Steel pipe pile guide frame construction state real-time monitoring system and method

Abstract

The application relates to the technical field of offshore engineering construction monitoring, and discloses a steel pipe pile guide frame construction state real-time monitoring system and method, which comprises a data acquisition module, which is used for acquiring multi-source data such as flow velocity profiles and real-time seabed topography; a hydrodynamic inversion module, which is used for inversely calculating distributed hydrodynamic force based on flow velocity profile data; a boundary condition correction module, which is used for adaptively correcting the constraint boundary conditions of the steel pipe pile based on seabed topography data; a posture prediction module, which is used for establishing and solving a pile body mechanical model with the distributed hydrodynamic force as a load and the corrected constraint boundary as a condition to obtain a predicted posture; and a risk index calculation module, which is used for calculating and outputting a predictive stability index based on the predicted posture. The application converts invisible construction risks into measurable predictive indexes, realizes dynamic quantification and forward-looking early warning of the instability risks of the steel pipe pile, and improves the safety and active control capability of the construction.

Description

Technical Field

[0001] This invention relates to the field of marine engineering construction monitoring technology, specifically to a real-time monitoring system and method for the construction status of steel pipe pile guide frames. Background Technology

[0002] Large-diameter steel pipe piles are one of the most widely used foundation types in the construction of offshore platforms, cross-sea bridges, and offshore wind power projects. To ensure that the verticality of the steel pipe piles meets design requirements during the pile driving process, underwater guide frames (or guide templates) are usually used for auxiliary construction. The guide frames are pre-placed on the seabed to provide initial positioning and lateral constraints for the steel pipe piles, and are crucial for ensuring the stability of the pile's posture during the sinking phase under its own weight or the initial hammering stage.

[0003] However, during the construction of steel pipe piles, due to the large length-to-diameter ratio of the piles, their underwater portions are exposed to the complex marine environment, making the piles highly susceptible to displacement due to hydrodynamic loads such as ocean currents and waves. Simultaneously, the scouring of the seabed around the bottom legs of the guide frame by the water flow can reduce the support capacity of the guide frame, weakening its restraining effect on the piles. If the pile displacement exceeds the allowable range, it will not only increase the difficulty, time, and cost of correction operations, but in severe cases, it may even affect the final bearing capacity of the pile foundation and the safety of the superstructure.

[0004] Existing construction monitoring technologies typically focus on passive, delayed measurements of the final attitude of steel pipe piles. For example, underwater inclinometers deployed on the pile or guide frame, or underwater acoustic positioning systems, are used to obtain information on the pile's inclination and displacement. While these methods provide measurement results of the pile's attitude, they are essentially "post-hoc" measurements and cannot reveal the underlying physical mechanisms causing attitude deviations. They fail to synchronously and quantitatively monitor and analyze the key factors triggering pile deviations—namely, the dynamic hydrodynamic loads acting on the pile and the real-time changes in the guide frame's constraint capacity.

[0005] Therefore, by the time existing technologies detect excessive pile posture deviations, the optimal adjustment window has often already passed. Construction workers rely entirely on delayed responses to measurement results, lacking the ability to predict risk trends. Existing technologies generally lack a forward-looking risk assessment capability; that is, they cannot predict the pile's posture evolution over a future period based on current environmental conditions and structural status, thus failing to provide proactive and quantifiable guidance for construction decisions. This significantly limits the safety and efficiency of construction. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a real-time monitoring system and method for the construction status of steel pipe pile guide frames. This solves the problem that existing technologies can only passively and laggingly measure the attitude of steel pipe piles, lacking real-time quantification of key physical factors such as hydrodynamic loads and the stability of the guide frame foundation, thus failing to provide a forward-looking assessment of construction risks.

[0007] The purpose of this invention is to provide a real-time monitoring system and method for the construction status of steel pipe pile guide frames, so as to solve the technical problem that the existing technology can only passively measure the attitude deviation of steel pipe piles and lacks the ability to quantify and proactively evaluate key physical factors such as hydrodynamic loads that cause deviation and the stability of the guide frame foundation in real time.

[0008] To achieve the above objectives, the first aspect of the present invention provides a real-time monitoring system for the construction status of a steel pipe pile guide frame.

[0009] The system includes: a data acquisition module, a hydrodynamic inversion module, a boundary condition correction module, an attitude prediction module, and a risk index calculation module.

[0010] The data acquisition module is used to synchronously acquire multi-source heterogeneous data related to the steel pipe pile, including velocity profile data and real-time seabed topography data. In one embodiment, the data acquisition module includes: an intelligent sensing ring temporarily fastened to the steel pipe pile body, on which multiple acoustic Doppler velocity profilers are integrated for acquiring velocity profile data; and multiple high-frequency forward-looking multibeam imaging sonars deployed near the bottom legs of the guide frame for acquiring real-time seabed topography data.

[0011] The hydrodynamic inversion module is connected to the data acquisition module. Its function is to perform real-time inversion calculations of the distributed hydrodynamic forces acting on the steel pipe pile based on the velocity profile data. Specifically, this module uses a spatial interpolation algorithm to fuse the discrete velocity profile data collected by multiple acoustic Doppler current profilers into a continuous velocity field surrounding the steel pipe pile. Subsequently, based on this continuous velocity field and according to the Morrison equation, the distributed hydrodynamic forces along the underwater portion of the steel pipe pile are calculated. The distributed hydrodynamics By drag force and inertial force Composition, including drag force Calculated using the following formula:

[0012] ;

[0013] in, Because of the water depth, For time, In water depth and time The drag force, The density of water, This is the drag coefficient. The outer diameter of the steel pipe pile. (for water depth) and time The velocity vector of the merged water flow.

[0014] The boundary condition correction module is connected to the data acquisition module. This module's function is to adaptively correct the constraint boundary conditions of the steel pipe pile based on the real-time seabed topography data. Specifically, this module quantifies the topographic change below the bottom legs of the guide frame by comparing the real-time seabed topography data with a pre-stored initial benchmark topography. Based on this topographic change, a stiffness correction coefficient is generated. Finally, the stiffness correction coefficient is used to update the initial constraint stiffness matrix representing the guide frame constraint in the pile mechanics prediction model. The stiffness correction coefficient... Generate using the following formula:

[0015] ;

[0016] in, For the index of the guide frame legs, For time, For the first One support leg in time Stiffness correction factor To flush out the sensitivity coefficient, For the first The guide frame support legs are below the time The amount of topographic change.

[0017] The attitude prediction module is connected to the hydrodynamic inversion module and the boundary condition correction module. The function of this module is to establish and solve a pile mechanics prediction model with the distributed hydrodynamic force as the external load and the adaptively corrected constraint boundary conditions as the boundary, in order to obtain the predicted attitude of the steel pipe pile. In one embodiment, the pile mechanics prediction model is a finite element model based on Euler-Bernoulli beam theory.

[0018] The risk index calculation module is connected to the attitude prediction module. The function of this module is to calculate and output a predictive stability index characterizing construction risk based on the predicted attitude and a preset allowable attitude threshold. Specifically, this module calculates the predicted inclination angle of the steel pipe pile obtained by the attitude prediction module. With the preset allowable tilt angle threshold The predictive stability index is calculated by comparing the two indices using the following formula. :

[0019] ;

[0020] in, For time, For time The predictive stability index, For time The predicted dip angle, To allow tilt angle threshold, This is the exponential sensitivity coefficient.

[0021] The system provided by this invention establishes a quantitative predictive relationship between hydrodynamic load, constraint boundary, and pile response by acquiring hydrodynamic field and guide frame foundation bed morphology data in real time. This transforms invisible construction risks into measurable predictive stability indices, thereby providing forward-looking and quantitative guidance information for construction operations and replacing the passive correction operation mode that relies on hysteresis measurements.

[0022] A second aspect of the present invention provides a method for real-time monitoring of the construction status of a steel pipe pile guide frame, the method comprising the following steps:

[0023] S1: Synchronously collect multi-source heterogeneous data related to steel pipe piles through the data acquisition module. The multi-source heterogeneous data includes velocity profile data and real-time seabed topography data.

[0024] S2: Based on the velocity profile data, the distributed hydrodynamic forces acting on the steel pipe pile are calculated in real time using the hydrodynamic inversion module.

[0025] S3: The boundary condition correction module adaptively corrects the constraint boundary conditions of the steel pipe pile based on the real-time seabed topography data.

[0026] S4: Establish and solve the pile mechanics prediction model with the distributed hydrodynamic force as the external load and the adaptively corrected constraint boundary conditions as the boundary through the attitude prediction module, so as to obtain the predicted attitude of the steel pipe pile.

[0027] S5: The risk index calculation module calculates and outputs a predictive stability index that characterizes construction risk based on the predicted posture and the preset allowable posture threshold.

[0028] This invention provides a real-time monitoring system and method for the construction status of steel pipe pile guide frames. It has the following beneficial effects:

[0029] 1. This invention quantifies the hydrodynamic loads acting on the steel pipe pile and the support state changes of the guide frame foundation in real time by setting up a hydrodynamic inversion module and a boundary condition correction module. These dynamic parameters are used as inputs to the pile mechanics prediction model, thereby realizing the forward-looking prediction of the risk of pile attitude instability. This changes the limitation of traditional technology, which can only perform hysteresis attitude measurement, and provides active guidance capability for construction.

[0030] 2. This invention deploys a high-frequency forward-looking multibeam imaging sonar and sets up a boundary condition correction module. The real-time monitored scour or siltation of the guide frame foundation bed is dynamically updated in the form of stiffness correction coefficients to update the constraint boundary conditions in the pile mechanical prediction model. This makes the calculation of the mechanical model closer to the real engineering environment, avoids prediction deviations caused by ignoring changes in boundary support conditions, and improves the accuracy of the system monitoring results.

[0031] 3. This invention, by setting up a risk index calculation module, compares and normalizes the complex predicted attitude parameters output by the attitude prediction module with the thresholds allowed by engineering specifications, generating a standardized predictive stability index. This transforms professional mechanical analysis results into intuitive and easy-to-interpret risk level signals, providing clear and explicit decision support for on-site construction personnel and reducing operational errors that may result from difficulties in interpreting or delaying information. Attached Figure Description

[0032] Figure 1 This is a system architecture diagram of the present invention;

[0033] Figure 2 This is a flowchart of the method of the present invention. Detailed Implementation

[0034] The technical solutions of 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.

[0035] Please see the appendix Figure 1 -Appendix Figure 2 This invention provides a real-time monitoring system and method for the construction status of steel pipe pile guide frames, comprising:

[0036] The data acquisition module is used to synchronously acquire multi-source heterogeneous data related to steel pipe piles, including flow velocity profile data and real-time seabed topography data.

[0037] In this embodiment, the data acquisition module is configured as the data foundation for subsequent analysis, prediction, and decision-making in this invention. Its core function is to synchronously and continuously acquire physical field data of multiple dimensions directly related to the construction status of the steel pipe piles. To this end, the module has undergone a specialized integrated design in its physical structure to adapt to the complex underwater construction environment.

[0038] Specifically, the data acquisition module physically includes an underwater intelligent sensing assembly, which consists of an intelligent sensing ring and a high-frequency forward-looking multibeam imaging sonar, and communicates with the central processing unit on the water surface through a data link.

[0039] The intelligent sensing ring is a closable ring structure designed for temporary and convenient fastening to the steel pipe pile body of the pile segment to be driven before construction. Its closable structure allows it to accommodate steel pipe piles of different diameters and enables rapid disassembly and recycling after construction. The intelligent sensing ring highly integrates two types of key sensing units:

[0040] Firstly, multiple acoustic Doppler current profilers are used to acquire velocity profile data. Preferably, these acoustic Doppler current profilers are evenly distributed circumferentially along the intelligent sensing loop, for example, deployed in four mutually orthogonal directions. The purpose of this arrangement is to simultaneously capture the water flow velocity and direction information of multiple cross-sections around the steel pipe pile. Since underwater flow fields typically exhibit significant non-uniformity, single-point measurements cannot accurately characterize the complete hydrodynamic environment surrounding the pile. Arrayed measurements provide discrete raw data input for subsequent hydrodynamic inversion modules to reconstruct the three-dimensional non-uniform velocity field.

[0041] It is an inertial measurement unit used to acquire the real-time attitude of steel pipe piles. This inertial measurement unit typically contains a three-axis accelerometer and a three-axis gyroscope, capable of calculating the pitch angle, roll angle, and other attitude parameters of the steel pipe pile in the geographic coordinate system in real time. These attitude parameters serve as direct verification of the final prediction results and also provide the system with direct observations of the pile's own motion state.

[0042] Accordingly, a high-frequency forward-looking multibeam imaging sonar was deployed near the bottom leg structure of the underwater guide frame, and its acoustic detection sector was adjusted to completely cover the contact area between each leg and the seabed and the adjacent area. The function of this imaging sonar is to periodically emit sound waves and receive echoes, thereby generating a three-dimensional topographic acoustic image of the seabed within its detection range.

[0043] The purpose of deploying this imaging sonar is to provide the necessary data input for the boundary condition correction module. At the start of construction, the sonar first acquires one or more terrain data sets, which are then processed to form an initial baseline terrain. The data was then stored. During subsequent construction, the sonar continuously collected real-time seabed topographic data. By comparing the real-time terrain with the baseline terrain, the boundary condition correction module can accurately quantify the changes in terrain below the guide frame foundation caused by water erosion or siltation. This is a prerequisite for achieving adaptive correction of constraint boundary conditions.

[0044] To ensure that the multi-source heterogeneous data collected by the data acquisition module can be effectively utilized by subsequent modules, the data link and synchronization mechanism in this embodiment have also been configured accordingly. Preferably, the underwater intelligent sensing assembly and the surface central processing unit are connected via an optical-electric composite cable to ensure data transmission bandwidth and anti-interference capability. In certain specific scenarios, high-bandwidth underwater acoustic communication technology can also be used.

[0045] Crucially, all data streams acquired from the acoustic Doppler current profiler, inertial measurement unit, and high-frequency forward-looking multibeam imaging sonar are assigned high-precision timestamps upon generation. Synchronization via a unified clock source ensures that at any given moment, the current profile data, pile attitude data, and seabed topography data received by the central processing unit accurately describe the same physical instant. This strict time synchronization is essential for the subsequent attitude prediction module to build and solve the dynamic mechanical model, as it guarantees the consistency of the external loads and boundary conditions input to the model in the time dimension.

[0046] In summary, the data acquisition module in this embodiment, through structured hardware integration and strict timing control, can provide a complete, synchronous physical field dataset directly related to construction risks. This dataset includes not only external hydrodynamic field information that induces changes in pile attitude, but also boundary support condition information that affects pile stability, thus providing sufficient and necessary data support for the present invention to achieve a technological leap from passive measurement to active prediction.

[0047] The hydrodynamic inversion module, connected to the data acquisition module, is used to perform real-time inversion calculations of the distributed hydrodynamic forces acting on the steel pipe piles based on flow velocity profile data.

[0048] In this embodiment, the hydrodynamic inversion module inherits the function of the data acquisition module and provides key external load input for the subsequent attitude prediction module. Its core technical task is to transform the discrete velocity profile data distributed around the circumference of the steel pipe pile obtained from the data acquisition module into a continuous distributed hydrodynamic force that acts on the entire pile and dynamically changes with time and space.

[0049] The purpose of this module is to solve the technical challenge of directly quantifying the forces exerted by non-uniform flow fields on large cylindrical structures in existing technologies. Through a series of calculation steps, this module reconstructs the physical process from point measurement to field action.

[0050] Specifically, the hydrodynamic inversion module receives synchronous data streams from multiple acoustic Doppler velocity profilers in the data acquisition module. These data are velocity profiles at multiple discrete locations, denoted as... ,in Number the sensor. Because of the water depth, For time.

[0051] Therefore, this module first performs a data fusion step. Due to the spatial non-uniformity of the flow field, these discrete, multi-directional velocity profile data need to be spatially interpolated to reconstruct a continuous velocity field that can describe the complete flow regime around the pile. Preferably, this module uses Kriging interpolation or radial basis function interpolation. Using these algorithms, the module can calculate the velocity field at any water depth. and circumferential angle of any pile section velocity vector at the location The completion of this step provides a continuous, high-resolution input field for subsequent accurate calculations of the hydrodynamic forces acting at every point on the pile.

[0052] After obtaining the continuous velocity field, the hydrodynamic inversion module then performs distributed hydrodynamic calculations. This calculation is based on the well-established Morrison equations in fluid dynamics, which are applicable to calculating the forces acting on slender structures under wave or current conditions. According to these equations, the total hydrodynamic force acting per unit length of the pile is calculated. By drag force and inertial force It is composed of two linearly superimposed parts:

[0053] ;

[0054] Among them, drag force This is due to the viscosity of water and the obstruction of water flow by the pile, and it is proportional to the square of the water flow velocity. This module calculates it using the following formula:

[0055] ;

[0056] In the formula, Because of the water depth, For time, In water depth and time The drag force, The density of water, The drag force coefficient is related to the surface roughness and Reynolds number of the pile. The outer diameter of the steel pipe pile. For the data obtained in the data fusion step, at water depth and time The continuous water flow velocity vector at that location.

[0057] Correspondingly, inertial force This is caused by the acceleration or deceleration of water particles around the pile, and is directly proportional to the acceleration of the water particles. This module calculates this using the following formula:

[0058] ;

[0059] In the formula, The inertial force coefficient is related to the shape of the pile. Let be the cross-sectional area of ​​the steel pipe pile, and be the acceleration term of the water particles. Then by analyzing the continuous velocity field The time series data is obtained in real time by performing high-order numerical differencing.

[0060] Finally, the hydrodynamic inversion module will calculate the complete distributed hydrodynamic function point by point along the entire underwater section of the steel pipe pile, from the water surface to the mud surface. This function, in the form of a vector field, precisely describes the magnitude and direction of the force exerted by the water flow on various parts of the pile at any given moment.

[0061] This distributed hydrodynamic function is one of the key technological achievements that distinguishes this embodiment from traditional methods. It transforms an invisible, dynamically changing flow field into a definite external load input that can be used for structural mechanics analysis. This output is then transmitted to the attitude prediction module as a forced driving force for solving the pile mechanics prediction model, thus forming the mechanical basis for the present invention to achieve forward-looking risk assessment.

[0062] The boundary condition correction module, connected to the data acquisition module, is used to adaptively correct the constraint boundary conditions of the steel pipe piles based on real-time seabed topographic data.

[0063] In this embodiment, the boundary condition correction module plays a crucial role in the entire system. It receives real-time seabed topography data from the data acquisition module and provides the attitude prediction module with dynamically updated constraint boundary conditions that reflect the actual support state.

[0064] The purpose of this module is to overcome the limitations of traditional mechanical analysis that treats the guide frame as an idealized, constant elastic or fixed constraint. In actual underwater construction, water erosion can cause the seabed beneath the guide frame legs to be eroded, significantly weakening its constraint on the steel pipe piles. The core function of this module is to quantify these boundary condition changes caused by environmental factors in real time and incorporate them into the mechanical prediction model.

[0065] Specifically, the boundary condition correction module is first configured to receive and process real-time seabed topography data streams acquired by high-frequency forward-looking multibeam imaging sonar. Simultaneously, during the system initialization phase, this module retrieves and stores an initial benchmark terrain measured before construction. .

[0066] Therefore, the first step of this module is to perform terrain comparison and change quantification. By registering and differentiating real-time terrain data with initial baseline terrain data, the module can identify and calculate the average change in terrain elevation under each guide frame leg. This change is defined as positive when scouring occurs and negative when sedimentation occurs.

[0067] After obtaining the terrain change, the core task of the boundary condition correction module is to establish a mapping relationship between this physical change and the constraint stiffness parameters in the mechanical model. Directly applying the terrain change to the mechanical model is not feasible; therefore, this module introduces a dimensionless stiffness correction coefficient. The concept of . This coefficient characterizes the effect of topographic changes on the . The degree of reduction or change in the actual constraint stiffness of each outrigger relative to its ideal stiffness.

[0068] Preferably, the stiffness correction factor It is generated using a nonlinear exponential function to reflect the physical characteristics that have a more significant impact on support capacity during the initial stage of scour. Its specific mathematical expression is as follows:

[0069] ;

[0070] In the formula, For the index of the guide frame legs, For time, For the first One support leg in time Stiffness correction factor This is a pre-defined scour sensitivity coefficient that characterizes the scour sensitivity of different soil types. For the first The guide frame support legs are below the time The amount of topographic change. In this formula... The application of the function ensures that the stiffness correction factor will be less than 1 only when scouring occurs, thereby weakening the constraint stiffness.

[0071] Finally, the boundary condition correction module utilizes the stiffness correction coefficients calculated for each outrigger. For a pre-defined initial constraint stiffness matrix representing the guide frame under ideal support conditions, Make corrections. Through specific matrix operation functions. Each correction coefficient is applied to the corresponding position in the initial constraint stiffness matrix, thereby generating a dynamically changing, adaptively corrected constraint stiffness matrix that changes over time. .

[0072] The adaptively corrected constraint stiffness matrix This is the final output of this module. It is no longer a static, idealized parameter, but a dynamic variable that reflects the stability state of the guide frame foundation in real time. This output is then transmitted to the attitude prediction module as the elastic boundary condition applied at the guide frame location that most closely approximates the actual physical condition when solving the pile mechanics prediction model. In this way, the present invention internalizes the influence of the external environment on the support boundary into the solution process of the mechanics model, providing a key guarantee for the accuracy of the prediction results.

[0073] The attitude prediction module, connected to the hydrodynamic inversion module and the boundary condition correction module, is used to establish and solve the pile mechanics prediction model with distributed hydrodynamics as the external load and adaptively corrected constraint boundary conditions as the boundary, so as to obtain the predicted attitude of the steel pipe pile.

[0074] In this embodiment, the attitude prediction module is the forward-looking analysis hub that realizes the core function of the present invention. The function of this module is to integrate and utilize the dynamic information from the upstream module, namely the distributed hydrodynamics output by the hydrodynamic inversion module and the adaptively corrected constraint boundary conditions output by the boundary condition correction module, and to obtain the predicted attitude of the steel pipe pile in a very short time step in the future by constructing and solving a mechanical model that can accurately reflect the physical reality.

[0075] The purpose of this module is to establish a deterministic causal prediction chain from "external forces" to "structural response." It unifies environmental loads and structural boundary changes within a single mechanical framework, thereby enabling the assessment of pile attitude to move from a lagging judgment based on historical measurements to an instantaneous extrapolation based on the current physical state.

[0076] Specifically, after receiving the input data, the attitude prediction module first constructs a pile mechanics prediction model to describe the stress-deformation behavior of the steel pipe pile. Preferably, this model is based on the Euler-Bernoulli beam theory in structural mechanics. This theory is suitable for analyzing the bending deformation of slender members with a large length-to-diameter ratio, such as steel pipe piles, under external forces, and can obtain solutions that meet engineering accuracy requirements with high computational efficiency.

[0077] Therefore, the core of this module is a partial differential governing equation describing the lateral vibration of a beam element:

[0078] ;

[0079] In the formula, The elastic modulus of the steel pipe pile material. Let be the moment of inertia of the cross section of the steel pipe pile. For the pile body in water depth Location, Time The lateral displacement, while the right side of the equation The distributed hydrodynamic load is calculated and provided in real time by the hydrodynamic inversion module.

[0080] To solve this partial differential equation, the attitude prediction module in this embodiment employs the finite element method for numerical discretization. This method discretizes the continuous steel pipe pile along its axial direction into a series of interconnected beam elements of finite length. In this way, the complex partial differential equation is transformed into a large but solvable system of linear algebraic equations, the classical form of which is: .

[0081] The key innovation of this module in the solution process lies in the way the model input, namely the external loads and boundary conditions, are applied:

[0082] On the one hand, the distributed hydrodynamic output of the hydrodynamic inversion module After integration along each beam element, the loads are transformed into equivalent nodal loads applied to each node of the finite element model, forming the external load vector in the aforementioned algebraic equations. .

[0083] On the other hand, and crucially, the constraint stiffness matrix output by the boundary condition correction module is an adaptively corrected matrix that changes dynamically over time. This matrix is ​​directly used as the boundary condition for the nodes corresponding to the guide frame positions in the model. This matrix is ​​integrated into the overall stiffness matrix of the entire model. In this way, the weakening of the support capacity of the guide frame due to the scouring of the foundation bed can be directly and in real time reflected in the solution process of the mechanical model. At the same time, for the part of the steel pipe pile embedded in the soil, another corresponding elastic or fixed constraint boundary is applied according to the embedment depth and soil engineering parameters.

[0084] At each computation time step, the attitude prediction module utilizes the latest external load vector. and overall stiffness matrix The finite element equations are solved in real time to obtain the displacement vectors of all nodes in the model. This displacement vector accurately describes the predicted deformation curve of the entire steel pipe pile under the combined action of the current load and boundary conditions. .

[0085] Finally, based on the predicted deformation curve, the module calculates the predicted attitude of the steel pipe pile as its final output. Specifically, this is done by analyzing the predicted deformation curve function. At the top of the pile ( Find its spatial coordinates. The first derivative is used to obtain the predicted pile top inclination angle at that moment. :

[0086] ;

[0087] The predicted pile top inclination angle As a key physical quantity that can proactively reflect the stability trend of the pile, it is then transmitted to the risk index calculation module as the direct basis for generating the final risk assessment index.

[0088] The risk index calculation module, connected to the attitude prediction module, is used to calculate and output a predictive stability index that characterizes construction risk based on the predicted attitude and the preset allowable attitude threshold.

[0089] In this embodiment, the risk index calculation module serves as the final output link of the system's analysis chain. Its function is to receive and process the output from the attitude prediction module, thereby generating a standardized index that can intuitively and quantitatively characterize the current construction risk level.

[0090] The purpose of this module is to transform the predicted attitude parameters output by the attitude prediction module—which have clear physical meaning but are not intuitive for on-site operators—into a standardized risk index that is easy to understand and interpret. This index provides a direct basis for subsequent visualization and tiered early warning systems.

[0091] Specifically, the risk index calculation module is first configured to receive the core prediction result calculated in real time by the attitude prediction module, namely the predicted pile top inclination angle of the steel pipe pile. This input quantity directly reflects the forward-looking risk assessment achieved by this invention.

[0092] Therefore, the core task of this module is to construct a mathematical model that takes the input predicted tilt angle as input. The attitude threshold is compared with and normed by a preset permissible attitude threshold derived from engineering design specifications or construction safety regulations. Preferably, this permissible attitude threshold is a defined permissible tilt angle threshold. .

[0093] This module generates a predictive stability index by performing the following calculation steps. Its specific mathematical expression is as follows:

[0094] ;

[0095] The calculation process in the above formula will be explained:

[0096] This module first calculates the absolute value of the predicted tilt angle. With allowable tilt angle threshold The ratio of the predicted attitude deviation from the center to the safety boundary is a dimensionless parameter. This ratio directly reflects the degree to which the predicted attitude deviates from the center. When the predicted tilt angle is zero, the ratio is 0; when the predicted tilt angle reaches the allowable limit, the ratio is 1.

[0097] Furthermore, in order to adjust the sensitivity of the index when it approaches the risk boundary, this module performs an exponential calculation on the above ratio, that is, introduces an exponential sensitivity coefficient. .when The exponential function exhibits non-linear characteristics, resulting in a relatively gradual decline in the exponent when the predicted tilt angle is small, but a sharp drop when the predicted tilt angle approaches the allowable threshold. This design aims to provide a more significant warning effect for approaching risks.

[0098] The module then subtracts the indexed ratio from 1. The purpose of this step is to reverse the logic so that the index value is positively correlated with the stability of the pile, that is: the more stable the pile's posture, the closer the calculation result is to 1; conversely, the closer it is to the risk boundary, the closer the calculation result is to 0.

[0099] Finally, to ensure that the output range of this index is bounded and easy to apply in engineering, the module adopts... The function prevents the index from becoming negative due to extreme predicted values ​​and multiplies the final result by 100, thus reducing the predictive stability index. The output range is standardized to a range.

[0100] The predictive stability index As the core quantitative risk assessment result of this system, it is the final output of this module. A result close to 100... The value represents the high attitude stability of the pile in the present and foreseeable future; while a value close to 0... The value clearly indicates an extremely high risk of instability in the pile. This output is then transmitted to the visual human-machine interface, serving as the direct basis for driving the dashboard display and triggering different levels of warning signals.

Claims

1. A steel pipe pile guide frame construction state real-time monitoring system, characterized in that, Comprise: a data acquisition module for synchronously acquiring multi-source heterogeneous data related to a steel pipe pile, the multi-source heterogeneous data comprising flow velocity profile data and real-time seabed topography data; a hydrodynamic inversion module connected with the data acquisition module, for inversely calculating distributed hydrodynamic force acting on the steel pipe pile based on the flow velocity profile data; a boundary condition correction module connected with the data acquisition module, for adaptively correcting constraint boundary conditions of the steel pipe pile based on the real-time seabed topography data; a posture prediction module connected with the hydrodynamic inversion module and the boundary condition correction module, for establishing and solving a pile body mechanics prediction model taking the distributed hydrodynamic force as external load and the adaptively corrected constraint boundary conditions as boundary, to obtain a predicted posture of the steel pipe pile; a risk index calculation module connected with the posture prediction module, for calculating and outputting a predictive stability index representing construction risk based on the predicted posture and a preset allowable posture threshold.

2. The system of claim 1, wherein, The data acquisition module comprises: an intelligent sensing ring temporarily fastened to a pile body of the steel pipe pile, the intelligent sensing ring being integrated with a plurality of acoustic Doppler current profilers for acquiring the flow velocity profile data and an inertial measurement unit for acquiring a real-time posture of the steel pipe pile; a high-frequency forward-looking multi-beam imaging sonar deployed near a bottom leg of a guide frame used for construction of the steel pipe pile, for acquiring the real-time seabed topography data.

3. The system of claim 2, wherein, The hydrodynamic inversion module is configured to: fuse discrete flow velocity profile data collected by the plurality of acoustic Doppler current profilers into a continuous velocity field surrounding the steel pipe pile using a spatial interpolation algorithm; calculate the distributed hydrodynamic force along the length of the underwater part of the steel pipe pile based on the continuous velocity field and according to the Morison equation.

4. The system of claim 3, wherein, The distributed hydrodynamic forces consist of drag forces and inertial forces The drag forces are calculated by the following equation: ； wherein, is the water depth, is the time, is the water flow velocity vector at the water depth and the time is the drag force, is the density of the water, is the drag force coefficient, is the outer diameter of the steel pipe pile, is the water flow velocity vector at the water depth and the time after the fusion.

5. The system of claim 1, wherein, The boundary condition correction module is configured to: quantify a topography change amount under the bottom leg of the guide frame by comparing the real-time seabed topography data with a pre-stored initial reference topography; generate a stiffness correction coefficient based on the topography change amount; update an initial constraint stiffness matrix representing the constraint effect of the guide frame in the pile body mechanics prediction model using the stiffness correction coefficient, thereby obtaining adaptively corrected constraint boundary conditions.

6. The system of claim 5, wherein, the rigidity correction coefficient is generated by the following equation: ； wherein, is an index of the outrigger leg, is time, is the stiffness correction factor of the leg at time t, is the scour sensitivity factor, is the outrigger leg below at time the terrain change.

7. The system of claim 1, wherein, The posture prediction module uses a finite element model established based on Euler-Bernoulli beam theory as the pile body mechanics prediction model.

8. The system of claim 1, wherein, The risk index calculation module is configured to compare a predicted inclination of the steel pipe pile obtained by the posture prediction module with an allowable inclination threshold in the preset allowable posture threshold, thereby calculating the predictive stability index.

9. The system of claim 1, wherein, Further comprise: a visual human-computer interaction interface connected with the risk index calculation module, for displaying the predictive stability index in a graphical manner and triggering a hierarchical early warning according to the value of the predictive stability index.

10. A method for real-time monitoring of the construction state of a steel pipe pile guide frame according to any one of claims 1-9, characterized in that, Comprise the following steps: S1: synchronously acquire multi-source heterogeneous data related to a steel pipe pile through a data acquisition module, the multi-source heterogeneous data comprising flow velocity profile data and real-time seabed topography data; S2: Inverting and calculating the distributed hydrodynamic force acting on the steel pipe pile in real time based on the flow velocity profile data through a hydrodynamic inversion module; S3: Self-adaptively modifying the constraint boundary condition of the steel pipe pile based on the real-time seabed topography data through a boundary condition modification module; S4: Establishing and solving a pile mechanics prediction model with the distributed hydrodynamic force as an external load and the self-adaptively modified constraint boundary condition as a boundary to obtain a predicted attitude of the steel pipe pile through an attitude prediction module; S5: Calculating and outputting a predictive stability index representing the construction risk based on the predicted attitude and a preset allowable attitude threshold through a risk index calculation module.

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