Temperature prediction method and system for prestressed reinforced concrete long-span girder bridge

Abstract

The invention discloses a temperature prediction method and system for a prestressed reinforced concrete long-span beam bridge, and relates to the field of bridge temperature effect analysis. The method comprises the following steps of: 1, acquiring a construction design position coordinate, and monitoring a structure temperature in the construction design position coordinate; step 2, carrying out ANSYS modeling on the structure temperature to divide grids, and establishing a structure temperature field according to the single structure temperature in each grid; 3, acquiring a time sequence corresponding to the single structure temperature, establishing a mapping relation between the time sequence and the structure temperature field, and establishing a coordinate relation between the time sequence and the structure temperature field; and step 4, predicting the temperature at the next moment according to the coordinate relationship between the time sequence and the structural temperature field by using an LS-SVM regression algorithm based on the time sequence. Through temperature monitoring, the distribution rule of a temperature field is mastered, and the influence of the predicted temperature on the deformation of the main beam in the construction process is theoretically analyzed, so that the stress and deformation in the construction process can be timely and intuitively evaluated.

Description

Technical Field

[0001] The present invention relates to the field of bridge temperature effect analysis, and more specifically to a temperature prediction method and system for a prestressed reinforced concrete long-span beam bridge. Background Art

[0002] Prestressed concrete continuous beam bridge (abbreviated as prestressed continuous beam bridge) is an important structure widely used in large bridges. During the construction process, the closure temperature of the prestressed continuous beam bridge is a very important parameter, which directly affects the health and safety of the structure.

[0003] Prestressed continuous beam bridge is a bridge structure composed of multiple concrete continuous beams. Prestressed continuous beam bridge adopts prestressing technology to enhance the bearing capacity and stiffness of the beam, and is an important part of modern bridge engineering. During the construction process, the structural and process requirements of prestressed continuous beam bridges are very strict, and the control of closure temperature is the top priority. When selecting a reasonable main beam closure scheme, when the closure temperature is inconsistent with the design reference temperature, it is necessary to use measured data within a certain period of time to explore the temperature influence law clearly, and adjust by adding counterweights to the last segment to ensure that the bridge state is consistent with the design. Therefore, how to predict the temperature in time is of great significance for the exploration of the temperature influence law. Summary of the invention

[0004] In view of this, the present invention provides a temperature prediction method and system for a prestressed reinforced concrete large-span beam bridge to achieve real-time temperature prediction. Through real-time temperature prediction, technical means are used to timely reduce the temperature difference of the bridge and improve the safety of beam bridge construction.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] A temperature prediction method for a prestressed reinforced concrete long-span beam bridge comprises the following steps:

[0007] Step 1: Obtain the construction design position coordinates and monitor the structural temperature in the construction design position coordinates;

[0008] Step 2: Use ANSYS to model and divide the structural temperature into grids, and establish the structural temperature field according to the single structural temperature in each grid;

[0009] Step 3: Obtain the time series corresponding to the temperature of a single structure, establish a mapping relationship between the time series and the structural temperature field, and establish a coordinate relationship between the time series and the structural temperature field;

[0010] Step 4: Use the coordinate relationship between the time series and the structural temperature field, and use the LS-SVM regression algorithm based on the time series to predict the temperature at the next moment.

[0011] Optionally, it also includes obtaining the transverse temperature difference and the longitudinal temperature difference based on the temperature prediction results, and correcting the temperature of the beam bridge closure.

[0012] Optionally, in step one, the process of acquiring the construction design position coordinates is as follows: a total station is used and a height illuminator and a ranging prism installed at each control point are used as sighting targets to perform polar coordinate or trigonometric height measurement for multiple rounds of observation to obtain the three-dimensional geodetic coordinates of the control measuring points, and the construction design position coordinates of the control measuring points are calculated through coordinate transformation.

[0013] Optionally, in step three, the mapping relationship between the time series and the structural temperature field is established as follows: based on the temperature field data of a single structural temperature, image segmentation is performed on the temperature field at different coordinates of the detection area, and the temperature data sequence is reconstructed in phase space, and a mapping relationship is established between the reconstructed temperature data sequence and the time series.

[0014] Optionally, in step 2, the temperature monitoring data is subjected to dimensionality reduction processing using principal component analysis before the structural temperature is modeled and meshed using ANSYS, thereby eliminating data with a correlation less than a preset threshold.

[0015] Optionally, the correction of the bridge temperature is specifically as follows: constructing thermodynamic maps for the transverse temperature difference and the longitudinal temperature difference respectively, and selecting a correction method for the bridge temperature according to indications of the thermodynamic maps.

[0016] A temperature prediction system for a prestressed reinforced concrete long-span beam bridge, comprising:

[0017] Temperature monitoring module: used to obtain the construction design location coordinates and monitor the structural temperature in the construction design location coordinates;

[0018] Structural temperature field building module: used to divide the structural temperature into grids using ANSYS modeling, and establish the structural temperature field based on the single structural temperature in each grid;

[0019] Coordinate relationship establishment module: used to obtain the time series corresponding to the temperature of a single structure, establish the mapping relationship between the time series and the structural temperature field, and establish the coordinate relationship between the time series and the structural temperature field;

[0020] Temperature prediction module: It is used to predict the temperature at the next moment by using the LS-SVM regression algorithm based on the time series based on the coordinate relationship between the time series and the structural temperature field.

[0021] Optionally, a temperature correction module is also included: used to obtain the transverse temperature difference and the longitudinal temperature difference according to the temperature prediction result, and to correct the closing temperature of the beam bridge.

[0022] It can be seen from the above technical solution that compared with the prior art, the present invention provides a temperature prediction method and system for a prestressed reinforced concrete large-span beam bridge. Through temperature monitoring, the temperature field distribution law is mastered, and the influence of temperature on the deformation of the main beam during construction is predicted through theoretical analysis. The stress and deformation during construction can be evaluated in a timely and intuitive manner; the influence of temperature on the construction stage of the main bridge can be analyzed and predicted to ensure the cross-season and all-weather construction of the bridge; and the extreme temperature loads that may occur during construction are predicted. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0024] Figure 1 It is a schematic diagram of the process of the present invention;

[0025] Figure 2 It is a schematic diagram of the structure of the present invention. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] Ambient temperature is an important factor affecting the closure temperature of prestressed continuous beam bridges. In a high temperature environment, there will be large thermal stress inside the beam, causing thermal relaxation and plastic deformation of the prestressed steel strands. Therefore, when constructing in a high temperature environment, measures need to be taken to control the closure temperature to avoid negative effects on the structure.

[0028] The embodiment of the present invention discloses a temperature prediction method for a prestressed reinforced concrete long-span beam bridge. Figure 1 As shown, the following steps are included:

[0029] Step 1: Obtain the construction design position coordinates and monitor the structural temperature in the construction design position coordinates;

[0030] Step 2: Use ANSYS to model and divide the structural temperature into grids, and establish the structural temperature field according to the single structural temperature in each grid;

[0031] Step 3: Obtain the time series corresponding to the temperature of a single structure, establish a mapping relationship between the time series and the structural temperature field, and establish a coordinate relationship between the time series and the structural temperature field;

[0032] Step 4: Use the coordinate relationship between the time series and the structural temperature field, and use the LS-SVM regression algorithm based on the time series to predict the temperature at the next moment.

[0033] Furthermore, it also includes obtaining the transverse temperature difference and the longitudinal temperature difference based on the temperature prediction result, and correcting the closing temperature of the beam bridge.

[0034] Furthermore, in step one, the process of acquiring the construction design position coordinates is as follows: a total station is used and a height illuminator and a ranging prism installed at each control point are used as sighting targets to perform polar coordinate or trigonometric height measurement for multiple rounds of observation to obtain the three-dimensional geodetic coordinates of the control measuring points, and the construction design position coordinates of the control measuring points are calculated through coordinate transformation.

[0035] Furthermore, in step two, the present invention buries temperature sensors at different positions of different cross sections of the actual bridge to obtain temperature values ​​of the actual bridge in different seasons, at different times and under different sunshine conditions, and fits these data to obtain the temperature field distribution function of the concrete box girder; a solid model of the entire bridge at the maximum cantilever stage is established using the large-scale general finite element software ANSYS, and the deflection and stress distribution of the actual bridge under the temperature load applied according to the railway bridge regulations, highway bridge regulations and the measured temperature field are calculated respectively; by comparing the finite element simulation calculation results, an overall evaluation of the temperature effect of the bridge is made, and reasonable suggestions are put forward.

[0036] Furthermore, in step three, the mapping relationship between the time series and the structural temperature field is established as follows: based on the temperature field data of a single structural temperature, image segmentation is performed on the temperature field of different coordinates of the detection area, and the temperature data sequence is reconstructed in phase space, and a mapping relationship is established between the reconstructed temperature data sequence and the time series.

[0037] Once a bridge component is erected, the error adjustment range is very limited. In order to achieve the final reasonable state of the bridge, it is necessary to fully consider the influence of various parameters in the calculation, accurately calculate, and accurately erect. At the same time, parameter collection and feedback are carried out on the basis of the erected structure, and the next erection correction is made. Monitoring testing and monitoring measurement mainly feedback the internal forces and linear conditions of actual construction, thereby verifying the design and providing measured value data for monitoring calculation. The role of monitoring calculation is to: check the design parameters; provide the ideal linear shape and internal force data of each stage of construction, compare and analyze the measured values ​​and theoretical values ​​of each stage of construction, identify and adjust the structural parameters, predict and feedback the state of the bridge, and provide necessary control data. Therefore, in step 2, the principal component analysis method is used to reduce the dimension of the temperature monitoring data before the structural temperature is divided into grids using ANSYS modeling, and the data with correlation less than the preset threshold is eliminated.

[0038] Furthermore, the correction of the bridge temperature is specifically as follows: constructing thermodynamic maps for the transverse temperature difference and the longitudinal temperature difference respectively, and selecting a correction method for the bridge temperature according to the indication of the thermodynamic map.

[0039] At each stage of construction, in order to examine whether the deformation of the main beam conforms to the theoretical calculation data, it is necessary to monitor the deformation of each control section during the construction process, including vertical deflection, lateral and longitudinal displacement. Taking into account external influences such as temperature, the measurement time will be chosen as much as possible before sunrise in the morning or at night when the temperature is relatively constant.

[0040] When monitoring the control point position coordinates, the structural temperature should be monitored at the same time. Only after the structural temperature tends to be stable, the observed control point position coordinates can be used as monitoring results. For the standard problem of structural temperature tending to be stable, it can be determined based on experience: if the average temperature of the surface measuring points on the same section of the structural component is used as the cross-sectional test temperature of the structural component, the maximum temperature difference of the test section in the length direction of the component should not exceed 2°C, and the maximum temperature difference of the measuring point temperature on the same test section should not exceed 1°C.

[0041] Furthermore, the arrangement principle of the temperature measurement points in the present invention is as follows:

[0042] 1) The temperature measuring point should be arranged at the same position as the stress measuring point, and a stress sensor integrating temperature and stress testing should be selected.

[0043] 2) Temperature measuring points should be arranged at the upper and lower edges of the control section.

[0044] 3) For concrete structures, no less than three temperature measuring points should be arranged at each location along the outside, middle and inside of the concrete wall thickness.

[0045] The temperature measurement frequency in the present invention is as follows:

[0046] Temperature monitoring conditions and frequency should not be less than the following requirements:

[0047] 1) While testing the stress monitoring section, the temperature monitoring section in the corresponding range should be tested.

[0048] 2) When making linear measurements, if the temperature influence may be large, the temperature monitoring section in the corresponding range should be tested.

[0049] and Figure 1 Corresponding to the method shown, the present invention also discloses a temperature prediction system for a prestressed reinforced concrete long-span beam bridge, the specific structure of which is as follows Figure 2 As shown, including:

[0050] Temperature monitoring module: used to obtain the construction design location coordinates and monitor the structural temperature in the construction design location coordinates;

[0051] Structural temperature field building module: used to divide the structural temperature into grids using ANSYS modeling, and establish the structural temperature field based on the single structural temperature in each grid;

[0052] Coordinate relationship establishment module: used to obtain the time series corresponding to the temperature of a single structure, establish the mapping relationship between the time series and the structural temperature field, and establish the coordinate relationship between the time series and the structural temperature field;

[0053] Temperature prediction module: It is used to predict the temperature at the next moment by using the LS-SVM regression algorithm based on the time series based on the coordinate relationship between the time series and the structural temperature field.

[0054] Furthermore, it also includes a temperature correction module: used to obtain the transverse temperature difference and the longitudinal temperature difference according to the temperature prediction result, and correct the closing temperature of the beam bridge.

[0055] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0056] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A temperature prediction method for a prestressed reinforced concrete long-span beam bridge, characterized in that: The following steps are involved: Step 1: Obtain the construction design position coordinates and monitor the structural temperature in the construction design position coordinates; Step 2: Use ANSYS to model and divide the structural temperature into grids, and establish the structural temperature field according to the single structural temperature in each grid; Step 3: Obtain the time series corresponding to the temperature of a single structure, establish a mapping relationship between the time series and the structural temperature field, and establish a coordinate relationship between the time series and the structural temperature field; Step 4: Use the coordinate relationship between the time series and the structural temperature field, and use the LS-SVM regression algorithm based on the time series to predict the temperature at the next moment.

2. The temperature prediction method for a prestressed reinforced concrete long-span beam bridge according to claim 1 is characterized in that: It also includes obtaining the lateral temperature difference and the longitudinal temperature difference based on the temperature prediction results, and correcting the temperature of the beam bridge closure.

3. The temperature prediction method for a prestressed reinforced concrete long-span beam bridge according to claim 1 is characterized in that: In step one, the process of obtaining the construction design position coordinates is as follows: a total station is used and a height illuminator and a ranging prism installed at each control point are used as sighting targets to perform polar coordinate or trigonometric height measurement for multiple rounds of observation to obtain the three-dimensional geodetic coordinates of the control measuring points, and the construction design position coordinates of the control measuring points are calculated through coordinate transformation.

4. The temperature prediction method for a prestressed reinforced concrete long-span beam bridge according to claim 1 is characterized in that: In step three, the mapping relationship between the time series and the structural temperature field is established as follows: based on the temperature field data of a single structural temperature, the temperature field of different coordinates of the detection area is image segmented, the temperature data sequence is reconstructed in phase space, and a mapping relationship is established between the reconstructed temperature data sequence and the time series.

5. The temperature prediction method for a prestressed reinforced concrete long-span beam bridge according to claim 1, characterized in that: In step 2, the principal component analysis method is used to reduce the dimension of the temperature monitoring data before the structural temperature is modeled and meshed using ANSYS, and the data with correlation less than the preset threshold are eliminated.

6. The temperature prediction method for a prestressed reinforced concrete long-span beam bridge according to claim 2, characterized in that: The correction of bridge temperature is specifically as follows: constructing thermal maps for the transverse temperature difference and the longitudinal temperature difference respectively, and selecting the correction method of the bridge temperature according to the indication of the thermal map.

7. A temperature prediction system for a prestressed reinforced concrete long-span beam bridge, characterized in that: include: Temperature monitoring module: used to obtain the construction design location coordinates and monitor the structural temperature in the construction design location coordinates; Structural temperature field building module: used to divide the structural temperature into grids using ANSYS modeling, and establish the structural temperature field based on the single structural temperature in each grid; Coordinate relationship establishment module: used to obtain the time series corresponding to the temperature of a single structure, establish the mapping relationship between the time series and the structural temperature field, and establish the coordinate relationship between the time series and the structural temperature field; Temperature prediction module: It is used to predict the temperature at the next moment by using the LS-SVM regression algorithm based on the time series based on the coordinate relationship between the time series and the structural temperature field.

8. The temperature prediction system for a prestressed reinforced concrete long-span beam bridge according to claim 7, characterized in that: It also includes a temperature correction module: it is used to obtain the transverse temperature difference and the longitudinal temperature difference according to the temperature prediction results, and to correct the temperature of the beam bridge closure.

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