A quality and safety four-dimensional collaborative dynamic management and control system for large-scale infrastructure projects

Abstract

This invention discloses a four-dimensional collaborative dynamic control system for quality and safety in large-scale infrastructure projects, belonging to the field of construction engineering management technology. Specifically, it includes: collecting geological body response data and structural deformation data; conducting spatiotemporal correlation analysis on the two types of data to identify the interaction patterns between the geological body and the structure at the same time point, and extracting the evolution laws of the interaction patterns at different construction stages; constructing a geological-structural collaborative response model, coupling the constitutive relationship of the geological body with the mechanical behavior of the structure, reflecting the dynamic response of the system under construction disturbances; generating control commands based on the model, including adjusting the distribution of construction loads and controlling the timing of support, and issuing them to the on-site execution equipment, which then operates the hydraulic control system and support devices according to the commands. This invention achieves four-dimensional collaborative dynamic control of quality and safety in large-scale infrastructure projects, accurately adapting to construction needs and improving the effectiveness and timeliness of control.

Description

Technical Field

[0001] This invention relates to the field of construction engineering management technology, specifically to a four-dimensional collaborative dynamic control system for quality and safety in large-scale infrastructure projects. Background Technology

[0002] The scale and complexity of large-scale infrastructure projects such as bridges, tunnels, and large underground spaces are increasing daily. The construction quality and safety management of these projects are directly related to the success or failure of the project and its long-term operational safety. Traditional management methods rely heavily on pre-established construction plans and human experience, making it difficult to cope with dynamic risks caused by uncertainties in geological conditions and disturbances from multiple overlapping operations during construction. Therefore, achieving refined, intelligent, and dynamic management and control of the construction process has become an urgent need for the industry's development.

[0003] Currently, existing technical solutions in this field typically involve deploying sensor networks to monitor key parameters during construction, such as earth pressure, structural displacement, and strain. Furthermore, some existing technologies attempt to establish numerical models of geological bodies or structures, using monitoring data to update certain parameters of the models, aiming to analyze and predict the project's condition and provide a reference for construction decisions. These methods lay the foundation for the digital management of engineering construction.

[0004] However, existing technical solutions typically assume that geological parameters remain constant during construction or can only change slowly and linearly, failing to fully consider the real-time and dynamic changes in soil mechanical properties caused by continuous construction machinery operations. This simplified approach results in models that cannot accurately capture the complex interactions and real-time responses between the geological body and the structure under construction disturbances. This leads to discrepancies between the control commands generated based on model analysis and the actual dynamic needs of the project, thus limiting the accuracy and timeliness of control effectiveness. Summary of the Invention

[0005] The purpose of this invention is to provide a four-dimensional collaborative dynamic control system for quality and safety in large-scale infrastructure projects, addressing the following technical problems:

[0006] Existing technical solutions often assume that geological parameters are constant during construction or only allow them to change slowly and linearly, without fully considering the real-time dynamic impact of continuous operation of construction machinery on the mechanical properties of the soil. This results in a discrepancy between the control instructions generated by the model and the actual dynamic needs of the project.

[0007] The objective of this invention can be achieved through the following technical solutions:

[0008] A four-dimensional collaborative dynamic management and control system for quality and safety in large-scale infrastructure projects includes:

[0009] The data acquisition module is used to collect geological response data and structural deformation data in the construction area. The geological response data includes soil stress distribution and pore water pressure changes, while the structural deformation data includes support structure displacement and concrete surface strain.

[0010] The spatiotemporal correlation module is used to perform spatiotemporal correlation analysis on geological body response data and structural deformation data, including identifying the interaction patterns between geological bodies and structures at the same time point, and extracting the evolution patterns of interaction patterns in different construction stages.

[0011] The model building module is used to construct a geological-structural coordinated response model based on the interaction mode and evolution law. The geological-structural coordinated response model reflects the dynamic response process of the system under construction disturbance by coupling the constitutive relationship of the geological body and the mechanical behavior of the structure.

[0012] The instruction generation module is used to generate construction control instructions based on the geological-structural collaborative response model. The construction control instructions include adjusting the distribution of construction loads and controlling the support sequence.

[0013] The instruction execution module is used to issue construction control instructions to the on-site execution equipment, which then operates the hydraulic control system and support device according to the instructions.

[0014] As a further aspect of the present invention: the specific process of acquiring geological response data and structural deformation data of the construction area in the data acquisition module is as follows:

[0015] An array of earth pressure sensors is deployed in typical geological units within the construction area. The array of earth pressure sensors is distributed in a grid pattern, and each sensor node has a self-calibration function. Fiber optic strain sensors and tilt measurement units are installed at key structural nodes. The fiber optic strain sensors are pasted along the main force direction, and the tilt measurement units are fixed to the structural surface.

[0016] Control all sensor nodes to collect data in event-triggered mode. Event triggering conditions include changes in the operating status of construction machinery and sudden changes in natural environmental influencing factors. During the collection process, data quality is verified in real time, abnormal data segments are marked, and redundant nodes are activated to collect data.

[0017] The collected geological response data is processed by stratigraphic compensation. The stratigraphic compensation process establishes a compensation function based on the stress history and creep characteristics of soil at different depths. Temperature effect removal is performed on the structural deformation data. Temperature effect removal is calculated using the thermal expansion coefficient of the structural material and real-time temperature monitoring values. All compensated and removed data are integrated into a unified dataset according to spatiotemporal tags.

[0018] As a further aspect of the present invention: the specific process of performing spatiotemporal correlation analysis on geological body response data and structural deformation data in the spatiotemporal correlation module is as follows:

[0019] Geological body response data and structural deformation data are mapped to the same spatiotemporal coordinate system, with the spatiotemporal coordinate system based on the construction progress time axis, and the spatial dimension is divided into grids according to the construction zones.

[0020] Within each spatiotemporal grid, the mutual information of geological body and structural body data is calculated. The mutual information is used to quantify the correlation strength between the two under disturbance. Construction events corresponding to the extreme points of mutual information are extracted, and a construction event-correlation strength mapping table is established.

[0021] The evolution trend of correlation strength in different construction stages was analyzed. The evolution trend was realized by fitting the curve of correlation strength changing with time. The curve fitting adopted a non-parametric regression method. Based on the fitting results, the dominant factors of construction disturbance and their influence paths were identified.

[0022] For each construction event, a disturbance propagation map is generated, which records the transmission path and delay time from the geological body response to the structural deformation. All maps are archived according to the construction stage and used for subsequent updates to the geological-structural co-response model.

[0023] As a further aspect of the present invention: the construction event-association strength mapping table specifically includes:

[0024] When generating the construction event-association strength mapping table, a unique event identifier is assigned to each construction event. The event identifier includes the type of construction machinery, the location of the operation, and the start time. The association strength data comes from the extreme values ​​of mutual information between geological bodies and structural bodies in the corresponding spatiotemporal grid. The extreme values ​​of mutual information are normalized.

[0025] The mapping table is stored using a hierarchical index structure. The first-level index is divided according to the construction stage, and the second-level index is divided according to the geological zone number. Each table entry records the basic information of the construction event, the correlation strength value, the corresponding disturbance propagation spectrum identifier, and the status flag indicating whether it has been called by the model.

[0026] When using the mapping table during the construction process, the mapping table is retrieved based on the current construction progress and location information to find historical similar events and their correlation strength. The matched event data is then input into the geological-structural collaborative response model as a reference for initializing model parameters. After each construction stage is completed, the status flags of the events that have been called in the mapping table are updated and archived to the historical database.

[0027] As a further aspect of the present invention: the specific process of constructing a geological-structural synergistic response model based on interaction patterns and evolution laws in the model construction module is as follows:

[0028] A dynamic response sub-model of soil is established based on the constitutive relationship of geological bodies, which incorporates the degradation of soil stiffness and changes in damping characteristics caused by construction vibration; a dynamic response sub-model of structure is established based on the mechanical behavior of structure, which incorporates the cumulative effect of material fatigue and nonlinear deformation of connection nodes.

[0029] The dynamic response sub-model of soil and the dynamic response sub-model of structure are connected through a coupling interface. The coupling interface handles two types of data exchange, including stress boundary conditions transmitted from soil to structure and displacement constraints fed back from structure to soil. The coupling interface uses an implicit iterative algorithm to maintain the numerical convergence of the data exchange process.

[0030] Construction process variables are embedded in the collaborative response model. These variables include excavation sequence, support timing, and mechanical operation intensity. During model operation, parameter weights are dynamically adjusted based on the real-time construction progress. The parameter weights are learned from historical data. The collaborative response model outputs the joint response state of the geological and structural systems. The joint response state is used to determine whether the system is in a stable range.

[0031] As a further aspect of the present invention: the coupling interface handles two types of data exchange, specifically including:

[0032] The soil dynamic response sub-model outputs the soil stress field and pore water pressure distribution to the coupling interface. The coupling interface interpolates the stress field distribution to obtain the stress boundary conditions at the structural foundation location. The structural dynamic response sub-model outputs the structural displacement field and strain energy density to the coupling interface. The coupling interface extracts the displacement constraint conditions of the soil contact surface based on the displacement field.

[0033] The coupling interface performs bidirectional data matching within each computation step. The data matching adopts a distance-weighted interpolation method to map the stress data of the soil grid nodes to the structural grid nodes, and at the same time, the displacement data of the structural grid nodes to the soil grid nodes. The mapped data is smoothed to eliminate numerical oscillations caused by differences in grid density.

[0034] After each data exchange is completed, the coupling interface checks the compatibility conditions of stress and displacement. The compatibility conditions require that the soil and structure meet the requirements of stress continuity and displacement coordination at the contact surface. When the compatibility conditions are not met, the coupling interface automatically adjusts the interpolation weights and re-exchanges data until the convergence tolerance is met.

[0035] As a further aspect of the present invention: the dynamic adjustment of parameter weights based on the real-time construction progress during model operation specifically includes:

[0036] Real-time monitoring of the operating status and work position of construction machinery, including machinery type, working gear and throttle opening, and work position is obtained through a global positioning system; environmental monitoring data is collected simultaneously, including ambient temperature and humidity.

[0037] The collected real-time data is matched with historical construction progress data. The matching process calculates the similarity between the current operation status and the historical status. The similarity calculation adopts a distance metric method based on multi-feature weighting. The initial values ​​of the corresponding parameter weights in the historical database are selected according to the matching results.

[0038] The parameter weights are dynamically adjusted based on the degree of deviation between the real-time construction progress and the planned progress. The degree of deviation is obtained by comparing the percentage difference between the actual completed work and the planned work. The adjustment process adopts a gradient adjustment strategy, and the weight adjustment range is proportional to the degree of deviation.

[0039] The adjusted parameter weights are input into the geological-structural co-response model. The model adopts the new weight values ​​in the next iteration. After each construction cycle is completed, the actual parameter weights and model output results of that cycle are recorded to update the weight learning samples in the historical database.

[0040] As a further aspect of the present invention: the specific process of generating construction control instructions based on the geological-structural coordinated response model in the instruction generation module is as follows:

[0041] The joint response state output by the geological-structural collaborative response model is input into the construction strategy generator. The construction strategy generator determines whether the current construction parameters are within the allowable range based on the response state. If they exceed the allowable range, the construction strategy generator starts the control logic.

[0042] The control logic first identifies abnormal indicators in the joint response state, including soil stress concentration coefficient and structural deformation acceleration. Based on the type and severity of the abnormal indicators, it matches a preset control strategy library, which contains various construction load adjustment schemes and support sequence combinations.

[0043] The optimal control strategy is selected from the control strategy library. The selection process takes into account the balance between construction efficiency costs and stability gains. The optimal control strategy is then transformed into specific construction control instructions, which include adjusting the excavator's travel speed and digging depth, adjusting the lifting force and point of action of the hydraulic support system, and delaying or advancing the installation time of support components.

[0044] As a further aspect of the present invention: the specific process of matching the construction strategy generator with the control strategy library is as follows:

[0045] The control strategy library stores various control strategies categorized by construction type and geological conditions. Each control strategy is associated with an effect evaluation function, which calculates the expected stability gain and construction delay cost after the strategy is implemented.

[0046] The construction strategy generator searches the control strategy library based on the abnormal indicators in the current joint response status. The search conditions include the type of abnormal indicator, construction stage and geological zone. The retrieved control strategies are sorted according to the effect evaluation function, and the strategy with the highest evaluation score is selected as the candidate strategy.

[0047] Feasibility verification is performed on candidate strategies. Feasibility verification includes checking whether the current status of the construction equipment supports strategy execution and whether the on-site work space meets the operational requirements. If the verification is successful, the candidate strategy is converted into a sequence of instructions that the equipment can execute. If the verification fails, the manual intervention process is initiated.

[0048] As a further aspect of the present invention: in the instruction execution module, the specific process by which the field execution equipment operates the hydraulic control system and the support device according to the instruction content is as follows:

[0049] On-site execution equipment receives construction control instructions, parses the equipment operation parameters in the instructions, including the target pressure value of the hydraulic cylinder, the installation position and timing plan of the support components, converts the equipment operation parameters into control signals, and transmits the control signals to the hydraulic controller and support robot through the industrial bus;

[0050] The hydraulic controller adjusts the output flow and pressure of the hydraulic pump station according to the control signal, drives the hydraulic cylinder to perform lifting or retraction actions, and the support robot locates the installation point according to the control signal, grabs the support components and completes the installation in the specified sequence.

[0051] All operations are recorded in real time. The execution log includes the action completion time, actual pressure value and installation deviation data. The execution log is sent back to the central control system to update the construction process variables in the geological-structure collaborative response model.

[0052] The beneficial effects of this invention are:

[0053] This invention constructs a multi-source sensor network to synchronously collect geological response data and structural deformation data of the construction area, and performs spatiotemporal correlation analysis on these data to identify the interaction patterns and evolution laws between the geological body and the structure. This leads to the establishment of a geological-structural collaborative response model, which couples the constitutive relationship of the geological body with the mechanical behavior of the structure, reflecting the dynamic response process of the system under construction disturbances. Based on the model output, construction control commands are generated to dynamically adjust the distribution of construction loads and the timing of support, effectively overcoming the shortcomings of existing technologies that, due to the assumption of constant geological parameters, cannot respond to real-time changes in soil mechanical properties caused by construction disturbances. By real-time monitoring of the construction process and dynamic adjustment of model parameter weights, as well as establishing a mapping relationship between construction events and correlation strength, precise, real-time, and forward-looking control of the quality and safety status of large-scale infrastructure projects is achieved, significantly improving the adaptability and accuracy of the construction process. Attached Figure Description

[0054] The invention will now be further described with reference to the accompanying drawings.

[0055] Figure 1 This is a schematic diagram of the modules of the present invention. Detailed Implementation

[0056] 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.

[0057] Please see Figure 1 As shown, this invention is a four-dimensional collaborative dynamic management and control system for quality and safety in large-scale infrastructure projects, comprising:

[0058] The data acquisition module focuses on acquiring two types of key data in the construction area. One type is geological response data, which focuses on collecting soil stress distribution and pore water pressure changes to capture the impact of construction on the mechanical state of the geological layer. The other type is structural deformation data, which mainly collects the displacement of the supporting structure and the strain of the concrete surface to monitor the deformation of the engineering structure in real time during construction, providing comprehensive and accurate basic data support for subsequent analysis.

[0059] The spatiotemporal correlation module is responsible for conducting spatiotemporal correlation analysis on the collected geological body response data and structural deformation data. This module first meticulously identifies the interaction patterns between the geological body and the structural body at the same time point, clarifying their dynamic correlation at the same construction moment. Simultaneously, it extracts the evolution patterns of this interaction pattern in different construction stages, such as excavation, support, and main structure pouring, and analyzes the impact trend of the construction process on the interaction relationship between the two.

[0060] Based on the interaction patterns and evolution laws derived from the spatiotemporal correlation module, the model construction module constructs a geological-structural collaborative response model. This model deeply couples the constitutive relationship of the geological body with the mechanical behavior of the structure, fully incorporating various disturbance factors during construction, such as mechanical operation disturbance and excavation disturbance, thereby accurately reflecting the dynamic response process of the system jointly composed of the geological body and the structure under the action of construction disturbance.

[0061] The instruction generation module uses the output of the geological-structural coordinated response model as its core basis to generate specific construction control instructions. These instructions are designed around key construction aspects, including adjusting the distribution of construction loads to ensure that the construction loads in each area of ​​the project are within a reasonable range, and controlling the timing of support to adapt the support work to the dynamic changes of geology and structure, avoiding safety and quality problems caused by supporting too early or too late.

[0062] The instruction execution module plays a crucial role in implementing instructions, accurately distributing the generated construction control instructions to the on-site execution equipment. Based on the instructions, the on-site execution equipment operates the hydraulic control system and the support device. The hydraulic control system adjusts the power output and operating parameters of the construction machinery, while the support device performs actions such as installation and adjustment of the support structure according to the instructions, ensuring that the control instructions are effectively translated into on-site construction operations.

[0063] In a preferred embodiment of the present invention, the specific process of collecting geological response data and structural deformation data of the construction area in the data acquisition module is as follows:

[0064] Within the construction area, based on the preliminary geological survey results, typical geological units with significantly different mechanical properties should be selected, and array-type earth pressure sensors should be deployed within these units. To ensure the comprehensiveness and uniformity of data acquisition, the array-type earth pressure sensors adopt a grid-like distribution, with the distribution density flexibly adjusted according to the actual size and geological complexity of the construction area. Each sensor node has a self-calibration function, which can automatically verify and correct its own acquisition accuracy periodically, effectively avoiding measurement deviations caused by long-term use. Simultaneously, fiber optic strain sensors and tilt measurement units are installed at key structural nodes of the engineering structure, such as beam-column connection points and critical concrete pouring sections. The fiber optic strain sensors must be attached along the principal force direction determined by structural mechanics analysis to accurately capture strain changes in the structure during stress; the tilt measurement units are fixed to the structural surface with high-strength adhesive to prevent construction vibrations from causing positional shifts that would affect the accuracy of the tilt data.

[0065] After the sensors are deployed, all sensor nodes are controlled to collect data in an event-triggered mode to balance the timeliness and efficiency of data acquisition. Event triggering conditions mainly cover two categories: changes in the operating status of construction machinery, including starting and stopping, switching operating gears, and moving the work position; and sudden changes in natural environmental factors, such as a sudden increase in rainfall, a rapid change in ambient temperature, or wind exceeding safe operating thresholds. During data acquisition, the system verifies the quality of the collected data in real time, including the stability of data transmission and whether numerical fluctuations are within a reasonable range. Once an abnormal data segment is detected, the system immediately marks it and activates pre-set redundant nodes for supplementary acquisition. These redundant nodes are distributed in the same area as the main sensor nodes and can quickly replace abnormal nodes to complete data acquisition, ensuring data continuity.

[0066] After data acquisition, the raw data needs to be processed. For geological response data, stratigraphic compensation processing is required. This processing is based on the stress history and creep characteristics of soil at different depths. The stress history refers to the stress state formed by past geological activities in the area, while the creep characteristics are based on the deformation law of the soil under long-term stress. By establishing a compensation function, the interference of the inherent characteristics of soil at different depths on the acquired data is eliminated, restoring the true geological response. The specific compensation function formula is as follows:

[0067] σ comp =σ mon -Δσ hist -Δσ creep ;

[0068] Where, σ compThis represents the compensated geological body response data, in kPa, corresponding to the soil stress distribution or pore water pressure change; σ mon This represents the collected original geological body response data;

[0069] Δσ hist The stress history compensation term represents the deviation between the initial stress of the soil before construction due to geological evolution and the stress at the current monitoring depth. The calculation formula is: Δσ hist =γh-σ0(h), where γ is the effective unit weight of the soil, in kN / m³, for example, 18~20kN / m³ for soft soil and 22~25kN / m³ for rock strata, h is the sensor burial depth, and σ0(h) is the initial effective stress of the soil at depth h, which is obtained from in-situ tests during the geological exploration stage, such as water pressure test and vane shear test.

[0070] Δσ creep This represents the creep compensation term, characterizing the stress loss corresponding to the creep deformation of the soil under long-term self-weight or early construction loads. The calculation formula is Δσ. creep =σ mon (1-e -kd ), k is the soil creep coefficient, obtained from indoor triaxial creep tests, and d is the duration of the soil bearing the current load, which is timed from the start of the first excavation or loading of the area.

[0071] For structural deformation data, temperature effect elimination is required. Workers will first determine the thermal expansion coefficients of materials such as concrete and steel used in the structure, and then combine this with real-time temperature monitoring values ​​obtained from temperature sensors placed near the structure. Appropriate processing will be used to eliminate spurious deformation data caused by temperature changes, ensuring that the deformation data only reflects the true deformation of the structure under construction conditions.

[0072] For strain data monitored by fiber optic strain sensors, the specific formula for eliminating temperature effects is as follows:

[0073] ε true =ε mon -βΔT;

[0074] Where, ε true ε represents the true strain after removing the temperature effect. mon This represents the collected raw structural deformation data, where β represents the coefficient of linear expansion of the structural material, in °C. -1 The concrete should be 1.0×10 -5 ~1.5×10 -5 ℃ -1 The steel material is 1.2 × 10 -5 ~1.4×10 -5 ℃ -1ΔT represents the temperature change, which is the difference between the real-time ambient temperature and the reference temperature (i.e., the ambient temperature 24 hours after the structure is poured) or the reference temperature of the construction plan.

[0075] For the angular displacement data monitored by the tilt measurement unit, the specific formula for eliminating temperature effects is as follows:

[0076] ;

[0077] Where, θ true θ represents the true angular displacement after eliminating temperature effects. mon L represents the original angular displacement monitored by the sensor; H represents the horizontal length of the monitored section of the structure, such as the span of a support beam; and H represents the vertical height of the monitored section of the structure, such as the height of a column.

[0078] After completing the above compensation and elimination processes, all data are integrated according to the precise time label of the acquisition time and the spatial labels such as the specific construction zone and coordinate location of the sensor, forming a unified data set to provide standardized data support for the analysis work of subsequent modules.

[0079] In another preferred embodiment of the present invention, the specific process of performing spatiotemporal correlation analysis on geological body response data and structural deformation data in the spatiotemporal correlation module is as follows:

[0080] The geological response data and structural deformation data need to be mapped to the same spatiotemporal coordinate system to establish a unified benchmark for subsequent analysis. This spatiotemporal coordinate system uses the construction progress timeline as its core benchmark. The timeline's scale is divided in conjunction with key process nodes in the project construction plan, such as excavation layer switching, completion of support work batches, and concrete pouring and curing cycles, ensuring a high degree of synchronization between the time dimension and the actual construction progress. The spatial dimension is strictly divided into grids according to the construction zones planned in the early stages of the project. The grid division takes into account differences in geological conditions, structural density, and the operating range of construction machinery in the construction area. For areas with complex geological structures and concentrated structural elements, the grid density will be appropriately increased, while for areas with relatively uniform geological conditions and less construction activity, the grid density can be moderately reduced. This ensures both data accuracy and analytical efficiency.

[0081] After data mapping is completed, the correlation strength quantification stage begins. Within each predefined spatiotemporal grid, the system calculates the mutual information between geological body response data and structural deformation data. This information, derived from information theory, measures the degree of information sharing between two random variables X (geological body response data) and Y (structural deformation data). Its value is non-negative; MI(X,Y)=0 when X and Y are independent, and reaches its maximum value when X and Y are perfectly correlated. In this invention, X represents geological body data within the spatiotemporal grid, and Y represents structural data within the same grid. The calculation is performed in a discrete manner, using the following formula:

[0082] ;

[0083] Wherein, MI(X,Y) represents the mutual information between geological body data X and structural data Y, in bits;

[0084] x is a discrete value of X, such as a certain interval of soil stress; y is a discrete value of Y, such as a certain interval of structural strain; P(x,y) represents the joint probability of X=x and Y=y; P(x) represents the marginal probability of X=x; P(y) represents the marginal probability of Y=y.

[0085] Mutual information effectively quantifies the correlation strength between two types of data under construction disturbances. When construction activities disturb the geological body, if the structural deformation data changes significantly, the mutual information value will increase significantly; conversely, it will remain at a low level. Staff continuously monitor the changes in mutual information, extracting the construction events corresponding to extreme points (including peaks and troughs). For example, when a large excavator starts excavation, the mutual information reaches its peak, while it may drop to a trough during construction pauses. These construction events are mapped one-to-one with their corresponding mutual information extremes, establishing a construction event-correlation strength mapping table to provide fundamental data support for subsequent analysis.

[0086] Subsequently, the system analyzes the evolution trend of correlation strength in different construction stages. To accurately represent this trend, a non-parametric regression method is used to fit the curve of correlation strength changing over time. Non-parametric regression does not require a pre-defined fixed function form, allowing for more flexible application of the complex and non-linear changes in correlation strength during construction, avoiding analytical biases caused by discrepancies between pre-defined functions and actual conditions. Through the fitted curves, staff can clearly observe the changing characteristics of correlation strength in different construction stages. For example, in the initial excavation stage, correlation strength may show a rapid upward trend, while after entering the support operation stage, the correlation strength gradually stabilizes. Combining the curve's changing characteristics with the corresponding construction activity records, the dominant factors of construction disturbance can be further identified. For instance, if a significant change in correlation strength in a certain stage is mainly caused by the continuous operation of large machinery, then the machinery operation is the dominant disturbance factor in that stage. Simultaneously, the influence path of the disturbance can be traced: the machinery operation first disturbs the geological body of the construction area, leading to changes in soil stress distribution. This change is further transmitted to surrounding structures, ultimately causing structural deformation.

[0087] Finally, for each extracted construction event, the system generates a corresponding disturbance propagation map. This map details the complete transmission path from the geological body response to the structural deformation. For example, it records the process from the moment a change is detected by an earth pressure sensor in a geological unit, sequentially marking the transmission of this change to adjacent geological areas and then to the structural support nodes. It also records the delay time during the transmission process, i.e., the time interval from the first change in geological data to the corresponding change in structural data. All generated disturbance propagation maps are categorized and archived according to construction stages, such as storing maps for the excavation stage, support stage, and main structure pouring stage separately. This facilitates quick retrieval of map data for the corresponding construction stage when updating the geological-structural co-response model, allowing the model to more accurately reflect the disturbance propagation patterns at different stages.

[0088] In a preferred embodiment of this invention, the construction event-associated strength mapping table specifically includes:

[0089] When generating the construction event-association strength mapping table, a unique event identifier is first assigned to each construction event. The event identifier must contain three key pieces of information: the type of construction machinery, such as a tracked excavator, hydraulic support trolley, concrete pump, etc.; the work location, accurate to the construction zone number and the coordinate range within that zone, such as "Z3 construction zone (X120-Y85 to X150-Y110)"; and the start time, accurate to the minute. This ensures that each event identifier is unique and can quickly distinguish different construction events. The association strength data is derived from the extreme values ​​of mutual information between geological and structural data within the corresponding spatiotemporal grid. To facilitate comparative analysis of association strength between different construction events, the extreme values ​​of mutual information are normalized, ensuring that all association strength values ​​are within a uniform and comparable range.

[0090] The mapping table uses a hierarchical index structure for storage, which significantly improves data retrieval efficiency. The first-level index is divided according to construction stages, such as foundation construction, main structure construction, and ancillary facility construction. The second-level index further divides each construction stage according to geological zone numbers, such as geological zone D1 and geological zone D2 under the foundation construction stage. In addition to recording basic information about the construction event (including event name, operation duration, number of participating equipment, etc.), correlation strength value, and corresponding disturbance propagation spectrum identifier, each table entry also adds a status flag indicating whether it has been called by the model. The status flag is divided into two categories: "called" and "not called," which facilitates staff to monitor the data usage in real time.

[0091] When using the mapping table during construction, the system automatically retrieves the table based on the current construction progress and work location information. For example, if the main structure is under construction and hydraulic support work is being carried out in geological zone D2, the system will search for past construction events of the same type of hydraulic support work in geological zone D2 and similar geological zones under this stage, finding historical similar events and their associated intensity data. This matched event data is input into the geological-structural collaborative response model as a reference for model parameter initialization, making the initial state of the model more closely match the current construction situation and reducing model debugging time. After each construction stage is completed, the staff updates the event status flags in the mapping table that have been called by the model within that stage, changing "not called" to "called," and archives the mapping table data for the entire stage to the historical database. This facilitates data management for subsequent construction stages and provides historical data for data analysis of similar projects.

[0092] In another preferred embodiment of the present invention, the specific process of constructing a geological-structural synergistic response model based on interaction patterns and evolution laws in the model construction module is as follows:

[0093] Dynamic response sub-models were established for the different mechanical properties of geological bodies and structural bodies. When constructing the dynamic response sub-model for soil, the constitutive relationship of the geological body was used as the theoretical basis, with a focus on incorporating the changes in soil stiffness degradation and damping characteristics caused by construction vibration. During construction, the continuous operation of large machinery such as tunnel boring machines and tracked excavators generates periodic vibrations. These vibrations alter the arrangement of particles within the soil, potentially causing tightly packed particles to loosen, leading to a decrease in the soil's overall resistance to deformation—that is, soil stiffness degradation. Simultaneously, vibration energy is absorbed by friction between soil particles and the flow of pore water, changing the soil's ability to dissipate vibration energy—that is, changes in damping characteristics. Incorporating these two types of changes into the sub-model allows for a more realistic simulation of the mechanical behavior of soil under construction vibration, avoiding prediction errors in geological body response due to neglecting the influence of vibration.

[0094] When constructing the structural dynamic response sub-model, the core focus is on the mechanical behavior of the structure, with particular emphasis on the cumulative effect of material fatigue and the nonlinear deformation of connection nodes. During construction, engineering structures are subjected to repeated loads. For example, concrete support beams experience repeated changes in soil pressure due to excavation, and steel components experience periodic stresses due to mechanical vibration. Long-term repeated loading leads to the gradual accumulation of micro-damage within the materials, i.e., the cumulative effect of material fatigue. This effect causes the load-bearing capacity of the material to gradually decrease over time. Simultaneously, structural connection nodes, such as bolted connections and welded joints, do not exhibit linear deformation under stress. When the load is small, the node deformation is roughly linear with the load, but when the load reaches a certain level, the nodes exhibit slight slippage or plastic deformation, i.e., nonlinear deformation of the connection nodes. Integrating these two characteristics into the sub-model allows for accurate capture of the mechanical response patterns of the structure under long-term construction loads, ensuring the accuracy of the predicted dynamic response of the structure.

[0095] After the sub-models are constructed, the soil dynamic response sub-model and the structural dynamic response sub-model are connected through a coupling interface to form a basic framework for coordinated response. The core function of the coupling interface is to enable bidirectional data interaction between the two types of sub-models. During construction, the soil and structure are not isolated entities; when the soil is disturbed, it transmits stress to the structure, and the deformation of the structure, in turn, constrains the displacement of the soil. This interaction needs to be simulated through data exchange. The coupling interface mainly handles two types of data exchange: one is the stress boundary conditions transmitted from the soil to the structure. The soil dynamic response sub-model calculates the soil stress field and pore water pressure distribution at different locations within the construction area. The calculation of the soil stress field is based on the stress balance equation under construction disturbance (xy plane strain problem in Cartesian coordinates), specifically:

[0096] ;

[0097] in, and τ represents the effective normal stress in the x and y directions, respectively, with units of kPa; xy Represents the shear stress in the xy plane; ρ represents the soil density; g represents the gravitational acceleration; α represents the dip angle of the strata in the construction area; u x and u y represents the soil displacement in the x and y directions, respectively; t is time; and These are the accelerations in the x and y directions, respectively, representing the dynamic effects of construction vibration. They are calculated from the mechanical vibration frequency monitored by vibration sensors. For example, if the excavator's vibration frequency is 2~5Hz, then the acceleration amplitude is 0.1~0.5m / s².

[0098] Based on Darcy's law, the governing equation for pore water pressure distribution is:

[0099] ;

[0100] Among them, u w This represents pore water pressure, with units of kPa; k x and k y This represents the soil permeability coefficient in the x and y directions, expressed in m / s. For soft soil, a value of 1 × 10⁻⁶ is used. -8 ~1×10 -6 m / s, for sand and gravel strata, take 1×10 -4 ~1×10 -2 m / s; γ w ε represents the specific weight of water, taken as 9.8 kN / m³. v The displacement represents the volumetric strain of the soil, calculated from the stress equilibrium equations. ; e represents the soil void ratio, which is 0.8~1.2 for soft soil and 0.5~0.8 for cohesive soil. This represents the rate of change of the porosity over time.

[0101] The coupling interface processes the stress data based on the actual location of the foundation to obtain the stress boundary conditions borne by the foundation, ensuring that the stress on the structure in the model is consistent with the actual soil action. Another type of constraint is the displacement constraint condition fed back from the structure to the soil. The structural dynamic response sub-model outputs the displacement field and strain energy density of the structure after being subjected to stress. The coupling interface extracts the displacement data of the contact surface between the structure and the soil as a constraint condition for soil deformation, avoiding mismatches between soil and structural displacements. To ensure the stability of the values ​​during data exchange, the coupling interface employs an implicit iterative algorithm. After each data exchange, it checks whether the calculation results of the two types of sub-models are consistent. If a discrepancy exists, the data exchange and calculation are repeated until the values ​​converge, ensuring the reliability of the calculation results of the collaborative response model.

[0102] Finally, construction process variables are embedded in the collaborative response model to achieve dynamic adaptation between the model and actual construction. These variables encompass excavation sequence, support timing, and mechanical operation intensity. These variables directly affect the intensity and frequency of construction disturbances. For example, different excavation sequences, such as layered or segmented excavation, lead to different areas and times of soil exposure. Support timing that is too early or too late alters the timing of load bearing on the structure. Mechanical operation intensity, such as the excavator's tunneling speed and the tunnel boring machine's thrust, directly determines the magnitude of the disturbance. During model operation, the parameter weights corresponding to these variables are dynamically adjusted based on the real-time construction progress. The determination of these parameter weights relies on historical data learning. By analyzing the impact of parameters on the model's output under different construction processes in similar past projects, the initial weights of each parameter at different stages are determined. The collaborative response model ultimately outputs the joint response state of the geological and structural systems. Based on this state, staff can determine whether the current system is in a stable range. If indicators such as soil stress and structural displacement in the joint response state are within the preset safety range, the system is stable; if they exceed the range, subsequent command generation processes need to be initiated for adjustment.

[0103] In a preferred embodiment, the coupling interface handles two types of data exchange, specifically including:

[0104] The soil dynamic response sub-model continuously outputs soil stress field and pore water pressure distribution data within the construction area to the coupling interface. The soil stress field data reflects the magnitude and direction of pressure exerted on the soil at different locations, while the pore water pressure distribution data reflects the pressure state of the water in the soil pores. These two types of data jointly determine the forces exerted by the soil on the structure. Upon receiving this data, the coupling interface performs interpolation based on the specific location of the structural foundation. Since the positions of the soil mesh nodes and the structural foundation nodes are not completely coincident, an interpolation method is needed to map the stress data of the soil mesh nodes onto the structural foundation nodes, ultimately obtaining the stress boundary conditions at the structural foundation location. This ensures that the stress exerted on the structure in the model matches the actual soil action.

[0105] Simultaneously, the structural dynamic response sub-model outputs displacement field and strain energy density data of the structure to the coupling interface. The displacement field data records the magnitude and direction of displacement at each node of the structure after being subjected to force, while the strain energy density data reflects the energy stored within the structure due to deformation. These two types of data directly reflect the deformation state of the structure. The coupling interface extracts the displacement data of the contact surface between the structure and the soil from the displacement field data, using it as a displacement constraint condition for the soil contact surface. That is, at the contact point with the structure, the displacement of the soil cannot exceed the displacement of the structure, ensuring that the soil and structure do not separate or embed at the contact point, conforming to the mechanical equilibrium principles in practical engineering.

[0106] Within each computational step, the coupling interface performs bidirectional data matching to ensure that the soil and structural data are compatible. Data matching employs a distance-weighted interpolation method, which assigns weights based on the distance between soil and structural mesh nodes. Closer nodes have a greater weight in influencing the target node, while farther nodes have a smaller weight. This method effectively ensures the accuracy of the interpolation results and avoids data distortion caused by differences in node positions. After interpolation, the coupling interface smooths the mapped data. Since the mesh densities of the soil and structural meshes may differ (e.g., the soil mesh is coarser and the structural mesh is finer), direct mapping can lead to drastic data fluctuations. Smoothing eliminates these fluctuations, making the data changes more consistent with actual mechanical laws and providing a stable data foundation for subsequent calculations.

[0107] After each data exchange, the coupling interface checks the compatibility conditions of stress and displacement. The core requirement for compatibility is that the soil and structure at the contact surface satisfy stress continuity and displacement coordination. Stress continuity means that the stresses on both sides of the contact surface are equal in magnitude and opposite in direction, without abrupt stress changes. Displacement coordination means that the displacements on both sides of the contact surface are equal in magnitude and consistent in direction, without gaps or overlaps. When the compatibility conditions are not met, for example, if there is a significant deviation between the soil stress and structural stress at the contact surface, or if there is a displacement mismatch, the coupling interface automatically adjusts the interpolation weights, correcting the interpolation weights of nodes in areas with large deviations, and then re-exchanges and matches the data. This process is repeated until the stress and displacement meet the preset convergence tolerance, ensuring that the interaction between the soil and structure in the model conforms to actual mechanical laws and providing a guarantee for the calculation accuracy of the cooperative response model.

[0108] In a preferred embodiment of this invention, the dynamic adjustment of parameter weights based on the real-time construction progress during model runtime specifically includes:

[0109] The first step is real-time monitoring. The system continuously monitors the operating status and location of construction machinery using sensors and positioning devices. The operating status includes machine type, operating gear, and throttle opening. Different types of machinery, such as excavators, cranes, and tunnel boring machines, significantly vary in their disturbance intensity to the construction area. The operating gear (high or low speed) directly affects the machine's operating efficiency and vibration frequency, while the throttle opening determines the machine's power output, thus affecting the intensity of work. The operating location is obtained through a global positioning system, which can capture the machine's specific coordinates within the construction area in real time, accurately locating the machine's operating range and providing locational basis for subsequent analysis of construction disturbance in the area. Simultaneously, the system also collects environmental monitoring data, mainly including ambient temperature and humidity. Temperature affects the thermal expansion and contraction of structural materials, thus altering the deformation characteristics of the structure, while humidity affects the soil's moisture content, leading to changes in the soil's mechanical properties. These environmental factors must all be considered in the parameter weighting adjustment.

[0110] The next step is data matching. The system matches the collected real-time data with data in the historical construction progress database. The core of the matching process is calculating the similarity between the current operating state and the historical state. A multi-feature weighted distance metric method is used, which selects multiple key features such as machinery type, working level, work location, ambient temperature, and ambient humidity as matching indicators. Different weights are assigned to each feature based on its impact on construction disturbances; for example, machinery type has a much greater impact on disturbances than ambient humidity, therefore, machinery type has a higher weight. By calculating the comprehensive distance between the current data and historical data on these features, the smaller the distance, the higher the similarity. Based on the matching results, the system selects the parameter weights corresponding to the historical construction data with the highest similarity from the historical database and uses them as the initial values ​​for the current model's parameter weights. Such initial values ​​are more closely aligned with the current construction scenario and can significantly reduce model initialization errors.

[0111] Next comes the deviation correction stage. The system compares the real-time construction progress with the planned construction progress and calculates the degree of deviation. The degree of deviation is obtained by comparing the percentage difference between the actual completed work and the planned work. For example, if a construction phase plans to complete 20% of the excavation, but only 12% is actually completed, the deviation is 8%. Based on the degree of deviation, the system uses a gradient adjustment strategy to dynamically correct the parameter weights. If the deviation is large, it means that the current parameter weights deviate significantly from the actual construction situation, requiring a substantial adjustment of the weights; if the deviation is small, only a small adjustment of the weights is needed. This adjustment method can quickly adapt to changes in the construction progress while avoiding drastic fluctuations in the model output caused by sudden changes in weights, ensuring the stability of the model operation.

[0112] Finally, there's the weight application and closed-loop update stage. The system inputs the adjusted parameter weights into the geological-structural co-response model. In the next iteration, the model uses the new weight values ​​to make the calculation results more closely reflect the actual situation of the current construction progress. After each construction cycle, such as a complete excavation and support operation cycle, the system records the actual parameter weights used in that cycle and the joint response state results output by the model, and archives this data to a historical database as new samples for subsequent weight learning. As construction progresses, the samples in the historical database become increasingly rich, and the adjustment of the model parameter weights becomes more and more accurate, forming a closed-loop mechanism of "monitoring, adjustment, application, and updating," continuously improving the co-response model's adaptability to dynamic changes in construction.

[0113] In another preferred embodiment of the present invention, the specific process of generating construction control instructions based on the geological-structural coordinated response model in the instruction generation module is as follows:

[0114] First, the joint response state output from the geological-structural collaborative response model is completely input into the construction strategy generator. The joint response state encompasses key data such as soil stress distribution, structural displacement, pore water pressure changes, and structural strain values ​​within the construction area. These data collectively reflect the overall stress and deformation state of the geological body and structure. The construction strategy generator invokes pre-defined judgment logic to compare each data point in the joint response state with the allowable ranges of construction parameters. These allowable ranges are comprehensively determined based on engineering design standards, geological survey reports, and safe operation cases of similar projects. For example, the allowable soil stress value is set according to the soil strength characteristics at different depths, and the allowable structural displacement value is determined in conjunction with the material bearing capacity of the structure. If all data are within the allowable range, the current construction state is stable, and no control is required. If any data exceeds the allowable range, such as the soil stress concentration factor exceeding the design threshold or the structural deformation acceleration exceeding the safety limit, the construction strategy generator will immediately activate the control logic and proceed to the next step of anomaly handling.

[0115] After the control logic is activated, it first accurately identifies abnormal indicators in the joint response state. These abnormal indicators mainly include soil stress concentration coefficient and structural deformation acceleration. Abnormal soil stress concentration coefficients typically occur in areas with uneven excavation intensity, such as concentrated excavator operation at a certain construction section, causing local soil stress to far exceed that of the surrounding area. Abnormal structural deformation acceleration may stem from insufficient support strength or a lag in the connection between support and excavation operations, causing the structure to deform faster under soil pressure. After identifying the abnormal indicators, the system further analyzes the type of anomaly (whether it's a soil stress problem or a structural deformation problem) and its severity (e.g., the proportion of stress exceeding the allowable range, the rate of increase in deformation acceleration), and uses this information to match a pre-set control strategy library. The control strategy library stores solutions for different construction scenarios, covering a variety of construction load adjustment schemes and support sequence combinations. Construction load adjustment schemes include adjusting the intensity of mechanical operations in different areas and optimizing the stacking position of slack materials. Support sequence combinations include pre-installing temporary support components, adjusting the interval between permanent support and excavation operations, and optimizing the installation sequence of support components, ensuring that a corresponding alternative strategy can be found for each abnormal situation.

[0116] Next, the system will select the optimal control strategy from the matched candidate strategies. The core of the selection process is to balance the cost of construction efficiency with the gain of stability: the gain of stability mainly evaluates the effect of the strategy on the return of abnormal indicators to the safe range after implementation, such as whether a strategy can reduce the soil stress concentration coefficient to below the allowable value, or significantly slow down the structural deformation acceleration; the cost of construction efficiency focuses on the impact of the strategy on the construction progress, such as whether implementing a strategy requires suspending some operations, or whether it will increase the time for machinery scheduling. For example, one strategy can quickly control the structural deformation acceleration to a safe range, but requires suspending excavation operations for 2 hours. Another strategy, although it reduces the rate of deformation acceleration slightly, only requires adjusting the machinery operating parameters and does not require suspending operations. The system will comprehensively judge the balance between the two and select the strategy with less impact on efficiency as the optimal solution under the premise of ensuring safety. Once the optimal control strategy is determined, the system will translate it into specific and executable construction control instructions. These instructions will clearly target specific construction equipment and operational requirements. For example, adjusting the excavator's travel speed to reduce the frequency of excavation disturbance, adjusting the excavator's digging depth to control the intensity of soil disturbance during a single excavation, adjusting the lifting force of the hydraulic support system to balance excessively high local soil pressure, adjusting the position of the hydraulic support's application point to optimize the structural stress distribution, and delaying or advancing the installation time of support components based on the structural deformation to ensure that the support operation can promptly offset the impact of soil pressure on the structure.

[0117] In a preferred embodiment of this invention, the specific process of matching the construction strategy generator with the control strategy library is as follows:

[0118] The control strategy library manages various control strategies using a categorized storage approach. The main categorization dimensions include construction type and geological conditions. Construction types are divided according to the core operational stages of the project, such as excavation, support, main structure pouring, and installation of ancillary facilities. Different construction types correspond to different disturbance factors and risk points. For example, the risks of excavation are mainly concentrated on changes in soil stress, while the risks of support are mainly concentrated on the strength and timing of support. Geological conditions are divided according to the soil characteristics of the construction area, such as soft soil, weathered rock, gravel, and cohesive soil. Different geological conditions respond significantly differently to construction disturbances. For example, soft soil is more sensitive to load changes and is prone to significant settlement, while weathered rock requires special attention to prevent rockfall. Multiple targeted control strategies are stored under each category, and an effect evaluation function is associated with each strategy. The effectiveness evaluation function incorporates engineering practice data to quantify the expected stability gain and construction delay cost after implementing the strategy. The expected stability gain is determined by simulating the improvement of abnormal indicators after the strategy is implemented, such as the expected decrease in the soil stress concentration factor after the strategy is implemented. The construction delay cost is determined by analyzing the duration of the strategy's impact on the schedule of key processes, such as the additional work time required to implement the strategy. The specific calculation formula for the effectiveness evaluation function is as follows:

[0119] S = w1G - w2C;

[0120] Where S represents the effectiveness evaluation score of the control strategy, with a value range of -10 to 10; w1 represents the stability gain weight, with a value range of 0.6 to 0.8, determined according to the engineering safety priority; w2 represents the delay cost weight, with a value range of 0.2 to 0.4, satisfying w1+w2=1;

[0121] G represents the expected stable gain, ranging from 0 to 10. It is used to quantify the degree to which outlier indicators return to a safe range after the strategy is implemented. The calculation formula is: ;ΔI max This represents the measured value of the current abnormal index, such as the measured value of the soil stress concentration factor being 1.8; ΔI safe Safety thresholds representing abnormal indicators, such as a safety threshold of 1.2 for the soil stress concentration factor; ΔI post This indicates the expected value of abnormal indicators after the implementation of a strategy, such as the expected stress concentration factor decreasing to 1.3 after implementing a certain strategy.

[0122] C represents the cost of construction delay, ranging from 0 to 10, used to quantify the impact of the strategy on the construction schedule. The calculation formula is as follows: ;t delay This indicates the additional delay caused by strategy implementation, such as the additional 2 hours required to adjust support timing; t cycleThis indicates the planned duration of the current construction cycle, such as a planned duration of 12 hours for the excavation-support cycle.

[0123] When a matching strategy is needed, the construction strategy generator initiates a precise search based on anomalous indicators in the current joint response state. Search criteria include not only the type of anomalous indicator (abnormal soil stress or structural deformation), but also the current construction stage and geological zoning. Construction stages include initial site leveling, mid-term excavation and support, and later structural pouring. Different stages have different construction objectives and permissible control methods. For example, the initial excavation stage allows for more adjustable parameters, while the later pouring stage must avoid disturbing the already formed structure. Geological zoning corresponds to different pre-divided geological units within the construction area, ensuring that the retrieved strategy matches the geological characteristics of the current work area. Based on these search criteria, the system filters all suitable control strategies from the control strategy library and calls an effect evaluation function to score these strategies. The scoring process comprehensively considers the expected stability gain and the cost of construction delay; the higher the stability gain and the lower the delay cost, the higher the strategy's evaluation score. The system sorts the strategies from highest to lowest evaluation score and selects the highest-scoring strategy as a candidate strategy, ensuring that the candidate strategy achieves the optimal balance between safety and efficiency.

[0124] Once a candidate strategy is determined, the system will conduct a rigorous feasibility check to prevent execution failure due to incompatibility between the strategy and actual site conditions. The feasibility check mainly includes two aspects: First, it checks whether the current status of the construction equipment supports strategy execution. For example, if a candidate strategy requires the simultaneous operation of two hydraulic support trolleys, the system will verify the number of trolleys of that model on site, their operating status (whether there are any malfunctions), and whether they are performing other tasks. Second, it checks whether the on-site working space meets the operational requirements. For example, if the strategy requires adjusting the excavator's working path to distribute the load, the system will use on-site monitoring footage or 3D modeling data to determine whether there are obstacles on the adjusted path and whether the working space is sufficient for the excavator to turn and move. If the check passes, the system will break down the candidate strategy into a sequence of executable instructions for the equipment, specifying the operating steps, parameter requirements, and execution time for each piece of equipment. If the check fails, for example, due to insufficient equipment or limited working space, the system will immediately initiate a manual intervention process, synchronizing the candidate strategy, check results, and actual site conditions to the engineering team. Technical personnel will then adjust the strategy based on on-site research or develop new alternative solutions to ensure the smooth implementation of the control instructions.

[0125] In another preferred embodiment of the present invention, the specific process by which the field execution device operates the hydraulic control system and the support device according to the instruction content in the instruction execution module is as follows:

[0126] The on-site execution equipment first receives construction control instructions from the instruction generation module. These instructions are transmitted in a standardized data format to avoid parsing errors caused by format differences. The equipment's built-in instruction parsing unit breaks down the instruction content segment by segment, focusing on extracting the equipment operating parameters. These parameters are the core basis for guiding equipment actions, including the target pressure value of the hydraulic cylinder, the installation position of the support components, and the timing plan. The target pressure value of the hydraulic cylinder determines the power output intensity of the hydraulic system and needs to be determined according to the support requirements of different construction scenarios. The installation position of the support components must accurately correspond to the structural nodes marked on the construction drawings to ensure that the support effect meets the design requirements. The timing plan clarifies the execution sequence and interval time of each action and must be synchronized with the overall construction progress. After parsing, the equipment converts these parameters into control signals that conform to industrial control standards. The control signals are transmitted to the hydraulic controller and the support robot via an industrial bus. The industrial bus has strong anti-interference capabilities and stable transmission rates, avoiding the impact of mechanical vibration and electromagnetic interference in the construction environment on signal transmission, ensuring that the control signals are transmitted completely and accurately to the target equipment.

[0127] After receiving the control signal, the hydraulic controller adjusts the output flow and pressure of the hydraulic pump station according to the parameters in the signal. When increased support is needed, the hydraulic controller increases the output pressure of the pump station, increasing the volume of hydraulic oil in the hydraulic cylinder, driving the hydraulic cylinder to perform a lifting action, thereby providing stronger support for the structure or soil. When adjusting the support position or retracting the hydraulic cylinder, the controller reduces the output pressure of the pump station or adjusts the flow in the opposite direction, causing the hydraulic cylinder to retract slowly. At the same time, the support robot activates its positioning function according to the control signal, accurately locating the preset installation points of the support components through linkage with the on-site positioning system. After positioning, the robot's gripping device stably grasps the support components and installs them in the designated positions according to the time nodes in the time sequence plan, ensuring that the installation is secure.

[0128] Throughout the entire operation, the on-site execution equipment records execution logs in real time. These logs contain key information, including action completion times for tracking progress at each stage; actual pressure values, which can be compared with target hydraulic cylinder pressure values ​​to verify the hydraulic system's execution accuracy; and installation deviation data, derived by measuring the deviation between the actual installation position and the design position of the support components, reflecting the precision of the installation work. The execution logs are transmitted back to the central control system in real time via a data transmission module. The central control system integrates this data to update the construction progress variables in the geological-structural collaborative response model, enabling the model to promptly acquire the actual on-site construction status and providing data support for generating more realistic control commands.

[0129] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A quality and safety four-dimensional collaborative dynamic management and control system for large-scale infrastructure projects, characterized in that, The method comprises the following steps: a data acquisition module is used to acquire geological body response data and structure deformation data in a construction area, the geological body response data including soil stress distribution and pore water pressure change, and the structure deformation data including support structure displacement and concrete surface strain; a space-time correlation module is used to perform space-time correlation analysis on the geological body response data and the structure deformation data, including identifying interaction modes between the geological body and the structure at the same time node, and extracting evolution rules of the interaction modes in different construction stages; a model construction module is used to construct a geological-structure collaborative response model according to the interaction modes and the evolution rules, the geological-structure collaborative response model reflecting a dynamic response process of the system under construction disturbance by coupling the geological body constitutive relation and the structure mechanical behavior; an instruction generation module is used to generate construction regulation and control instructions based on the geological-structure collaborative response model, the construction regulation and control instructions including adjusting construction load distribution and controlling support timing; an instruction execution module is used to issue the construction regulation and control instructions to on-site execution equipment, and the on-site execution equipment operates a hydraulic control system and a support device according to the instruction content; in the space-time correlation module, the specific process of performing space-time correlation analysis on the geological body response data and the structure deformation data is as follows: the geological body response data and the structure deformation data are mapped to the same space-time coordinate system, the space-time coordinate system taking a construction progress time axis as a reference, and a spatial dimension being grid divided according to construction zoning; the mutual information amount of the geological body and the structure data is calculated in each space-time grid, the mutual information amount being used to quantify the correlation strength of the two under disturbance; a construction event corresponding to an extreme point of the mutual information amount is extracted, and a construction event-correlation strength mapping table is established; the evolution trend of the correlation strength in different construction stages is analyzed, the evolution trend being realized by fitting a curve of the correlation strength changing with time, and a non-parametric regression method being used for curve fitting; the dominant factor of construction disturbance and its influence path are identified according to the fitting result; a disturbance propagation graph is generated for each construction event, the disturbance propagation graph recording a transmission path and a delay time of the geological body response to the structure deformation; all the graphs are archived according to construction stages, and are used to update the geological-structure collaborative response model subsequently; the construction event-correlation strength mapping table specifically comprises: when the construction event-correlation strength mapping table is generated, a unique event identifier is assigned to each construction event, the event identifier including a construction machinery type, a work position and a start time; the correlation strength data is derived from the mutual information amount extreme value of the geological body and the structure data in the corresponding space-time grid, and the mutual information amount extreme value is subjected to normalization processing; the mapping table is stored in a hierarchical index structure, a first layer index being divided according to construction stages, and a second layer index being divided according to geological zoning numbers; each table entry records basic information of a construction event, a correlation strength value, a corresponding disturbance propagation graph identifier and a state marker indicating whether the table entry has been called by the model. In the construction process, the mapping table is retrieved according to the current construction progress and position information, a similar historical event and its associated strength are found, the matched event data are input into the geological-structure collaborative response model as a reference basis for model parameter initialization, and the state markers of the called events in the mapping table are updated and archived to the historical database after each construction stage is completed.

2. The quality and safety four-dimensional collaborative dynamic management and control system for large-scale infrastructure projects according to claim 1, characterized in that, The specific process of collecting geological body response data and structure deformation data in the data collection module is as follows: Arrayed soil pressure sensors are arranged in the typical geological unit of the construction area, the arrayed soil pressure sensors are distributed in a grid shape, each sensor node has a self-calibration function, optical fiber strain sensors are pasted along the main stress direction, and an inclination measuring unit is fixed on the structure surface; All sensor nodes collect data in an event-triggered mode, the event-triggered conditions include changes in the operation state of construction machinery and mutations in natural environmental influence factors, the data quality is checked in real time during the collection process, abnormal data segments are marked and redundant node re-collection is started; The collected geological body response data are subjected to stratum compensation processing, the stratum compensation processing is based on the stress history and creep characteristics of soil bodies at different depths to establish a compensation function, the structure deformation data are subjected to temperature effect elimination, the temperature effect elimination is calculated by using the thermal expansion coefficient of the structure material and the real-time temperature monitoring value; and all the compensated and eliminated data are integrated into a unified data set according to the space-time label.

3. The quality and safety four-dimensional collaborative dynamic management and control system for large-scale infrastructure projects according to claim 1, characterized in that, The specific process of constructing the geological-structure collaborative response model according to the interaction mode and evolution law in the model construction module is as follows: A soil dynamic response sub-model is established based on the constitutive relation of the geological body, the soil dynamic response sub-model introduces the soil stiffness degradation and damping characteristic changes caused by construction vibration; a structure dynamic response sub-model is established based on the mechanical behavior of the structure body, the structure dynamic response sub-model introduces the material fatigue accumulation effect and nonlinear deformation of the connecting node; The soil dynamic response sub-model and the structure dynamic response sub-model are connected through a coupling interface, the coupling interface processes data exchange between the two types of data, including stress boundary conditions transmitted from the soil to the structure and displacement constraint conditions fed back from the structure to the soil, and the coupling interface uses an implicit iteration algorithm to maintain numerical convergence in the data exchange process; Construction process variables are embedded in the collaborative response model, the construction process variables include excavation step sequence, support timing and mechanical operation intensity, the model dynamically adjusts parameter weights according to real-time construction progress during operation, the parameter weights are obtained through historical data learning, and the collaborative response model outputs the joint response state of the geological and structure systems, which is used to judge whether the system is in a stable interval.

4. The quality and safety four-dimensional collaborative dynamic management and control system for large-scale infrastructure projects according to claim 3, characterized in that, The specific process of the coupling interface processing two types of data exchange includes: The soil dynamic response sub-model outputs soil stress field and pore water pressure distribution to the coupling interface, the coupling interface interpolates the stress field distribution to obtain the stress boundary conditions of the structure foundation position; and the structure dynamic response sub-model outputs structure displacement field and strain energy density to the coupling interface, the coupling interface extracts the displacement constraint conditions of the soil contact surface according to the displacement field. The coupling interface performs bidirectional data matching in each calculation step, which adopts a distance-weighted interpolation method to map the stress data of the soil grid nodes to the structural grid nodes and the displacement data of the structural grid nodes to the soil grid nodes, and then performs smoothing processing on the mapped data to eliminate numerical oscillation caused by the difference in grid density; After each data exchange, the coupling interface checks the compatibility conditions of stress and displacement, which require that the soil and the structure satisfy the stress continuity and displacement compatibility at the contact surface. When the compatibility conditions are not met, the coupling interface automatically adjusts the interpolation weight and re-performs data exchange until the convergence tolerance is met.

5. The quality and safety four-dimensional collaborative dynamic management and control system for large-scale infrastructure projects according to claim 3, characterized in that, The model runs dynamically adjust the parameter weights according to the real-time construction progress, which specifically includes: Real-time monitoring of the operating state and working position of the construction machinery, the operating state including the type of machinery, the working gear and the throttle opening, and the working position being obtained through a global positioning system; simultaneously collecting environmental monitoring data, including environmental temperature and humidity; Matching the collected real-time data with historical construction progress data, the matching process calculating the similarity of the current operating state and the historical state, the similarity calculation adopting a distance measurement method based on multi-feature weighting, and selecting the corresponding initial value of the parameter weight in the historical database according to the matching result; Dynamically correcting the parameter weight according to the deviation degree of the real-time construction progress and the planned progress, the deviation degree being obtained by comparing the percentage difference between the actual completed engineering quantity and the planned engineering quantity, and the correction process adopting a gradient adjustment strategy, the weight adjustment amplitude being proportional to the deviation degree; Inputting the adjusted parameter weight into the geology-structure collaborative response model, the model using the new weight value in the next iteration calculation, and recording the actual parameter weight and the model output result of each construction cycle for updating the weight learning samples in the historical database.

6. The quality and safety four-dimensional collaborative dynamic management and control system for large-scale infrastructure projects according to claim 1, characterized in that, In the instruction generation module, the specific process of generating construction control instructions based on the geology-structure collaborative response model is: Inputting the joint response state output by the geology-structure collaborative response model into the construction strategy generator, the construction strategy generator determining whether the current construction parameter is within the allowable range based on the response state, and if it exceeds the allowable range, the construction strategy generator starts the control logic; The control logic first identifies abnormal indicators in the joint response state, including the soil stress concentration coefficient and the structural deformation acceleration, matches the preset control strategy library according to the type and severity of the abnormal indicators, and the control strategy library contains multiple construction load adjustment schemes and support timing combinations; Selecting the optimal control strategy from the control strategy library, considering the balance between construction efficiency cost and stability gain, converting the optimal control strategy into specific construction control instructions, and the construction control instructions including adjusting the travel speed and digging depth of the excavator, adjusting the jacking force and action point position of the hydraulic support system, and delaying or advancing the installation time of the support member.

7. The quality and safety four-dimensional collaborative dynamic management and control system for large-scale infrastructure projects according to claim 6, characterized in that, The specific process of the construction strategy generator matching the control strategy library is: The regulation strategy library stores multiple regulation strategies according to construction types and geological conditions, each regulation strategy is associated with an effect evaluation function, the effect evaluation function calculates the expected stability gain and construction delay cost after the implementation of the strategy; The construction strategy generator retrieves the regulation strategy library according to the abnormal indicators in the current joint response state, the retrieval conditions include abnormal indicator type, construction stage and geological partition, sorts the retrieved regulation strategies according to the effect evaluation function, and selects the strategy with the highest evaluation score as the candidate strategy; The feasibility of the candidate strategy is checked, which includes checking whether the current state of the construction equipment supports the execution of the strategy and whether the field operation space meets the operation requirements; after the verification, the candidate strategy is converted into an executable instruction sequence for the equipment; if the verification fails, an artificial intervention process is started.

8. The quality and safety four-dimensional collaborative dynamic management and control system for large-scale infrastructure projects according to claim 1, characterized in that, In the instruction execution module, the specific process of the field execution equipment operating the hydraulic control system and the supporting device according to the instruction content is as follows: The field execution equipment receives the construction regulation instruction, analyzes the equipment operation parameters in the instruction, the equipment operation parameters include the target pressure value of the hydraulic cylinder, the installation position and timing plan of the supporting member, converts the equipment operation parameters into control signals, and transmits the control signals to the hydraulic controller and the supporting manipulator through the industrial bus; The hydraulic controller adjusts the output flow and pressure of the hydraulic pump station according to the control signal, drives the hydraulic cylinder to perform the jacking or retracting action, and the supporting manipulator positions the installation point according to the control signal, grabs the supporting member and completes the installation according to the specified timing; All operation processes record execution logs in real time, the execution logs include action completion time, actual pressure value and installation deviation data, the execution logs are fed back to the central control system, and are used to update the construction progress variables in the geological-structure collaborative response model.

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