CN114741920B - Method for evaluating smoothness of large-span bridge - Google Patents
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Abstract
The invention discloses a method for evaluating smoothness of a large-span bridge, which solves the problem that the existing long-wave irregularity in the prior art is difficult to meet the linear smoothness evaluation requirement of a large-span bridge section. The invention comprises the following steps: s1, loading a load by establishing a bridge entity model, and collecting sensitive parameters affecting track smoothness; s2, combining loads, extracting bridge deformation characteristics, vehicle body vibration acceleration data and main parameters of ride control; s3, processing data and analyzing the data to obtain a key control index; and S4, obtaining a large-span bridge smoothness evaluation method and a conclusion based on the solving parameters and the sensitivity indexes.
Description
Technical field:
the invention belongs to the technical field of rail transit, and relates to a method for evaluating smoothness of a large-span bridge.
The background technology is as follows:
The key point of the design and research of the large-span bridge section of the high-speed railway at present is a rail surface linear smoothness evaluation method under the condition of large vertical deformation of the bridge. In the existing high-speed railway smoothness assessment, the rail smoothness is assessed by mainly depending on rail detection data and adopting a long-wave irregularity calculation result, and design, maintenance and repair are guided. However, the mode is more concerned with static and quasi-static line conditions, the fact that the large-span bridge is subjected to larger vertical deformation along with the environment is not considered, and particularly under the action of vehicle load, the large-span bridge is subjected to larger vertical deformation, and the structural characteristics of the large-span bridge are greatly different from those of roadbeds, tunnels and common short bridges. Therefore, the existing long-wave irregularity is difficult to meet the linear smoothness assessment requirement of the large-span bridge section, the line deformation evolution state of the large-span bridge working point cannot be mastered in time, and the method is mainly characterized in that:
(1) The invention is characterized in that the research and induction of sensitive parameters influencing the vibration acceleration of the vehicle body after the bridge deformation are not accurate enough, the larger the radius of a vertical curve is, the smaller the vibration acceleration of the vehicle body is, the reduction value of the vibration acceleration of the vehicle body caused by the increase of the radius of a unit vertical curve is gradually reduced, when the radius of curvature is larger than 45000-55000m, the vibration acceleration of the vehicle body in a curve section is basically the same as the vibration acceleration of the vehicle body in a straight section, and preferably, the curve with the radius of curvature larger than 50000m can be analyzed according to a straight line.
(2) The curve length and number affect the vehicle body vibration acceleration, and when the curve length is in the range of 50-120m, the vehicle body vibration acceleration is obviously increased when the curve radius is the same. In the fixed length range, the number of curves is increased, and the vibration acceleration of the vehicle body is increased. Preferably, when different working conditions are analyzed, the length of the vertical curve can be taken according to 60m, the number of the vertical curves can be taken according to 5 values, at the moment, the vibration acceleration reaction of the vehicle body is severe, and the most unfavorable vibration condition of the vehicle body can be better reflected when the same main span length is achieved.
(3) The invention provides a method for calculating the long wave irregularity and analyzing the bridge deck deformation smoothness, which only considers the temperature load and the shrinkage creep deformation, and does not consider the bridge deck deformation caused by the action of the train load at different bridge positions.
(4) The polynomial fitting power of the accurate large-span bridge deformation curve is not given, and the analysis of the actual engineering data shows that the fitting accuracy of the least square method is good and the engineering feasibility is high when the 24 th power is adopted preferably.
(5) The method for evaluating the deformation of the large bridge is not provided exactly, and the analysis shows that the curvature radius is solved by fitting a curve, and the method for evaluating the deformation of the large bridge can be solved by limiting the thought of the minimum curvature radius.
(6) The calculation and analysis find that the vehicle body vibration acceleration is used as an anchor point, the linear evaluation standard of the large-span bridge can be divided into excellent and general, and the smoothness evaluation conclusion of the evaluated bridge can be obtained by combining the solved minimum curvature radius of the fitting curve, preferably, the minimum curvature radius limit value can be 16500m on the premise of ensuring the operation safety.
The invention comprises the following steps:
The invention aims to provide a method for evaluating the smoothness of a large-span bridge, which solves the problems that the existing long-wave irregularity in the prior art is difficult to meet the linear smoothness evaluation requirement of a large-span bridge section and the line deformation evolution state of a large-span bridge working point cannot be mastered in time.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a method for evaluating smoothness of a large-span bridge is characterized by comprising the following steps: the method comprises the following steps:
s1, loading a load by establishing a bridge entity model, and collecting sensitive parameters affecting track smoothness;
s2, combining loads, extracting bridge deformation characteristics, vehicle body vibration acceleration data and main parameters of ride control;
s3, processing data and analyzing the data to obtain a key control index;
and S4, obtaining a large-span bridge smoothness evaluation method and a conclusion based on the solving parameters and the sensitivity indexes.
In S1, according to the design characteristics of the actual working point of the bridge, a bridge entity model is established through Ansys and Midas software, and the stress deformation characteristics of the bridge structure are fully reflected.
In S1, after modeling, loading temperature load and vehicle load on a model according to the environmental parameters of the working point where the bridge is located, the model number of an operation train, the material parameters and the structural design level, finally extracting deformation parameters, obtaining sensitive indexes, and determining main influencing factors of bridge deformation and train vibration.
And S2, based on the main influencing factors obtained in the step S1, working condition combination is carried out, and the least adverse deformation parameters and the maximum vehicle body vibration acceleration of the bridge are extracted.
And S3, carrying out data processing and analysis based on the main calculation parameters obtained in the step S2 to obtain a critical control index, wherein the method comprises the following steps of:
(1) Fitting the deformation data to obtain a continuous guide curve, and solving the curvature radius;
(2) And extracting the minimum curvature radius in the vehicle body range under different working conditions.
And S1, loading a vehicle load on the bridge in 1/n steps, and extracting bridge deformation data.
In the step (1), after bridge model node deformation data under different working conditions are obtained, curve fitting is carried out, and linear fitting is carried out by adopting a least square method.
In the step (1), according to the obtained fitted curve expression, the curve curvature radius is solved, and the curvature radius is obtained according to the following expression:
where R is the radius of curvature, y 'is the second derivative of the curve, and y' is the first derivative of the curve.
After the radius of curvature is solved, the minimum radius of curvature within the vehicle body range is extracted, namely the minimum radius of curvature R 0 under the action of the working condition.
The least squares linear fit includes: an approximation curve f (x) is solved based on the extracted bridge deformation discrete data (x i,yi) (where i=1, 2..n) such that the sum of squares of the deviations of the curve from the discrete points is minimized, where the deviation at a point can be expressed as δ i＝|f(xi)-yi |. Let the curve be polynomial, i.eThen the sum of squares of the deviationsWhere w i is the weight coefficient. To ensure that the R value is at a minimum, it should be satisfied that/>(Where i=0, 1,2 … k) to find the unknown coefficients a i in the polynomial. The equation set expression is:
and performing polynomial fitting of m powers on the original data under the same working condition, and observing the fitting effect by calculating R values under different powers.
In the steps:
(1) The length of the vertical curve can be taken according to 60m, and the number of the vertical curves can be taken according to 5;
(2) A curve with the radius of curvature larger than 50000m is analyzed according to a straight line;
(3) When n=8, the structural deformation reaction is the best, and the loading and calculating times are less;
(4) And performing the most unfavorable analysis and calculation according to the method that the curve section is simplified into a straight line and the length of the sensitive curve is controlled, and taking 16500m as a bridge smoothness control sensitive index.
(5) The degree of fitting of the polynomial fits works best with a power of 24.
Compared with the prior art, the invention has the following advantages and effects:
The invention relates to a linear evaluation method for a large-span bridge, which is used for obtaining a bridge smoothness evaluation conclusion in a mode of calculating bridge deformation data, fitting a deformation curve and solving a minimum curvature radius. Compared with a long wave irregularity linear evaluation method under static and quasi-static conditions, the method for guiding and evaluating the bridge design not only considers the deformation curve characteristics of the bridge when the vehicle load acts at the unused position, but also can reflect the line deformation evolution state when the vehicle operates step by step.
Description of the drawings:
FIG. 1 is a flow chart of an evaluation method of the present invention;
FIG. 2 is a schematic diagram of a load-carrying position according to the present invention;
FIG. 3 is a schematic diagram of the correspondence between a bridge deformation fitting curve and a curvature radius under a certain working condition;
FIG. 4 is a summary of calculated results for different vertical curve lengths, radii and maximum vehicle body vibration acceleration.
The specific embodiment is as follows:
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, the invention relates to a method for evaluating smoothness of a large-span bridge, which comprises the following steps:
s1, loading a load by establishing a bridge entity model, and collecting sensitive parameters affecting track smoothness;
s2, combining loads, extracting bridge deformation characteristics, vehicle body vibration acceleration data and main parameters of ride control;
s3, processing data and analyzing the data to obtain a key control index;
and S4, obtaining a large-span bridge smoothness evaluation method and a conclusion based on the solving parameters and the sensitivity indexes.
The invention comprises the following steps:
(1) And building a bridge entity model through Ansys, midas and other software, and fully reflecting the stress deformation characteristics of the bridge structure.
(2) And determining the main influence on bridge deformation according to the environmental parameters of the working point where the bridge is located, the model number of the operating train, the material parameters and the structural design level, loading other deformation influence factors such as temperature load, train load and the like on the model, finally extracting deformation data and train vibration acceleration, and determining the main influence factors on bridge deformation.
(3) The vehicle body loading stride can be loaded by the bridge main span length once every 1/2 stride, the bridge main span length once every 1/3 stride and the bridge main span length once every …/8 …, and the bridge main span length once every 1/10 stride, preferably, 1/8 stride is adopted after comparison and selection.
(4) After bridge model node deformation data under different working conditions are obtained, a least square method is adopted to conduct line fitting, an approximate curve f (x) is solved according to solved bridge deformation discrete data (x i,yi) (i=1, 2..n), so that the square sum of deviation of the curve and discrete points is minimum, and the deviation of a certain point can be expressed as delta i＝|f(xi)-yi I. Let the curve be polynomial, i.eSum of squares/>, of deviationsWhere w i is the weight coefficient. To ensure that the R value is at a minimum, it should be satisfied that/>(Where i=0, 1,2 … k) to find the unknown coefficients a i in the polynomial. The equation set expression is:
And (3) performing polynomial fitting of different highest powers on the original data under the same working condition, and observing the fitting effect by calculating R values under different powers, wherein according to a calculation result, as the polynomial powers are increased, the smaller the R value is, the better the overall fitting effect is, when the highest power is greater than 20, as the polynomial powers are increased, the R value reduction rate is slow, the fitting effect is basically stabilized at a numerical level, no obvious improvement is caused, and preferably, 24 powers are adopted for linear fitting.
(5) And (3) solving the curvature radius of the curve according to the fitted curve expression obtained in the step (4) to obtain the minimum curvature radius calculated under different working conditions. The radius of curvature can be determined according to the following equation:
where R is the radius of curvature, y 'is the second derivative of the curve, and y' is the first derivative of the curve.
(6) According to analysis of bridge deck deformation data fitting curves under different working conditions, the fitting curves are continuous curves formed by splicing and combining a plurality of arcs with obvious concave-convex characteristics, the corresponding relation between the deformation fitting curves and the curvature radius under certain working conditions is shown as a graph in fig. 3, the curvature radius characteristics are shown as the minimum value of the curvature radius of the arc 1 gradually reduced from infinity, gradually transited to approach infinity, then reversely gradually changed to be minimum value, gradually approaching infinity, the number of arcs under different working conditions is different, and the number of the minimum value of the curvature radius is also different.
(7) The larger the radius of curvature is, the smaller the vehicle body vibration acceleration is, and when the radius of curvature is larger than 45000-55000m, the vehicle body vibration acceleration of the curved section is substantially the same as the vehicle body vibration acceleration of the straight section, preferably, the curve with the radius of curvature larger than 50000m can be analyzed as a straight line.
The curve length and number affect the vehicle body vibration acceleration, and when the curve length is in the range of 50-120m, the vehicle body vibration acceleration is obviously increased when the curve radius is the same. In the fixed length range, the number of curves is increased, and the vibration acceleration of the vehicle body is increased. Preferably, when different working conditions are analyzed, the length of the vertical curve can be taken as 60m, the number of the vertical curves can be taken as 5, at the moment, the vibration acceleration reaction of the vehicle body is severe, and the most unfavorable vibration condition of the vehicle body can be better reflected when the same main span length is adopted.
Through the establishment of a linear bridge coupling model of the vehicle, when the vertical radius of the rail surface is more than 50000m, the vibration acceleration of the vehicle body is almost equal to that of a straight line section, and a curve with the radius of curvature of more than 50000m can be regarded as a straight line; the longer the approximate straight line between different small radii is, the smaller the vehicle body vibration acceleration is; the smaller the radius of curvature, the smaller the vehicle body vibration acceleration; under the same condition, when the length of the radius arc curve is about 60m, the vibration acceleration of the vehicle body is most sensitive. Therefore, a model with multiple sections of vertical curves directly connected under the most complex condition is established, and the calculated results of the vehicle body vibration acceleration under different conditions are shown in fig. 4.
(8) The large-span bridge deformation fitting curve is a continuous curve formed by splicing and combining a plurality of arcs with obvious concave-convex characteristics, the most unfavorable analysis and calculation are carried out according to the thought that the curve section is simplified into a straight line and the length of a sensitive curve is controlled, when the fitting curvature radius of the bridge deformation curve is not smaller than 150000-17000m, the vibration acceleration of the vehicle body is not larger than 1.5m/s 2, and preferably 16500m is taken as a bridge smoothness control sensitive index.
In FIG. 4, when the large radius of curvature is controlled to 50000m, the minimum curve radius corresponding to the vehicle body vibration acceleration is 30000m and 16500m, respectively, based on the bearing capacity (1.0 m/s 2,1.5m/s2) of the vehicle body vibration acceleration. Namely, the evaluation standard obtained according to a certain working point is as follows: the minimum curvature radius is not more than 30000m, the smoothness is excellent, when the minimum curvature radius is not more than 16500m, the vehicle body vibration acceleration is general, and when the minimum curvature radius is less than 16500m, the bridge smoothness evaluation does not meet the requirement.
The foregoing description is only illustrative of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, and all changes that may be made in the equivalent structures described in the specification and drawings of the present invention are intended to be included in the scope of the invention.
Claims (6)
1. A method for evaluating smoothness of a large-span bridge is characterized by comprising the following steps: the method comprises the following steps:
s1, loading a load by establishing a bridge entity model, and collecting sensitive parameters affecting track smoothness;
s2, combining loads, extracting bridge deformation characteristics, vehicle body vibration acceleration data and main parameters of ride control;
s3, processing data and analyzing the data to obtain a key control index;
S4, based on the solving parameters and the sensitive indexes, obtaining a large-span bridge smoothness evaluation method and a conclusion;
and S3, carrying out data processing and analysis based on the main calculation parameters obtained in the step S2 to obtain a critical control index, wherein the method comprises the following steps of:
(1) Fitting the deformation data to obtain a continuous guide curve, and solving the curvature radius;
(2) Extracting the minimum curvature radius in the vehicle body range under different working conditions;
In the step (1), after bridge model node deformation data under different working conditions are obtained, curve fitting is carried out, and a least square method is adopted for linear fitting;
In the step (1), according to the obtained fitted curve expression, the curve curvature radius is solved, and the curvature radius is obtained according to the following expression:
Wherein R is the radius of curvature, y 'is the second derivative of the curve, and y' is the first derivative of the curve;
After solving the curvature radius, extracting the minimum curvature radius in the vehicle body range, namely the minimum curvature radius R 0 under the action of the working condition;
The least squares linear fit includes: solving an approximation curve f (x) based on the extracted bridge deformation discrete data (x i,yi) (where i=1, 2..n) such that the sum of squares of the deviations of the curve from the discrete points is minimized, where the deviation at a point can be expressed as δ i＝|f(xi)-yi |; let the curve be polynomial, i.e Then the sum of squares of the deviationsWherein w i is a weight coefficient; to ensure that the R value is at a minimum, it should be satisfied that/>(Where i=0, 1,2 … k) to find the unknown coefficients a i in the polynomial; the equation set expression is:
and performing polynomial fitting of m powers on the original data under the same working condition, and observing the fitting effect by calculating R values under different powers.
2. The method for evaluating the smoothness of the large-span bridge according to claim 1, wherein the method comprises the following steps: in S1, according to the design characteristics of the actual working point of the bridge, a bridge entity model is established through Ansys and Midas software, and the stress deformation characteristics of the bridge structure are fully reflected.
3. The method for evaluating the smoothness of the large-span bridge according to claim 1, wherein the method comprises the following steps: in S1, after modeling, loading temperature load and vehicle load on a model according to the environmental parameters of the working point where the bridge is located, the model number of an operation train, the material parameters and the structural design level, finally extracting deformation parameters, obtaining sensitive indexes, and determining main influencing factors of bridge deformation and train vibration.
4. The method for evaluating the smoothness of the large-span bridge according to claim 1, wherein the method comprises the following steps: and S2, based on the main influencing factors obtained in the step S1, working condition combination is carried out, and the least adverse deformation parameters and the maximum vehicle body vibration acceleration of the bridge are extracted.
5. The method for evaluating the smoothness of a large-span bridge according to claim 3, wherein the method comprises the following steps: and S1, loading a vehicle load on the bridge in 1/n steps, and extracting bridge deformation data.
6. The method for evaluating the smoothness of a large-span bridge according to any one of claims 1 and 5, wherein the method comprises the following steps:
(1) The length of the vertical curve can be taken according to 60m, and the number of the vertical curves can be taken according to 5;
(2) A curve with the radius of curvature larger than 50000m is analyzed according to a straight line;
(3) When n=8, the structural deformation reaction is the best, and the loading and calculating times are less;
(4) Performing the most unfavorable analysis and calculation according to the method that the curve section is simplified into a straight line and the length of the sensitive curve is controlled, and taking 16500m as a bridge smoothness control sensitive index;
(5) The degree of fitting of the polynomial fits works best with a power of 24.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20120114439A (en) * | 2011-03-25 | 2012-10-17 | 한국유지관리 주식회사 | System for intelligent monitoring and safety evaluation of bridge based on usn |
| JP2018031189A (en) * | 2016-08-24 | 2018-03-01 | 公益財団法人鉄道総合技術研究所 | Scheduling method of operation management of railway bridge |
| CN114065358A (en) * | 2021-11-24 | 2022-02-18 | 重庆科技学院 | Deformation monitoring-based method for evaluating operation comfort of large-span public rail same-layer cable-stayed bridge |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20120114439A (en) * | 2011-03-25 | 2012-10-17 | 한국유지관리 주식회사 | System for intelligent monitoring and safety evaluation of bridge based on usn |
| JP2018031189A (en) * | 2016-08-24 | 2018-03-01 | 公益財団法人鉄道総合技術研究所 | Scheduling method of operation management of railway bridge |
| CN114065358A (en) * | 2021-11-24 | 2022-02-18 | 重庆科技学院 | Deformation monitoring-based method for evaluating operation comfort of large-span public rail same-layer cable-stayed bridge |
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