CN117054022A - Method and system for extracting fine deformation of bridge - Google Patents
Method and system for extracting fine deformation of bridge Download PDFInfo
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Abstract
The invention discloses a method and a system for extracting fine deformation of a bridge, which relate to the technical field of bridge deformation detection, and the method comprises the following steps: acquiring the lifting rail LOS deformation and the lowering rail LOS deformation of the bridge; separating the temperature deformation by using a bridge temperature deformation model; and inputting deformation data after temperature deformation separation into a bridge fusion model, and calculating the vertical trend deformation and the trend deformation along the longitudinal bridge direction of the bridge. According to the invention, the track lifting LOS deformation data and the track lowering LOS deformation data of the bridge are obtained based on satellites of different orbits, and the track lifting LOS deformation data and the track lowering LOS deformation data are combined, so that the density of monitoring points of the bridge is increased by adopting accurate data, and further, more accurate deformation parameters can be extracted; combining the temperature deformation model to accurately separate deformation caused by temperature; finally, the fine deformation parameters of the bridge are extracted by combining the bridge fusion model; the extraction precision of bridge deformation is improved effectively.
Description
Technical Field
The invention relates to the technical field of bridge deformation detection, in particular to a bridge analysis method and system based on bridge fine deformation extraction.
Background
Bridge is one of the most important traffic infrastructures in the current society, and plays an irreplaceable key role in regional economic development and traffic network construction. With the rapid development of human economy and society, the continuous growth of urban population gradually aggravates the operation burden of urban infrastructure, and especially brings serious challenges to the safe operation of the infrastructure such as urban bridges. And because the bridge operation time is continuously increased, under the action of numerous factors such as traffic jam, vehicle overload, frequent wind load, environmental deterioration, climate disasters and the like, the bridge structure inevitably has the problems of ageing, damage and uneven deformation, the problems directly or indirectly affect the health and the safety of the bridge, and the ordered development of public transportation and social economy is seriously threatened. Therefore, a scientific and efficient technical means is selected to monitor bridge deformation, and the method has important significance for preventing public casualties and property loss caused by bridge collapse and ensuring the safety of traffic infrastructure.
The traditional bridge deformation monitoring means have the defects of time consumption, labor consumption, high economic cost, serious influence by the observation environment, difficulty in synchronous observation among all measuring points and the like, and cannot effectively develop bridge deformation monitoring work. The bridge health monitoring system has the advantages of strong real-time performance and high sensitivity, but is limited by the problems of limited service life of electric parts, expensive equipment, difficult maintenance and the like, and is difficult to be widely applied to most bridges. The existing bridge deformation monitoring research results based on time sequence InSAR are mostly based on one-dimensional LOS deformation estimation temperature deformation obtained by single orbit satellite observation data, and the accuracy is not enough.
Disclosure of Invention
The invention aims to provide a method and a system for extracting fine deformation of a bridge.
In order to achieve the above object, the present invention provides the following solutions:
a method for extracting fine deformation of a bridge, the method comprising:
step 1: acquiring the ascending LOS deformation and the descending LOS deformation of the bridge according to the remote sensing satellite measurement data;
step 2: obtaining a bridge temperature deformation model, wherein the bridge temperature deformation model represents the relationship between the deformation and the temperature of a bridge;
step 3: separating temperature deformation from the track lifting LOS deformation and the track lowering LOS deformation by using the bridge temperature deformation model to obtain track lifting LOS trend deformation and track lowering LOS trend deformation of the bridge;
step 4: and carrying out fusion decomposition on the ascending rail LOS trend deformation and the descending rail LOS trend deformation to obtain the vertical trend deformation and the longitudinal bridge trend deformation of the bridge.
Optionally, the step 2 specifically includes:
determining the bridge temperature deformation model by using a least square method according to the bridge temperature data set; the bridge temperature data set comprises bridge temperature change data and deformation data corresponding to the temperature change data.
Optionally, the bridge temperature deformation model is as follows:
y＝kx+b，
wherein y represents the LOS deformation of the bridge caused by temperature change; x represents bridge temperature variation; k is a temperature influence factor and represents bridge deformation displacement caused by each 1 ℃ change of temperature; b is a constant; x is x i The temperature change of the bridge in the time interval from the first observation to the ith observation is obtained; y is i The bridge deformation observed based on SBAS in the time interval from the first observation to the ith observation is referred to; n is the number of observations.
Optionally, before step 4, the method further includes:
and synchronizing the ascending track LOS trend deformation and the descending track LOS trend deformation in a time domain and a space domain.
Optionally, the synchronizing the upward rail LOS trend deformation and the downward rail LOS trend deformation in the time domain and the space domain specifically includes:
and synchronizing the ascending track LOS trend deformation and the descending track LOS trend deformation in a time domain and a space domain by adopting a linear interpolation method and a natural neighborhood interpolation method.
Optionally, the step 4 specifically includes:
adopting a fusion decomposition model to carry out fusion decomposition on the ascending track LOS trend deformation and the descending track LOS trend deformation; the fusion decomposition model is as follows:
wherein d los tsx Indicating the deformation of the lifting rail LOS towards the trend; d, d los csk The deformation of the derailment LOS trend is represented; d, d ver Representing the vertical deformation of the bridge; d, d lon Representing deformation along the longitudinal bridge; g is a coefficient matrix; θ tsx Incident angle for an orbiting satellite SAR sensor; θ csk An incident angle for a down-track satellite SAR sensor; beta is the included angle between the bridge and the north direction; alpha tsx An azimuth angle of flight for an orbiting satellite; alpha csk Is the azimuth angle of flight of the orbiting satellite.
Optionally, the fusion decomposition model is solved by adopting a singular value decomposition method.
Optionally, step 4 further includes:
and determining the stress characteristics of the bridge based on a finite element analysis method.
Optionally, the building a finite element model, analyzing stress characteristics of the bridge specifically includes:
obtaining structural parameters, material parameters and boundary conditions of the bridge according to bridge design data;
based on structural parameters, material parameters and boundary conditions of a bridge, establishing a bridge three-dimensional structure model by using finite element software, and dividing the three-dimensional structure model into a plurality of finite element units;
inputting the finite element unit by taking the vertical trend deformation as a constraint condition;
and obtaining the stress characteristic of the bridge through finite element calculation and analysis.
The invention also provides a system for extracting the fine deformation of the bridge, which comprises:
the deformation data acquisition module is used for acquiring the ascending LOS-direction deformation and the descending LOS-direction deformation of the bridge according to the remote sensing satellite measurement data;
the temperature deformation model acquisition module is used for acquiring a bridge temperature deformation model, wherein the bridge temperature deformation model represents the relationship between the deformation and the temperature of a bridge;
the temperature deformation separation module is used for separating temperature deformation from the ascending LOS deformation and the descending LOS deformation by using the bridge temperature deformation model to obtain ascending LOS trend deformation and descending LOS trend deformation of the bridge;
and the fusion decomposition module is used for carrying out fusion decomposition on the ascending track LOS trend deformation and the descending track LOS trend deformation to obtain the vertical trend deformation and the longitudinal bridge trend deformation of the bridge.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides a method and a system for extracting fine deformation of a bridge, wherein the method comprises the following steps: acquiring the ascending LOS deformation and the descending LOS deformation of the bridge according to the remote sensing satellite measurement data; obtaining a bridge temperature deformation model; separating temperature deformation from the ascending LOS deformation and the descending LOS deformation by using the bridge temperature deformation model to obtain ascending LOS trend deformation and descending LOS trend deformation of the bridge structure; and (3) acquiring a bridge fusion model, inputting the upward rail LOS trend deformation and the downward rail LOS trend deformation into the bridge fusion model, and calculating the vertical trend deformation and the longitudinal bridge trend deformation of the bridge. Compared with the prior art that one-dimensional LOS deformation data of the bridge is obtained based on single orbit satellite observation data, and temperature deformation is estimated, the method and the device acquire the ascending LOS deformation data and the descending LOS deformation data of the bridge through satellites in different orbits, combine the ascending LOS deformation data and the descending LOS deformation data, increase the density of monitoring points of the bridge by adopting accurate data, and further facilitate extracting more accurate deformation parameters; combining the temperature deformation model to accurately separate deformation caused by temperature; finally, the fine deformation parameters of the bridge are extracted by combining the bridge fusion decomposition model; the extraction precision of bridge deformation is improved effectively.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for extracting fine deformation of a bridge, which is provided by an embodiment of the invention;
FIG. 2 is a flowchart of another method for extracting fine deformation of a bridge according to an embodiment of the present invention;
FIG. 3 is a finite element analysis modeling flow chart provided by an embodiment of the present invention;
FIG. 4 is a graph of a time series of deformation of key points and a temperature change of a bridge according to an embodiment of the present invention; FIG. 4 (a) is a graph showing positive correlation with temperature change; FIG. 4 (b) is a graph showing the negative correlation with temperature change; FIG. 4 (c) is a graph of linear deformation as dominant; fig. 4 (d) is a random vibration diagram.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
At present, the traditional bridge deformation monitoring means mainly comprise a precise level gauge, a laser interferometer, an accelerometer, a total station, a GPS and the like. The emerging bridge health monitoring system based on sensors in the last decade is also applied to the monitoring of partially newly built large bridges. The time sequence synthetic aperture radar interferometry is used as a non-contact active satellite earth observation technology, can rapidly acquire large-scale and high-precision earth surface deformation data by virtue of the advantages of low cost, all weather, periodic monitoring and the like, and is widely applied to earth surface subsidence, landslide, volcano, urban construction/structure, traffic road network and other earth object deformation monitoring in recent years. Along with the continuous improvement of the quantity and quality (including spatial resolution, time resolution, signal to noise ratio and the like) of the satellite-borne SAR data, the high-resolution X-band SAR data (such as Terra SAR-X/TanDEM-X and Italy COSMO-SkyMed in Germany) are combined with the TS-InSAR technology, so that the deformation information of different parts of the building/structure can be extracted with higher monitoring point density and deformation sensitivity, and the application potential in the bridge fine deformation monitoring work is gradually highlighted.
The traditional bridge deformation monitoring means have the defects of time consumption, labor consumption, high economic cost, serious influence by the observation environment, difficulty in synchronous observation among all measuring points and the like, and cannot effectively develop bridge deformation monitoring work. The bridge health monitoring system has the advantages of strong real-time performance and high sensitivity, but is limited by the problems of limited service life of electric parts, expensive equipment, difficult maintenance and the like, and is difficult to be widely applied to most bridges. The existing bridge deformation monitoring research results based on time sequence InSAR are mostly based on one-dimensional LOS to deformation estimation temperature deformation, lack of targeted analysis for different types of bridge deformation and stress characteristics, and rarely relate to three-dimensional deformation feature extraction and interpretation of bridge structures, and do not deeply discuss and study the stress state and health condition of the bridge after deformation.
Aiming at the problems existing in the existing bridge deformation monitoring method, the invention provides a method and a system for extracting the bridge fine deformation, which achieve the aims of extracting the bridge fine deformation parameters, acquiring the bridge stress state and researching the bridge deformation mechanism. The bridge deformation analysis method can extract accurate bridge temperature deformation, vertical deformation parameters and bridge stress states along the longitudinal bridge, accurately analyze bridge deformation rules, study bridge deformation mechanisms and provide reliable technical support and theoretical basis for bridge health monitoring work in future.
The invention aims to provide a method and a system for extracting fine deformation of a bridge.
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description.
Referring to fig. 1 and 2, the invention provides a method for extracting fine deformation of a bridge, which comprises the following steps:
step 1: acquiring the ascending LOS deformation and the descending LOS deformation of the bridge according to the remote sensing satellite measurement data;
step 2: obtaining a bridge temperature deformation model, wherein the bridge temperature deformation model represents the relationship between the deformation and the temperature of a bridge;
step 3: separating temperature deformation from the track lifting LOS deformation and the track lowering LOS deformation by using the bridge temperature deformation model to obtain track lifting LOS trend deformation and track lowering LOS trend deformation of the bridge;
step 4: and carrying out fusion decomposition on the ascending rail LOS trend deformation and the descending rail LOS trend deformation to obtain the vertical trend deformation and the longitudinal bridge trend deformation of the bridge.
In some embodiments, step 1 may specifically include:
bridge LOS deformation extraction based on time sequence InSAR: and processing the lifting rail SAR image dataset by using an SBAS-InSAR technology to obtain lifting rail LOS deformation parameters of the bridge, wherein the parameters mainly comprise data preprocessing, differential interference calculation and time and space domain deformation estimation.
In some embodiments, step 2 may specifically include:
determining the bridge temperature deformation model by using a least square method according to the bridge temperature data set; the bridge temperature data set comprises bridge temperature change data and deformation data corresponding to the temperature change data.
In some embodiments, the bridge temperature deformation model is as follows:
y＝kx+b (1)
wherein y represents the LOS deformation of the bridge caused by temperature change; x represents bridge temperature variation; k is a temperature influence factor and represents bridge deformation displacement caused by each 1 ℃ change of temperature; b is a constant; x is x i The temperature change of the bridge in the time interval from the first observation to the ith observation is obtained; y is i The bridge deformation observed based on SBAS in the time interval from the first observation to the ith observation is referred to; n is the number of observations.
The time interval between two adjacent observations is a short time interval, the time span is not too large, otherwise, the interference of structural deformation caused by load can be introduced, and the extraction accuracy of temperature deformation is affected. Such as: the time interval between two adjacent observations is the earth observation period of the SAR satellite. The SAR satellites are observed on the ground to obtain a scene image every time a period of time, and the period of each SAR satellite is fixed, for example, 12 days of TSX and 16 days of CSK.
In some embodiments, step 2 may specifically further include:
and carrying out regression analysis on seasonal deformation and seasonal temperature change data of the bridge by adopting a least square method, so as to realize modeling of the bridge temperature deformation.
In some embodiments, step 2 may specifically further include:
bridge temperature deformation modeling based on least squares regression analysis: based on temperature data and deformation data, a least square regression analysis method is utilized, the structural characteristics and material characteristics of different types of bridges are combined, a correlation model between time series deformation and temperature change of the bridge is quantitatively established, temperature influence factors are extracted according to correlation degree between time series deformation and temperature change, and finally bridge temperature deformation and structural trend deformation are separated. The relationship between the bridge key point deformation time sequence and the temperature change curve is shown in fig. 4.
In order to obtain more accurate bridge temperature deformation, the temperature deformation model of the embodiment is a relation model between the bridge time sequence deformation and the bridge structure temperature at SAR imaging moment. The surface air temperature is easy to obtain data, and the temperature of the concrete bridge deck steel bridge structure of the bridge can be obtained by air temperature conversion by using formulas (4) and (5).
When the air temperature is between 20 and 45 ℃):
when the air temperature is between-2 and-50 ℃):
wherein: t epsilon is the effective temperature (DEG C) of the bridge structure; t (T) 1 Is the daily average air temperature.
And (3) carrying out linear regression analysis by using a least square method in combination with the temperature data, and extracting the LOS deformation of the bridge caused by temperature change. The linear deformation model with temperature change can be expressed as:
Δd＝k(T m -T n )+b (6)
wherein Δd is the temperature from T n Rising to T m The relative amount of change in material length; k is a temperature influence factor and represents bridge deformation displacement caused by each 1 ℃ change of temperature; b is a constant. The parameters k and b can be obtained by the formulas (2) and (3). Equation (6) can be seen as another form of equation (1).
In some embodiments, the accuracy of the temperature deformation can be verified by:
the coefficient of linear thermal expansion is a physical quantity that can quantify the degree of thermal expansion of a solid material and represents the relative amount of change in length of an object per unit length in/°c for each 1 ℃ increase in temperature. The linear thermal expansion coefficient α of the bridge structure can be calculated according to the following formula. The accuracy of the results can be verified by comparing the linear thermal expansion coefficient estimated by the temperature deformation model with the actual physical properties of the material.
Wherein L is the original length, Δd is the temperature from T n Rising to T m The relative amount of change in material length.
In some embodiments, step 3 may specifically include:
in the bridge deformation monitoring result extracted by TS-InSAR, the total deformation d of each monitoring point is formed by long-term bridge structure trend deformation d 0 And periodic temperature deformations, in order to separate the two deformations, it is possible to introduce both deformations into the model simultaneously:
d＝k(T m -T n )+b+d 0 (8)
wherein k (T) m -T n ) +b represents a periodic temperature deformation, and the meaning of each parameter is the same as the corresponding parameter in formula (6).
The total deformation of the bridge is solved through TS-InSAR, after the temperature deformation of the bridge is obtained through modeling by using a least squares method, the temperature deformation is separated from the total deformation, and the LOS trend deformation of the bridge structure can be obtained.
In some embodiments, prior to step 4, the method may further comprise:
and synchronizing the ascending track LOS trend deformation and the descending track LOS trend deformation in a time domain and a space domain.
In some embodiments, the synchronizing the upward rail LOS toward trend deformation and the downward rail LOS toward trend deformation in the time domain and the space domain may specifically include:
and synchronizing the ascending track LOS trend deformation and the descending track LOS trend deformation in a time domain and a space domain by adopting a linear interpolation method and a natural neighborhood interpolation method.
In some embodiments, the synchronizing the ascending LOS trend deformation and the descending LOS trend deformation in the time domain and the space domain by using a linear interpolation method and a natural neighborhood interpolation method may specifically include:
according to the linear structural characteristics of the bridge, the three-dimensional deformation mainly comprises three parts of deformation along the longitudinal bridge direction, the transverse bridge direction and the vertical direction. The transverse bridge direction is restrained by the bridge support, so that the deformation magnitude is small, and the influence of the transverse bridge direction on the bridge can be ignored. It has been demonstrated by studies that the propagation direction of temperature deformation is highly dependent on the geometry of the structure, and generally manifests itself mainly in the direction along the longest side of the geometry of the structure, with the propagation direction of temperature deformation of structures of different shape characteristics being greatly different. Considering the side view imaging characteristics of the SAR sensor, removing the LOS deformation quantity of the bridge after temperature deformation can be regarded as the vector sum of the projection of the bridge along the longitudinal bridge direction and the vertical deformation in the LOS direction. Because of imaging visual angle difference of lifting and lowering track data, most of two groups of deformation monitoring points are derived from different parts of a bridge structure, fusion is difficult to be carried out in a mode of matching targets with the same name points, and because of different acquisition time of lifting and lowering track SAR data, two groups of deformation monitoring results are not uniform in a time domain. In order to solve the problem, the present embodiment adopts a time domain interpolation method and a spatial domain interpolation method, so that space-time references of two groups of data in a common period are unified. The method comprises the following steps:
according to the three-dimensional structural characteristics of the DEM and the bridge, imaging parameters of the lifting rail SAR sensor and the lifting rail LOS trend deformation of the bridge obtained in the step 3, firstly, unifying (synchronizing) time series deformation of two groups of data in a time domain by adopting a linear interpolation method; and then unifying (synchronizing) the two groups of data in the spatial domain by adopting a natural neighborhood interpolation method.
The principle of the natural neighborhood interpolation method is weighted average, namely, the calculation of the weight is limited in the nearest range, and the calculation formula for calculating the predicted value of an unknown point is as follows:
where F (X, Y) is the interpolation result at the unknown point of the coordinates (X, Y), n is the number of sample points involved in interpolation, F i (x i ,y i ) Interpolation for surrounding participation (x i ,y i ) True value, w, of a known sample point at a location i Is (x) i ,y i ) Weights of position sample points, w i The method can be obtained according to the following formula:
wherein a (X, Y) is the area of Thiessen polygon where the point to be interpolated at the coordinates (X, Y) is located, a i (x i ,y i ) For the area of the Thiessen polygon in which the known sample points taking part in interpolation around the point to be interpolated are located, a i (x i ,y i ) And n a (X, Y) is the area where the two meet.
After the space-time interpolation is completed, the lifting rail fusion decomposition can be performed (i.e. step 4 is entered).
In some embodiments, for the deformation of the lifting rail LOS of the bridge separated in the step 3 towards temperature, the following treatment may be performed:
respectively processing the LOS temperature deformation of the lifting rail of the bridge obtained in the step 3, and combining the three-dimensional structural characteristics of the bridge and the imaging parameters of the SAR sensor to obtain two groups of temperature deformation along the longitudinal bridge direction; and (3) performing space matching fusion on the two groups of temperature deformation along the longitudinal bridge by using a natural neighborhood interpolation method so as to obtain a temperature deformation field of the bridge along the longitudinal bridge.
The relationship between LOS temperature deformation and longitudinal bridging direction is as follows:
wherein d los tem Represents the temperature deformation of LOS direction, d lon tem The temperature deformation along the longitudinal bridge direction is represented, the beta temperature is the included angle between the extending direction of the bridge and the north direction, alpha is the flying azimuth angle of the satellite, and theta is the incident angle of the satellite.
Temperature is an important external environmental factor affecting bridge deformation, the influence of temperature on the structure is not negligible, and the change of temperature can lead to the occurrence of temperature effect on the bridge structure, wherein one form is uniform temperature effect, which can lead to the occurrence of displacement uniformly distributed along the longitudinal bridge direction of the bridge structure, but can not cause internal force of the structure. In another form, the gradient temperature effect is achieved, and solar radiation can enable a nonlinear temperature gradient to exist in the vertical direction or the transverse direction of the bridge, and corresponding structural sub-stress can be generated to influence structural stability of the bridge. Compared with the uniform temperature effect, the gradient temperature effect has small influence on the bridge deformation result in the magnitude and direction, so that only the influence of the uniform temperature effect of the bridge needs to be considered when the bridge temperature deformation modeling is carried out.
In some embodiments, step 4 may specifically include:
adopting a fusion decomposition model to carry out fusion decomposition on the ascending track LOS trend deformation and the descending track LOS trend deformation; the fusion decomposition model is as follows:
wherein d los tsx Indicating the deformation of the lifting rail LOS towards the trend; d, d los csk The deformation of the derailment LOS trend is represented; d, d ver Representing the vertical deformation of the bridge; d, d lon Representing deformation along the longitudinal bridge; g is a coefficient matrix; θ tsx Incident angle for an orbiting satellite SAR sensor; θ csk An incident angle for a down-track satellite SAR sensor; beta is the included angle between the bridge and the north direction; alpha tsx An azimuth angle of flight for an orbiting satellite; alpha csk Is the azimuth angle of flight of the orbiting satellite.
In some embodiments, the fused decomposition model is solved using a singular value decomposition method.
In some embodiments, the solution of the fusion decomposition model by adopting a singular value decomposition method can be specifically as follows:
the singular value decomposition is used as an important matrix decomposition method, and can achieve good effects in the aspects of noise suppression and linear inverse problem solving. The singular value decomposition of matrix G is as follows
Wherein u= (U) 1 ,…,u m ) Sum v= (V) 1 ,...,v n ) Respectively multiplying the orthogonal matrices of m-order and n-order with respective conjugate transpose matrices to obtain a unitary matrix, U T U＝V T V＝I n M×n order diagonal matrix Σ=diag (σ 1 ,…,σ n ) Is non-negative and σ 1 ≥…≥σ n And is more than or equal to 0. Element sigma on the sigma diagonal i Is a singular value of G. v i A feature vector that is G' G, also referred to as the right singular vector of G; u (u) i Is a feature vector of GG', also called a left singular vector of G.
G -1 ＝V∑ -1 U T (15)
After each non-zero element on the main diagonal of the matrix sigma is inverted, the sigma is obtained by transposition -1 I.e. the generalized inverse of Σ (pseudo-inverse).
Substituting the formula (14) into the formula (12),
and (3) carrying out inversion operation on the formula (16) to obtain the deformation of the bridge in the vertical direction and the trend along the longitudinal bridge direction:
in some embodiments, step 4 further comprises, after:
and determining the stress characteristics of the bridge based on a finite element analysis method.
Finite element analysis (Finite Element Analysis, FEA) is a mathematical approach to simulate real physical systems (e.g., geometric, dead load, dynamic load, etc.), by providing simple and interrelated elements (cells), achieving the goal of approximating a real system of infinite unknowns with a limited number of cells. In the field of bridge engineering, research based on finite element analysis is mainly applied to structural design, load evaluation, construction detection and bridge health monitoring.
As shown in fig. 3. In some embodiments, the establishing a finite element model, analyzing the stress characteristics of the bridge may specifically include:
obtaining structural parameters, material parameters and boundary conditions of the bridge according to bridge design data;
based on structural parameters, material parameters and boundary conditions of a bridge, establishing a bridge three-dimensional structure model by using finite element software, and dividing the three-dimensional structure model into a plurality of finite element units;
inputting the finite element unit by taking the vertical trend deformation as a constraint condition;
and obtaining the stress characteristic of the bridge through finite element calculation and analysis.
In some embodiments, the establishing a finite element model, analyzing the stress characteristics of the bridge may specifically further include:
based on the three-dimensional structure and the fine deformation parameters of the bridge, the bridge structure mechanical characteristics are combined, and a finite element model of the bridge is built. Firstly, referring to bridge design data, establishing a bridge three-dimensional structure model by using finite element software according to parameters such as bridge structure, materials, boundary conditions and the like, and dividing the bridge three-dimensional structure model into a plurality of finite element units; then, according to the vertical fine deformation parameters of the bridge obtained in the step 4, inputting finite element units of the bridge; and finally, obtaining the stress distribution state of the bridge through finite element calculation, and analyzing the stress characteristics of the bridge. The specific method involved in each step is as follows:
(1) Determining a displacement mode: the displacement of any point in the unit can be obtained by taking the displacement of the unit node as a basis, further, the displacement state of the whole structure system can be determined,
Δd＝Nδe (18)
where Δd represents the displacement of a point in the cell, N represents the matrix of functions of the type, and δe represents the matrix of displacements of the cell nodes.
(2) Deducing the relation between the strain at any position in the unit and the displacement of the node corresponding to the position based on the geometric equation,
ε＝Bδe (19)
where ε represents the strain matrix at any position in the cell and B represents the deformation matrix.
(3) There is a certain relationship between the stress at any position in the cell and the displacement of the cell node, which can be deduced based on a physical equation, namely the stress-strain relationship,
σ＝DBδe＝Sδe (20)
where σ represents the stress matrix at any position in the cell, D represents the elastic matrix related to the material, and S is the stress matrix.
(4) Based on the virtual displacement principle and the variational method, the stiffness equation of the unit is obtained:
Re＝Keδe (21)
where Re represents the cell node force matrix and Ke represents the cell stiffness matrix.
(5) After the stiffness equation of each unit is established, the stiffness matrix elements of each unit can be ordered according to the ordering of the corresponding displacement components, and added to obtain an overall stiffness matrix equation, and then the overall stiffness matrix equation is combined into the overall stiffness matrix equation according to boundary conditions, so that various parameters such as stress of a structural system are solved.
The invention also provides a system for extracting the fine deformation of the bridge, which comprises:
the deformation data acquisition module is used for acquiring the ascending LOS-direction deformation and the descending LOS-direction deformation of the bridge according to the remote sensing satellite measurement data;
the temperature deformation model acquisition module is used for acquiring a bridge temperature deformation model, wherein the bridge temperature deformation model represents the relationship between the deformation and the temperature of a bridge;
the temperature deformation separation module is used for separating temperature deformation from the ascending LOS deformation and the descending LOS deformation by using the bridge temperature deformation model to obtain ascending LOS trend deformation and descending LOS trend deformation of the bridge;
and the fusion decomposition module is used for carrying out fusion decomposition on the ascending track LOS trend deformation and the descending track LOS trend deformation to obtain the vertical trend deformation and the longitudinal bridge trend deformation of the bridge.
In summary, the invention has the following advantages:
(1) The invention can provide reliable technical support, theoretical basis and targeted solution for health monitoring work of different types of bridges by fusing the high-resolution lifting rail time sequence InSAR with the finite element analysis method for extracting the bridge fine deformation, and the experimental result is clear and objective.
(2) The temperature influence factors of bridge monitoring points are extracted by using a least square regression analysis method, a bridge temperature deformation model is constructed, separation of bridge temperature deformation and structural trend deformation can be realized, more accurate time sequence deformation parameters are obtained, the linear thermal expansion coefficient of a bridge structure is extracted through the bridge temperature deformation field, the linear thermal expansion coefficient is compared with the actual physical properties of materials, and the reliability of the result is verified.
(3) The bridge fine deformation extraction based on the lifting orbit SAR data fusion can successfully acquire the bridge vertical direction and mm-level fine deformation parameters along the longitudinal bridge direction, effectively improve the bridge deformation monitoring point density, and make up the limitation that single orbit satellite observation data can only acquire one-dimensional LOS deformation.
(4) The fine deformation extraction of the bridge based on the lifting rail SAR data fusion provides important data constraint for finite element analysis of the bridge. Under the constraint condition of fine deformation parameters, the bridge stress state can be obtained through finite element analysis by combining the three-dimensional structure and structural mechanical characteristics of the bridge, so that the bridge deformation mechanism is studied in depth, and the connection between the deformation characteristics and the stress characteristics of the bridge structure is explored.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
The principles and embodiments of the present invention have been described herein with reference to specific examples, the description of which is intended only to assist in understanding the methods of the present invention and the core ideas thereof; also, it is within the scope of the present invention to be modified by those of ordinary skill in the art in light of the present teachings. In view of the foregoing, this description should not be construed as limiting the invention.
Claims (10)
1. A method for extracting fine deformation of a bridge, the method comprising:
step 1: acquiring the ascending LOS deformation and the descending LOS deformation of the bridge according to the remote sensing satellite measurement data;
step 2: obtaining a bridge temperature deformation model, wherein the bridge temperature deformation model represents the relationship between the deformation and the temperature of a bridge;
step 3: separating temperature deformation from the track lifting LOS deformation and the track lowering LOS deformation by using the bridge temperature deformation model to obtain track lifting LOS trend deformation and track lowering LOS trend deformation of the bridge;
step 4: and carrying out fusion decomposition on the ascending rail LOS trend deformation and the descending rail LOS trend deformation to obtain the vertical trend deformation and the longitudinal bridge trend deformation of the bridge.
2. The method for extracting the fine deformation of the bridge according to claim 1, wherein the step 2 specifically comprises:
determining the bridge temperature deformation model by using a least square method according to the bridge temperature data set; the bridge temperature data set comprises bridge temperature change data and deformation data corresponding to the temperature change data.
3. The method for extracting the fine deformation of the bridge according to claim 2, wherein the bridge temperature deformation model is as follows:
y＝kx+b，
wherein y represents a temperatureBridge LOS deformation caused by change; x represents bridge temperature variation; k is a temperature influence factor and represents bridge deformation displacement caused by each 1 ℃ change of temperature; b is a constant; x is x i The temperature change of the bridge in the time interval from the first observation to the ith observation is obtained; y is i The bridge deformation observed based on SBAS in the time interval from the first observation to the ith observation is referred to; n is the number of observations.
4. The method for extracting fine deformation of a bridge according to claim 1, further comprising, before step 4:
and synchronizing the ascending track LOS trend deformation and the descending track LOS trend deformation in a time domain and a space domain.
5. The method for extracting the fine deformation of the bridge according to claim 4, wherein the step of synchronizing the upward-track LOS-direction trend deformation and the downward-track LOS-direction trend deformation in a time domain and a space domain specifically comprises the steps of:
and synchronizing the ascending track LOS trend deformation and the descending track LOS trend deformation in a time domain and a space domain by adopting a linear interpolation method and a natural neighborhood interpolation method.
6. The method for extracting the fine deformation of the bridge according to claim 1, wherein the step 4 specifically comprises the following steps:
adopting a fusion decomposition model to carry out fusion decomposition on the ascending track LOS trend deformation and the descending track LOS trend deformation; the fusion decomposition model is as follows:
wherein the method comprises the steps of，d los tsx Indicating the deformation of the lifting rail LOS towards the trend; d, d los csk The deformation of the derailment LOS trend is represented; d, d ver Representing the vertical deformation of the bridge; d, d lon Representing deformation along the longitudinal bridge; g is a coefficient matrix; θ tsx Incident angle for an orbiting satellite SAR sensor; θ csk An incident angle for a down-track satellite SAR sensor; beta is the included angle between the bridge and the north direction; alpha tsx An azimuth angle of flight for an orbiting satellite; alpha csk Is the azimuth angle of flight of the orbiting satellite.
7. The method for extracting the fine deformation of the bridge according to claim 6, wherein the fusion decomposition model is solved by a singular value decomposition method.
8. The method for extracting fine deformation of a bridge according to claim 1, further comprising, after the step 4:
and determining the stress characteristics of the bridge based on a finite element analysis method.
9. The method for extracting the fine deformation of the bridge according to claim 8, wherein the determining the stress characteristic of the bridge based on the finite element analysis method specifically comprises:
obtaining structural parameters, material parameters and boundary conditions of the bridge according to bridge design data;
based on structural parameters, material parameters and boundary conditions of a bridge, establishing a bridge three-dimensional structure model by using finite element software, and dividing the three-dimensional structure model into a plurality of finite element units;
inputting the finite element unit by taking the vertical trend deformation as a constraint condition;
and obtaining the stress characteristic of the bridge through finite element calculation and analysis.
10. A bridge fine deformation extraction system, the system comprising:
the deformation data acquisition module is used for acquiring the ascending LOS-direction deformation and the descending LOS-direction deformation of the bridge according to the remote sensing satellite measurement data;
the temperature deformation model acquisition module is used for acquiring a bridge temperature deformation model, wherein the bridge temperature deformation model represents the relationship between the deformation and the temperature of a bridge;
the temperature deformation separation module is used for separating temperature deformation from the ascending LOS deformation and the descending LOS deformation by using the bridge temperature deformation model to obtain ascending LOS trend deformation and descending LOS trend deformation of the bridge;
and the fusion decomposition module is used for carrying out fusion decomposition on the ascending track LOS trend deformation and the descending track LOS trend deformation to obtain the vertical trend deformation and the longitudinal bridge trend deformation of the bridge.
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