CN109033482A - A kind of abrasion rail type face economy polishing process - Google Patents
A kind of abrasion rail type face economy polishing process Download PDFInfo
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Abstract
Bullet train abrasion rail type surface curve equal arc length is divided, takes N number of discrete coordinate as data point, reconstruct rail type surface curve by a kind of bullet train abrasion rail Structure optimization design method of low abrasion, this method.Using the ordinate on N number of offset vertex as design variable, using the route mean value and wheel-rail lateral force for reducing rail wear function as objective function, using the concavity and convexity and continuity for wearing away rail type face statistic, type surface curve as geometry constraint conditions, bullet train abrasion rail type face Model for Multi-Objective Optimization is established, multi-objective optimization calculating is carried out to Optimized model using particle group intelligent bionic algorithm.The result shows that Optimization-type face track side surfaces are significantly reduced with wheel rim some contacts, one section of steel rail line average ratio abrasion rail type face reduces 25.3%；Wheel-rail lateral force reduces, and the root-mean-square value of wheel-rail lateral force reduces 16.5% and 17.5%；The root-mean-square value of Max.contact stress reduces 22.3% and 19.5% respectively；The root-mean-square value of derailment coefficients reduces 8.5% and 7.8%.
Description
Technical field
The present invention relates to a kind of abrasion bullet train rail type face economy polishing process, belong to bullet train rail technology neck
Domain.
Background technique
The abrasion problems of rail seriously affected the track structures such as rail track operation security and rail and wheel and
The service life of vehicle, rail type face are to influence bullet train vehicle hunting stability, curving performance, wheel-rail wear and derailing
The important parameter of the dynamic performances such as safety.In the design of rail type face economy polishing process, need repeatedly to carry out outer
Shape curve modification and performance calculate, particularly important using reasonable type face Parametric designing.At present for the mathematics in rail type face
Description method mainly has several: 1) the Mathematical Fitting method of finite discrete point, such as Hamid proposes the convexity interpolation of cubic spline
Method guarantees the concavity and convexity and monotonicity in rail type face；Zhang Jian, study of the Chinese classic pine is indicated using 3 battens of discrete point, and keeps rail
The abscissa y in type face is constant, selects ordinate z as design variable carry out type face numerical analysis；Choromaski Qie Bixue
Husband's orthogonal polynomial describes rail type face；2) using the geometrical property put on type face as the mathematics description method of design variable,
Heller etc. is using the arc radius at the tangent slope and the point put on type face as design variable, with the stability and curve of vehicle
Passage capacity is that objective function carries out Structure optimization；Persson is using the high-order derivative put on rail type face as design variable, with vehicle
The weighted sum of the relevant penalty factor of dynamic performance is that objective function establishes Structure optimization model；3) with limited section of circular fitting
Rail type face method, Cheng Di described, different radii circular arc that Wang Chengguo uses multistage to be connected and the center of circle are for design variable, foundation
The multi-objective optimization design of power model in type face.The scholar having simultaneously is design variable from wheel/rail contact geometric characteristic, and design object is excellent
Change function, counter to push away rail type face, Shen Gang, Ye Zhi are gloomy etc., and propositions design abrasion rail type face with the anti-method pushed away of contact angle curve
Economy polishing process, the economy polishing process for rail type face shape provides a new approaches.
Wheel/rail Match relationship directly affects the security feature and transportation cost of rolling stock.In set wheel rail system structure
And under operating environment, rail type face is optimized, good Wheel Rail Contact and matching properties are found, becomes reduction wheel-rail wear
Most direct effective method.
Summary of the invention
The object of the present invention is to according to existing steel rail grinding there are the problem of, the present invention proposes a kind of abrasion rail type face
Economy polishing process.
Realize the technical scheme is that, a kind of abrasion rail type face of the invention economy polishing process, by rail type
The segmentation of surface curve equal arc length obtains N number of discrete coordinate as data point, rail type surface curve is reconstructed, with N number of offset vertex
Ordinate is design variable, using the route mean value and wheel-rail lateral force for reducing rail wear function as objective function, with rail wear
Rail type face statistic, the concavity and convexity of type surface curve and continuity are geometry constraint conditions, establish abrasion rail type face multiple target
Optimized model, and multi-objective optimization calculating is carried out to Optimized model using PSO particle group intelligent bionic algorithm.
The design variable that the present invention wears away rail type face Model for Multi-Objective Optimization determines in the following manner: to abrasion rail type
Length of curve in x=[- 35, the 35] mm in face carries out 5,9,14 sections of equal arc length segmentations, obtains N=6,10,15 discrete coordinates
Point is set as data point di(i=0,1 ..., n) establishes nurbs curve parameterization design method, and calculates in the case of three kinds
The related coefficient of matched curve and CN curve is respectively 0.87,0.91,0.96, and 14 sections of split plot designs are chosen after comparative analysis and take N
=15 data points meet the good description to rail profile forms, seek the abscissa of NURBS parametric curve and data point
Position.With its corresponding ordinate yi(i=1,2 ... 15) be design variable, carries out the Parametric designing of rail type surface curve.
The present invention wears away rail Structure optimization model to reduce wheel-rail wear and wheel-rail lateral force as target, establishes following mesh
Scalar functions:
(1) rail wear objective function is reduced
W in formulaL(t)、WR(t) be respectively one section of rail left and right rail abrasion function, s is that the operating line that entirely emulates is long
Degree.
(2) maximum wheel-rail lateral force objective function
fmin(yi)=max | QL|, | QR|}
Q in formulaL, QRFor the wheel-rail lateral force of the left and right rail of one section of rail, and pass through low-pass filtering treatment.
The present invention wears away selecting for rail type face Model for Multi-Objective Optimization constraint condition: to keep type surface curve smooth, not going out
Existing singular point and wave point, select ordinate statistic, curve monotonicity, concavo-convex characteristic and the inflection point range in rail type face as
The geometry constraint conditions of rail type surface curve；Simultaneous selection wheel track Max.contact stress and derailment coefficients are as constraint condition.
1, rail geometry constraint conditions:
(1) the ordinate range constraint condition of data point
Choose rail type face and its up-and-down boundary of standard steel rail type face as design variable of certain high-speed railway downlink section
Condition:
Cdown(yi)≤yi≤CupI ∈ (1,2 ..., 15)
C in formuladown(yi), CupRespectively wear away the boundary condition in statistical face and its standard steel rail type face.
(2) monotone decreasing of rail tread curve
If optimization rail type surface curve fitting function is g (yi), then rail tread curve has:
f[g′(yi)] >=0 i ∈ (10 ..., 15)
(3) rail type face concavity and convexity constraint condition
It is statisticallyd analyze based on rail type face, sets type face and change as convex.
Convex changes constraint condition
f[g″(yi)] > 0 i ∈ (1,6) ∪ (11,15)
2, maximum wheel Rail Contact Stresses constraint condition
(PWheel_opti, max|rms-PWheel, max|rms)≤0
Wherein PWheel_opti, maxFor the wheel track Max.contact stress in Optimization-type face, and root-mean-square value is taken to it.
3, derailment coefficients constraint condition
According to Nadal formula, the derailing constraint condition of vehicle are as follows:
fD, wheel_opti|max-fD, wheel|max≤0
Q in formula, P are wheel-rail lateral force and vertical force, α1For wheel rim angle, root-mean-square value is taken to derailment coefficients.
The present invention carries out multiple target solution to Optimized model using PSO particle group intelligent bionic algorithm:
Particle swarm algorithm is the evolutionary computation method based on swarm intelligence.Cooperation and information sharing between individual in population are sought
Look for optimal solution.Each particle has oneself in the position x and flying speed υ in N-dimensional space, with objective function adaptive value and currently
Position updates oneself speed and position by experience best in the experience of oneself and group:
Wherein:
vi=(vi1, vi2... viN)TThe speed of particle i；
xi=(xi1, xi2... xiN)TThe position of particle i；
The speed of particle i d dimension in kth time iteration；
The position of particle i jth dimension in kth time iteration；
Current particle i is in the position of the d individual extreme point tieed up；
Current population is in the position of the d global extreme point tieed up；
c1, c2Studying factors:
W- is non-negative, is inertial factor.W value is larger, then global optimizing ability is strong, and local optimal searching ability is weak；W value is smaller on the contrary.
Using linear decrease weight (LDW) strategy:
wmin, wmaxWith the minimum and maximum value for respectively indicating weight, value is 0.4 and 0.9, k respectivelynFor current iteration number,
kmaxFor maximum number of iterations.
Type face parameter is adjusted and is associated with vehicle dynamics characteristics, solution is iterated using particle swarm algorithm, vehicle is dynamic
It is as shown in Figure 1 that Mechanics Calculation with population solution couples calculation process.
The invention has the advantages that the present invention solves Optimized model using population bionic Algorithm (PSO).Knot
Fruit shows: good improvement, optimization rail type side part and wheel rim part is distributed in the Wheel Rail Contact in Optimization-type face
Contact point significantly reduces, and the contact range of rail tread increases to [- 10 ,+8] mm from original [- 10 ,+5] mm；Using Optimization-type
Behind face, a steel rail line average ratio abrasion rail type face reduces 25.3%；Wheel-rail lateral force reduce, wheel-rail lateral force it is equal
Root value reduces 16.5% and 17.5%；The root-mean-square value of Max.contact stress reduces 22.3% and 19.5% respectively；It is de-
The root-mean-square value of rail coefficient reduces 8.5% and 7.8%.
The present invention is suitable for the optimization design in bullet train abrasion rail type face.
Detailed description of the invention
Fig. 1 is calculated for dynamics of vehicle and is coupled flow chart with rail Structure optimization；
Fig. 2 is the rail type surface curve and enlarged drawing of optimization.
Specific embodiment
A specific embodiment of the invention is as follows；
The present embodiment carries out 5,9,14 sections of equal arc length segmentations to the length of curve in x=[- 35, the 35] mm in abrasion rail type face,
N=6 is obtained, 10,15 discrete coordinates are set as data point di(i=0,1 ..., n), establishes nurbs curve Parametric designing
Method, and the related coefficient of the matched curve and abrasion rail curve in the case of three kinds of calculating is respectively 0.85,0.91,0.96,
14 sections of split plot designs are chosen after comparative analysis and take N=15 data point, are met the good description to rail profile forms, are sought
The abscissa positions of NURBS parametric curve and data point difference is as shown in table 1.
The coordinate points of 1 bullet train rail type surface curve of table, 14 equal portions arc length segmentation
It is shown.With its corresponding ordinate yi(i=1,2 ... 15) be design variable, and the parametrization for carrying out rail type surface curve is set
Meter.
The present embodiment obtains 6,10,15 to 5,9,14 sections of arc length of abrasion rail type surface curve of high-speed EMUs etc. point
Discrete coordinate reconstructs its type surface curve as data point, using non-uniform rational B-spline (NURBS) curve theory, with raw steel
Rail type surface curve related coefficient is 0.85,0.91,0.96, and 14 sections of split plot designs are chosen after comparative analysis and take N=15 data point,
It can satisfy the good description to rail profile forms.Optimize rail type surface curve result as shown in Fig. 2, with primary standard curve pair
Than known to analysis: in [18,33] mm, Optimization-type face is slightly more thinning than raw steel rail type face, and at 26mm, thinned amplitude is most
Greatly；In other parts, Optimization-type face is smaller than the ordinate value in primary standard type face, and for whole difference within 0.5mm, rail top of steel rail is wide
Shape has no significant change, and profile variation is mainly near rail gauge angle.
The present embodiment is established using the ordinate of 15 data points on rail type face as design variable, with the accumulative abrasion of rail
The minimum objective function of route mean value and wheel-rail lateral force of function, to reduce the route mean value and wheel-rail lateral force of rail wear function
For target, using rail wear rail type face statistic, the convexity of type surface curve and continuity as the rail type of geometry constraint conditions
Face multi-goal optimizing function.
The present embodiment solves Optimized model using population bionic Algorithm (PSO).The result shows that: Optimization-type face rail
Road side is significantly reduced with wheel rim some contacts, the contact range of rail tread increase to from original [- 10 ,+5] mm [-
10 ,+8] mm；One steel rail line average ratio abrasion rail type face reduces 25.3%；Wheel-rail lateral force reduces, wheel-rail lateral force
Root-mean-square value reduce 16.5% and 17.5%；The root-mean-square value of Max.contact stress reduces 22.3% He respectively
19.5%；The root-mean-square value of derailment coefficients reduces 8.5% and 7.8%.
Claims (4)
1. the bullet trains of low abrasion a kind of wears away rail Structure optimization design method, which is characterized in that the method is by rail
The segmentation of type surface curve equal arc length obtains N number of discrete coordinate as data point, reconstructs rail type surface curve；With N number of offset vertex
Ordinate be design variable ground using the route mean value and wheel-rail lateral force for reducing rail wear function as objective function with rail
Consuming rail type face statistic, the concavity and convexity of type surface curve and continuity is geometry constraint conditions, establishes bullet train rail type face
Model for Multi-Objective Optimization, and multi-objective optimization calculating is carried out to Optimized model using PSO particle group intelligent bionic algorithm.
2. a kind of abrasion rail type face according to claim 1 economy polishing process, which is characterized in that the target letter
Number includes reducing rail wear objective function and maximum wheel-rail lateral force objective function；
It is described reduce rail wear objective function expression formula be；
In formula, WL(t)、WR(t) be respectively one section of rail left and right wheel abrasion function, s is that the operating line that entirely emulates is long
Degree；TXL、TyLFor left side wheel vertical, horizontal Creep Forces；TXR、TyRFor right side wheels vertical, horizontal Creep Forces；nXL、nyLFor left side vehicle
Take turns vertical, horizontal creep rate；nXR,nyRFor right side wheels vertical, horizontal creep rate；A is Wheel Rail Contact spot area；M is wheel-rail friction system
Number；
The expression formula of the maximum wheel-rail lateral force objective function is；
fmin(yi)=max | QL|, | QR|}
In formula, Q in formulaL, QRFor the wheel-rail lateral force of the left and right wheels of a wheel pair, and pass through low-pass filtering treatment.
3. a kind of abrasion rail type face according to claim 1 economy polishing process, which is characterized in that the geometry is about
Beam condition includes rail geometry constraint conditions, maximum wheel Rail Contact Stresses constraint condition and derailment coefficients constraint condition；
It is described maximum wheel Rail Contact Stresses constraint condition be；
(PWheel_opti, max|rms-PWheel, max|rms)≤0
In formula, PWheel, maxFor wheel track Max.contact stress, and root-mean-square value is taken to it；PWheel_opti, maxTo optimize rail type face
Wheel track Max.contact stress；
The derailment coefficients constraint condition are as follows:
fD, wheel_opti|max-fD, wheel|max≤0
In formula, Q, P are wheel-rail lateral force and vertical force；α1For wheel rim angle；fdFor derailment coefficients；fD, wheel_opti|maxAnd fD, wheel
|maxFor the maximum derailment coefficients in Optimization-type face and standard type face；m1For wheel-rail friction coefficient.
4. a kind of abrasion rail type face according to claim 3 economy polishing process, which is characterized in that the rail is several
What constraint condition includes the ordinate range constraint condition of data point, and the monotone decreasing near rail top of steel rail to rail gauge angle is about
Beam condition and wheel profile convexity constraint condition；
The ordinate range constraint condition of the data point is to choose the abrasion of Beijing-Shanghai High-Speed Railway downlink K645~K650 section
The up-and-down boundary condition of statistical face and standard type face as design variable:
Cdown(yi)≤yi≤CupI ∈ (1,2 ..., 15)
In formula, Cdown(yi), CupRespectively wear away the boundary condition in statistical face and standard type face；
Monotone decreasing constraint condition near the rail top of steel rail to rail gauge angle is, if optimization rail type surface curve is fitted letter
Number is g (yi), then rail tread curve has:
f[g′(yi)] >=0 i ∈ (10 ..., 15)
Rail type face concavity and convexity constraint condition is to be statisticallyd analyze based on rail type face, sets type face and changes as convex；
Convex changes constraint condition
f[g″(yi)] > 0 i ∈ (1,6) ∪ (11,15).
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112464397A (en) * | 2020-11-07 | 2021-03-09 | 西南交通大学 | Railway turnout steel rail polishing profile optimization method |
| CN114925933A (en) * | 2022-06-16 | 2022-08-19 | 北京交通大学 | Method for realizing environmental vibration control by optimizing wheel rail abrasion intervention time |
| US11893322B2 (en) | 2020-06-26 | 2024-02-06 | Loram Technologies, Inc. | Method and system for predicting wear in a rail system |
| CN117973086A (en) * | 2024-03-28 | 2024-05-03 | 中铁第四勘察设计院集团有限公司 | Multi-objective optimization-based whole-path steel rail polishing planning method and system |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11893322B2 (en) | 2020-06-26 | 2024-02-06 | Loram Technologies, Inc. | Method and system for predicting wear in a rail system |
| US11947881B2 (en) | 2020-06-26 | 2024-04-02 | Loram Technologies, Inc. | Method and system for performing and comparing financial analysis of different rail life scenarios in a rail system |
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| CN114925933A (en) * | 2022-06-16 | 2022-08-19 | 北京交通大学 | Method for realizing environmental vibration control by optimizing wheel rail abrasion intervention time |
| CN117973086A (en) * | 2024-03-28 | 2024-05-03 | 中铁第四勘察设计院集团有限公司 | Multi-objective optimization-based whole-path steel rail polishing planning method and system |
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