Figure 1 is a flow chart of the method of the present invention;

[0065] Figure 2 It is a flow chart of the analysis of the deformation position and stress distribution of the chassis frame of the present invention under different working conditions;

[0066] Figure 3 This is a flow chart for obtaining fatigue prediction results of the present invention;

[0067] Figure 4 The figure is a flow chart for obtaining the fatigue evaluation coefficient of the present invention. DETAILED DESCRIPTION

[0068] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution 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. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0069] Embodiment 1, as Figures 1 to 4 As shown, the present invention provides a method for analyzing the fatigue life of a chassis frame of a combine harvester, comprising the following steps:

[0070] Step 1, obtain load data, pre-process the load data, and compile a load spectrum; the process of compiling the load spectrum is: deploy sensors on the chassis frame of the combine harvester to collect real-time load data on the chassis frame, including the size and direction changes of static and dynamic loads, such as at the engine installation point, transmission system connection, working part suspension point and the part connected to the wheel, etc., install various sensors, including strain gauges, acceleration sensors, power sensors, etc., and synchronously record the operating parameters of the combine harvester, including driving speed, working gear, working depth and steering angle, and perform data cleaning, data smoothing and data analysis on the collected load data. According to standardization and data segmentation, outliers and erroneous data are removed, and the pre-processed load data is sorted and counted, the distribution characteristics and change trends of the load data are analyzed, and the load change range, mean, standard deviation and other statistical characteristic parameters are determined. For example, the maximum, minimum, average and force change frequency of the vertical force borne by the chassis frame in a complete operation cycle are counted, and the load spectrum is compiled. The load spectrum usually includes parameters such as load size, load direction, and load action time. The load spectrum can be further subdivided into time history load spectrum, rain flow counting load spectrum, extreme value load spectrum and other types. Select the appropriate load spectrum type according to actual needs;

[0071] Step 2, based on the pre-processed load data, build a chassis frame finite element model, carry out strength verification analysis on the front axle, rear axle and body of the chassis frame, analyze the deformation position and stress distribution of the chassis frame under different working conditions, and output a stress analysis report, including stress distribution diagram, deformation diagram, stress values ​​of key parts, etc.; the analysis process of the deformation position and stress distribution of the chassis frame under different working conditions is as follows: according to the actual design size and structural shape of the combine harvester chassis frame, use the geometric modeling function of the finite element analysis software, such as ANSYS, Abaqus, etc., to create the front axle, rear axle, The geometric model of the body parts should capture the detailed features of the structure, such as ribs, holes, welded joints, etc., and assign material properties to each component in the geometric model, such as density, elastic modulus, Poisson's ratio, etc. At the same time, the geometric model grid is divided into discrete units and nodes. According to the pre-processed load data, static loads and dynamic loads are applied to the geometric model, and boundary conditions are set; for example: Set fixed constraints: Apply fixed constraints to the support points of the chassis frame to simulate the support conditions under actual working conditions, specifically: fix the support points of the front and rear axles; Sliding constraints: Apply sliding constraints to certain parts beam, simulate the relative movement between components, perform static and dynamic analysis on the chassis frame in the finite element analysis software, calculate its stress value, deformation value, strain and displacement under static load, and evaluate the performance of the chassis frame under dynamic load, including modal analysis, transient response analysis or spectrum analysis, etc. According to the analysis results of static analysis, analyze the stress distribution of the chassis frame under different working conditions, identify the stress concentration area, and compare the calculated stress value with the allowable stress of the chassis frame material to determine the strength requirements of the chassis frame, and predict the high stress area and low stress area of ​​the chassis frame. Area, according to the analysis results of static analysis, analyze the deformation distribution of chassis frame under different working conditions, compare the calculated deformation value with the allowable deformation value of chassis frame, judge whether the deformation requirements are met, and predict the deformation position and deformation amount. If the deformation value exceeds the allowable value, structural optimization or material improvement is required. At the same time, write a stress analysis report, including the chassis frame's geometric model, material properties, mesh division, boundary conditions and load application and other detailed information. In the report, use charts, images and tables to intuitively display the analysis results, including stress cloud map, deformation map, stress-time curve, etc.;

[0072] Step 3, based on the stress analysis report and the chassis frame finite element model, extract the strain time history of the chassis frame danger point, obtain its stress time history according to the relationship between stress and strain, and predict the fatigue life of the chassis frame under constant amplitude load, random load and mixed load, and output the fatigue prediction result, which should include information such as the fatigue life of the chassis frame, fatigue failure location and fatigue damage degree; the process of obtaining the fatigue prediction result is as follows: according to the stress analysis report, determine the location of the chassis frame danger point, and extract the strain time history of the danger point in the finite element analysis software, based on the material properties of the geometric model The stress-strain relationship is analyzed, and the extracted strain-time history and strain relationship are used to calculate the stress-time history of the dangerous point and obtain the stress-time history index. According to the load types of constant amplitude load, random load and mixed load of the chassis frame and the working environment, the fatigue parameters of the chassis frame material properties are determined by using the geometric model, and the fatigue life analysis index is obtained in combination with the stress-time history to predict the fatigue life of the chassis frame. The fatigue life prediction results under constant amplitude load, random load and mixed load are compared, and the influence of different load types on the fatigue life of the chassis frame is analyzed, and the fatigue prediction results are output;

[0073] Step 4, predict and analyze the fatigue life of the chassis frame according to the stress analysis report and fatigue prediction results, calculate the fatigue evaluation coefficient, and evaluate the reliability of the fatigue life analysis of the chassis frame; the process of obtaining the fatigue evaluation coefficient is as follows: apply a load spectrum to the chassis frame, calculate the stress distribution of the frame through the chassis frame finite element model, and calculate the fatigue life of each part of the chassis frame respectively; based on the fatigue life of each part of the chassis frame, analyze the fatigue damage of each part and accumulate it to obtain the overall fatigue life of the chassis frame; based on the fatigue damage of each part of the chassis frame, analyze the correlation between the overall fatigue life and the fatigue damage of each part; at the same time, calculate the fatigue evaluation coefficient in combination with the load spectrum; based on the obtained fatigue evaluation coefficient, quantify the performance of the chassis frame under fatigue load, evaluate the fatigue life reliability of the chassis frame, and the influence of uncertainty on the fatigue life prediction result of the chassis frame;

[0074] Step 5: predict the existing problems of the chassis frame, such as stress concentration, fatigue cracks, etc., based on the results of fatigue life analysis and reliability evaluation, and determine the warning level of the current chassis frame fatigue situation, and generate corresponding warning information according to the corresponding warning level; the process of warning information is: based on the fatigue evaluation coefficient, identify the parts of the chassis frame with low fatigue life reliability, and compare the fatigue life under different working conditions, and determine the high stress and high strain areas of the chassis frame in combination with the results of reliability evaluation, predict the existing problems of the chassis frame, including fatigue damage accumulation, insufficient structural strength, material performance degradation and failure of connectors, set different warning levels according to the fatigue life and reliability evaluation results of the chassis frame, which are low risk warning level, medium risk warning level and high risk warning level, match the determined different warning levels with the results of fatigue evaluation coefficient, set corresponding warning evaluation thresholds for different warning levels, and generate corresponding warning information;

[0075] Step 6, based on the early warning information, formulate corresponding improvement measures, such as adjusting the structural design, replacing materials or improving the manufacturing process, so as to improve the fatigue life of the chassis frame and the reliability of the whole machine; the process of formulating corresponding improvement measures is: based on the early warning information, formulate corresponding improvement measures for stress concentration areas and fatigue damage parts, including optimizing the structural design, selecting high-performance materials, strengthening fatigue life prediction and monitoring, and improving the manufacturing process, wherein, optimizing the structural design includes: optimizing the structural design for parts or components with low fatigue life reliability, improving the strength and rigidity of the structure, adopting a more reasonable connection method, and improving the reliability and durability of the connectors, and selecting high-performance materials includes: selecting materials with higher fatigue strength, corrosion resistance and wear resistance to replace existing materials, Strict performance testing and screening of materials are carried out to ensure that material properties meet design requirements. Strengthening fatigue life prediction and monitoring includes: adopting advanced fatigue life prediction methods and technologies to make more accurate fatigue life predictions for chassis frames, installing sensors at key locations of chassis frames to monitor stress, strain and other parameters in real time, promptly identifying potential problems and taking measures to repair or replace them, and improving manufacturing processes including: optimizing manufacturing process flow, improving manufacturing accuracy and quality control levels, strictly controlling key processes in the manufacturing process to ensure that product quality meets design requirements, and making actual modifications and optimizations to chassis frames based on the formulated improvement measures, and re-performing finite element analysis. Comparing the improved results with the previous analysis results to evaluate the expected effects of the improvement measures.

[0076] Embodiment 2, as Figures 1 to 4 As shown, based on Example 1, the present invention provides a technical solution: Preferably, the calculation formula of the stress time history index is:

[0077]

[0078] Where STH is the stress time history index, σ max,i is the maximum stress in the i-th stress cycle, σ min,i is the minimum stress in the ith stress cycle, σ f is the fatigue strength of the material, that is, the stress amplitude that causes material failure under infinite cycles, t i is the duration of the ith stress cycle, f i is the frequency of the ith stress cycle, α, β and γ are exponential parameters related to material properties and stress time history, and n is the total number of stress cycles;

[0079] The calculation formula of stress time history is:

[0080]

[0081] Where σ(t) is the stress at time t, E is the elastic modulus of the material, ε(t) is the strain at time t, a, b, c are coefficients related to the nonlinear behavior of the material, d is the coefficient related to the strain history effect, ω is the angular frequency of the strain history effect function, is the phase angle of the strain history influence function, τ is the integral variable, representing time;

[0082] The calculation formula of fatigue life analysis index is:

[0083]

[0084] Among them, N f is the fatigue life analysis index, D is the cumulative damage value, C,m,j is the fatigue parameter of the material, σ(t) is the stress at time t, σ a is the stress amplitude, i.e., the fluctuation of stress relative to its mean value, σ mean is the average value of stress, T is a complete load cycle; the calculation formula of fatigue evaluation coefficient is:

[0085]

[0086] Where FEC is the fatigue evaluation coefficient, δ max,i is the maximum stress value at the mth position, δ basei is the reference stress value, δ f,o is the fatigue strength of the oth part, that is, the stress level when the expected life of the component reaches a certain value under this stress, p is the power exponent of stress influence, which is used to adjust the contribution of stress to fatigue damage, f(μ o ) is the time history function, considering the influence of stress change over time on fatigue damage, μ o is the stress-time history of the oth position, g(Lo ) is the life influence function, considering the contribution of component life to fatigue damage, L o is the fatigue life of the oth part, that is, the number of cycles or time required for the component to reach fatigue failure under a given stress, and m is the number of parts considered in the chassis frame;

[0087] Multiple warning levels correspond to multiple warning assessment thresholds, where the warning assessment thresholds include an upper threshold and a lower threshold;

[0088] Multiple warning levels and multiple warning assessment thresholds satisfy the following relationship:

[0089] Low risk warning level FEC <S1;

[0090] Medium risk warning level S1≤FEC <S2;

[0091] High risk warning level FEC>S2;

[0092] Among them, FEC is the fatigue assessment coefficient, S1 is the upper threshold corresponding to the low risk warning level and the lower threshold corresponding to the medium risk warning level, and S2 is the upper threshold corresponding to the medium risk warning level and the lower threshold corresponding to the high risk warning level.

[0093] The above are only specific implementations of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for analyzing fatigue life of a chassis frame of a combine harvester, characterized in that: The following steps are involved: Step 1, obtaining load data, preprocessing the load data, and compiling a load spectrum; Step 2: Based on the pre-processed load data, a finite element model of the chassis frame is constructed, and strength verification analysis is performed on the front axle, rear axle, and body of the chassis frame. The deformation position and stress distribution of the chassis frame under different working conditions are analyzed, and a stress analysis report is output; Step 3: Based on the stress analysis report and the chassis frame finite element model, extract the strain time history of the chassis frame danger point, obtain its stress time history according to the relationship between stress and strain, and predict the fatigue life of the chassis frame under constant amplitude load, random load and mixed load, and output the fatigue prediction result; Step 4: According to the stress analysis report and fatigue prediction results, the fatigue life of the chassis frame is predicted and analyzed, and the fatigue evaluation coefficient is calculated, and the reliability evaluation of the fatigue life analysis of the chassis frame is performed. The process of obtaining the fatigue evaluation coefficient is as follows: Step 401, applying a load spectrum to the chassis frame, calculating the stress distribution of the frame through a finite element model of the chassis frame, and calculating the fatigue life of each part of the chassis frame respectively; Step 402, based on the fatigue life of each part of the chassis frame, analyzing and accumulating the fatigue damage of each part to obtain the overall fatigue life of the chassis frame; Step 403, based on the fatigue damage of each part of the chassis frame, the correlation between the overall fatigue life and the fatigue damage of each part is analyzed, and the fatigue assessment coefficient is calculated in combination with the load spectrum; Step 404, based on the obtained fatigue evaluation coefficient, quantify the performance of the chassis frame under fatigue load and evaluate the fatigue life reliability of the chassis frame; The calculation formula of the fatigue evaluation coefficient is: Where FEC is the fatigue evaluation coefficient, δ max,i is the maximum stress value at the mth position, δ basei is the reference stress value, δ f,o is the fatigue strength of the oth position, p is the power index of stress influence, f(μ o ) is the time history function, μ o is the stress-time history of the oth position, g(L o ) is the lifespan influence function, L o is the fatigue life of the oth part, m is the number of parts considered in the chassis frame; Step 5: predict the existing problems of the chassis frame according to the results of fatigue life analysis and reliability evaluation, determine the warning level of the current chassis frame fatigue situation, and generate corresponding warning information according to the corresponding warning level; Step 6: Develop corresponding improvement measures based on the early warning information.

2. A combine harvester chassis frame fatigue life analysis method according to claim 1, characterized in that: In step 1, the process of compiling the load spectrum is as follows: Step 101, deploying sensors on the chassis frame of the combine harvester to collect load data borne by the chassis frame in real time, including the size and direction changes of static load and dynamic load; Step 102, synchronously recording the operating parameters of the combine harvester, including driving speed, operating gear, operating depth and steering angle; Step 103, performing data cleaning, data smoothing, data standardization and data segmentation on the collected load data to remove abnormal values ​​and erroneous data; Step 104 , sorting and counting the pre-processed load data, analyzing the distribution characteristics and change trends of the load data, and compiling a load spectrum.

3. A combine harvester chassis frame fatigue life analysis method according to claim 2, characterized in that: In step 2, the analysis process of the deformation position and stress distribution of the chassis frame under different working conditions is as follows: Step 201, according to the actual design size and structural shape of the chassis frame of the combine harvester, use the geometric modeling function of the finite element analysis software to create a geometric model of the front axle, rear axle, and body parts of the chassis frame, assign material properties to each component in the geometric model, and divide the geometric model mesh into discrete units and nodes; Step 202, applying static loads and dynamic loads to the geometric model according to the preprocessed load data, and setting boundary conditions; Step 203, in finite element analysis software, static analysis and dynamic analysis are performed on the chassis frame to calculate the stress value, deformation value, strain and displacement under the static load, and to evaluate the performance of the chassis frame under the dynamic load; Step 204, analyzing the stress distribution of the chassis frame under different working conditions according to the analysis results of the static analysis, identifying the stress concentration area, and comparing the calculated stress value with the allowable stress of the chassis frame material to determine the strength requirement of the chassis frame, and predicting the high stress area and low stress area of ​​the chassis frame; Step 205, based on the analysis results of the static analysis, analyze the deformation distribution of the chassis frame under different working conditions, compare the calculated deformation value with the allowable deformation value of the chassis frame, determine whether the deformation requirements are met, predict the deformation position and deformation amount, and write a stress analysis report.

4. A combine harvester chassis frame fatigue life analysis method according to claim 3, characterized in that: In step 3, the process of obtaining the fatigue prediction result is as follows: Step 301, determining the position of the dangerous point of the chassis frame according to the stress analysis report, and extracting the strain time history of the dangerous point in the finite element analysis software; Step 302, based on the material properties of the geometric model, analyzing the stress-strain relationship, and using the extracted strain-time history and strain relationship, calculating the stress-time history of the dangerous point, and obtaining the stress-time history index; Step 303, according to the load types of constant amplitude load, random load and mixed load of the chassis frame and the working environment, the fatigue parameters of the material properties of the chassis frame are determined by using the geometric model, and the fatigue life analysis index is obtained in combination with the stress time history to predict the fatigue life of the chassis frame; Step 304 , compare the fatigue life prediction results under constant amplitude load, random load and mixed load, analyze the influence of different load types on the fatigue life of the chassis frame, and output the fatigue prediction results.

5. A combine harvester chassis frame fatigue life analysis method according to claim 4, characterized in that: The calculation formula of the stress time history index is: Where STH is the stress time history index, σ max,i is the maximum stress in the i-th stress cycle, σ min,i is the minimum stress in the ith stress cycle, σ f is the fatigue strength of the material, t i is the duration of the ith stress cycle, f i is the frequency of the ith stress cycle, α, β and γ are exponential parameters related to material properties and stress time history, and n is the total number of stress cycles; The calculation formula of fatigue life analysis index is: Among them, N f is the fatigue life analysis index, D is the cumulative damage value, C,m,j is the fatigue parameter of the material, σ(t) is the stress at time t, σ a is the stress amplitude, σ mean is the average value of stress, and T is a complete load cycle.

6. A combine harvester chassis frame fatigue life analysis method according to claim 5, characterized in that: In step 5, the process of early warning information is: Step 501, based on the fatigue evaluation coefficient, identifying the parts of the chassis frame with low fatigue life reliability, and comparing the fatigue life under different working conditions; Step 502, combining the reliability evaluation results, determining high stress and high strain areas of the chassis frame, and predicting problems existing in the chassis frame, including fatigue damage accumulation, insufficient structural strength, material performance degradation, and connector failure; Step 503, according to the fatigue life and reliability evaluation results of the chassis frame, different warning levels are set, namely, a low risk warning level, a medium risk warning level, and a high risk warning level; Step 504, matching the determined different warning levels with the result of the fatigue assessment coefficient, setting corresponding warning assessment thresholds for different warning levels, and generating corresponding warning information.

7. A combine harvester chassis frame fatigue life analysis method according to claim 6, characterized in that: A plurality of the warning levels correspond to a plurality of the warning assessment thresholds, wherein the warning assessment thresholds include an upper threshold and a lower threshold; The multiple warning levels and the multiple warning assessment thresholds satisfy the following relationship: Low risk warning level FEC <S1; Medium risk warning level S1≤FEC <S2; High risk warning level FEC>S2; Among them, FEC is the fatigue assessment coefficient, S1 is the upper threshold corresponding to the low risk warning level and the lower threshold corresponding to the medium risk warning level, and S2 is the upper threshold corresponding to the medium risk warning level and the lower threshold corresponding to the high risk warning level.

8. A combine harvester chassis frame fatigue life analysis method according to claim 7, characterized in that: In step 6, the process of formulating corresponding improvement measures is as follows: Step 601, based on the early warning information, formulate corresponding improvement measures for stress concentration areas and fatigue damage parts, including optimizing structural design, selecting high-performance materials, strengthening fatigue life prediction and monitoring, and improving manufacturing processes; Step 602, according to the formulated improvement measures, the chassis frame is actually modified and optimized, and the finite element analysis is re-performed, and the improved results are compared with the previous analysis results to evaluate the expected effects of the improvement measures.

Images