阅读说明：本技术 一种考虑连续车流耦合效应的梁式桥冲击系数检测方法 (A kind of beam bridge impact coefficient detection method considering continuous wagon flow coupling effect ) 是由 刘晨光 高庆飞 郭斌强 刘洋 于 2019-09-05 设计创作，主要内容包括：一种考虑连续车流耦合效应的梁式桥冲击系数检测方法,属于桥梁检测试验技术领域。先获得桥梁动位移实测数据,再计算得到不同车速、不同车辆数的车队荷载作用下可能引起的桥梁最不利冲击系数；而后综合结果形成检测桥梁的最不利冲击系数影响面,可对检测桥梁实际车流荷载作用下的冲击系数进行评价。本发明提出了一种混合试验方法,可搜索更全面的可行加载工况,避免遗漏最不利工况。相对于实际采用多辆试验车共同激励的冲击系数检测试验,本发明方法易于控制、耗时短、花费低；相对于目前通用的冲击系数检测方法,在不增加现场检测的工作量的同时,可使检测结果的数据价值得到更充分的开发利用。(A kind of beam bridge impact coefficient detection method considering continuous wagon flow coupling effect, belongs to Bridge Detection Experiment technical field.First obtain bridge moving and be displaced measured data, then be calculated different speeds, different vehicle number fleet's load action under the bridge least favorable impact coefficient that may cause；The least favorable impact coefficient that then synthesis result forms detection bridge influences face, can evaluate the impact coefficient under the practical traffic flow loads effect of detection bridge.The invention proposes a kind of bulk testing methods, can search for more fully feasible loading condition, avoid omitting the most unfavorable processing condition.Test is detected relative to the practical impact coefficient using more instruction carriage common activations, the method for the present invention is easily controllable, time-consuming is short, cost is low；The data value of testing result can be made more fully to be developed and used while not increasing the workload of on-site test relative to impact coefficient detection method general at present.)

1. a kind of beam bridge impact coefficient detection method for considering continuous wagon flow coupling effect, it is characterised in that: the method packet Include following steps:

Step 1: the sport car exciter test of live single instruction carriage is carried out to bridge to be detected, and is adopted in bridge spaning middle section Bridge moving displacement measured data is measured with acquisition equipment amount；Measured data includes: bridge quail-static displacement s₀And instruction carriage In one group of sport car excited vibration displacement data set { s of equivalent variation within the scope of bridge highest operating speed_i}；

Step 2: it according to the across footpath of bridge to be detected and the length of test vehicle, determines fleet maximum vehicle number N, is then used for The fleet vehicle number of calculating is respectively n_i=2,3 ..., N；

Step 3: in least favorable impact coefficient random search algorithm main program, fleet vehicle number n in this calculating is given_i, vehicle Team travel speed v_iSpecific value and the main program in genetic algorithm specific algorithm parameter；

Step 4: bridge quail-static displacement s is imported into main program described in step 3₀, according to fleet's travel speed in step 3 v_iImport corresponding sport car excited vibration displacement data s_i, with vehicle spacing set { x in fleet_jIt is used as analysis and Control variable, according to Fleet vehicle number n described in step 3_iControl variable vehicle spacing set { x is determined with span of bridge_jValue range, further according to The algorithm parameter given in step 3, generates first generation vehicle spacing sample matrix X at random in value range_k；

Step 5: by the bridge quail-static displacement s in step 4₀, sport car excited vibration displacement data s_iAnd first generation vehicle spacing Sample matrix X_kFitness function counting subroutine is passed to, first generation vehicle spacing sample matrix X is calculated by subprogram_kIn Each separate vehicle spacing set { x_jCorresponding fitness function value, fitness function value presses sample vehicle spacing set {x_jArrangement fleet's load pass through the Bridge Impact Coefficient excited when bridge；

Step 6: the fitness function value that step 5 sub-routine is calculated is passed back main program, main program is to fitness letter Numerical value store and sort by size to fitness value, and the sorting position of fitness value is corresponded to according to each sample, to this generation Sample carry out genetic evolution, obtain next-generation new vehicle spacing sample matrix X_k+1；

Step 7: using the sample matrix X in step 6_k+1Instead of first generation vehicle spacing sample matrix X_k, and repeat step 5 With step 6 to convergence is calculated, maximum adaptation degree functional value is obtained to get to by n_iFleet's load of instruction carriage composition presses vehicle Team travel speed v_iWhen crossing detection bridge, least favorable impact coefficient caused by institute's energy；

Step 8: to all fleet's speed of operation v_iCorresponding sport car excited vibration displacement data s_iAnd all fleet's maximum vehicles Fleet vehicle number n in number N_i, step 3 is carried out to the analysis of step 7, obtains the least favorable under various fleet's driving cycles The bridge least favorable impact coefficient matrix U under traffic flow loads effect can be obtained in impact coefficient_v,n, according to the matrix U_v,nIt draws Least favorable impact coefficient influences face out, can be realized in the case where considering wagon flow synergistic effect, to the impact coefficient of bridge into Row detection evaluation.

2. a kind of beam bridge impact coefficient detection method for considering continuous wagon flow coupling effect according to claim 1, It is characterized in that: the instruction carriage fleet speed of operation v of one group of sport car of the variation of equivalent described in step 1_iAre as follows: minimum speed v₁= 10km/h, the max speed v_maxTo detect bridge Maximum speed limit, median speed is incremented by value by velocity gradient 20km/h.

3. a kind of beam bridge impact coefficient detection method for considering continuous wagon flow coupling effect according to claim 1, Be characterized in that: algorithm parameter described in step 3 includes: initial sample size, elite sample reservation probability, sample cross probability And sample variation probability.

4. a kind of beam bridge impact coefficient detection method for considering continuous wagon flow coupling effect according to claim 1, It is characterized in that: fitness function counting subroutine described in step 5 comprising the steps of:

Step 1: the vehicle spacing set { x provided according to the main program_j, determine the arrangement form of fleet；

Step 2: according to actual measurement sport car excited vibration displacement data s_i, generate and move displacement point in fleet caused by each instruction carriage Amount；

Step 3: it using the delay addition method, obtains under fleet's load action, the dynamic displacement curve Y (x) of bridge can Approximate Equivalent Are as follows:

Wherein, n_iFor the vehicle fleet of fleet in this calculating；

Step 4: according to actual measurement bridge quail-static displacement s₀, using method identical with above-mentioned steps two and step 3, obtain vehicle Under team's load action, the equivalent static displacement curve Y of bridge₀(x)；

Step 5: according to equivalent static displacement curve Y₀(x) and dynamic displacement curve Y (x), in curve Y₀(x) maximum Static Correction is measured on y_s, maximum dynamic displacement y is measured on curve Y (x)_d, then the dynamic impact coefficient μ of bridge under fleet's load action can be calculated,

Impact coefficient μ is vehicle spacing set { x_jCorresponding fitness function value.

5. a kind of beam bridge impact coefficient detection method for considering continuous wagon flow coupling effect according to claim 4, Be characterized in that: the step 2 process is as follows: being run to the jth vehicle in fleet according to its time gap away from tail of the queue vehicle Vehicle excited vibration displacement data s_iThe remained shock signal of upper interception corresponding length, obtains intermediate quantity y'(x)；Further according to the spacing head of the queue vehicle Time gap in y'(x) signal leading portion supplement respective numbers zero, obtain y_j(x), y_j(x), as fleet's load action Displacement component is moved in lower fleet caused by jth vehicle.

Technical field

The present invention relates to a kind of beam bridge impact coefficient detection methods for considering continuous wagon flow coupling effect, belong to bridge inspection Survey experimental technique field.

Background technique

When move vehicle load passes through bridge, it can make bridge structure that forced vibration occur, it is such to be forced in science of bridge building The caused load enlarge-effect of vibration is referred to as shock effect, is described by impact coefficient.

In current science of bridge building, the research work of impact coefficient is mostly the design direction progress for newly building bridge, Research for existing bridge machinery direction impact coefficient is relatively fewer, designs and detects grinding about impact coefficient therebetween Though studying carefully relevant, research contents and target are again not exactly the same:

It is the conjunction for finding an impact coefficient to the main target of impact coefficient research in newly building bridge design work The upper limit is managed, guarantees that the design value of impact coefficient can meet the security requirement of a major class bridge, does not pursue and is rushed for specific bridge The Exact calculation for hitting coefficient is the macro -examination for impact coefficient.In the work of existing bridge machinery, research object is specific Bridge is detected, goal in research is the acquisition true shock effect of trystate flowering structure, and accordingly under bridge operation state Shock effect judges, to evaluate the working performance of bridge.The thin sight that job requirement is detected for impact coefficient is studied, and is needed Consider the thin portion influence factor of more impact coefficients.

According to current specification direction and engineering practice situation, the detection of impact coefficient is mostly when being passed a bridge based on vehicle Response-time graph calculated, but the curve obtained under which kind of loading condition without explicitly specification definition.It runs Vehicle test method(s) generallys use single instruction carriage and crosses the dynamic response that bridge carrys out incentive structure, but during actual operation, bridge What structure was undertaken is continuous traffic flow loads, acts on bridge simultaneously there are more vehicles and fleet sequentially continuously crosses bridge Load case.Under this two kinds of operating conditions, influencing each other between fore-aft vehicle and coupling in wagon flow, it will influence bridge The dynamic response that girder construction is actually inspired, the operating condition that the impact coefficient of bridge structure can also be motivated with single vehicle exist not Together.

It can be seen that currently used Bridge Impact Coefficient detection method, test excitation load is deposited with actual operation load The significant difference the problem of, can difference between the two make impact coefficient testing result accurately reflect the practical power of bridge State becomes unknown number, and testing result does not have specific representativeness, and impact coefficient detection method needs to improve.

Directly use more vehicles as excitation load simultaneously in impact coefficient detection test, however, it would be possible to solve above-mentioned Problem, but on the one hand, actual traffic flow loads are a random processes, it is difficult to as bridge static loading test, extract one A feasible test loading scheme carries out equivalent simulation to it；On the other hand, it is difficult to it is specific to realize that testing ground is accurately organized Speed, particular arrangement mode fleet cross bridge, and between actual fleet's state and test preset state inevitably It has differences, it is difficult to the accuracy that guarantee test is implemented.Therefore, it is necessary to seek from other angles it is contemplated that practical vehicle Flow the impact coefficient detection method of coupling effect.

Summary of the invention

To solve the problems in the background art, the present invention provides a kind of beam bridge for considering continuous wagon flow coupling effect Impact coefficient detection method.

Realize that above-mentioned purpose, the present invention take following technical proposals: a kind of beam bridge considering continuous wagon flow coupling effect Impact coefficient detection method, the described method comprises the following steps:

Step 1: the sport car exciter test of live single instruction carriage is carried out to bridge to be detected, and is cut in bridge span Face measures bridge moving displacement measured data using acquisition equipment amount；Measured data includes: bridge quail-static displacement s₀And examination It validates the car within the scope of bridge highest operating speed in one group of sport car excited vibration displacement data set { s of equivalent variation_i}；

Step 2: according to the across footpath of bridge to be detected and the length of test vehicle, fleet maximum vehicle number N is determined, then Fleet vehicle number for calculating is respectively n_i=2,3 ..., N；

Step 3: in least favorable impact coefficient random search algorithm main program, fleet vehicle number in this calculating is given n_i, fleet travel speed v_iSpecific value and the main program in genetic algorithm specific algorithm parameter；

Step 4: bridge quail-static displacement s is imported into main program described in step 3₀, according to fleet's row in step 3 Sail speed v_iImport corresponding sport car excited vibration displacement data s_i, with vehicle spacing set { x in fleet_jBecome as analysis and Control Amount, the fleet vehicle number n according to step 3_iControl variable vehicle spacing set { x is determined with span of bridge_jValue range, Further according to the algorithm parameter given in step 3, first generation vehicle spacing sample matrix X is generated at random in value range_k；

Step 5: by the bridge quail-static displacement s in step 4₀, sport car excited vibration displacement data s_iAnd first generation vehicle Spacing sample matrix X_kFitness function counting subroutine is passed to, first generation vehicle spacing sample matrix is calculated by subprogram X_kIn each separate vehicle spacing set { x_jCorresponding fitness function value, fitness function value presses sample vehicle spacing Gather { x_jArrangement fleet's load pass through the Bridge Impact Coefficient excited when bridge；

Step 6: the fitness function value that step 5 sub-routine is calculated is passed back main program, main program is to adaptation Degree functional value store and sort by size to fitness value, and the sorting position of fitness value is corresponded to according to each sample, right The sample in this generation carries out genetic evolution, obtains next-generation new vehicle spacing sample matrix X_k+1；

Step 7: using the sample matrix X in step 6_k+1Instead of first generation vehicle spacing sample matrix X_k, and repeat to walk Rapid five and step 6 to convergence is calculated, obtain maximum adaptation degree functional value to get to by n_iFleet's load of instruction carriage composition By fleet travel speed v_iWhen crossing detection bridge, least favorable impact coefficient caused by institute's energy；

Step 8: to all fleet's speed of operation v_iCorresponding sport car excited vibration displacement data s_iAnd all fleets are maximum Fleet vehicle number n in vehicle number N_i, step 3 is carried out to the analysis of step 7, is obtained under various fleet's driving cycles most The bridge least favorable impact coefficient matrix U under traffic flow loads effect can be obtained in unfavorable impact coefficient_v,n, according to the matrix U_v,nDrawing least favorable impact coefficient influences face, can be realized in the case where considering wagon flow synergistic effect, to the impact system of bridge Number carries out detection evaluation.

Compared with prior art, the beneficial effects of the present invention are: the present invention is directed to current impact coefficient detection method pilot scale It tests load and operation load has significant difference, based on the acquisition of field measurement data, by being based on genetic algorithm The random search algorithm of the least favorable impact coefficient of frame, the least favorable that analysis obtains impact coefficient under traffic flow loads act on take Value；The bulk testing method combined by field test with optimization algorithm is swashed relative to practical using more instruction carriages jointly The impact coefficient detection test encouraged, the method for the present invention can search for more feasible loading conditions, avoid omitting the most unfavorable processing condition, simultaneously Due to only needing the preventing test of practical carry out single vehicle, the method for the present invention field test link is easily controllable, time-consuming is short, spends It is low；And main inventive work is excavated to the processing method of test data in current detection test, relative to conventional impact Coefficient detection method does not increase the workload of on-site test, but by innovation algorithm, obtain the data value of testing result It more fully develops and uses, effectively improves the application value of current beam bridge impact coefficient testing result.

Detailed description of the invention

Fig. 1 is case Bridge sectional schematic diagram of the present invention；

Displacement diagram is moved across span centre in when Fig. 2 is single instruction carriage sport car, in which:

Across span centre displacement diagram is moved during figure a is speed when being 10km/h；

Across span centre displacement diagram is moved during figure b is speed when being 30km/h；

Across span centre displacement diagram is moved during figure c is speed when being 50km/h；

Across span centre displacement diagram is moved during figure d is speed when being 70km/h；

Across span centre displacement diagram is moved during figure e is speed when being 90km/h；

Fig. 3 is genetic algorithm evolutionary process figure；

Fig. 4 is that least favorable impact coefficient influences face figure；

Fig. 5 be under friction speed impact coefficient with vehicle number variation diagram；

Fig. 6 across span centre moves displacement comparison figure in being.

Specific embodiment

Following will be combined with the drawings in the embodiments of the present invention, is clearly and completely retouched to the technical solution in the present invention It states, it is clear that described embodiment is only a part of the embodiment of invention, instead of all the embodiments, based in the present invention Embodiment, every other embodiment obtained by those of ordinary skill in the art without making creative efforts, It shall fall within the protection scope of the present invention.