CN108052753B

CN108052753B - Basic brake device mitigation performance optimization method based on DOE and MBD

Info

Publication number: CN108052753B
Application number: CN201711384491.4A
Authority: CN
Inventors: 孙可心; 曲宝章; 韩朝建; 卢碧红
Original assignee: Dalian Jiaotong University
Current assignee: Dalian Jiaotong University
Priority date: 2017-12-20
Filing date: 2017-12-20
Publication date: 2021-05-07
Anticipated expiration: 2037-12-20
Also published as: CN108052753A

Abstract

The invention discloses a basic brake device alleviation performance optimization method based on DOE and MBD, which comprises the following steps of: s1, determining controllable factors of a performance optimization DOE test: s2, designing a performance optimization DOE test scheme. S3, MBD implementation of the performance optimization DOE test scheme. S4, and analyzing the response of the performance optimization DOE test. And S5, selecting optimal schemes of the DOE test for optimizing the performance. And obtaining the optimal combination scheme with the minimum relieving force and the maximum signal-to-noise ratio in the scheme. The basic brake device alleviation performance optimization method based on DOE and MBD considers the contact collision between objects, accurately describes the influence of clearance factors on the basic brake device of the bogie, provides important reference for designers through the optimal rod piece size provided by the method, is an effective method for researching the alleviation performance of the truck, and obtains the optimal clearance configuration scheme of the hinge and the rod piece by taking the minimum alleviation force as a test index, thereby achieving the purpose of optimizing the alleviation performance of the basic brake device.

Description

Basic brake device mitigation performance optimization method based on DOE and MBD

Technical Field

The invention relates to the field of truck braking, in particular to a basic braking device alleviation performance optimization method based on DOE and MBD.

Background

The bogie base brake device is an actuating mechanism for implementing deceleration and stop of a train and is a necessary device for ensuring safe operation of the train.

With the increase of the load and the traction tonnage of the vehicle, higher requirements are placed on the performance of a basic braking device, the requirements are stable and reliable during braking, and safety and high efficiency are achieved during relieving; the reliability of the performance of the braking system directly affects the safety of train operation.

Therefore, the performance analysis of the basic brake device is particularly necessary, and measures for improving the performance of the brake device are firstly adopted for adopting a new brake technology and secondly for improving and optimizing the structure of the existing brake device.

At present, the problems of uneven wheel tread abrasion, abrasion of brake rods, poor brake beam alleviation and the like in the application field are serious, and the problems are not solved after a mature brake technology is adopted.

The research and analysis show that the problems occurring in the application field are related to the stress condition of the components of the basic braking device, and the components are easy to generate stiffness and clamping stagnation during the braking transmission process, so that the movement is not flexible. Based on the analysis thought, a feasible engineering solution needs to be made for improving and optimizing the performance of the bogie foundation braking device.

Disclosure of Invention

According to the technical problems provided by the above, a basic brake device mitigation performance optimization method based on DOE and MBD is provided, which is used for solving the defects that components of the existing basic brake device are stressed, and other forces and clamping stagnation are easy to occur among the components in the brake transmission process, so that the movement is inflexible. The technical means adopted by the invention are as follows:

a basic brake device mitigation performance optimization method based on DOE and MBD comprises the following steps:

s1, determining controllable factors of a performance optimization DOE test:

the shaft diameter of the pin shaft, the thickness of the traveling lever, the width of a middle pull rod clamping plate and the width of a brake beam upright column groove are used as controllable factors of the DOE test.

S2, designing a performance optimization DOE test scheme.

S3, MBD implementation of the performance optimization DOE test scheme.

S4, and analyzing the response of the performance optimization DOE test.

And S5, selecting optimal schemes of the DOE test for optimizing the performance.

And obtaining the optimal combination scheme with the minimum relieving acting force and the maximum signal-to-noise ratio in the scheme.

In the preferred step S1, the specific determination steps of the controllable factors of the performance optimization DOE test are as follows:

s11, the clearance combination result of each joint of the braking device has great influence on the release performance, and therefore, the size of each braking connecting piece is the factor influencing the release performance.

S12, the stress condition of the connecting pin shaft reflects whether the mechanism is blocked or not and the severity of the mechanism, and the size of the pin shaft with abnormal stress is a key factor influencing the relieving performance.

S13, determining the shaft diameter of the pin shaft, the thickness of the traveling lever, the width of the middle pull rod clamp plate and the width of the brake beam upright post groove as controllable factors of the DOE test.

Preferably, in step S12, the pin axis with abnormal stress is determined by the following steps:

s121, determining identification indexes of key influence factors:

for the basic braking device, all connecting pin shafts are numbered in sequence for analysis, and a stress model at the pin shaft connecting part is simplified into a combination form of three components, namely a lever, a clamping plate and a pin shaft.

And (3) taking the pin shaft as a research object to independently perform stress statistical analysis, wherein the section I and the section III are action areas of two side columns of the clamping plate facing the pin shaft, and the section II is an action area of the middle lever facing the pin shaft, so that the index for identifying key influence factors is as follows.

a. The three sections of the pin shaft are unbalanced in stress:

criterion A: i F_X(I)+F_X(II)+F_X(III)|≥ε_F

Criterion B: i F_Y(I)+F_Y(II)+F_Y(III)|≥ε_F

Wherein: f_X(I)、F_X(II)、F_X(III) the stress of the pin shafts at the sections I, II and III is expressed in the unit of N;

ε_Fthe maximum tolerance error of the stress is expressed in the unit of N,

and when the known experimental data meet the criterion A or the criterion B, judging that the three-section force stress imbalance phenomenon of the pin shaft occurs.

b. The forces are balanced but not reasonably distributed:

criterion C:

or

Criterion D:

or

Wherein: k is the stress multiple difference coefficient with the unit of 1,

and when the known experimental data meet the criterion C or the criterion D, judging that the three-section force stress of the pin shaft is balanced but distributed unreasonably.

S122, identifying key influence factors by combining known experimental data:

and judging whether the stress of the pin shaft is balanced or not according to the identification indexes for determining the key influence factors and the measured experimental data, and judging whether the stress of the pin shaft is reasonable or not if the stress is balanced.

The shaft diameter of the pin shaft, the thickness of the traveling lever, the width of the middle pull rod clamping plate and the width of the brake beam upright post groove which have influences on the clamping stagnation of the mechanism are determined.

In the preferred step S2, the specific scheme of the DOE test for performance optimization is designed as follows:

s21, DOE test encoding of controllable factors:

setting the thickness controllable factor code of the traveling lever as alpha; the width controllable factor code of the middle pull rod end clamping plate is beta; the width controllable factor of the brake beam strut groove is encoded as gamma; the shaft diameter controllable factor of the hinge pin shaft of the traveling lever and the middle pull rod is coded into theta; the shaft diameter controllable factor code of the hinge pin shaft of the traveling lever and the brake beam upright post is mu; the fixed lever and the brake beam column hinge pin shaft diameter controllable factor is encoded into rho; the controllable factor of the shaft diameter of the hinge pin shaft of the fixed lever and the middle pull rod is coded as tau.

S22, setting the DOE test controllable factors horizontally:

the encoding in step S21 selects two horizontal settings.

S23, selection of a DOE orthogonal test scheme table:

when the table is selected, the table is selected from the L tables of two levels, three levels or four levels according to the level number of each factor, and then the L table is determined according to the factors and the experimental requirements.

S24, response of DOE test:

the test response is an evaluation index of the optimized object, the optimized object is the relieving performance of the basic braking device, and therefore the response of the DOE test is the relieving acting force.

S25, quality characteristics of DOE test:

the quality characteristic is the desired small characteristic signal-to-noise ratio.

As a preferred step S3, the MBD implementation of the DOE test protocol for performance optimization specifically includes the following steps:

s31, establishing a geometric model of the basic braking device:

and modeling a basic brake device in the CAD software to ensure correct assembly, and storing a coupler basic brake device model in the CAD software as a file in a STEP format.

S32, importing the geometric model into MBD simulation software:

the STEP-formatted file in STEP S31 is imported into MBD simulation software, and is appropriately simplified and merged.

S33, establishing a physical model of the basic brake device:

the establishment of the physical model comprises rigid body modeling, constraint modeling, contact modeling, external load modeling and parametric modeling, and the parametric modeling is accompanied with each modeling process.

S34, MBD implementation of DOE test protocol:

applying a reverse relieving acting force on the upper end of the traveling lever, wherein the expression of a driving function is as follows: STEP (time, 0, 0, 1, -158) for extracting an F-t curve between a brake shoe and a wheel tread; when 4 brake shoes are completely separated from the wheel, namely the brake shoes and the wheelWhen the contact force between the two parts is 0, the minimum relieving acting force F required to be applied by each scheme is correspondingly output_kThis mitigation effort is the response output of this test.

In a preferred step S4, the DOE test response analysis for performance optimization includes the following specific analysis processes:

analyzing the problem of poor releasing of the basic braking device, overcoming various frictional resistances of the mechanism by using an equivalent releasing acting force, wherein the smaller the releasing acting force is, the better the releasing acting force is, and the quality characteristic of the test index belongs to the small characteristic;

the signal-to-noise ratio calculation formula is as follows:

where eta is the signal-to-noise ratio, y_iN is the test frequency; the larger the signal-to-noise ratio value of the small characteristic is expected to be, the stronger the anti-interference capability is, and the better the stability is.

Compared with the prior art, the basic brake device mitigation performance optimization method based on the DOE and the MBD has the following advantages:

1. the basic brake device alleviation performance optimization method based on DOE and MBD is low in investment cost, high in simulation precision and high in practical value.

2. The basic brake device alleviation performance optimization method based on DOE and MBD simulates the working condition of braking and alleviation of the basic brake device.

3. The basic brake device alleviation performance optimization method based on DOE and MBD can know the working principle of the basic brake device by watching simulation files.

4. According to the basic brake device alleviation performance optimization method based on DOE and MBD, the alleviation acting force is reduced by optimizing the rod piece size.

5. The basic brake device mitigation performance optimization method based on DOE and MBD provides certain guiding significance for the transformation and upgrading of the existing bogie brake device.

The invention relates to a basic brake device alleviation performance optimization method based on DOE and MBD, which considers the contact collision between objects, accurately describes the influence of clearance factors on a basic brake device of a bogie, provides important reference for designers through the optimal rod piece size provided by the method, is an effective method for researching the alleviation performance of a truck, takes the minimum alleviation acting force as a test index, converts the connection pair configuration clearance of the basic brake device into the design parameters of components as influence factors, analyzes the signal-to-noise ratio and contribution degree of each controllable factor according to the test result, and obtains the optimal clearance configuration scheme of a hinge and a rod piece, thereby achieving the purpose of optimizing the alleviation performance of the basic brake device.

According to the basic brake device alleviation performance optimization method based on DOE and MBD, the actual running state of the truck basic brake device is simulated in a multi-body dynamics software platform, and the dynamics parameters of the basic brake device under different working conditions are solved.

Drawings

The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.

FIG. 1 is a schematic view of the numbering of the connecting pins of the basic braking device of the present invention.

Fig. 2 is a schematic diagram of a three-section contact area of the pin shaft of the present invention.

FIG. 3 is a schematic diagram of a model of a foundation brake assembly in CAD software according to the present invention.

FIG. 4 is a graph of the mean main effect of the present invention.

Fig. 5 is a graph of the signal-to-noise ratio primary effect of the present invention.

Wherein: a. the brake comprises a traveling lever, a high friction composite brake shoe, a fixed lever fulcrum seat, a middle pull rod, a rear brake beam, a front brake beam, a flexible fulcrum and a chain shoe ring, and a fixed lever.

Detailed Description

As shown in fig. 1 to 5, a basic brake device mitigation performance optimization method based on DOE and MBD includes the following steps:

s1, determining controllable factors of a performance optimization DOE test:

the shaft diameter of the pin shaft, the thickness of the traveling lever, the width of a middle pull rod clamp plate and the width of a brake beam upright column groove are used as controllable factors of the DOE test; in step S1, the specific determination steps of the performance optimization DOE test controllable factors are as follows:

S12, reflecting whether the mechanism is blocked or not and the severity of the mechanism according to the stress condition of the connecting pin shaft, wherein the size of the pin shaft which is abnormally stressed is a key factor influencing the relieving performance; in step S12, the concrete determination steps of the pin shaft with abnormal stress are as follows:

s121, determining identification indexes of key influence factors:

for the foundation brake, the connecting pins are numbered in sequence for analysis, the numbering being shown in fig. 1.

The stress model at the pin joint is simplified into a combination form of three components, namely a lever, a clamping plate and a pin; the pin shaft is taken as a research object to carry out stress statistical analysis independently, the section I and the section III are action areas of two side columns of the clamping plate facing the pin shaft, and the section II is an action area of the middle lever facing the pin shaft, as shown in figure 2.

The index identifying the key influencing factor is:

a. the three sections of the pin shaft are unbalanced in stress:

criterion A: i F_X(I)+F_X(II)+F_X(III)|≥ε_F

Criterion B: i F_Y(I)+F_Y(II)+F_Y(III)|≥ε_F

Wherein: f_X(I)、F_X(II)、F_X(III) the stress of the pin shafts at the sections I, II and III is expressed in the unit of N; epsilon_FFor the maximum tolerance of the stress, the unit is N, the concrete numerical value is properly selected by engineering technicians in combination with the actual engineering, and the embodiment sets epsilon_F＝10N。

b. The forces are balanced but not reasonably distributed:

criterion C:

or

Criterion D:

or

Wherein: k is the stress multiplication coefficient, the unit is 1, the specific numerical value is properly selected by engineering technicians in combination with the actual engineering, and k is set to be 1.5 in the embodiment.

S122, identifying key influence factors by combining known experimental data:

according to the identification indexes of the determined key influence factors, whether the stress of the pin shaft is balanced or not is judged through the measured experimental data, and if the stress is balanced, whether the stress of the pin shaft is reasonable or not is judged; the shaft diameter of the pin shaft, the thickness of the traveling lever, the width of the middle pull rod clamping plate and the width of the brake beam upright post groove which have influences on the clamping stagnation of the mechanism are determined.

Taking the known experimental data in table 1 as an example for analysis: (I) - (III) two component forces F of each pin shaft_X、F_YThe three sections of the pin shaft are in stress balance; component force F at pin shaft_X(I)≥1.5F_X(III) force component F at pin shaft_Y(III)≥1.5F_Y(I) The stress of the pin shaft meets the criterion C or the criterion D, namely the stress is balanced but distributed unreasonably; the stress of the pin shafts is balanced, and the influence on the clamping stagnation of the mechanism is small.

Combining the above analysis of the known experimental data in table 1, the key factors affecting the alleviation are the following seven: the shaft diameter of the pin shaft, the thickness of the traveling lever, the width of a middle pull rod clamping plate and the width of a brake beam upright post groove.

TABLE 1 pressure (unit: N) of different sections of the pin shaft in the relaxed state of the braking device

S13, determining the shaft diameter of the pin shaft, the thickness of the traveling lever, the width of a middle pull rod clamp plate and the width of a brake beam upright column groove as controllable factors of the DOE test;

specifically, the seven key factors in curve step S12 influence the mitigation as controllable factors for the DOE test.

S2, designing a performance optimization (DOE) test scheme;

in step S2, the specific scheme design of the DOE test for performance optimization is as follows:

s21, DOE test encoding of controllable factors:

S22, setting the DOE test controllable factors horizontally:

selecting two horizontal settings for the encoding in step S21;

the levels of the controllable factors need to be combined with the actual setting of engineering, the number of tests is increased due to excessive levels, the time cost is high, the test results obtained due to insufficient levels are wide, and the practical guiding significance is lacked. In this example, two representative levels are selected for the seven controllable factors. The controllable factor level configuration is shown in table 2.

TABLE 2 controllable factors and level configuration table

Controllable factor/mm	Horizontal	1/mm	Horizontal	2/mm
					α	α₁	α₂
β	β₁	β₂
			γ	γ₁	γ₂
θ	θ₁	θ₂
			μ	μ₁	μ₂
ρ	ρ₁	ρ₂
			τ	τ₁	τ₂

In this example α₁、α₂23, 26; beta is a₁、β ₂29, 31; gamma ray₁、γ₂28, 32; theta₁、μ₁、ρ₁、τ₁Is 35.63; theta₂、μ₂、ρ₂、τ₂Is 35.88.

S23, selection of a DOE orthogonal test scheme table:

selecting the L table from the L tables of two levels, three levels or four levels according to the level number of each factor when selecting the L table, and then determining the L table according to the factors and the experimental requirements;

when the experiment precision requirement is high, the factors are multiple, and the interaction is multiple, a large L table is selected, otherwise a small L table is selected.

This embodiment selects L8 (2)⁷) The orthogonal test protocol is shown in table 3.

TABLE 3L 8 (2)⁷) Orthogonal test table

S24, response of DOE test:

S25, quality characteristics of DOE test:

S3, MBD realization of a DOE test scheme for performance optimization;

in step S3, the MBD implementation of the DOE test scheme for performance optimization specifically includes the following steps:

s31, establishing a geometric model of the basic braking device:

and modeling a basic brake device in the CAD software to ensure correct assembly, and storing a coupler basic brake device model in the CAD software as a file in a STEP format as shown in figure 3.

S32, importing the geometric model into MBD simulation software:

S33, establishing a physical model of the basic brake device:

S34, MBD implementation of DOE test protocol:

applying a reverse relieving acting force on the upper end of the traveling lever, wherein the expression of a driving function is as follows: STEP (time, 0, 0, 1, -158) for extracting an F-t curve between a brake shoe and a wheel tread; when 4 brake shoes are completely separated from the wheel, namely the contact force between the brake shoes and the wheel is 0, the minimum relieving force F required to be applied corresponding to each output scheme_kThis mitigation effort is the response output of this test.

S4, response analysis of a performance optimization DOE test;

in step S4, the performance optimization DOE test response analysis includes the following specific analysis processes:

the signal-to-noise ratio calculation formula is as follows:

where eta is the signal-to-noise ratio, y_iN is the test frequency; the larger the signal-to-noise ratio of the small characteristic is expected to be, the stronger the anti-interference capability is, and the better the stability is; the test indexes are more visual and convenient to examine by using the signal to noise ratio. Watch (A)And 4, test responses corresponding to the DOE orthogonal test schemes of the groups are shown.

TABLE 4 test response of DOE orthogonal test protocol

Test number	Relieving the acting force F_K(N)	Signal-to-noise ratio (dB)
			1	104.8	-40.40
2	92.3	-39.30
			3	105.8	-40.49
4	83.4	-38.42
			5	130.3	-42.30
6	121.5	-41.69
			7	125.6	-41.98
8	107.3	-40.61

As can be seen from Table 4, the optimization of the parameters determined by the maximum SNR rule is test 4 (. alpha.) (₁β₂γ₂θ₂μ₂ρ₁τ₁). In order to further optimize parameters, the method carries out visual analysis of main effects and analysis of mean values and signal-to-noise ratio main effects on test results based on an orthogonal table 3.

S41, analyzing the main effect;

according to the comprehensive comparability of the orthogonal test orthogonal table, the test conditions of different level combinations of factors are considered to be the same, so that the comparative analysis can be intuitively carried out.

The experimental indexes are subjected to visual range analysis by using a Tiankou design tool in Minitab software, and visual analysis results of orthogonal test influence factors are obtained after arrangement and are shown in a table 5.

The main effect analysis is performed on each factor, and a mean main effect graph of the resistance response of the alleviation can be obtained, as shown in fig. 4.

TABLE 5 visual analysis table of influence factors (Unit: N)

Note: k is the difference between R and k_max-k_min，K₁、K₂Respectively representing the sum of corresponding responses in the test in which the 1 st and 2 nd levels of each factor are located; k is a radical of₁、k₂The average values are respectively corresponding to 4 numbers of each level; tau is an insignificant factor and can be taken between two levels as appropriate.

S42, analyzing signal-to-noise ratio;

the signal-to-noise ratio may reflect the robustness of the product quality. The larger the signal-to-noise ratio value is, the more stable the quality index is. Similarly, the signal-to-noise ratio analysis of the desired small characteristics was performed using the Minitab design tool, and the results shown in fig. 5 were obtained.

Available in step S2; the thickness alpha of the traveling lever contributes most to the relieving performance, and the shaft diameter rho of the pin shaft phi follows, and the influence of other factors is relatively insignificant.

The predicted value of the alleviation acting force of each test is used as a response, Minitab software is used for carrying out field analysis, and the influence sequence of different levels of each factor on the response is obtained, as shown in table 6.

The following can be obtained: the thickness of the floating lever has the greatest contribution to the relieving performance and is arranged at the head; the influence of the shaft diameter of the pin shaft (IV) on the action relieving effect is very slight and is an extremely insignificant factor. Through analysis of the signal-to-noise ratio, the significant factors influencing the relieving performance are determined to be the thickness alpha of the swimming lever and the shaft diameter rho of the first pin shaft.

TABLE 6 SNR responser table (Unit: dB)

S5, selecting optimal schemes of the DOE test for optimizing performance;

obtaining an optimal combination scheme with minimum relieving acting force and maximum signal-to-noise ratio in the scheme;

the optimal combination of fig. 4 and fig. 5 can minimize the mitigation force and maximize the signal-to-noise ratio in the scheme.

And selecting a horizontal value corresponding to each factor when the signal to noise ratio is large by combining the table 6, wherein the shaft diameter tau of the pin shaft (IV) is an insensitive factor and can be selected according to the economical efficiency of variables. Finally, the optimal scheme combination of the experimental design is alpha₁β₂γ₁θ₂μ₂ρ₁τ. The values of the optimum levels of the respective factors are shown in table 7.

TABLE 7 optimal solution factors and horizon

S6, verifying the optimal scheme of the performance optimization DOE test;

and verifying the rationality of the optimization scheme determined by the table 7, namely, the release performance is better, setting parameters according to the factor level obtained by the above analysis of the sensitivity of the Taguchi region, changing the size of the component, reestablishing a multi-body dynamics model, and carrying out a simulation experiment of the release performance.

Is derived at alpha₁β₂γ₁θ₂μ₂ρ₁Under the tau combination scheme, the minimum relieving acting force required by the basic braking device for complete relieving is 75.4N, compared with the relieving acting force 85N of the component in the original scheme, the minimum relieving acting force is reduced by 11.3%, and the signal-to-noise level is improved by 1.04dB, so that the rationality of the DOE optimal scheme is proved.

The basic brake device alleviation performance optimization method based on DOE and MBD provided by the invention is characterized in that a multi-body dynamics theory and technology are applied, and orthogonal experimental Design (DOE) and MBD (RecurDyn multi-body dynamics) theoretical technology are combined to simulate the basic brake device of the railway wagon in a multi-body dynamics simulation platform, so that the alleviation performance of the basic brake device of the railway wagon is optimized.

And designing an orthogonal test scheme by using DOE software according to the level of key factors of the actual configuration of the engineering.

And obtaining the signal-to-noise ratio and the contribution degree of each controllable factor through orthogonal test data analysis, and further selecting the optimal parameter level combination, wherein the size of the corresponding rod piece is the optimal gap configuration of the hinge.

According to the invention, the release performance optimization of the basic brake device of the railway wagon is realized through the MBD simulation technology and the DOE experimental design, and the method has the characteristics of low investment cost, high simulation precision, high research and development efficiency, strong practical value and the like. The invention provides important basis for optimizing the size parameters of the basic brake device components of the railway wagon.

The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.

Claims

1. A basic brake device mitigation performance optimization method based on DOE and MBD is characterized by comprising the following steps:

s1, determining controllable factors of a performance optimization DOE test:

the shaft diameter of the pin shaft, the thickness of the traveling lever, the width of a middle pull rod clamp plate and the width of a brake beam upright column groove are used as controllable factors of the DOE test;

s2, designing a performance optimization (DOE) test scheme;

s3, MBD realization of a DOE test scheme for performance optimization;

s4, response analysis of a performance optimization DOE test;

s5, selecting optimal schemes of the DOE test for optimizing performance;

in step S1, the specific determination steps of the performance optimization DOE test controllable factors are as follows:

s11, the clearance combination result of each connection part of the braking device has influence on the release performance, so the size of each braking connection part is the factor influencing the release performance;

s12, the stress condition of the connecting pin shaft can reflect whether the mechanism is blocked or not and the severity of the mechanism, and the size of the abnormally stressed pin shaft is a key factor influencing the relieving performance;

in step S12, the concrete determination steps of the pin shaft with abnormal stress are as follows:

s121, determining identification indexes of key influence factors:

for the basic braking device, all connecting pin shafts are numbered in sequence for analysis, and a stress model at the pin shaft connecting part is simplified into a combination form of three components, namely a lever, a clamping plate and a pin shaft;

use the round pin axle to carry out the statistical analysis of atress alone as the research object, I section, III section are the splint both sides post to the region of action of round pin axle, and II section is the region of action of middle lever to the round pin axle, then the index of discerning key influence factor is:

a. the three sections of the pin shaft are unbalanced in stress:

criterion A: i F_X(I)+F_X(II)+F_X(III)|≥ε_F

Criterion B: i F_Y(I)+F_Y(II)+F_Y(III)|≥ε_F

Wherein, F_X(I)、F_X(II)、F_X(III) the I, II and III sections of pin shafts are stressed in the X-axis direction, F_Y(I)、F_Y(II)、F_Y(III) the I, II and III sections of pin shafts are stressed in the Y-axis direction, and the unit is N; epsilon_FThe maximum tolerance error of the stress is expressed in the unit of N,

when the known experimental data meet the criterion A or the criterion B, judging that the three-section force stress imbalance phenomenon of the pin shaft occurs;

b. the forces are balanced but not reasonably distributed:

criterion C:

or

Criterion D:

or

Wherein: k is the force multiplication factor,

when the known experimental data meet the criterion C or the criterion D, judging that the three-section force stress of the pin shaft is balanced but distributed unreasonably;

s122, identifying key influence factors by combining known experimental data:

according to the identification indexes of the determined key influence factors, whether the stress of the pin shaft is balanced or not is judged through the measured experimental data, and if the stress is balanced, whether the stress of the pin shaft is reasonable or not is judged;

determining the shaft diameter of a pin shaft, the thickness of a traveling lever, the width of a middle pull rod clamping plate and the width of a brake beam upright post groove which have influence on the clamping stagnation of a mechanism;

s21, DOE test encoding of controllable factors:

setting the thickness controllable factor code of the traveling lever as alpha;

the width controllable factor code of the middle pull rod end clamping plate is beta;

the width controllable factor of the brake beam strut groove is encoded as gamma;

the shaft diameter controllable factor of the hinge pin shaft of the traveling lever and the middle pull rod is coded into theta;

the shaft diameter controllable factor code of the hinge pin shaft of the traveling lever and the brake beam upright post is mu;

the fixed lever and the brake beam column hinge pin shaft diameter controllable factor is encoded into rho;

the fixed lever and the middle pull rod hinge pin shaft diameter controllable factor is coded into tau;

s22, setting the DOE test controllable factors horizontally:

selecting two horizontal settings for the encoding in step S21;

s23, selection of a DOE orthogonal test scheme table:

s24, response of DOE test:

the test response is an evaluation index of an optimized object, and the optimized object is the relieving performance of the basic braking device, so that the response of the DOE test is the relieving acting force;

s25, quality characteristics of DOE test:

the quality characteristic is the signal-to-noise ratio of the desired small characteristic;

s31, establishing a geometric model of the basic braking device:

modeling a basic brake device in CAD software to ensure correct assembly, and storing a basic brake device model as a file in a STEP format;

s32, importing the geometric model into MBD simulation software:

importing the file in the STEP format in the STEP S31 into MBD simulation software for proper simplification and combination;

s33, establishing a physical model of the basic brake device:

the establishment of the physical model comprises rigid body modeling, constraint modeling, contact modeling and external load modeling;

s34, MBD implementation of DOE test protocol:

applying a reverse relieving acting force on the upper end of the traveling lever, wherein the expression of a driving function is as follows:

STEP(time，0，0，1，-158)，

extracting a time-varying curve of the acting force between the brake shoe and the wheel tread, namely an F-t curve;

when 4 brake shoes are completely separated from the wheel, namely the contact force between the brake shoes and the wheel is 0, the minimum relieving force F required to be applied corresponding to each output scheme_kThe relieving acting force is the response output of the test;

analyzing the problem of poor releasing of the basic braking device, and overcoming various frictional resistances of the mechanism by using an equivalent releasing acting force, wherein the smaller the releasing acting force is, the better the releasing acting force is;

the signal-to-noise ratio calculation formula is as follows:

where eta is the signal-to-noise ratio, y_iThe DOE test result is the relief acting force, and n is the test frequency;

the larger the signal-to-noise ratio value of the small characteristic is expected to be, the stronger the anti-interference capability is, and the better the stability is.