A stress self-adaptive pre-paving intelligent control method for a steel box girder bridge of incremental launching

Abstract

The present application relates to the field of bridge construction technology, especially to a kind of intelligent control method for stress self-adaptive pre-paving of steel bridge deck of incremental launching steel box girder bridge, comprising the following steps: first, build incremental launching whole process analysis model, input construction parameters to calculate paving layer stress response, determine stress allowable value;According to stress distribution, steel bridge deck is zoned and differential paving structure is set;During paving construction, stress collection elements of synchronous consolidation are embedded, and pre-deformation adjustment is combined with incremental launching displacement;During construction, internal stress of paving is measured and compared with allowable value, construction parameters are corrected according to deviation result, and the cycle is iterated until the end of incremental launching construction.The present application establishes incremental launching whole process analysis model of steel box girder, extracts paving stress extreme value envelope as allowable value, and uses the corresponding relationship between stress and construction parameters for whole process control, solves the problems of traditional experience control, lack of unified stress reference in local calculation, and lack of unified safety judgment standard.

Description

Technical Field

[0001] This invention relates to the field of bridge construction technology, and in particular to an intelligent control method for adaptive pre-paving of steel deck stress in a jacking steel box girder bridge. Background Technology

[0002] The incremental launching construction of steel box girder bridges is a common method for erecting long-span bridges. The basic process involves assembling the steel box girder segment by segment on an assembly platform, and then gradually advancing it to the designed bridge location along the bridge axis using launching equipment. To improve construction efficiency and reduce high-altitude work, a pre-paving technology for the steel bridge deck has been developed. This involves completing the steel bridge deck pavement layer on the assembly platform before the incremental launching of the steel box girder, allowing the pavement layer to participate in the launching process synchronously with the overall structure of the steel box girder. Simultaneously, with the development of curved bridges, skew bridges, and other bridges with complex spatial alignments, a combined launching construction method integrating longitudinal launching and lateral correction has emerged. Furthermore, a full-process mechanical analysis model is being used to calculate and simulate the structural response during the launching process for construction scheme design and parameter determination.

[0003] In existing steel box girder launching construction, most of the methods used are empirical stress control or local stress verification. Due to the lack of a unified stress extreme value constraint benchmark for the whole process, it is difficult to form a consistent safety judgment basis for the pavement layer during the joint launching process. Summary of the Invention

[0004] To overcome the above shortcomings, this invention provides an intelligent control method for adaptive pre-paving of steel bridge deck stress in jacking steel box girder bridges. It aims to improve the problem that existing steel box girder jacking construction methods mostly rely on empirical stress control or local stress calculation, which easily leads to difficulties in forming a consistent safety judgment basis for the pavement layer during the joint jacking process.

[0005] This invention provides the following technical solution: a method for intelligent control of adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge, comprising the following steps:

[0006] S1. Construct a full-process analysis model for the jacking of a steel box girder bridge, take the joint jacking construction process parameters as input conditions, calculate the stress response of the steel bridge deck pavement during the jacking process, establish the correspondence between the stress response of the steel bridge deck pavement and the jacking construction process parameters, and extract the stress extreme value envelope of the steel bridge deck pavement during the jacking process from the stress response as the allowable stress value.

[0007] S2. Based on the stress response distribution results, the steel bridge deck is divided into zones, and differentiated pavement structures are configured in different zones;

[0008] S3. During the formation of the differentiated pavement structure, stress acquisition elements are embedded inside the steel bridge deck pavement structure, and the stress acquisition elements are synchronously fixed with the pavement structure. The pavement structure is pre-deformed and adjusted according to the displacement changes during the jacking process.

[0009] S4. During the jacking construction, collect stress response data inside the steel bridge deck pavement structure, compare the stress response data with the allowable stress value, and obtain the stress state deviation result.

[0010] S5. Adjust the jacking construction process parameters according to the stress state deviation results, and re-input the adjusted jacking construction process parameters into the full-process analysis model of the steel box girder bridge jacking. Repeat S1 to S5 until the jacking construction is completed.

[0011] By adopting the above technical solution, a full-process analysis model of the jacking of steel box girder bridges is constructed, and the stress extreme value envelope of the steel bridge deck pavement layer during the jacking process is extracted as the allowable stress value. Then, the correspondence between the stress response of the steel bridge deck pavement layer and the parameters of the jacking construction process is integrated into the full-process analysis and control logic. This improves the problem that most existing steel box girder jacking constructions rely on empirical stress control or local stress verification. Due to the lack of a unified full-process stress extreme value constraint benchmark, it is difficult to form a consistent safety judgment basis for the pavement layer during the joint jacking process.

[0012] Furthermore, in S1, the steps for constructing the full-process analysis model of the steel box girder bridge launching include:

[0013] Discretize the steel box girder bridge to generate beam segment elements;

[0014] By using the piers and temporary supports as fulcrum constraint nodes, spatial constraint relationships between each beam segment unit are established.

[0015] The steel bridge deck pavement layer is treated as a continuous layer unit attached to the top plate of the steel box girder, and the continuous layer unit is assigned layered calculation properties.

[0016] The parameters of the joint jacking construction process are used as boundary conditions for each construction step and input into the full-process analysis model of the steel box girder bridge jacking after discretization and the establishment of spatial constraint relationships.

[0017] Furthermore, in S1, the step of calculating the stress response of the steel bridge deck pavement layer during the jacking process includes:

[0018] Based on the analysis model of the entire process of launching the steel box girder bridge, the nodal displacement distribution of the steel box girder bridge in each launching construction step is solved.

[0019] The nodal displacement of the top plate of the steel box girder is used as a boundary condition and transferred to the steel bridge deck pavement.

[0020] Calculate the strain distribution of the steel bridge deck pavement layer based on the deformation gradient of the steel bridge deck pavement layer under the boundary conditions.

[0021] The stress distribution of the steel bridge deck pavement is calculated based on the strain distribution of the pavement.

[0022] Further, in S1, the step of extracting the stress extreme value envelope of the steel bridge deck pavement layer during the jacking process as the allowable stress value from the stress response includes:

[0023] The stress response data of the steel bridge deck pavement layer in all jacking construction steps are traversed and a stress time series is formed.

[0024] The maximum tensile stress, maximum compressive stress, and maximum shear stress values ​​are extracted for each spatial node in the stress time series set.

[0025] The maximum tensile stress, maximum compressive stress, and maximum shear stress values ​​of the same spatial node are combined and compared to determine the node control stress value;

[0026] The nodal control stress values ​​of all spatial nodes are spatially aggregated to form a stress extremum envelope.

[0027] Furthermore, in S2, the step of partitioning the steel bridge deck based on the distribution results of the stress response includes:

[0028] Extract the set of nodal stress values ​​of the steel bridge deck pavement layer under the action of various parameters in the jacking construction process;

[0029] Spatial coordinate mapping is performed on the set of nodal stress values ​​to generate a spatial distribution matrix of stress response on the steel bridge deck.

[0030] Gradient variation calculations were performed on the spatial distribution matrix of stress response on the steel bridge deck to obtain stress gradient variation data;

[0031] The steel bridge deck partition boundaries are determined based on stress gradient variation data, and the partition results are output.

[0032] Furthermore, in S2, the step of configuring differentiated paving structures in different zones includes:

[0033] Based on the zoning results of the steel bridge deck, the pavement layer thickness parameters and pavement layer material parameters corresponding to each zone are determined. The pavement layer thickness parameters include the pavement layer thickening ratio in the stress-sensitive area.

[0034] Map the pavement thickness parameters and pavement material parameters of each zone to the steel bridge deck area of ​​the corresponding zone;

[0035] Based on the pavement layer thickness parameters and pavement layer material parameters corresponding to each zone, a layered pavement structure composition sequence is generated within the corresponding zone;

[0036] According to the sequence of the layered paving structure, the paving structure in different zones is laid and formed.

[0037] Furthermore, in S3, the step of embedding the stress acquisition element inside the steel bridge deck pavement structure and synchronously consolidating the stress acquisition element with the pavement structure includes:

[0038] During the formation of the steel bridge deck pavement structure, the embedding location of the stress acquisition element inside the steel bridge deck pavement structure is determined, and a set of embedding location coordinates is generated.

[0039] When the steel bridge deck pavement structure is in an uncured state, the stress acquisition element is placed into the preset embedment depth position inside the steel bridge deck pavement structure according to the aforementioned embedment location coordinate set.

[0040] After the stress acquisition element is placed, a holding constraint is applied to the spatial position of the stress acquisition element so that the stress acquisition element maintains the spatial position corresponding to the set of embedded position coordinates before the steel bridge deck pavement structure is cured.

[0041] During the curing process of the steel bridge deck pavement structure, the stress acquisition element is simultaneously cured with the steel bridge deck pavement structure.

[0042] Furthermore, in S4, the step of collecting stress response data inside the steel bridge deck pavement structure during the jacking construction includes:

[0043] The strain signal output by the stress acquisition element inside the steel bridge deck pavement structure is continuously sampled to form a raw strain signal sequence;

[0044] The original strain signal sequence is time-calibrated according to the time progression relationship of the jacking construction process to generate time-series strain data corresponding to the jacking construction stage;

[0045] Temperature correction processing is performed on time-series strain data to generate corrected strain data;

[0046] The corrected strain data were converted into stress response data within the steel bridge deck pavement structure.

[0047] Further, in S4, the step of comparing the stress response data with the allowable stress value to obtain the stress state deviation result includes:

[0048] Obtain stress response data inside the steel bridge deck pavement structure and allowable stress values ​​at corresponding locations on the steel bridge deck pavement structure;

[0049] The stress response data and allowable stress values ​​are matched according to the spatial coordinates of the steel bridge deck pavement structure.

[0050] The difference between the matched stress response data and the allowable stress value is calculated to generate stress deviation data.

[0051] Stress state deviation results are generated based on stress deviation data.

[0052] Furthermore, in S5, the step of adjusting the jacking construction process parameters according to the stress state deviation results and re-inputting the adjusted jacking construction process parameters into the full-process analysis model of the steel box girder bridge jacking includes:

[0053] Component analysis was performed on the stress state deviation results to obtain deviation direction and deviation magnitude information that correspond one-to-one with each jacking construction process parameter;

[0054] Based on the correspondence between the stress response of the steel bridge deck pavement and the parameters of the jacking construction process, the corresponding influence relationship between each jacking construction process parameter and the stress state deviation result is determined.

[0055] Based on the corresponding influence relationship and deviation information, the parameters of each jacking construction process are corrected to obtain the adjusted jacking construction process parameters;

[0056] The adjusted jacking process parameters were re-inputted into the full-process analysis model of the steel box girder bridge jacking, and the correspondence between the stress response of the steel bridge deck pavement and the jacking process parameters was updated.

[0057] The present invention has the following beneficial effects:

[0058] 1. In this invention, a full-process analysis model of the jacking of a steel box girder bridge is constructed, and the stress extreme value envelope of the steel bridge deck pavement layer during the jacking process is extracted as the allowable stress value. Then, the correspondence between the stress response of the steel bridge deck pavement layer and the parameters of the jacking construction process is integrated into the full-process analysis and control logic. This improves the problem that most existing steel box girder jacking constructions rely on empirical stress control or local stress verification. Due to the lack of a unified full-process stress extreme value constraint benchmark, it is difficult to form a consistent safety judgment basis for the pavement layer during the joint jacking process.

[0059] 2. In this invention, the steel bridge deck is divided into zones based on the distribution of stress response of the steel bridge deck pavement layer, and differentiated pavement structures are configured in different zones. This allows the steel bridge deck pavement layer to form corresponding structural adaptations under different spatial stress distribution conditions. This improves the problem that most existing steel bridge deck pavement structures adopt uniform structural parameter design, which does not consider the spatial stress difference distribution during the jacking process, resulting in insufficient adaptability of local stress concentration areas.

[0060] 3. In this invention, stress response data inside the steel bridge deck pavement structure is collected during the jacking construction process and compared with the allowable stress value to obtain the stress state deviation result. Based on the deviation result, the jacking construction process parameters are adjusted and fed back into the full-process analysis model of the steel box girder bridge jacking, thereby forming an iterative closed-loop control of construction parameters and stress response. This improves the problem that most existing jacking construction process control methods adopt a one-way parameter correction method. Due to the lack of a continuous feedback update mechanism based on the stress state of the pavement layer, the construction parameters are difficult to adapt to the dynamic structural response changes during the jacking process. Attached Figure Description

[0061] Figure 1 This is a flowchart of an intelligent control method for adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge according to the present invention.

[0062] Figure 2 This is a flowchart illustrating the construction of the full-process analysis model and stress response calculation for the steel box girder bridge launching in this invention.

[0063] Figure 3 This is a flowchart of the stress extremum envelope extraction process for the steel bridge deck pavement layer in this invention;

[0064] Figure 4 This is a flowchart illustrating the stress response distribution zoning and differentiated pavement structure configuration of the steel bridge deck in this invention.

[0065] Figure 5 This is a flowchart illustrating the embedding, synchronous consolidation, and pre-deformation adjustment of the stress acquisition element in this invention.

[0066] Figure 6 This is a module architecture diagram of the intelligent control system for adaptive pre-paving of steel bridge deck stress in an embodiment of the present invention. Detailed Implementation

[0067] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0068] In an embodiment of the present invention, a method for adaptive pre-laying intelligent control of steel deck stress in a jacking steel box girder bridge is provided, such as... Figure 1As shown, the process includes the following steps: S1. Construct a full-process analysis model for the jacking of a steel box girder bridge, take the joint jacking construction process parameters as input conditions, calculate the stress response of the steel bridge deck pavement layer during the jacking process, establish the correspondence between the stress response of the steel bridge deck pavement layer and the jacking construction process parameters, and extract the stress extreme value envelope of the steel bridge deck pavement layer during the jacking process from the stress response as the allowable stress value.

[0069] like Figure 2 As shown, further, in S1, the steps for constructing the full-process analysis model of the steel box girder bridge launching process include:

[0070] Discretize the steel box girder bridge to generate beam segment elements;

[0071] By using the piers and temporary supports as fulcrum constraint nodes, spatial constraint relationships between each beam segment unit are established.

[0072] The steel bridge deck pavement layer is treated as a continuous layer unit attached to the top plate of the steel box girder, and the continuous layer unit is given layered calculation properties.

[0073] The parameters of the joint jacking construction process are used as boundary conditions for each construction step and input into the full-process analysis model of the jacking of the steel box girder bridge after discretization and the establishment of spatial constraint relationships.

[0074] Specifically, the steel box girder bridge is first discretized, dividing it into several segment units along the longitudinal direction. The length of each segment unit is determined based on the curvature gradient; smaller unit lengths are used where curvature changes drastically, and larger unit lengths are used where curvature is gentle. Piers and temporary supports are used as support constraint nodes, and vertical and lateral displacement constraints are applied at these nodes to establish spatial constraint relationships between segment units, forming a complete structural constraint system. The steel bridge deck pavement is used as a continuous layer unit attached to the top plate of the steel box girder. Geometric properties are assigned to the continuous layer units based on the actual thickness of the pavement, and modulus and density values ​​are assigned according to the pavement material layers. The parameters of the joint jacking construction process are used as boundary conditions for each construction step and input into the discretized and spatially constraint-established full-process analysis model of the steel box girder bridge jacking. These parameters include longitudinal jacking step length, lateral correction stroke, longitudinal jacking force, lateral jacking force, and lateral jacking inner and outer synchronization deviation. Each construction step corresponds to a set of parameters. Boundary conditions are applied sequentially according to the construction sequence. The synchronous deviation of the inner and outer sides of the lateral jacks is simulated by setting the jacking displacement of the inner and outer jacks to different values. The deviation is applied according to the preset percentage or absolute value of the deviation to reflect the transient torsional effect on the beam during the lateral correction process. Through the above discretization processing, constraint relationship establishment, pavement layer attribute assignment and boundary condition input, an analytical model that can be directly used for simulation calculation of the entire jacking process is formed. On this basis, the correspondence between the stress response of the steel bridge deck pavement layer and the jacking construction process parameters is established in S1. A parametric scanning method is used: the jacking construction process parameters are changed sequentially at preset step sizes near the nominal value. Each time the parameter is changed, the simulation calculation of the entire jacking process is re-executed. The stress response change of each stress control point in the stress control sensitive area is recorded. The ratio of the stress response change to the corresponding parameter change is used as the stress sensitivity coefficient of the parameter at that control point. The stress sensitivity coefficients of all control points are summarized to form a quantitative mapping relationship.

[0075] Furthermore, in S1, the steps for calculating the stress response of the steel bridge deck pavement layer during the jacking process include:

[0076] Based on the full-process analysis model of the jacking of steel box girder bridge, the nodal displacement distribution of the steel box girder bridge in each jacking construction step is solved;

[0077] The nodal displacement of the top plate of the steel box girder is used as a boundary condition and transferred to the steel bridge deck pavement.

[0078] Calculate the strain distribution of the steel bridge deck pavement layer based on the deformation gradient of the pavement layer under boundary conditions.

[0079] The stress distribution of the steel bridge deck pavement is calculated based on the strain distribution of the pavement.

[0080] Specifically, based on the full-process analysis model of the jacking of a steel box girder bridge, the nodal displacement distribution of the steel box girder bridge is solved step by step according to the construction sequence. The nodal displacement distribution of each construction step is obtained by solving the equilibrium equations, which include the stiffness contribution of each element and the load terms corresponding to the boundary conditions. The nodal displacements of the top plate of the steel box girder are used as boundary conditions and transferred to the steel bridge deck pavement layer. The transfer method is to extract the displacement values ​​of each node on the upper surface of the top plate of the steel box girder and use the extracted displacement values ​​as the displacement boundary conditions of the bottom surface of the continuous layer unit of the steel bridge deck pavement layer. After obtaining the displacement boundary conditions of the bottom surface of the steel bridge deck pavement layer, shape function interpolation is performed on the displacement boundary conditions within the continuous layer unit, and the deformation gradient is obtained by differentiating along the thickness direction. The strain distribution of the steel bridge deck pavement layer is calculated based on the deformation gradient. The relationship between strain and displacement satisfies ;in For strain components, and For displacement components, and Using spatial coordinates, the strain components include longitudinal normal strain, transverse normal strain, and in-plane shear strain. Based on the strain distribution of the steel bridge deck pavement, the stress distribution of the pavement is calculated using the constitutive relation of the pavement material. The relationship between stress and strain satisfies... ;in For stress components, The elastic matrix of the pavement material is determined by taking values ​​for the elastic parameters of low-modulus epoxy asphalt concrete and medium-modulus epoxy asphalt concrete assigned by each layer. The stress components include longitudinal normal stress, transverse normal stress, and in-plane shear stress. Simultaneously, interface elements are set at the interface between the steel bridge deck pavement and the top plate of the steel box girder. The interface elements adopt a cohesive constitutive model, and the interface shear stiffness is determined based on the shear modulus of the high-elasticity epoxy resin primer. The interface bond strength is taken as the nominal shear strength value of the high-elasticity epoxy resin primer. The relative slip between the upper and lower surfaces of the interface elements is extracted, and the interlayer shear stress is calculated based on the constitutive relationship of the interface elements. The interlayer shear stress is the shear stress at the interface between the pavement and the steel bridge deck. After calculation, the values ​​of longitudinal normal stress, transverse normal stress, in-plane shear stress, and interlayer shear stress at the interface are obtained for each spatial node of the steel bridge deck pavement under each construction step.

[0081] like Figure 3 As shown, further, in S1, the step of extracting the stress extreme value envelope of the steel bridge deck pavement layer during the jacking process as the allowable stress value from the stress response includes:

[0082] The stress response data of the steel bridge deck pavement layer in all jacking construction steps are traversed and a stress time series is formed.

[0083] The maximum tensile stress, maximum compressive stress, and maximum shear stress values ​​are extracted for each spatial node in the stress time series set.

[0084] The maximum tensile stress, maximum compressive stress, and maximum shear stress values ​​of the same spatial node are combined and compared to determine the node control stress value;

[0085] The nodal control stress values ​​of all spatial nodes are spatially aggregated to form a stress extremum envelope.

[0086] Specifically, in step S1, when extracting the stress extremum envelope of the steel bridge deck pavement layer during the jacking process from the stress response as the allowable stress value, the stress response data of the steel bridge deck pavement layer in all jacking construction steps are traversed. The stress components of each spatial node in each construction step are arranged in the order of the construction steps to form a stress time series set for each spatial node. For each spatial node in the stress time series set, the extrema of each stress component are extracted: the maximum positive value of the longitudinal normal stress and the transverse normal stress are extracted as the tensile stress extremum of that node, and the minimum negative value of the longitudinal normal stress and the transverse normal stress are extracted as the compressive stress extremum of that node. The maximum absolute value of the in-plane shear stress is taken as the extreme value of the in-plane shear stress of the node, and the maximum absolute value of the inter-layer shear stress is extracted as the extreme value of the inter-layer shear stress of the node. The extreme values ​​of each stress of all spatial nodes are spatially summarized, and tensile stress extreme value envelope, compressive stress extreme value envelope, in-plane shear stress extreme value envelope, and inter-layer shear stress extreme value envelope covering the entire bridge deck are formed according to the planar coordinate position of each node. Each stress extreme value envelope is the allowable stress value of the corresponding stress type of the steel bridge deck pavement layer during the jacking process. In this scheme, the allowable stress value is directly taken as the value of each stress extreme value envelope, and the graded early warning threshold is set in the subsequent monitoring stage.

[0087] S2. Based on the distribution of stress response, the steel bridge deck is divided into zones, and differentiated pavement structures are configured in different zones.

[0088] like Figure 4 As shown, further, in S2, the step of partitioning the steel bridge deck based on the stress response distribution results includes:

[0089] Extract the set of nodal stress values ​​of the steel bridge deck pavement layer under the action of various parameters in the jacking construction process;

[0090] Spatial coordinate mapping is performed on the set of nodal stress values ​​to generate a spatial distribution matrix of stress response on the steel bridge deck.

[0091] Gradient variation calculations were performed on the spatial distribution matrix of stress response on the steel bridge deck to obtain stress gradient variation data;

[0092] The steel bridge deck partition boundaries are determined based on stress gradient variation data, and the partition results are output.

[0093] Specifically, in the step of partitioning the steel bridge deck based on the stress response distribution in S2, the set of nodal stress values ​​of the steel bridge deck pavement layer under the action of parameters in each jacking construction process is extracted. The set of nodal stress values ​​includes the longitudinal normal stress, transverse normal stress, in-plane shear stress, and inter-layer shear stress of each spatial node of the steel bridge deck pavement layer under all construction steps. Spatial coordinate mapping is performed on the set of nodal stress values, and the plane coordinates of each node are mapped to the corresponding extreme values ​​of tensile stress, compressive stress, in-plane shear stress, and inter-layer shear stress, respectively, to generate a spatial distribution matrix of the steel bridge deck stress response. Gradient change calculation is performed on the spatial distribution matrix of the steel bridge deck stress response. The difference between the stress extreme values ​​of adjacent nodes is calculated along the longitudinal and transverse directions, and the absolute value of the difference is taken as the stress gradient in that direction. The larger value of the longitudinal stress gradient and the transverse stress gradient of each stress component is taken as the node position. The system collects comprehensive stress gradient change data; based on this data, it determines the zoning boundaries of the steel bridge deck, with the zoning boundaries located at nodes where local peaks appear in the comprehensive stress gradient change data. Adjacent areas where the comprehensive stress gradient change data exceeds a preset gradient threshold are designated as stress-sensitive zones, while areas where the comprehensive stress gradient change data is less than or equal to the preset gradient threshold are designated as conventional stress zones. In this scheme, the preset gradient threshold is 1.5 times the average value of the comprehensive stress gradient change data at each node. The stress-sensitive zones are further divided into three typical areas based on the stress concentration causes: lateral jacking sensitive zones, pier top negative bending moment zones, and corner shear stress concentration zones. The lateral jacking sensitive zones correspond to stress concentration locations caused by lateral correction torsion, the pier top negative bending moment zones correspond to stress concentration locations caused by negative bending moments at the supports, and the corner shear stress concentration zones correspond to stress concentration locations caused by corner shearing of the curve segment.

[0094] Furthermore, in S2, the steps for configuring differentiated paving structures within different zones include:

[0095] Based on the zoning results of the steel bridge deck, the pavement layer thickness parameters and pavement layer material parameters corresponding to each zone are determined. The pavement layer thickness parameters include the pavement layer thickening ratio in the stress-sensitive area.

[0096] Map the pavement thickness parameters and pavement material parameters of each zone to the steel bridge deck area of ​​the corresponding zone;

[0097] Based on the pavement layer thickness parameters and pavement layer material parameters corresponding to each zone, a layered pavement structure composition sequence is generated within the corresponding zone;

[0098] Following the sequence of layered paving structures, the paving structures in different zones are laid and formed.

[0099] Specifically, the entire steel bridge deck is first subjected to sandblasting to remove rust, achieving a cleanliness level of Sa2.5 and a roughness of Rz 50μm to 100μm. After sandblasting, the pavement layer thickness and material parameters for each zone are determined based on the zoning results of the steel bridge deck. The pavement layer thickness parameters include the pavement layer thickening ratio in stress-sensitive areas. In this scheme, the pavement layer thickness in stress-sensitive areas is increased by 25% compared to the pavement layer thickness in conventional stress areas. The pavement layer material parameters include the dynamic modulus of the lower low-modulus epoxy asphalt concrete and the upper medium-modulus epoxy asphalt concrete. In this scheme, the preferred dynamic modulus of the lower low-modulus epoxy asphalt concrete is 500MPa. The dynamic modulus of the upper medium-modulus epoxy asphalt concrete is preferably between 1500MPa and 2200MPa, up to 800MPa. The pavement layer thickness parameters and pavement material parameters corresponding to each zone are mapped to the corresponding steel bridge deck area, establishing a one-to-one correspondence between zones and pavement parameters. Based on the pavement layer thickness parameters and pavement material parameters corresponding to each zone, a layered pavement structure sequence is generated within the corresponding zone. The layered pavement structure sequence, from bottom to top, consists of a high-elasticity epoxy resin primer layer, a low-modulus epoxy asphalt concrete lower layer, and a medium-modulus epoxy asphalt concrete upper layer. The thickness of the high-elasticity epoxy resin primer layer in the stress-sensitive zone is greater than the thickness of the primer layer in the conventional stress zone. In this scheme, the thickness of the high-elasticity epoxy resin primer layer in the conventional stress zone is preferably 1mm to 2mm, and the thickness of the high-elasticity epoxy resin primer layer in the stress-sensitive zone is preferably 3mm to 5mm. The dynamic modulus of the high-elasticity epoxy resin primer layer does not exceed 100MPa, and the elongation at break is not less than 50%. Following the layered paving structure sequence, a paver is used to lay and shape the paving structure in different zones according to the zone boundaries. After the high-elasticity epoxy resin primer layer is completed, the lower layer of low-modulus epoxy asphalt concrete is immediately laid within the wet time window before it dries to ensure a continuously bonded stress-relieving system at the interface. A sloping gradual transition is used at the boundary between the stress-sensitive zone and the conventional stress zone. The section length is not less than 10 times the thickness difference between the two sides. During paving, the materials in both zones are simultaneously rolled and formed in the transition section to avoid obvious joints and abrupt changes in thickness. In this gradient modulus composite pavement structure, the lower layer of low-modulus epoxy asphalt concrete undergoes flexible deformation first under the action of jacking stress to absorb and disperse stress energy. The upper layer of medium-modulus epoxy asphalt concrete provides structural integrity and functionality. The modulus increases gradually from bottom to top to avoid stress concentration caused by abrupt changes in modulus and to inhibit the reflection and propagation of cracks from bottom to top. With the above-mentioned quantitatively designed differentiated gradient modulus pavement structure, even if the subsequent active control system temporarily fails due to a malfunction, the pavement structure itself can still independently resist the most unfavorable stress during the entire jacking process, avoiding cracking and debonding.

[0100] S3. During the formation of the differentiated pavement structure, stress acquisition elements are embedded inside the steel bridge deck pavement structure, and the stress acquisition elements are synchronously fixed with the pavement structure. The pavement structure is pre-deformed and adjusted according to the displacement changes during the jacking process.

[0101] like Figure 5 As shown, further, in S3, the step of embedding the stress acquisition element inside the steel bridge deck pavement structure and synchronously consolidating the stress acquisition element with the pavement structure includes:

[0102] During the formation of the steel bridge deck pavement structure, the embedding location of the stress acquisition element inside the steel bridge deck pavement structure is determined, and a set of embedding location coordinates is generated.

[0103] When the steel bridge deck pavement structure is in an uncured state, the stress acquisition elements are assembled according to the coordinates of their embedding positions and placed into the preset embedding depth positions inside the steel bridge deck pavement structure.

[0104] After the stress acquisition element is installed, a holding constraint is applied to the spatial position of the stress acquisition element so that the stress acquisition element maintains the spatial position corresponding to the set of embedded position coordinates before the steel bridge deck pavement structure is cured.

[0105] During the curing process of the steel bridge deck pavement structure, the stress acquisition element is simultaneously cured with the steel bridge deck pavement structure.

[0106] Specifically, in the step S3 of embedding stress acquisition elements inside the steel bridge deck pavement structure and synchronously consolidating the stress acquisition elements with the pavement structure, fiber optic strain sensors and fiber optic temperature sensors are selected as the stress acquisition elements. During the formation of the steel bridge deck pavement structure, specifically within the time window between the completion of the lower layer of low-modulus epoxy asphalt concrete paving and the start of the upper layer of medium-modulus epoxy asphalt concrete paving, the embedding position of the stress acquisition elements inside the steel bridge deck pavement structure is determined. The embedding position is determined based on the stress gradient distribution within the stress control sensitive area divided in S1. Fiber optic strain sensors are installed longitudinally and laterally in the transverse jacking sensitive area to form an orthogonal sensing grid. Fiber optic strain sensors are installed longitudinally in the negative bending moment area at the pier top. The sensors include fiber optic strain sensors installed along a 45° diagonal in the corner shear stress concentration area to indirectly monitor the principal shear stress. Fiber optic temperature sensors are simultaneously deployed next to each fiber optic strain sensor for temperature compensation. Sensors are densely deployed at locations with large stress gradients, generating a set of embedding location coordinates. While the lower layer of low-modulus epoxy asphalt concrete is in an uncured, plastic state, the stress acquisition elements are placed at a preset embedding depth within the steel bridge deck pavement structure, corresponding to the embedding location coordinates. The preset embedding depth is half the thickness of the lower pavement layer. After the stress acquisition elements are placed, a holding constraint is applied to their spatial position using temporary positioning clamps, ensuring the stress acquisition elements remain firmly in place on the steel bridge deck pavement. Before the structure solidifies, maintain the spatial position corresponding to the set of embedded location coordinates to prevent displacement of the stress acquisition element due to the flow of paving materials or vibration operations. During the solidification process of the steel bridge deck paving structure, as the low-modulus epoxy asphalt concrete gradually solidifies, the stress acquisition element and the steel bridge deck paving structure are synchronously solidified to form an integral structure. After solidification, there is no relative slippage between the stress acquisition element and the paving material. The sensor leads are protected by flexible sheaths inside the paving layer. The sheaths are synchronously solidified with the surrounding paving material. The leads are uniformly led out from both sides of the bridge deck and converge to a waterproof junction box installed on the inner side of the web at the beam end. The waterproof junction box has a protection level of not less than IP67 to prevent compression or rainwater intrusion during the jacking process before connecting to the data acquisition module. For S3... Pre-deformation adjustment: Before the paving layer is laid, the analysis model of the entire process of the steel box girder bridge jacking established by S1 is used to extract the cumulative change value of vertical displacement of each node of the bridge deck during the entire process of the combined longitudinal and transverse jacking, forming the envelope diagram of the pre-camber change of the entire bridge deck; During the paving of the lower and upper layers, according to the cumulative change value of vertical displacement of each node, the principle of equal reverse compensation is adopted. In areas where settlement is predicted, the paving layer thickness is increased by an equal amount, and in areas where bulging is predicted, the paving layer thickness is decreased by an equal amount. The paving thickness adjustment is executed in real time through the elevation control system of the paver screed, and the thickness control deviation does not exceed ±1mm, so that the elevation of the top surface of the paving layer is restored to the design alignment after the steel box girder has undergone all jacking steps and is finally in place;When setting tiered early warning thresholds for the data acquisition module, the allowable stress value at each control point is used as a benchmark. A yellow warning is triggered when the stress response data reaches 70% of the allowable stress value, and a red warning is triggered when the stress response data reaches 85% of the allowable stress value.

[0107] S4. During the jacking construction, collect stress response data inside the steel bridge deck pavement structure, compare the stress response data with the allowable stress value, and obtain the stress state deviation result.

[0108] Furthermore, in S4, the steps for collecting stress response data within the steel bridge deck pavement structure during the jacking construction process include:

[0109] The strain signal output by the stress acquisition element inside the steel bridge deck pavement structure is continuously sampled to form a raw strain signal sequence;

[0110] The original strain signal sequence is time-calibrated according to the time progression relationship of the jacking construction process to generate time-series strain data corresponding to the jacking construction stage;

[0111] Temperature correction processing is performed on time-series strain data to generate corrected strain data;

[0112] The corrected strain data were converted into stress response data within the steel bridge deck pavement structure.

[0113] Specifically, in the step of collecting stress response data inside the steel bridge deck pavement structure during the jacking construction in S4, the strain signal output by the stress acquisition element inside the steel bridge deck pavement structure is continuously sampled. The sampling frequency is set according to the jacking speed. In this scheme, the sampling frequency is 1Hz when the jacking speed is below 5mm / min, 5Hz when the jacking speed is between 5mm / min and 10mm / min, and 10Hz when the jacking speed is above 10mm / min. After sampling, a raw strain signal sequence is formed. The raw strain signal sequence is time-calibrated according to the time progression of the jacking construction process. Each sampling data point is labeled with the corresponding jacking construction step number and timestamp, generating time-series strain data for the corresponding jacking construction stage. The time-series strain data is then subjected to temperature correction processing. The temperature correction formula is as follows: ;in To correct the strain data; These are the raw strain readings from the time-series strain data; The coefficient of thermal expansion of the fiber Bragg grating strain sensor; The coefficient of thermal expansion of the pavement material at the location where the stress acquisition element is buried is determined by taking the corresponding coefficient of thermal expansion value according to the type of pavement material in the zone where the burial location is located. The value represents the difference between the current temperature and the reference temperature, which is the temperature at which the pavement layer was fully cured. After temperature correction, corrected strain data is generated. This corrected strain data is then converted into stress response data within the steel bridge deck pavement structure. The stress conversion formula is as follows: ;in For stress response data, The elastic modulus of the pavement material at the location where the stress acquisition element is embedded is determined by taking the corresponding modulus value of low-modulus epoxy asphalt concrete or medium-modulus epoxy asphalt concrete according to the zone where the stress acquisition element is embedded.

[0114] Furthermore, in S4, the step of comparing the stress response data with the allowable stress value to obtain the stress state deviation result includes:

[0115] Obtain stress response data inside the steel bridge deck pavement structure and allowable stress values ​​at corresponding locations on the steel bridge deck pavement structure;

[0116] The stress response data and allowable stress values ​​are matched according to the spatial coordinates of the steel bridge deck pavement structure.

[0117] The difference between the matched stress response data and the allowable stress value is calculated to generate stress deviation data.

[0118] Stress state deviation results are generated based on stress deviation data.

[0119] Specifically, in step S4, when comparing the stress response data with the allowable stress value to obtain the stress state deviation result, the stress response data inside the steel bridge deck pavement structure and the allowable stress value at the corresponding position of the steel bridge deck pavement structure are obtained. The stress response data are the stress values ​​at the positions of each stress acquisition element obtained in the previous conversion step, and the allowable stress values ​​are the values ​​of the tensile stress extreme value envelope, compressive stress extreme value envelope, in-plane shear stress extreme value envelope, and inter-layer shear stress extreme value envelope established in S1 at the corresponding spatial coordinate positions. The stress response data and the allowable stress value are matched according to the spatial coordinates of the steel bridge deck pavement structure. The matching method is to take the plane coordinates of each stress acquisition element and find the allowable value of the corresponding stress type at the same coordinate position in the spatial distribution of the allowable stress value to form a one-to-one corresponding data pair. The difference between the matched stress response data and the allowable stress value is calculated. The difference calculation method is as follows: ;in This represents the stress deviation data at the location of the i-th stress acquisition element. For the stress response data at this location, This represents the allowable stress value for the corresponding stress type at that location. Stress state deviation results are generated based on the stress deviation data, including the stress deviation value, stress type, and deviation direction at each stress acquisition element location. This scheme uniformly defines tensile stress as positive, compressive stress as negative, and shear stress as controlled by its absolute value. A positive deviation is defined when the measured tensile stress exceeds the allowable tensile stress value; a negative deviation is defined when the measured compressive stress algebraic value is less than the allowable compressive stress algebraic value; a shear stress deviation is defined when the measured absolute shear stress value exceeds the allowable absolute shear stress value; all other cases are considered no deviation.

[0120] S5. Adjust the jacking construction process parameters according to the stress state deviation results, and re-input the adjusted jacking construction process parameters into the full-process analysis model of the steel box girder bridge jacking. Repeat S1 to S5 until the jacking construction is completed.

[0121] Furthermore, in S5, the steps of adjusting the jacking process parameters based on the stress state deviation results and re-inputting the adjusted jacking process parameters into the full-process analysis model of the steel box girder bridge jacking include:

[0122] Component analysis was performed on the stress state deviation results to obtain deviation direction and deviation magnitude information that correspond one-to-one with each jacking construction process parameter;

[0123] Based on the correspondence between the stress response of the steel bridge deck pavement and the parameters of the jacking construction process, the corresponding influence relationship between each jacking construction process parameter and the stress state deviation result is determined.

[0124] Based on the corresponding influence relationships and deviation information, the parameters of each jacking construction process are corrected to obtain the adjusted jacking construction process parameters;

[0125] The adjusted jacking process parameters were re-inputted into the full-process analysis model of the steel box girder bridge jacking, and the correspondence between the stress response of the steel bridge deck pavement and the jacking process parameters was updated.

[0126] Specifically, in the step of implementing S5, when adjusting the jacking construction process parameters based on the stress state deviation results and re-inputting the adjusted jacking construction process parameters into the full-process analysis model of the steel box girder bridge jacking, the stress state deviation results are analyzed by component analysis. The stress deviation values ​​at each stress acquisition element location are classified according to their stress type and corresponding jacking construction process parameters. The longitudinal normal stress deviation is classified into the deviation component corresponding to the longitudinal jacking force, the transverse normal stress deviation is classified into the deviation component corresponding to the transverse jacking force, and the in-plane shear stress deviation and inter-layer shear stress deviation are classified into the deviation component corresponding to the transverse jacking synchronization deviation. This yields deviation direction and deviation amplitude information corresponding one-to-one with each jacking construction process parameter. Based on the quantitative mapping relationship between the stress response of the steel bridge deck pavement layer and the jacking construction process parameters established in S1, the stress sensitivity coefficient between each jacking construction process parameter and the stress state deviation results is determined. The dimension is MPa / kN, corresponding to the lateral jack thrust. The dimension is MPa / kN, and the corresponding lateral jack synchronization deviation is... The unit is MPa / mm, and the stress sensitivity coefficient is positive, indicating that the stress response of the pavement layer increases synchronously when the corresponding construction parameters increase. Based on the stress sensitivity coefficient and deviation information, the parameters of each jacking construction process are corrected using the following formula: ;in These are the adjusted parameters for the jacking construction process. These are the parameters for the current jacking construction process. The stress deviation value is the result of the stress state deviation, and S is the corresponding stress sensitivity coefficient. This is substituted into the longitudinal jack thrust correction. For the correction of the thrust of the lateral jack, the input time For the correction of the synchronization deviation of the lateral jack, the input λ is the adjustment step size coefficient, which in this scheme is taken as a value between 0.5 and 0.8 to obtain the adjusted jacking construction process parameters. Specific control strategies include: when a lateral tensile strain exceeding the limit warning occurs in the lateral jacking sensitive area, reducing the jacking speed of the lateral correction jacks and adjusting the synchronization deviation of the inner and outer jacks so that the jacking speed of the outer jacks is lower than that of the inner jacks, thereby reducing the transient torsional curvature of the beam and reducing the lateral tensile stress acting on the pavement layer; when a longitudinal tensile strain exceeding the limit warning occurs in the negative bending moment area at the pier top, fine-tuning the jacking force distribution at each pier top, reducing the jacking force at the pier top corresponding to the exceeding area, and slightly increasing the jacking force of adjacent piers to change the support elevation, unload the peak negative bending moment, and allow the longitudinal tensile strain of the pavement layer to return to the safe range; the adjusted jacking construction process parameters are then re-inputted into the full-process analysis model of the steel box girder bridge jacking. The system replaces the corresponding parameters in the original boundary conditions with the adjusted jacking construction process parameters, updates the correspondence between the stress response of the steel bridge deck pavement and the jacking construction process parameters, and recalculates the updated stress response and allowable stress value. After the control command is executed, the system continuously monitors the strain data changes in the corresponding area at a high sampling frequency. If the strain value falls below the yellow warning threshold after control, the control is confirmed to be effective, and the jacking parameters are gradually restored to normal. If the strain value does not fall after control, a second diagnosis and control are initiated, adjusting the magnitude and strategy until the strain returns to the safe range. After each round of control is completed, the system automatically stores the parameter adjustment amount and stress change amount of this control, and continuously iterates and calibrates the stress sensitivity coefficient to gradually improve the control accuracy as the construction progresses. Then, the system enters the next round of monitoring and control cycle, repeating the process until the jacking construction is completed.

[0127] Example 2: In the second embodiment of the present invention, the present invention provides an intelligent control system for adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge, such as... Figure 6 As shown, it includes the following modules:

[0128] The analysis and modeling module is used to construct an analysis model of the entire process of launching a steel box girder bridge. It takes the joint launching construction process parameters as input conditions, calculates the stress response of the steel bridge deck pavement during the launching process, establishes the correspondence between the stress response of the steel bridge deck pavement and the launching construction process parameters, and extracts the stress extreme value envelope of the steel bridge deck pavement during the launching process as the allowable stress value from the stress response.

[0129] The data acquisition module is used to collect the signals output by the stress acquisition element pre-embedded inside the steel bridge deck pavement structure during the jacking construction process, convert the signals into stress response data inside the steel bridge deck pavement structure, and output the stress response data to the analysis and comparison module.

[0130] The analysis and comparison module receives the allowable stress value output by the analysis and modeling module and the stress response data output by the data acquisition module. It compares the stress response data with the allowable stress value, generates the stress state deviation result, and outputs the stress state deviation result to the control and iteration module.

[0131] The control and iteration module receives the stress state deviation results output by the analysis and comparison module, generates adjusted jacking construction process parameters based on the stress state deviation results, and re-inputs the adjusted jacking construction process parameters into the analysis and modeling module to trigger the analysis and modeling module to update the correspondence between the stress response of the steel bridge deck pavement layer and the jacking construction process parameters, and recalculates the subsequent stress response and allowable stress value.

[0132] A new curved steel box girder bridge spanning an existing railway line is being constructed in a certain city. Due to railway operation restrictions beneath the bridge, a combined longitudinal and transverse jacking construction method is required. To shorten the construction period and avoid the risks of working at heights, a pre-paving process for the steel bridge deck is adopted. However, the bridge's alignment is complex, requiring multiple lateral corrections during the jacking process. The pavement layer is subjected to longitudinal bending, lateral tensile and compressive stresses, and torsional coupling stresses, making it highly susceptible to cracking and debonding. Existing passive reinforcement solutions cannot address this issue at its root. To solve these problems, an intelligent control system for adaptive pre-paving of the steel bridge deck for jacking steel box girder bridges, as provided in this invention, is employed. Figure 6 As shown, the specific implementation process of this system is as follows:

[0133] First, the analysis and modeling module constructs a full-process analysis model of the steel box girder bridge launching based on the bridge's design parameters and predetermined launching scheme. It takes construction parameters such as longitudinal launching step length, lateral correction stroke, and jack launching force as inputs, calculates the stress response of the pavement layer in all construction steps, establishes the correspondence between the pavement layer stress response and launching construction parameters, and extracts the stress extreme value envelope as the allowable stress value, providing a unified quantitative benchmark for subsequent pavement design and construction control.

[0134] Then, in the initial paving stage, the steel bridge deck was divided into a conventional stress zone and a stress-sensitive zone based on the stress response distribution results. In the sensitive zone, the pavement layer was locally thickened and configured with a gradient modulus material. During the paving of the lower layer, fiber optic strain sensors and temperature sensors were embedded inside the pavement structure and simultaneously consolidated. Pre-deformation compensation was performed based on the cumulative vertical deformation value extracted from the model throughout the jacking process. The differentiated pavement provided an intrinsic resistance foundation for the pavement layer, and the pre-deformation compensation eliminated smoothness defects after the bridge was completed.

[0135] During the jacking construction, the data acquisition module continuously samples the sensor signals embedded in the pavement layer and converts them into stress response data, which is then output in real time. In the lateral correction step, strain data in the lateral sensitive area is acquired at a higher sampling frequency to capture stress changes caused by transient torsion.

[0136] The analysis and comparison module receives stress response data and allowable stress values, performs matching and difference calculations based on spatial coordinates, generates stress state deviation results, and outputs them to the control and iteration module when the stress at the measuring point exceeds the limit.

[0137] After receiving the deviation results, the control iteration module performs component analysis. Based on the established correspondence between the pavement stress response and the jacking construction parameters, it determines the deviation parameters and their correction amounts. For example, when tensile strain exceeds the limit in the lateral sensitive area, the speed of the lateral jacks is automatically reduced and the synchronization deviation between the inner and outer sides is adjusted to reduce the transient torsional curvature, so that the tensile stress falls back to within the allowable value, thus preventing pavement cracking from the root cause.

[0138] The adjustment and iteration module re-inputs the adjusted construction parameters into the analysis and modeling module, updates the stress response and allowable stress values, and achieves adaptive iteration of the model. The system continuously executes closed-loop control of data acquisition, comparison, and adjustment until the steel box girder is pushed into place.

[0139] Ultimately, the pavement layer of the curved steel box girder bridge did not exhibit any defects such as cracking or debonding during the entire longitudinal and transverse two-way combined jacking process. After the bridge deck was jacked into place, the flatness of the bridge surface met the requirements, eliminating the need for secondary leveling. This demonstrated the reliable application of pre-paved pavement in complex spatial jacking conditions.

[0140] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for intelligent control of adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge, characterized in that, Includes the following steps: S1. Construct a full-process analysis model for the jacking of a steel box girder bridge, take the joint jacking construction process parameters as input conditions, calculate the stress response of the steel bridge deck pavement during the jacking process, establish the correspondence between the stress response of the steel bridge deck pavement and the jacking construction process parameters, and extract the stress extreme value envelope of the steel bridge deck pavement during the jacking process from the stress response as the allowable stress value. S2. Based on the stress response distribution results, the steel bridge deck is divided into zones, and differentiated pavement structures are configured in different zones; S3. During the formation of the differentiated pavement structure, stress acquisition elements are embedded inside the steel bridge deck pavement structure, and the stress acquisition elements are synchronously fixed with the pavement structure. The pavement structure is pre-deformed and adjusted according to the displacement changes during the jacking process. S4. During the jacking construction, collect stress response data inside the steel bridge deck pavement structure, compare the stress response data with the allowable stress value, and obtain the stress state deviation result. S5. Adjust the jacking construction process parameters according to the stress state deviation results, and re-input the adjusted jacking construction process parameters into the full-process analysis model of the steel box girder bridge jacking. Repeat S1 to S5 until the jacking construction is completed.

2. The intelligent control method for adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge according to claim 1, characterized in that, In S1, the steps for constructing the full-process analysis model of the steel box girder bridge launching include: Discretize the steel box girder bridge to generate beam segment elements; By using the piers and temporary supports as fulcrum constraint nodes, spatial constraint relationships between each beam segment unit are established. The steel bridge deck pavement layer is treated as a continuous layer unit attached to the top plate of the steel box girder, and the continuous layer unit is assigned layered calculation properties. The parameters of the joint jacking construction process are used as boundary conditions for each construction step and input into the full-process analysis model of the steel box girder bridge jacking after discretization and the establishment of spatial constraint relationships.

3. The intelligent control method for adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge according to claim 1, characterized in that, In S1, the step of calculating the stress response of the steel bridge deck pavement layer during the jacking process includes: Based on the analysis model of the entire process of launching the steel box girder bridge, the nodal displacement distribution of the steel box girder bridge in each launching construction step is solved. The nodal displacement of the top plate of the steel box girder is used as a boundary condition and transferred to the steel bridge deck pavement. Calculate the strain distribution of the steel bridge deck pavement layer based on the deformation gradient of the steel bridge deck pavement layer under the boundary conditions. The stress distribution of the steel bridge deck pavement is calculated based on the strain distribution of the pavement.

4. The intelligent control method for adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge according to claim 1, characterized in that, In S1, the step of extracting the stress extreme value envelope of the steel bridge deck pavement layer during the jacking process as the allowable stress value from the stress response includes: The stress response data of the steel bridge deck pavement layer in all jacking construction steps are traversed and a stress time series is formed. The maximum tensile stress, maximum compressive stress, and maximum shear stress values ​​are extracted for each spatial node in the stress time series set. The maximum tensile stress, maximum compressive stress, and maximum shear stress values ​​of the same spatial node are combined and compared to determine the node control stress value; The nodal control stress values ​​of all spatial nodes are spatially aggregated to form a stress extremum envelope.

5. The intelligent control method for adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge according to claim 1, characterized in that, In S2, the step of partitioning the steel bridge deck based on the distribution of the stress response includes: Extract the set of nodal stress values ​​of the steel bridge deck pavement layer under the action of various parameters in the jacking construction process; Spatial coordinate mapping is performed on the set of nodal stress values ​​to generate a spatial distribution matrix of stress response on the steel bridge deck. Gradient variation calculations were performed on the spatial distribution matrix of stress response on the steel bridge deck to obtain stress gradient variation data; The steel bridge deck partition boundaries are determined based on stress gradient variation data, and the partition results are output.

6. The intelligent control method for adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge according to claim 1, characterized in that, In S2, the step of configuring differentiated paving structures in different zones includes: Based on the zoning results of the steel bridge deck, the pavement layer thickness parameters and pavement layer material parameters corresponding to each zone are determined. The pavement layer thickness parameters include the pavement layer thickening ratio in the stress-sensitive area. Map the pavement thickness parameters and pavement material parameters of each zone to the steel bridge deck area of ​​the corresponding zone; Based on the pavement layer thickness parameters and pavement layer material parameters corresponding to each zone, a layered pavement structure composition sequence is generated within the corresponding zone; According to the sequence of the layered paving structure, the paving structure in different zones is laid and formed.

7. The intelligent control method for adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge according to claim 1, characterized in that, In S3, the step of embedding the stress acquisition element inside the steel bridge deck pavement structure and synchronously consolidating the stress acquisition element with the pavement structure includes: During the formation of the steel bridge deck pavement structure, the embedding location of the stress acquisition element inside the steel bridge deck pavement structure is determined, and a set of embedding location coordinates is generated. When the steel bridge deck pavement structure is in an uncured state, the stress acquisition element is placed into the preset embedment depth position inside the steel bridge deck pavement structure according to the aforementioned embedment location coordinate set. After the stress acquisition element is placed, a holding constraint is applied to the spatial position of the stress acquisition element so that the stress acquisition element maintains the spatial position corresponding to the set of embedded position coordinates before the steel bridge deck pavement structure is cured. During the curing process of the steel bridge deck pavement structure, the stress acquisition element is simultaneously cured with the steel bridge deck pavement structure.

8. The intelligent control method for adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge according to claim 1, characterized in that, In S4, the step of collecting stress response data inside the steel bridge deck pavement structure during the jacking construction includes: The strain signal output by the stress acquisition element inside the steel bridge deck pavement structure is continuously sampled to form a raw strain signal sequence; The original strain signal sequence is time-calibrated according to the time progression relationship of the jacking construction process to generate time-series strain data corresponding to the jacking construction stage; Temperature correction processing is performed on time-series strain data to generate corrected strain data; The corrected strain data were converted into stress response data within the steel bridge deck pavement structure.

9. The intelligent control method for adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge according to claim 1, characterized in that, In S4, the step of comparing the stress response data with the allowable stress value to obtain the stress state deviation result includes: Obtain stress response data inside the steel bridge deck pavement structure and allowable stress values ​​at corresponding locations on the steel bridge deck pavement structure; The stress response data and allowable stress values ​​are matched according to the spatial coordinates of the steel bridge deck pavement structure. The difference between the matched stress response data and the allowable stress value is calculated to generate stress deviation data. Stress state deviation results are generated based on stress deviation data.

10. The intelligent control method for adaptive pre-laying of steel bridge deck stress in a jacking steel box girder bridge according to claim 1, characterized in that, In S5, the step of adjusting the jacking construction process parameters according to the stress state deviation results and re-inputting the adjusted jacking construction process parameters into the full-process analysis model of the steel box girder bridge jacking includes: Component analysis was performed on the stress state deviation results to obtain deviation direction and deviation magnitude information that correspond one-to-one with each jacking construction process parameter; Based on the correspondence between the stress response of the steel bridge deck pavement and the parameters of the jacking construction process, the corresponding influence relationship between each jacking construction process parameter and the stress state deviation result is determined. Based on the corresponding influence relationship and deviation information, the parameters of each jacking construction process are corrected to obtain the adjusted jacking construction process parameters; The adjusted jacking process parameters were re-inputted into the full-process analysis model of the steel box girder bridge jacking, and the correspondence between the stress response of the steel bridge deck pavement and the jacking process parameters was updated.

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