CN106596002A - High-speed railway steel truss arch bridge vehicle-bridge resonance curve measuring method - Google Patents

Abstract

The invention discloses a method for measuring the car-bridge resonance performance curve of a high-speed railway steel truss arch bridge, comprising: step 10) collecting bridge acceleration data, dynamic strain data and vehicle speed data: the collected acceleration data includes corresponding accelerations under the action of trains at different times value. The dynamic strain data includes the corresponding dynamic strain values under the action of trains at different times. Speed sample data corresponds to the speed value when different trains pass; step 20) divides the train load into working conditions: utilizes the time-space correlation between the grating strain gauge and the acceleration sensor to accurately identify the train load working condition; step 30) draws different working conditions Lower girder acceleration peak value and train speed correlation scatter diagram; Step 40) determine the corresponding vehicle speed value of scatter diagram extremum point, the whole vehicle speed variation range is divided into a plurality of vehicle speed sections, adopts the method for polyline fitting, Form the resonance performance curve. The determination method can accurately determine the car-bridge resonance performance curve of high-speed railway steel truss arch bridge.

Description

Determination method of car-bridge resonance performance curve of high-speed railway steel truss arch bridge

technical field

The invention relates to a method for measuring vehicle-bridge resonance performance curves applied to high-speed railway steel truss arch bridges, and relates to the field of bridge health monitoring.

Background technique

When a high-speed train passes through a railway bridge, due to the serpentine movement of the EMU, the unevenness of the track, the loading rate and the regular arrangement of the axle load of the EMU to produce periodic dynamic effects, the strength of the EMU at a certain speed may The vibration frequency is close to a certain order natural frequency of the bridge or 1/i (i=1,2,3...) of a certain order natural frequency of the bridge, thus generating resonance or superharmonic resonance. Liu Penghui and Yang Yiqian carried out dynamic performance tests on common-span simply supported girder bridges with speeds of 200-250 km/h and 300-350 km/h, respectively. The research shows that the existing high-speed railway design code effectively controls the vertical resonance of the beam by controlling the vertical natural frequency of the simply supported beam, but superharmonic resonance still occurs at a specific speed. Therefore, it is of great significance to study the measurement method of the vehicle-bridge resonance performance curve for steel truss arch bridges, which are special bridge types of high-speed railway bridges.

At present, in various civil engineering and transportation fields, there are several methods for the determination of railway bridge vehicle-bridge resonance performance curves: (1) field test method: this method uses the vehicle-line-bridge system test method to carry out bridge dynamics. Field test of characteristics, because the number of trains in the field test is less, it is difficult to grasp the vehicle-bridge resonance characteristics of the bridge, and it is not certain; (2) single working condition analysis method: most of the research at home and abroad is for a single train load The study of the vehicle-bridge resonance performance method based on the actual situation does not carry out a complete and systematic study on all working conditions, so it is not feasible; (3) Theoretical calculation and assumption method: this method only simplifies the bridge into a simply supported beam bridge, Through theoretical calculation and derivation, the vehicle-bridge resonance mechanism of the bridge is obtained, so as to set limits for early warning. However, there is a large difference between the actual bridge and the simply supported beam bridge, and the vehicle-bridge resonance in the actual situation is relatively random, so the applicability of this method is poor. Therefore, it is necessary to study a new method with high accuracy, good feasibility and strong applicability for the determination method of vehicle-bridge resonance performance curve of steel truss arch bridge.

Contents of the invention

The object of the present invention is to provide a method for measuring the vehicle-bridge resonance performance curve of a high-speed railway steel truss arch bridge, which can accurately measure the vehicle-bridge resonance performance curve of a high-speed railway steel truss arch bridge.

The technical scheme adopted in the present invention is: a method for measuring the car-bridge resonance performance curve of a high-speed railway steel truss arch bridge, comprising the following steps:

Step 10) collecting acceleration data, dynamic strain data and vehicle speed data samples;

Step 20) divide the train load into working conditions;

Step 30) draw a scatter diagram of the correlation between peak acceleration and train speed under each working condition;

Step 40) Using a polyline fitting method to form a resonance performance curve between the acceleration peak value and the train speed.

As preferably, the bridge acceleration data collected in the step 10) includes corresponding acceleration values under the action of trains at different times, the dynamic strain data includes corresponding dynamic strain values under the action of trains at different times, and the vehicle speed data is different when trains pass by. Corresponding speed value.

Preferably, the acceleration data in step 10) is collected by acceleration sensors arranged in the spans at both ends of the bridge.

As preferably, described step 20) in the specific content of sub-working mode is:

a. utilize the acceleration data collected by the train through said step 10) to obtain the order in which the acceleration data at both ends produce peak values, thereby determining the driving direction;

b. Utilize the dynamic strain data that described step 10) collects, determine whether the train runs on the upstream side or the downstream side;

c. Use the number of extreme points in the dynamic strain data of the main girder to determine the number of carriages of the EMU, that is, to determine the type of carriage formation of the EMU.

As preferably, the specific process of said step 30) is: based on the historical data of acceleration and vehicle speed under the working conditions determined in said step 20), obtain the maximum value of the absolute value of the acceleration of the measuring point and the train speed when a single train passes value, with the train speed as the abscissa and the maximum absolute value of the acceleration as the ordinate, draw a scatter diagram of the correlation between the peak acceleration and the train speed under this working condition.

As preferably, the specific content of said step 40) is: first according to the acceleration peak value drawn in step 30) and the train speed correlation scatter diagram, determine the correspondence between the maximum value at the peak of the scatter diagram and the minimum value at the valley place The speed value of the vehicle, the interval between two adjacent vehicle speed values is regarded as a vehicle speed segment, thereby dividing the vehicle speed variation range of the entire correlation scatter diagram into multiple vehicle speed segments;

Then linearly fit the scattered point data in each vehicle speed segment to form a polyline, which is the vehicle-bridge resonance performance curve.

Beneficial effect: compared with the prior art, the present invention has the following advantages:

(1) Accurately measure the vehicle-bridge resonance performance curve of the high-speed railway steel truss arch bridge. Based on the correlation scatter diagram of acceleration peak samples and train speed samples, the present invention provides a method for measuring the car-bridge resonance performance curve of a high-speed railway steel truss arch bridge. There are many research results on the relationship between bridge vibration response and vehicle speed at home and abroad, but the correlation relationship has not been accurately studied, and the correlation relationship is only based on a small number of experiments. However, the present invention can avoid the randomness and large errors caused by a small amount of experiments based on the correlation relationship researched out of the massive data of health monitoring, and the conclusions obtained from a small amount of experiments cannot form an obvious vehicle-bridge resonance correlation scatter diagram, which is very important for curve measurement. accuracy is greatly affected. Simultaneously, the correlation researched out by the present invention is real-time, and can provide basis for early warning of bridges, but a small amount of tests can only be carried out during the bridge inspection process, and do not have real-time performance. Therefore, the present invention can make late-stage curve determination more efficient.

(2) Since the vast majority of bridges do not have special equipment to identify train load conditions, most of the current research at home and abroad is only on the vehicle-bridge resonance performance under a single working condition or regardless of the working condition. However, the actual train load has multiple working conditions. Only by grasping the vehicle-bridge resonance performance under each working condition can a complete and effective vehicle-bridge resonance performance curve be determined. At the same time, the vehicle-bridge resonance performance curves studied under a single working condition and regardless of working conditions are not accurate, and the influence of the driving direction, driving lane and number of train cars on the curve measurement has not been eliminated. However, the present invention accurately identifies the train load conditions by using the time-space correlation between the grating strain gauge and the acceleration sensor, thereby obtaining the correlation scatter diagram under each condition, and finally forming a complete and accurate vehicle-bridge resonance performance curve .

(3) The method is simple and practical, and has good feasibility. The method of the invention is simple and practical, has good feasibility, and makes up for the defects of field test method, theoretical calculation and assumption method and single working condition analysis method in the prior art. Simultaneously, the method of the present invention can be applicable to the mensuration of vehicle-bridge resonance performance curve of various high-speed railway steel truss arch bridges, making the method more feasible and accurate when used for the measurement of vehicle-bridge resonance performance curves of high-speed railway steel truss arch bridges and applicability, and can be widely promoted and applied.

Description of drawings

Fig. 1 is a long-term variation curve of acceleration peak samples P ₁ collected in an embodiment of the present invention.

Figure 2(a) is the strain time history curve collected by the DWY-11-25 strain gauge when a single train is running on the downstream side.

Figure 2(b) is the strain time history curve collected by the DWY-11-26 strain gauge when a single train is running on the downstream side.

Figure 3(a) is the strain time history curve collected by the DWY-11-25 strain gauge when a single train is running on the downstream side.

Figure 3(b) is the strain time history curve collected by the DWY-11-26 strain gauge when a single train is running on the downstream side.

Figure 4(a) shows the extreme points generated when a train with 8 carriages crosses the bridge.

Figure 4(b) shows the extreme points generated when the 16-car train crosses the bridge.

Figure 5(a) is the acceleration time history curve of the train traveling from south to north.

Figure 5(b) is the acceleration time history curve of the train traveling from north to south.

Fig. 6 is a scatter diagram of the correlation between the acceleration peak value of the measuring point and the train speed under the working condition 1 of the embodiment of the present invention.

Fig. 7 is the vehicle-axle resonance performance curve of the embodiment of the present invention.

detailed description

The technical solutions of the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

The method for measuring the vehicle-bridge resonance performance curve of the high-speed railway steel truss arch bridge of the present invention comprises the following steps:

Step 10) Collect acceleration data, dynamic strain data and vehicle speed data samples:

Step 10a) The acceleration sensor is connected to the acceleration acquisition system, and then the acceleration sensor is used to collect the acceleration of the measuring point, and the acceleration sensor transmits the acquired acceleration information to the acceleration acquisition system to form an acceleration sample. Acceleration samples contain corresponding acceleration values under the action of trains at different times.

Step 10b) Use a fiber optic strain gauge at the symmetrical position on the upstream and downstream sides of the main span, connect the fiber optic strain gauge to the strain acquisition system, and then use the fiber optic strain gauge to collect the dynamic strain of the measuring point, and the obtained measured The inching strain information is transmitted to the dynamic strain acquisition system to form a dynamic strain sample. The dynamic strain samples contain the corresponding dynamic strain values under the action of trains at different times.

Step 10c) Connect the speedometer to the vehicle speed acquisition system, and then use the speedometer to collect the train speed, and the speedometer transmits the acquired vehicle speed information to the vehicle speed acquisition system to form a vehicle speed sample. The vehicle speed sample contains the corresponding vehicle speed values when different trains pass by.

Step 20) divide the train load into working conditions:

Step 20a) Determine the driving direction: use the acceleration sensors in the side spans at both ends of the bridge (the two sensors are represented by A1 and A2 respectively), when the train passes, A1 and A2 collect corresponding acceleration signals respectively, if A1 collects If the acceleration signal collected by A2 has an extreme point earlier than that collected by A2, it can be determined that the train travel direction is from A1 to A2. On the contrary, it is from A2 to A1.

Step 20b) Determine whether the train is running on the upstream side or the downstream side: use an optical fiber strain gauge on the symmetrical position of the upstream and downstream sides of the main span (the optical fiber strain gauges on the upstream side and the downstream side are represented by S1 and S2 respectively), when the train passes , the change range of the dynamic strain data collected by S1 is greater than that collected by S2, and the train is running on the upstream side. On the contrary, the train travels on the downstream side.

Step 20c) Determine the type of EMU: my country's EMUs generally have two types of 8 cars and 16 cars, and use the dynamic strain data collected in S1 and S2 in step 20b) for analysis. When the train with 8 cars passes through S1 and S2, due to the uneven track, 9 pairs of rollers will generate 9 extreme points in the dynamic strain data; correspondingly, 17 pairs of rollers in 16 cars will generate 17 extreme points in the dynamic strain data. Therefore, the number of carriages of the train can be determined.

Through the analysis of steps 20a), 20b), and 20c), the train operating conditions can be accurately identified.

Step 30) draw a scatter diagram of the correlation between peak acceleration and train speed under different working conditions:

In the calculation step 10a), from all the acceleration data in the time period required for analysis, the data corresponding to the train load condition is selected for analysis, and the peak value of the acceleration sample of the measuring point (that is, the absolute value of the acceleration sample) is obtained when a single train passes. maximum value) and the train speed value recognized by the speedometer. The abscissa is the train speed value, and the ordinate is the acceleration peak value to draw a scatter diagram of the correlation between the acceleration peak value and the train speed under different working conditions.

Step 40) adopt the method of polyline fitting, form acceleration peak value and train speed resonance performance curve:

According to the scatter diagram drawn in step 30), the distribution of the "M" waveform is roughly formed, and the vehicle speed values corresponding to the maximum value at the peak and the minimum value at the valley of the "M" waveform scatter diagram are determined, so that the entire vehicle speed variation range is obtained. Divided into multiple speed sections, the speed sections are [minimum vehicle speed, vehicle speed value corresponding to the maximum value at the first peak], [vehicle speed value corresponding to the maximum value at the first peak, minimum value at the subsequent trough Corresponding vehicle speed value], ... and so on, the scatter diagram in each vehicle speed segment is linearly distributed, therefore, use linear fitting to scatter point data to form a polyline. This polyline is the vehicle-axle resonance performance curve.

Example:

The specific implementation process of the present invention will be described below by taking the acceleration samples on the main girder steel deck of the Dashengguan Bridge as an example.

(1) The acceleration peak sample P ₁ of a measuring point of the main girder steel bridge deck from 2014 to 2015 is obtained by using the acceleration sensor, and its long-term change curve is shown in Figure 1. In Fig. 1, the ordinate represents the peak value, and the unit is mm/s ² ; the abscissa represents the number of data (that is, the number of passing trains). Get an acceleration peak each time the train passes. At the same time, the speedometer can be used to obtain a vehicle speed value each time a train passes, forming a train speed sample C ₁ corresponding to the acceleration peak sample P ₁ one-to-one.

(2) Divide the train load into working conditions: one grating strain gauge is installed on each of the upstream and downstream beams in the main span of the main beam, and the number of the strain gauge on the downstream beam is DWY-11-25; The dynamic strain sensor number is DWY-11-26. Two acceleration sensors are installed on the bridge at Pier 2 (North) and Pier 20 (South), and the sensor numbers are JSD-02-01 and JSD-20-10 respectively. The specific method of dividing the working conditions is as follows: a. Figure 2 and Figure 3 show the strain time history curves collected by DWY-11-25 and DWY-11-26 when the train is running on the downstream side and upstream side respectively. When the train is running on the downstream lane, DWY-11-25 will produce a large change, compared with DWY-11-26, the change is relatively small; when the train is running on the upstream lane, DWY-11-26 will produce a relatively Big changes, while DWY-11-25 changes relatively little. So it can be judged which side the train is running on; b. When the train with 8 carriages passes through the strain sensor, due to the uneven track, 9 pairs of rollers will produce 9 extreme points; the corresponding 16 carriages and 17 pairs of rollers will produce 17 extreme points, as shown in Figure 4. Further, the number of carriages of the train can be judged; c. When the train travels from north to south, the acceleration sensor JSD-02-01 appears the extreme point earlier than JSD-20-10, and vice versa, as shown in Figure 5. Thus, the driving direction is determined. Finally, the train load case can be accurately identified.

(3) From the acceleration peak samples P ₁ and train speed C ₁ obtained in (1), select train load cases 1 to 8 for analysis. Figure 6 shows the scatter diagram of the correlation between the peak acceleration of the measuring point and the train speed under working condition 1. In FIG. 6 , the ordinate represents the peak value in mm/s ² ; the abscissa represents the vehicle speed in km/h. Determine the vehicle speed value corresponding to the extreme point of the scatter diagram, divide the entire vehicle speed range into multiple vehicle speed segments, and use the polyline fitting method to form the vehicle-bridge resonance performance curve, as shown in Figure 7.

It should be pointed out that those skilled in the art can make some improvements and modifications without departing from the principle of the present invention, and these improvements and modifications should also be regarded as the protection scope of the present invention. All components that are not specified in this embodiment can be realized by existing technologies.

Claims (6)

1. a kind of high-speed railway steel truss arched bridge car-bridge resonance performance curve determination method, it is characterised in that：Comprise the steps：

Step 10）Collection acceleration information, dynamic strain data and vehicle speed data sample；

Step 20）Divided working status are carried out to train load；

Step 30）Draw acceleration peak value and train speed's correlation scatter diagram under each operating mode；

Step 40）The method being fitted using multi-section-line, forms acceleration peak value with train speed's resonance performance curve.

2. high-speed railway steel truss arched bridge car according to claim 1-bridge resonance performance curve determination method, its feature exists In：The step 10）The bridge acceleration information of middle collection includes not corresponding accekeration under train effect in the same time, described Dynamic strain packet containing not corresponding dynamic strain value under train effect in the same time, vehicle speed data difference train by when correspondence Vehicle speed value.

3. high-speed railway steel truss arched bridge car according to claim 1-bridge resonance performance curve determination method, its feature exists In：The step 10）Acceleration information collected by the acceleration transducer for being arranged on bridge two ends end bay span centre.

4. high-speed railway steel truss arched bridge car according to claim 1-bridge resonance performance curve determination method, its feature exists In：The step 20）The particular content of middle divided working status is：

A. using train by the step 10）The acceleration information of collection, obtains the elder generation that two ends acceleration information produces peak value Afterwards sequentially, so that it is determined that direction of traffic；

B. the step 10 is utilized）The dynamic strain data of collection, determine train driving in upstream side or downstream；

C. determine motor train unit carriage number using girder dynamic strain data extreme point number, that is, determine the compartment compartment class of EMUs Type.

5. high-speed railway steel truss arched bridge car according to claim 1-bridge resonance performance curve determination method, its feature exists In：The step 30）Idiographic flow be：Based on the step 20）The history of acceleration and speed under the operating mode of middle determination Data, obtain the maximum and train speed value of measuring point acceleration absolute value when single train passes through, with train speed value as horizontal stroke Coordinate, the maximum of acceleration absolute value are ordinate, draw acceleration peak value under the operating mode scattered with train speed correlation Point diagram.

6. high-speed railway steel truss arched bridge car according to claim 1-bridge resonance performance curve determination method, its feature exists In：The step 40）Particular content be：First according to step 30）Middle drawn acceleration peak value is related to train speed Property scatter diagram, determines the vehicle speed value at maximum and trough corresponding to minimum at scatter diagram crest, by two neighboring vehicle speed value Interval as a speed section, so as to the speed excursion of whole correlation scatter diagram is divided into into multiple speed sections；

Then the scatterplot data in each vehicle speed section of linear fit, form multi-section-line, as car-bridge resonance performance curve.