Construction control method for pile foundation with slight disturbance close to structure

Abstract

The application relates to the technical field of pile foundation construction, in particular to a pile foundation micro-disturbance construction control method close to a structure, which comprises the following steps: S1, a digital twin model containing a pile foundation, a soil body and a structure is constructed, the anti-disturbance capability of the structure is evaluated, and a control threshold is set; S2, drilling in-situ data are collected, the mechanical parameters of the soil body around the pile are inverted, and the digital twin model is updated; S3, construction parameters, drilling in-situ data, external monitoring data and the updated digital twin model are preprocessed and time-space synchronized, and a multi-dimensional time sequence fusion data set is generated; S4, the multi-dimensional time sequence fusion data set is analyzed, and a structure disturbance prediction result is obtained; S5, based on the structure disturbance prediction result, in combination with the control threshold, a multi-objective optimization function is solved, and a construction control instruction is output; and S6, the construction control instruction is real-timely issued to a corresponding execution system, and a substantial change from passive remediation to active control is realized.

Description

Technical Field

[0001] This application relates to the field of pile foundation construction technology, and in particular to a method for controlling micro-disturbance during pile foundation construction adjacent to a structure. Background Technology

[0002] As urban underground space development moves towards high density and deep foundation pits, many new projects are located adjacent to extremely sensitive structures such as operating subways, old buildings, historical sites, and high-voltage pipelines. Traditional pile foundation construction adopts a passive control mode of "construction first, monitoring later," with construction parameters relying on manual experience for adjustment. This results in long response times and is prone to causing irreversible structural damage.

[0003] Therefore, there is a need to provide an improved technical solution that addresses the shortcomings of the existing technology. Summary of the Invention

[0004] The purpose of this application is to provide a method for controlling the micro-disturbance of pile foundations in close proximity to structures, so as to solve or alleviate the problems existing in the prior art.

[0005] To achieve the above objectives, this application provides the following technical solution: A method for controlling micro-disturbance during pile foundation construction adjacent to structures, wherein the micro-disturbance construction control method includes: Step S1: Construct a digital twin model including pile foundation, soil and structure, deploy external monitoring units, assess the structure's resistance to disturbance and set corresponding control thresholds; Step S2: Collect in-situ data while drilling, invert the mechanical parameters of the soil around the pile in real time, and dynamically update the digital twin model; Step S3: Preprocess and spatiotemporally synchronize the construction parameters, in-situ drilling data, external monitoring data, and the updated digital twin model to generate a multi-dimensional time-series fusion dataset; Step S4: Analyze the multidimensional time-series fusion dataset using a preset coupling analysis model to obtain the structure disturbance prediction results; Step S5: Based on the predicted disturbance results of the structure, and combined with the control threshold, solve the multi-objective optimization function and output the construction control command; Step S6: Send the construction control command to the corresponding execution system in real time to drive each execution system to adjust the construction parameters synchronously.

[0006] Preferably, in step S1, the disturbance resistance capability of the structure is assessed based on the structure type, structural form and service life, and corresponding control thresholds are set.

[0007] Preferably, step S2 specifically involves: collecting in-situ data while drilling, inverting the mechanical parameters of the soil around the pile in real time, and using the drilling rig vibration as an active source, in conjunction with an external monitoring unit, identifying geological anomalies, and dynamically updating the digital twin model.

[0008] Preferably, in step S3, the preprocessing specifically involves: using an adaptive filtering algorithm to filter out noise and outliers in the in-situ data and external monitoring data while drilling, and interpolating the missing data.

[0009] Preferably, step S4 includes: Step S41: Based on the multi-dimensional time series fusion dataset, initialize the coupled analysis model and load boundary conditions; Step S42: Interactively couple and solve for the stress field, seepage field, vibration field, and damage field; Step S43: Output the predicted results of structure disturbance.

[0010] Preferably, step S5 includes: Step S51: Based on the predicted disturbance results of the structure, compare them with the control thresholds to determine the risk level; Step S52: Adjust the weight coefficients of the multi-objective optimization function according to the risk level, and solve the multi-objective optimization function; Step S53: Output construction control instructions.

[0011] Preferably, in step S1, the control thresholds are divided into emergency control thresholds, alarm control thresholds, and early warning control thresholds in a proportionally decreasing manner.

[0012] Preferably, in step S51, the multi-objective optimization function is: , in, For structure risk, it is defined as the ratio of the predicted disturbance result of the structure to the control threshold. This refers to the current construction period for the pile foundation. For construction costs; , , These are the weighting coefficients. .

[0013] Preferably, in step S51, the risk level includes green risk, yellow risk, orange risk, and red risk; When the predicted disturbance results of the structure are all below the early warning control threshold, it is judged as a green risk; When any disturbance prediction result of a structure exceeds its early warning control threshold but falls below its alarm control threshold, it is judged as a yellow risk. When any disturbance prediction result of a structure exceeds its alarm control threshold but falls below its emergency control threshold, it is judged as an orange risk. When any disturbance prediction result of a structure exceeds its emergency control threshold, it is judged as a red risk.

[0014] Preferably, in step S52, The risk levels increase progressively in the order of green, yellow, orange, and red. , The risk levels are reduced progressively in the order of green, yellow, orange, and red.

[0015] Compared with the closest prior art, the technical solution of this application has the following beneficial effects: This application aims to achieve dynamic model correction by constructing a digital twin model of pile foundation-soil-structure and combining it with in-situ drilling data. It integrates multi-source data to generate a standardized multi-dimensional time-series fusion dataset, relies on a multi-physics coupling analysis model to predict the disturbance effect of the structure in advance, and then outputs precise construction control commands through multi-objective optimization and drives multiple execution systems to adjust synchronously. This realizes the essential transformation of pile foundation construction adjacent to the structure from passive remediation to proactive forward control. Attached Figure Description

[0016] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. Wherein: Figure 1 This is a schematic diagram of a construction control method provided according to some embodiments of this application. Detailed Implementation

[0017] The present application will now be described in detail with reference to the accompanying drawings and embodiments. Various examples are provided by way of explanation and not by way of limitation. In fact, those skilled in the art will recognize that modifications and variations can be made to the present application without departing from the scope or spirit thereof. For example, a feature shown or described as part of one embodiment may be used in another embodiment to produce yet another embodiment. Therefore, it is desirable that the present application encompass such modifications and variations that fall within the scope of the appended claims and their equivalents.

[0018] In the following description, the terms "first / second / third" are used merely to distinguish similar objects and do not represent a specific order of objects. It is understood that "first / second / third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used herein is for the purpose of describing embodiments of this disclosure only and is not intended to limit this disclosure.

[0020] In the description of this application, the terms "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," and "bottom," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this application and do not require that this application be constructed and operated in a specific orientation, and therefore should not be construed as limiting this application. The terms "connected," "linked," and "set up" used in this application should be interpreted broadly. For example, they can refer to fixed connections or detachable connections; direct connections or indirect connections through intermediate components; wired connections, radio connections, or wireless communication signal connections. Those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances.

[0021] The following will be combined with the appendix Figure 1 The method for controlling the micro-disturbance of pile foundations adjacent to structures in this application is further described in detail.

[0022] Methods for controlling micro-disturbance during pile foundation construction adjacent to structures, including: Step S1: Construct a digital twin model including pile foundation, soil and structure, deploy external monitoring units, assess the structure's resistance to disturbance and set corresponding control thresholds; Step S2: Collect in-situ data while drilling, invert the mechanical parameters of the soil around the pile in real time, and dynamically update the digital twin model; Step S3: Preprocess and spatiotemporally synchronize the construction parameters, in-situ drilling data, external monitoring data, and the updated digital twin model to generate a multi-dimensional time-series fusion dataset; Step S4: Analyze the multidimensional time-series fusion dataset using a pre-defined coupling analysis model to obtain the structure disturbance prediction results; Step S5: Based on the predicted disturbance results of the structure, combined with the control threshold, solve the multi-objective optimization function and output the construction control command; Step S6: Send the construction control instructions to the corresponding execution systems in real time to drive each execution system to adjust the construction parameters synchronously.

[0023] In a specific embodiment of this application, In step S1, refined geological survey data (static cone penetration test, vane shear test, core drilling), pile foundation engineering design drawings, as-built drawings of sensitive structures, and current status inspection reports are integrated. A 1:1 scale three-dimensional digital twin model of the pile foundation, soil, and structure is constructed using BIM modeling software. Initial physical and mechanical parameters (soil elastic modulus, Poisson's ratio, cohesion, pile foundation concrete strength, structure stiffness, etc.) are assigned to each component in the model. External monitoring units are deployed along the axis of the sensitive structure to monitor the structure's response, and soil condition monitoring points are deployed within a range of three times the pile diameter around the pile to monitor the soil condition. The finite element numerical simulation method is used to calculate the structural response of the structure under different disturbance intensities. The disturbance resistance capability is assessed in conjunction with design specifications to determine the control threshold. This achieves a precise digital mapping of the physical world, providing a unified geometric base and parameter benchmark for subsequent full-process simulation and control. The safety boundaries of the structure are clearly defined in advance to avoid blind construction.

[0024] In step S2, a miniature drilling sensor array is integrated at the drill pipe end to collect real-time in-situ data such as drilling pressure, torque, rotational speed, triaxial vibration acceleration, soil resistivity, and drill bit temperature during drilling. The in-situ data is transmitted to the edge computing unit, and a random forest machine learning algorithm is used to invert key soil mechanical parameters such as elastic modulus, cohesion, and internal friction angle of the soil within a range of 0-1 times the pile diameter around the pile in real time, based on the mapping relationship between the in-situ data and soil mechanical parameters. The inverted soil mechanical parameters are then synchronized to the three-dimensional digital twin model in real time to replace the initial exploration parameters and update the soil property distribution of the model.

[0025] In step S3, drilling rig construction parameters (drilling speed, mud pressure / flow rate), in-situ data while drilling, data from external monitoring units, and update data from the digital twin model are collected. All data are preprocessed to eliminate noise, outliers, and missing values. All data are aligned to the same time base (synchronization accuracy better than 1ms) using the PTP precise time synchronization protocol and uniformly converted into structured JSON format. Data from different dimensions are correlated according to timestamps to generate a multi-dimensional time-series fusion dataset containing construction parameters, drilling parameters, soil conditions, and structure responses.

[0026] In step S4, the multidimensional time-series fusion dataset is used as input and loaded into the preset "stress-seepage-vibration-damage" four-field coupled analysis model; the four-field coupled control equations are solved simultaneously to simulate the soil stress redistribution, excess pore water pressure dissipation, vibration propagation and soil structural damage evolution process during pile foundation construction; and the cumulative deformation and deformation rate of sensitive structures are predicted forward in the next 24 hours.

[0027] In step S5, the predicted disturbance results of the structure are compared with the preset control threshold to assess the current construction risk; a multi-objective optimization function containing three objectives: safety, efficiency, and cost is constructed; the optimization function is solved using the non-dominated sorting genetic algorithm (NSGA-III) to generate a Pareto optimal solution set; the optimal solution is selected according to the actual needs of the project and converted into executable construction control instructions.

[0028] In step S6, construction control commands are sent in real time to the drilling rig, mud circulation system, dual-liquid grouting system and other execution systems via industrial Ethernet; after receiving the commands, each execution system automatically adjusts the corresponding construction parameters (drilling speed, mud specific gravity, grouting pressure, etc.).

[0029] To achieve precise and differentiated control, ensuring the absolute safety of extremely sensitive structures while avoiding delays and increased costs caused by excessive control over general sensitive structures, in step S1, the disturbance resistance capability of the structures is assessed based on the structure type, structural form, and service life, and corresponding control thresholds are set.

[0030] In a specific embodiment of this application, an evaluation index system for the disturbance resistance capacity of sensitive structures is established. The indexes include structure type (operating subway, historical building, high-voltage pipeline, old residential building), structural form (shield tunnel, frame structure, brick-concrete structure), and service life (≤10 years, 10-30 years, ≥30 years). The Analytic Hierarchy Process (AHP) is used to determine the weight of each index, and the structures are quantitatively scored, classifying the disturbance resistance capacity into three levels: Level I (extremely sensitive), Level II (sensitive), and Level III (generally sensitive). Differentiated control thresholds are set for different disturbance resistance levels, such as: Level I structures: cumulative settlement ≤1mm, settlement rate ≤0.1mm / 24h; Level II structures: cumulative settlement ≤2mm, settlement rate ≤0.2mm / 24h; Level III structures: cumulative settlement ≤3mm, settlement rate ≤0.3mm / 24h.

[0031] Step S2 specifically involves: collecting in-situ data while drilling, inverting the mechanical parameters of the soil around the pile in real time, using the drilling rig vibration as an active source, cooperating with external monitoring units to identify geological anomalies, and dynamically updating the digital twin model.

[0032] In a specific embodiment of this application, the vibration generated by the drill bit cutting the soil during drilling is used as an active vibration source. The reflected wave signal from the geological body in front is received by distributed optical fiber vibration sensors deployed around the pile. The reflected wave signal is processed by an offset imaging algorithm to generate a three-dimensional imaging result of the geological body within a 5m range around the pile. The location, size and shape of geological anomalies such as boulders, weak interlayers, and cavities are identified. The geological anomaly information is updated to the three-dimensional digital twin model in real time to correct the geological boundary conditions of the model.

[0033] In step S3, the preprocessing specifically involves: using an adaptive filtering algorithm to filter out noise and outliers in the in-situ data and external monitoring data while drilling, and interpolating the missing data.

[0034] In a specific embodiment of this application, an adaptive median filtering algorithm is used to filter out impact noise and electromagnetic interference noise in the drilling vibration data, and the size of the filtering window is adaptively adjusted according to the noise intensity; the 3σ criterion is used to identify outliers in the data and remove the identified outliers; linear interpolation is used to complete short-term missing data (≤10s), and LSTM neural network prediction based on historical data is used to complete long-term missing data (>10s).

[0035] Step S4 includes: Step S41: Based on the multi-dimensional time series fusion dataset, initialize the coupled analysis model and load boundary conditions; Step S42: Interactively couple and solve for the stress field, seepage field, vibration field, and damage field; Step S43: Output the predicted results of structure disturbance.

[0036] In a specific embodiment of this application, Step S41 specifically involves: reading the multidimensional time-series fusion dataset, using construction parameters as dynamic load boundaries, soil state parameters as initial stress and seepage boundaries, and structure response parameters as displacement constraint boundaries, and loading them into the coupled analysis model; Step S42 specifically involves: using a partitioned iterative solution method to alternately solve the stress field, seepage field, vibration field, and damage field, taking into account the nonlinear interactions between the fields (such as damage leading to increased permeability and vibration leading to soil liquefaction). Step S43 specifically involves outputting the cumulative deformation and deformation rate of the structure over the next 24 hours.

[0037] Step S5 includes: Step S51: Based on the predicted disturbance results of the structure, compare them with the control thresholds to determine the risk level; Step S52: Adjust the weight coefficients of the multi-objective optimization function according to the risk level, and solve the multi-objective optimization function; Step S53: Output construction control instructions.

[0038] In a specific embodiment of this application, the cumulative deformation and deformation rate of the structure within the next 24 hours are compared with a control threshold to determine the current construction risk level; the weight coefficients of the multi-objective optimization function are adjusted according to the risk level, the NSGA-III algorithm is called to solve the optimization problem, and a Pareto optimal solution set is generated; the optimal solution is converted into specific construction parameter adjustment instructions, including drilling rig parameters (drilling speed, drilling pressure, rotation speed), mud parameters (specific gravity, viscosity, pressure), and grouting parameters (pressure, flow rate, initial setting time). In step S1, the control thresholds are divided into emergency control threshold, alarm control threshold, and early warning control threshold in a proportionally decreasing manner.

[0039] In a specific embodiment of this application, the maximum allowable deformation value required by the design is used as the emergency control threshold; the alarm control threshold is set to 90% of the emergency control threshold; the early warning control threshold is set to 70% of the emergency control threshold; for example, if the emergency control threshold is a cumulative settlement of 1 mm and a settlement rate ≤ 0.1 mm / 24 h, then the alarm control threshold is 0.9 mm and 0.09 mm / 24 h, and the early warning control threshold is 0.7 mm and 0.07 mm / 24 h.

[0040] In step S51, the multi-objective optimization function is: , in, For structure risk, it is defined as the ratio of the predicted disturbance result of the structure to the control threshold. This refers to the current construction period for the pile foundation. For construction costs; , , These are the weighting coefficients. .

[0041] In step S51, the risk levels include green risk, yellow risk, orange risk, and red risk; When the predicted disturbance results of the structure are all below the early warning control threshold, it is judged as a green risk; When any disturbance prediction result of a structure exceeds its early warning control threshold but falls below its alarm control threshold, it is judged as a yellow risk. When any disturbance prediction result of a structure exceeds its alarm control threshold but falls below its emergency control threshold, it is judged as an orange risk. When any disturbance prediction result of a structure exceeds its emergency control threshold, it is judged as a red risk.

[0042] In step S52, The risk levels increase progressively in the order of green, yellow, orange, and red. , The risk levels are reduced progressively in the order of green, yellow, orange, and red.

[0043] In a specific embodiment of this application, when a structure is determined to be a green risk, the weight settings of the multi-objective optimization function can be as follows: Balancing safety, efficiency, and cost; when a structure is assessed as having a yellow risk level, the weights of the multi-objective optimization function can be set as follows: Prioritizing safety while appropriately reducing efficiency and cost requirements; when a structure is assessed as having orange risk, the weights of the multi-objective optimization function can be set as follows: Prioritizing safety, efficiency and cost requirements are significantly reduced; when a structure is classified as a red-risk structure, the weights of the multi-objective optimization function can be set as follows: Construction must be stopped immediately and emergency measures must be activated.

[0044] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for controlling micro-disturbance during pile foundation construction adjacent to structures, characterized in that, The micro-disturbance construction control method includes: Step S1: Construct a digital twin model including pile foundation, soil and structure, deploy external monitoring units, assess the structure's resistance to disturbance and set corresponding control thresholds; Step S2: Collect in-situ data while drilling, invert the mechanical parameters of the soil around the pile in real time, and dynamically update the digital twin model; Step S3: Preprocess and spatiotemporally synchronize the construction parameters, in-situ drilling data, external monitoring data, and the updated digital twin model to generate a multi-dimensional time-series fusion dataset; Step S4: Analyze the multidimensional time-series fusion dataset using a preset coupling analysis model to obtain the structure disturbance prediction results; Step S5: Based on the predicted disturbance results of the structure, and combined with the control threshold, solve the multi-objective optimization function and output the construction control command; Step S6: Send the construction control command to the corresponding execution system in real time to drive each execution system to adjust the construction parameters synchronously.

2. The method for controlling micro-disturbance construction of pile foundations adjacent to structures as described in claim 1, characterized in that, In step S1, the disturbance resistance capability of the structure is assessed based on the structure type, structural form and service life, and corresponding control thresholds are set.

3. The method for controlling micro-disturbance construction of pile foundations adjacent to structures as described in claim 1, characterized in that, Step S2 specifically involves: collecting in-situ data while drilling, inverting the mechanical parameters of the soil around the pile in real time, using the drilling rig vibration as an active source, cooperating with an external monitoring unit to identify geological anomalies, and dynamically updating the digital twin model.

4. The method for controlling micro-disturbance construction of pile foundations adjacent to structures as described in claim 1, characterized in that, In step S3, the preprocessing specifically involves: using an adaptive filtering algorithm to filter out noise and outliers in the in-situ data and external monitoring data while drilling, and interpolating the missing data.

5. The method for controlling micro-disturbance construction of pile foundations adjacent to structures as described in claim 1, characterized in that, Step S4 includes: Step S41: Based on the multi-dimensional time series fusion dataset, initialize the coupled analysis model and load boundary conditions; Step S42: Interactively couple and solve for the stress field, seepage field, vibration field, and damage field; Step S43: Output the predicted results of structure disturbance.

6. The method for controlling micro-disturbance construction of pile foundations adjacent to structures as described in claim 1, characterized in that, Step S5 includes: Step S51: Based on the predicted disturbance results of the structure, compare them with the control thresholds to determine the risk level; Step S52: Adjust the weight coefficients of the multi-objective optimization function according to the risk level, and solve the multi-objective optimization function; Step S53: Output construction control instructions.

7. The method for controlling micro-disturbance construction of pile foundations adjacent to structures as described in claim 6, characterized in that, In step S1, the control thresholds are divided into emergency control threshold, alarm control threshold, and early warning control threshold in a proportionally decreasing manner.

8. The method for controlling micro-disturbance construction of pile foundations adjacent to structures as described in claim 7, characterized in that, In step S51, the multi-objective optimization function is: ， in, For structure risk, it is defined as the ratio of the predicted disturbance result of the structure to the control threshold. This refers to the current construction period for the pile foundation. For construction costs; , , These are the weighting coefficients. .

9. The method for controlling micro-disturbance construction of pile foundations adjacent to structures as described in claim 8, characterized in that, In step S51, the risk levels include green risk, yellow risk, orange risk, and red risk; When the predicted disturbance results of the structure are all below the early warning control threshold, it is judged as a green risk; When any disturbance prediction result of a structure exceeds its early warning control threshold but falls below its alarm control threshold, it is judged as a yellow risk. When any disturbance prediction result of a structure exceeds its alarm control threshold but falls below its emergency control threshold, it is judged as an orange risk. When any disturbance prediction result of a structure exceeds its emergency control threshold, it is judged as a red risk.

10. The method for controlling micro-disturbance construction of pile foundations adjacent to structures as described in claim 9, characterized in that, In step S52, The risk levels increase progressively in the order of green, yellow, orange, and red. , The risk levels are reduced progressively in the order of green, yellow, orange, and red.

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