Digital construction control system and method for cast-in-situ bored pile

Abstract

The invention discloses a cast-in-situ bored pile digital construction control method which comprises the following steps: S1, collecting historical data, and establishing a cast-in-situ bored pile construction information database; s2, geological modeling is established, and a pile hole area three-dimensional stratum and soil layer distribution corresponding to all pile holes are generated in a fitting mode; s3, according to the cast-in-situ bored pile construction information database, finding out average construction efficiency and cost data under various hole forming processes of similar stratums in various stratums of a pile hole area, and calculating the construction period and cost of different hole forming processes of a single pile for construction management personnel to select the hole forming processes and equipment specifications; s4, monitoring early warning and auxiliary decision making in construction; and S5, post evaluation analysis. According to the system and the method, key construction parameters of the bored pile are automatically monitored by relying on core construction equipment and devices, the production dynamic state of the bored pile is visually displayed through online monitoring and early warning of the key parameters by the system and the platform, a friendly interactive interface is provided for operators, and construction parameter selection is assisted.

Description

Technical Field

[0001] The present invention relates to the field of digital construction control of bored cast-in-place piles. More specifically, the present invention relates to a digital construction control system and method for bored cast-in-place piles. Background Art

[0002] In recent years, with the acceleration of China's urbanization process, hundreds of millions of bored cast-in-place piles need to be completed every year. The construction technology of bored cast-in-place piles is on-site hole formation and pouring, which belongs to underground concealed works. Therefore, its construction efficiency, cost, and quality are closely related to the geological conditions of the project area. If the construction parameters do not match the geological conditions, problems such as low hole formation efficiency, poor verticality, and poor pile body integrity will occur, seriously affecting the safety of the superstructure, and the treatment of pile foundation defects is difficult and costly.

[0003] At present, the control of the efficiency, cost, and quality during the construction process of bored cast-in-place piles highly depends on the construction team's selection of matching hole formation processes, construction machinery, drilling parameters, and mud ratios based on the construction experience of bored cast-in-place pile projects in similar strata. However, such construction experience and summaries cannot be accumulated and iterated in the form of data, and there are many types of regions and strata involved in bored piles, making it difficult to establish systematic and highly generalized experience through the summary of a small number of project construction experiences.

[0004] Facing the current trend of digital transformation, adjacent industries such as petroleum, coal, and mines have begun to conduct research and application of digital and intelligent technologies. Therefore, it is also imperative to combine digital technology with the construction technology of bored cast-in-place piles. It is urgent to establish a closed management system from "pre-event prediction - in-event control - post-event evaluation" with the control of key parameters of process efficiency, cost, and quality as the main line to improve the intelligent construction and refined management level of bridge bored cast-in-place pile projects and ensure the quality of bored cast-in-place piles. Summary of the Invention

[0005] To achieve these and other advantages according to the present invention, a preferred embodiment of the present invention provides a digital construction control method for bored cast-in-place piles, including the following steps:

[0006] S1. Historical data collection

[0007] Statistical data of the strata, hole formation processes, equipment specifications, drilling efficiency, drilling costs, and corresponding drilling pressure, torque, and rotational speed of historical engineering projects are collected to establish a construction information database for bored cast-in-place piles;

[0008] S2. Geological modeling

[0009] Based on the geological exploration borehole data and soil physical and mechanical parameters of the new construction project, a three-dimensional formation of the pile hole area and the soil layer distribution corresponding to each pile hole are fitted and generated;

[0010] S3. Pre-construction Plan Recommendation

[0011] Based on the three-dimensional strata in the pile hole area and the soil layer distribution corresponding to each pile hole, according to the construction information database of bored cast-in-place piles, find the average construction efficiency and cost data of each hole-forming process in the similar strata in each stratum of the pile hole area, and calculate the construction duration and cost of different hole-forming processes for a single pile, so as to provide construction management personnel with the selection of hole-forming processes and equipment specifications;

[0012] S4. Monitoring, Early Warning and Auxiliary Decision-making during Construction

[0013] Automatically identify the process status of each pile hole of each pile, monitor construction parameters and give early warnings, and conduct visual display; according to the drilling parameters of the constructed pile holes, establish calculation models for drilling rate, hole-forming verticality, and hole-forming cost, and according to the improved NSGA-III multi-objective optimization algorithm, obtain the control range of the drilling rig construction parameters that meet the construction requirements;

[0014] S5. Post-event Evaluation and Analysis

[0015] Collect the construction progress, quality, and cost parameters of bored piles from different project departments for comprehensive assessment and evaluation, and establish a construction parameter database for bored piles of the enterprise and a quota database for bored cast-in-place piles of the enterprise to provide data support for the subsequent project duration and cost calculation work.

[0016] According to a preferred implementation of the present invention, in S4, according to the improved NSGA-III multi-objective optimization algorithm, it includes the following steps;

[0017] A41. Drilling Data Collection

[0018] Obtain the rotary pressure, rotational speed, torque, bit diameter, mud displacement, formation drillability index, and drilling cost during the construction of the bored piles in the project;

[0019] A42. Data Segmentation

[0020] Segment the drilling rig shutdown data, fault repair data, and drill pipe installation and removal data according to data characteristics to obtain the pure drilling data of the drilling rig;

[0021] A43. Abnormal Data Elimination

[0022] Use the 3σ rule to identify the outliers in the pure drilling data of the drilling rig and replace the mean value;

[0023] A44. Parameter Normalization

[0024] Use the normalization method to normalize various types of original data so that the output range of various types of data is between [0,1];

[0025] A45. Model Establishment

[0026] Use the SVM algorithm to establish regression prediction functions for the weight on bit, rotational speed, torque, mud displacement, formation drillability index and hole forming efficiency, hole forming verticality, and construct a drilling cost calculation model;

[0027] A46. Parameter optimization

[0028] Take the drilling speed, drilling cost, and hole forming verticality as the fitness functions of the improved NSGA-Ⅲ algorithm, and construct an SVM-NSGA-Ⅲ multi-objective optimization model; determine the control range of the drilling construction parameters that meet the drilling rate, hole forming verticality, and hole forming cost according to the Pareto optimal solution set obtained by the improved NSGA-Ⅲ algorithm.

[0029] According to a preferred implementation of the present invention, in A45, the regression prediction function is f1 =

[0030] -[SVM-regression(Xi)], i = 1, 2, …, 6;

[0031] f2 = [SVM-regression(Xi)], i = 1, 2, …, 6

[0032] wherein, f1 represents the drilling efficiency; f2 represents the hole forming verticality; X1, X2, X3, X4, X5, X6 respectively represent the weight on bit, rotational speed, torque, bit diameter, mud displacement, formation drillability index, and SVM-regression(Xi) is the SVM regression function.

[0033] According to a preferred implementation of the present invention, in A45, the drilling cost calculation model is:

[0034]

[0035] wherein, Cb represents the bit cost, C R represents the rig cost, t T represents the tripping time, t represents the pure drilling time of the bit, and Ht represents the bit footage.

[0036] According to a preferred implementation of the present invention, in S4, automatically identifying the operation status of the pile hole process includes the following operations:

[0037] B41. Identification of the process in the hole forming stage: Obtain the center coordinates of the rig through the Beidou positioning system of the rig, and then calculate the distance from the center coordinates of the pile hole. The pile hole with the closest distance is the pile hole being drilled, and the pile number is associated with the rig; automatically unbind the rig from the pile number after confirming the end of the hole;

[0038] B42. Identification of construction processes in the steel cage installation stage: After the automatic confirmation of the end of drilling in the pile hole by the drilling rig, the steel cage lowering stage begins. The Beidou positioning system of the crawler crane calculates the distance between the coordinates of the crawler crane for lowering the steel cage and the coordinates of the pile hole where the steel cage is to be lowered. The pile hole with the closest distance is the pile hole where the steel cage is being lowered, and the pile number is associated with the crawler crane. During the process of lowering the steel cage, the on-vehicle RFID reader automatically reads the RFID tags on the steel cage, records the time and number of sections of the steel cage being lowered, and automatically unbinds the crawler crane from the pile number after confirming the completion of the steel cage lowering.

[0039] Among them, the start time of the steel cage lowering is: the time when the RFID reader reads the tag of the first steel cage after the crawler crane is associated with the pile number.

[0040] The completion time of the steel cage lowering is: the time when the RFID reader reads the tag of the last steel cage after the crawler crane is associated with the pile number.

[0041] B43. Identification of construction processes in the concrete pouring stage: After automatically confirming the completion of the steel cage lowering, the concrete pouring stage begins. The Beidou positioning system of the concrete mixer truck calculates the distance between the coordinates of the concrete mixer truck for concrete pouring and the coordinates of the pile hole where the steel cage is to be poured. The pile hole with the closest distance is the pile hole where the concrete is being poured, and the pile number is associated with the concrete mixer truck. After confirming the completion of the concrete pouring, the concrete mixer truck is automatically unbounded from the pile number.

[0042] Among them, the start time of the concrete pouring: the moment when the first concrete mixer truck is associated with the pile number.

[0043] The completion time of the concrete pouring: the latest moment among the moments when all concrete mixer trucks are associated with the pile number.

[0044] On the other hand, the present invention also provides a digital construction control system for bored cast-in-place piles, including:

[0045] Information entry module: used to enter the formation, hole-forming process, equipment specifications, drilling efficiency, drilling cost, and corresponding bit pressure, torque, and rotation speed of historical engineering projects, and establish a construction information database for bored cast-in-place piles.

[0046] Geological model establishment module: According to the geological exploration borehole data and soil physical and mechanical parameters of historical engineering projects, a three-dimensional formation of the pile hole area and the soil layer distribution corresponding to each pile hole are fitted and generated.

[0047] Process identification module: automatically identify the process status of the pile hole of each pile.

[0048] Parameter warning module: real-time monitor the collected construction parameters and compare them with the threshold values. If the collected construction parameters are not within the threshold values, the parameter warning module issues an alarm to remind relevant technical personnel, and displays the specific pile position number, warning reason, and specific construction time where the abnormality occurs.

[0049] According to a preferred embodiment of the present invention, it further includes

[0050] Visualization module: Visualize and display the overall situation and completion status of the project and the construction progress of the current construction pile positions, and respectively display the corresponding three-dimensional digital twin models for the working conditions of hole formation, reinforcement cage lowering, and concrete pouring, making the concealed works visible;

[0051] Log push module: After the completion of each pile process, automatically push information such as the construction duration and energy consumption of the process to the construction management personnel; automatically push the construction log to the construction management personnel every day, showing the quantities of hole formation, reinforcement cage lowering, and concrete pouring completed at the construction pile positions on the current day.

[0052] According to a preferred embodiment of the present invention, it further includes

[0053] Auxiliary decision-making module: Based on the actual drilling parameters collected for the project and the NSGA-III multi-objective optimization algorithm, and based on the constraint conditions of hole formation efficiency, hole formation perpendicularity, and hole formation energy consumption, give an optimized decision on dynamic drilling parameters;

[0054] Enterprise management module: Used for the enterprise to collect data on project work efficiency, cost, and quality, comprehensively evaluate the bored pile construction of different project departments, and establish a database of bored pile construction parameters and a quota library of bored cast-in-place piles for enterprises, providing data support for subsequent project duration and cost calculation work.

[0055] The present invention has at least the following beneficial effects:

[0056] (1) This application proposes a digital construction control method for bored cast-in-place piles. At the project decision-making stage, relying on enterprise-level big data, it guides the project to select matching construction techniques, hole formation equipment, and construction parameters according to the geological conditions of the area where the project is located.

[0057] (2) This application proposes a digital construction control device for bored cast-in-place piles. During the construction process, various construction data are collected to establish a comprehensive and thorough perception system, realizing online monitoring and timely warning of key parameters of key processes, saving the workload of manual measurement and statistics.

[0058] (3) This application proposes a digital construction control system for bored cast-in-place piles. Through the function of quickly importing basic project information based on OCR and intelligent collection devices, it realizes automatic filling and collection of system parameters, greatly reducing the workload of manual statistics and input, with simple operation and strong project promotion.

[0059] (4) This application proposes a digital construction control system for bored cast-in-place piles, which realizes the automatic recognition of construction processes and states, automatically generates various construction reports, and at the same time, through a visual data dashboard, assists project managers to timely, accurately, and comprehensively understand the production dynamics of bored cast-in-place piles and make timely construction management decision-making actions.

[0060] (5) This application proposes a digital construction control system for bored cast-in-place piles, which establishes an enterprise-level production and cost database for bored cast-in-place piles. Through multi-dimensional data statistics and analysis, it reflects the management level of the project for bored piles, and realizes the precipitation and knowledge reuse of project work efficiency, cost, and quality data.

[0061] Other advantages, objectives, and features of the present invention will be partially reflected by the following description and partially understood by those skilled in the art through the research and practice of the present invention. Detailed Description of the Invention

[0062] The following further elaborates on the present invention in conjunction with embodiments, enabling those skilled in the art to implement it with reference to the text of the specification.

[0063] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art can think of other obvious variations. The basic principles defined in the following description can be applied to other implementation schemes, variation schemes, improvement schemes, equivalent schemes, and other technical schemes that do not deviate from the spirit and scope of the present invention.

[0064] It can be understood that the term "one" should be understood as "at least one" or "one or more". That is, in one embodiment, the number of an element can be one, while in other embodiments, the number of the element can be multiple. The term "one" cannot be understood as a limitation on the number.

[0065] A preferred embodiment of the present invention provides a digital construction control method for bored cast-in-place piles, including the following steps:

[0066] S1. Historical data collection

[0067] Statistical data of the formation, hole-forming process, equipment specifications, drilling efficiency, drilling cost, and corresponding drill pressure, torque, and rotational speed of historical engineering projects are collected to establish a construction information database for bored cast-in-place piles.

[0068] The construction information database for bored cast-in-place piles is exemplified as follows:

[0069] Table 1 Construction Information Database for Bored Cast-in-Place Piles

[0070]

[0071] S2. Establish geological modeling

[0072] According to the geological exploration borehole data and soil physical and mechanical parameters of the new construction project, a three-dimensional stratum in the pile hole area and the soil layer distribution corresponding to each pile hole are fitted and generated;

[0073] S3. Recommend pre-construction plan

[0074] Based on the three-dimensional stratum in the pile hole area and the soil layer distribution corresponding to each pile hole, according to the construction information database of bored cast-in-place piles, find out the average construction efficiency and cost data of each hole-forming process in the similar strata in each stratum of the pile hole area, and calculate the construction period and cost of different hole-forming processes for a single pile, so as to provide construction management personnel with the selection of hole-forming processes and equipment specifications;

[0075] Table 2 Construction period and cost of different hole-forming processes for a single pile

[0076]

[0077] S4. Monitoring, early warning and auxiliary decision-making during construction

[0078] Automatically identify the pile hole process status of each pile, monitor construction parameters and give early warnings, and conduct visual display; according to the drilling parameters of the constructed pile holes, establish calculation models for drilling rate, hole-forming verticality and hole-forming cost, and obtain the control range of the drilling rig construction parameters that meet the construction requirements according to the improved NSGA-III multi-objective optimization algorithm;

[0079] Among them, according to the improved NSGA-III multi-objective optimization algorithm, it includes the following steps;

[0080] A41. Drilling data collection

[0081] Obtain the drilling pressure, rotation speed, torque, bit diameter, mud displacement, formation drillability index and drilling cost during the construction of the bored piles in the project;

[0082] A42. Data segmentation

[0083] According to the data characteristics, segment the drilling rig shutdown data, fault repair data and drill pipe installation and removal data to obtain the pure drilling data of the drilling rig;

[0084] A43. Abnormal data elimination

[0085] Adopt the 3σ rule to identify the abnormal values in the pure drilling data of the drilling rig and replace the mean value;

[0086] A44. Parameter normalization

[0087] Adopt the normalization method to normalize various types of original data so that the output range of various types of data is between [0,1];

[0088] A45. Model establishment

[0089] Use the SVM algorithm to establish regression prediction functions for the weight on bit, rotational speed, torque, mud displacement, formation drillability index and hole forming efficiency, hole forming verticality, and construct a drilling cost calculation model;

[0090] In the above A45, the drilling cost calculation model is:

[0091] f3 = C b +C R (t T +t)

[0092] H t

[0093] where C b represents the bit cost, C R represents the rig cost, t T represents the tripping time, t represents the pure drilling time of the bit, and H t represents the bit footage.

[0094] A46. Parameter optimization

[0095] Take the drilling speed, drilling cost, and hole forming verticality as the fitness functions of the improved NSGA-Ⅲ algorithm, and construct an SVM-NSGA-Ⅲ multi-objective optimization model; determine the control range of the drilling construction parameters that meet the drilling rate, hole forming verticality, and hole forming cost according to the Pareto optimal solution set obtained by the improved NSGA-Ⅲ algorithm.[[ID=#]]

[0096] According to a preferred implementation of the present invention, in the above A45, the regression prediction function is f1 =

[0097] -[SVM-regression(Xi)], i = 1, 2,..., 6;

[0098] f2 = [SVM-regression(Xi)], i = 1, 2,...,

[0099] where f1 represents the drilling efficiency; f2 represents the hole forming verticality; X1, X2, X3, X4, X5, X6 respectively represent the weight on bit, rotational speed, torque, bit diameter, mud displacement, and formation drillability index, and SVM-regression(Xi) is the SVM regression function.

[0100] Among them, in the above S4, automatically identifying the operation state of the pile hole process includes the following operations:

[0101] B41. Identification of the hole forming stage process: Obtain the center coordinates of the rig through the Beidou positioning system of the rig, and then calculate the distance from the center coordinates of the pile hole. The pile hole with the closest distance is the pile hole being drilled, and the pile number is associated with the rig; after confirming the end of the hole, the rig is automatically unbound from the pile number;

[0102] B42. Identification of construction processes in the stage of steel cage installation: After the automatic confirmation of the end of drilling in the pile hole, the stage of lowering the steel cage begins. The Beidou positioning system of the crawler crane calculates the distance between the coordinates of the crawler crane lowering the steel cage and the coordinates of the pile hole where the steel cage is to be lowered. The pile hole with the shortest distance is the pile hole where the steel cage is being lowered, and the pile number is associated with the crawler crane. During the process of lowering the steel cage, the on-vehicle RFID reader automatically reads the RFID tags on the steel cage, records the time and number of sections of the steel cage being lowered, and automatically unbinds the crawler crane from the pile number after confirming the completion of the steel cage lowering.

[0103] Among them, the start time of steel cage lowering is: the time when the RFID reader reads the tag of the first steel cage after the crawler crane is associated with the pile number.

[0104] The completion time of steel cage lowering is: the time when the RFID reader reads the tag of the last steel cage after the crawler crane is associated with the pile number.

[0105] B43. Identification of construction processes in the stage of concrete pouring: After automatically confirming the completion of the steel cage lowering, the stage of concrete pouring begins. The Beidou positioning system of the concrete mixer truck calculates the distance between the coordinates of the concrete mixer truck for pouring and the coordinates of the pile hole where the steel cage is to be poured. The pile hole with the shortest distance is the pile hole where the concrete is being poured, and the pile number is associated with the concrete mixer truck. After confirming the completion of the concrete pouring, the truck is automatically unbounded from the pile number.

[0106] Among them, the start time of concrete pouring: the moment when the first truck is associated with the pile number.

[0107] The completion time of concrete pouring: the latest moment among the moments when all trucks are associated with the pile number.

[0108] S5. Post-event evaluation and analysis

[0109] Collect the construction progress, quality, and cost parameters of bored piles from different project departments for comprehensive assessment and evaluation, and establish a construction parameter database for bored piles and an enterprise quota library for bored cast-in-place piles in the enterprise to provide data support for the subsequent project duration and cost calculation work.

[0110] The comprehensive assessment and evaluation include: the calculation methods of five indicators, namely the first-class pile index, hole-forming verticality index, concrete homogenization index, hole-forming work efficiency index, and concrete loss index, to achieve comprehensive benchmarking of pile foundation products between different projects.

[0111] The first-class pile index = the number of first-class piles / the total number of pile foundations in the project * 100%

[0112]

[0113] On the other hand, the present invention also provides a digital construction control system for bored cast-in-place piles, including:

[0114] Information input module: used to input the formation, hole-forming process, equipment specifications, drilling efficiency, drilling cost, and corresponding bit pressure, torque, and rotational speed of historical engineering projects, and establish a construction information database for bored cast-in-place piles;

[0115] Geological model establishment module: According to the geological exploration borehole data and soil physical and mechanical parameters of historical engineering projects, fit and generate the three-dimensional formation of the pile hole area and the soil layer distribution corresponding to each pile hole;

[0116] Process identification module: Automatically identify the hole-forming process status of each pile;

[0117] Parameter warning module: Real-time monitor the collected construction parameters and compare them with the threshold values. If the collected construction parameters are not within the threshold values, the parameter warning module will send an alarm to relevant technical personnel and display the specific pile position number, warning reason, and specific construction time where the abnormality occurs.

[0118] The warning parameters of the parameter warning module include: bit pressure, torque, drilling rate, hole-forming verticality, mud performance, waiting time for cage lowering, and catheter embedment depth. The warning threshold values of the warning parameters are set manually or automatically generate upper and lower limit warning threshold values according to the enterprise average level.

[0119] According to a preferred implementation of the present invention, it further includes

[0120] Visualization module: Visually display the overall situation and completion status of the project and the construction progress of the current construction pile position, respectively display the corresponding three-dimensional digital twin models for the hole-forming, cage lowering, and concrete pouring conditions, and visualize the concealed works;

[0121] Log push module: After the process of each pile is completed, automatically push information such as the construction duration and energy consumption of the process to the construction management personnel; automatically push the construction log to the construction management personnel every day to display the quantities of hole-forming, cage lowering, and concrete pouring completed at the construction pile positions on the current day.

[0122] According to a preferred implementation of the present invention, it further includes

[0123] Auxiliary decision-making module: Based on the actual drilling parameters collected for the project, and based on the NSGA-III multi-objective optimization algorithm and the constraints of hole-forming efficiency, hole-forming verticality, and hole-forming energy consumption, give an optimized decision on dynamic drilling parameters;

[0124] Enterprise management module: Used for the enterprise to collect project efficiency, cost, and quality data, comprehensively evaluate and assess the bored pile construction of different project departments, and establish a construction parameter database for bored piles of the enterprise and a quota library for bored cast-in-place piles of the enterprise, providing data support for the subsequent project duration and cost calculation work.

[0125] Digital twin cockpit interaction interface: To enable operators to effectively utilize the digital twin cockpit, an intuitive and user-friendly interaction interface is provided; this interface broadcasts warning information to the operator and allows the operator to view and analyze prediction results and adjust and optimize parameters.

[0126] Although the embodiments of the present invention have been disclosed as above, they are not limited to the applications listed in the specification and embodiments. It can be fully applied to various fields suitable for the present invention. For those familiar with the field, additional modifications can be easily made. Therefore, without departing from the general concept defined by the claims and the equivalent scope, the present invention is not limited to specific details and the embodiments shown and described herein.

Claims

1. A digital construction control method for bored cast-in-place piles, characterized in that, It includes the following steps: S1. Historical data collection Statistical formation, hole-forming process, equipment specifications, drilling efficiency, drilling cost, and corresponding bit pressure, torque, and rotational speed of historical engineering projects, and establish a construction information database for bored cast-in-place piles; S2. Geological modeling According to the geological exploration borehole data and soil physical and mechanical parameters of the newly built engineering project, fit and generate the three-dimensional formation of the pile hole area and the soil layer distribution corresponding to each pile hole; S3. Pre-construction plan recommendation Based on the three-dimensional formation of the pile hole area and the soil layer distribution corresponding to each pile hole, according to the construction information database of bored cast-in-place piles, find the average construction efficiency and cost data of each hole-forming process in the similar formations in the pile hole area, and calculate the construction period and cost of different hole-forming processes for a single pile, for construction management personnel to select the hole-forming process and equipment specifications; S4. Monitoring, early warning and auxiliary decision-making during construction Automatically identify the hole process status of each pile, monitor construction parameters and give early warnings, and perform visual display; according to the drilling parameters of the constructed pile holes, establish calculation models for drilling rate, hole-forming verticality, and hole-forming cost, and according to the improved NSGA-III multi-objective optimization algorithm, obtain the control range of the drilling rig construction parameters that meet the construction requirements; S5. Post-event evaluation and analysis Collect the construction progress, quality, and cost parameters of bored piles from different project departments for comprehensive assessment and evaluation, and establish a construction parameter database for bored piles of the enterprise and a quota database for bored cast-in-place piles of the enterprise to provide data support for the subsequent project duration and cost calculation work.

2. The digital construction control method for bored cast-in-place piles according to claim 1, wherein In the above S4, according to the improved NSGA-III multi-objective optimization algorithm, it includes the following steps; A41. Drilling data collection Obtain the bit pressure, rotational speed, torque, bit diameter, mud displacement, formation drillability index, and drilling cost during the construction of the bored piles in the project; A42. Data segmentation Segment the drilling rig shutdown data, fault repair data, and drill pipe installation and removal data according to data characteristics to obtain the pure drilling data of the drilling rig; A43. Abnormal data elimination Use the 3σ rule to identify the outliers in the pure drilling data of the drilling rig and replace the mean value; A44. Parameter normalization Use the normalization method to normalize various types of original data so that the output range of various data is between [0,1]; A45. Model establishment Use the SVM algorithm to establish regression prediction functions for bit pressure, rotational speed, torque, mud displacement, formation drillability index and hole-forming efficiency, hole-forming verticality, and construct a drilling cost calculation model; A46. Parameter optimization Take the drilling speed, drilling cost, and hole-forming verticality as the fitness functions of the improved NSGA-Ⅲ algorithm to construct an SVM-NSGA-Ⅲ multi-objective optimization model; according to the improved NSGA-Ⅲ algorithm, obtain the Pareto optimal solution set and determine the control range of the drilling construction parameters that meet the drilling rate, hole-forming verticality, and hole-forming cost.

3. The digital construction control method for bored cast-in-place piles according to claim 2, characterized in that, In the above A45, the regression prediction function is f1 = -[SVM-regression(Xi)], i = 1, 2, …, 6; [[ID= Among them, f1 represents the drilling efficiency; f2 represents the hole straightness; X1, X2, X3, X4, X5, and X6 respectively represent the drilling pressure, rotational speed, torque, bit diameter, mud displacement, and formation drillability index, and SVM-regression(Xi) is the SVM regression function.

4. The digital construction control method for bored cast-in-place piles according to claim 2, characterized in that, In the A45, the drilling cost calculation model is: Among them, C b represents the bit cost, C R represents the rig cost, t T represents the time for tripping in and out, t represents the pure drilling time of the bit, H t represents the footage of the bit.

5. The digital construction control method of bored cast-in-place piles according to claim 2, characterized in that In the S4, automatically identifying the working state of the pile hole process includes the following operations: B41. Identification of the process in the hole-forming stage: Obtain the center coordinates of the drill rig through the Beidou positioning system of the drill rig, and then calculate the distance from the center coordinates of the pile hole. The pile hole with the closest distance is the pile hole being drilled, and associate the pile number with the drill rig; Automatically unbind the drill rig from the pile number after confirming the end of the hole; B42. Identification of the process in the steel cage installation stage: After the pile hole automatically confirms the end of the hole by the drill rig, enter the stage of lowering the steel cage. The Beidou positioning system of the crawler crane obtains the coordinates of the crawler crane lowering the steel cage and calculates the distance from the coordinates of the hole position where the steel cage is to be lowered. The pile hole with the closest distance is the pile hole where the steel cage is being lowered, and associate the pile number with the crawler crane; During the process of lowering the steel cage, automatically read the RFID tag on the steel cage through the in-vehicle RFID reader, record the time and number of sections of the steel cage being lowered, and automatically unbind the crawler crane from the pile number after confirming the completion of the steel cage lowering; Among them, the start time of lowering the steel cage is: the time when the first steel cage tag is read by the RFID reader after the crawler crane is associated with the pile number; The completion time of lowering the steel cage is: the time when the last steel cage tag is read by the RFID reader after the crawler crane is associated with the pile number; B43. Identification of the process in the concrete pouring stage: After automatically confirming the completion of the steel cage lowering, enter the concrete pouring stage. The Beidou positioning system of the concrete mixer truck obtains the coordinates of the concrete mixer truck for pouring concrete and calculates the distance from the coordinates of the hole position where the steel cage is to be poured. The pile hole with the closest distance is the pile hole where the concrete is being poured, and associate the pile number with the concrete mixer truck; Automatically unbind the concrete mixer truck from the pile number after confirming the completion of the concrete pouring; Among them, the start time of concrete pouring: the moment when the first concrete mixer truck is associated with the pile number; The completion time of concrete pouring: the latest moment among the moments when all concrete mixer trucks are associated with the pile number.

6. A digital construction control system for bored cast-in-place piles, characterized in that, Including: Information input module: Used to input the formation, hole-forming process, equipment specifications, drilling efficiency, drilling cost, and corresponding drilling pressure, torque, and rotational speed of historical engineering projects, and establish a construction information database for bored cast-in-place piles; Geological model establishment module: According to the geological exploration borehole data and soil physical and mechanical parameters of historical engineering projects, fit and generate the three-dimensional formation of the pile hole area and the soil layer distribution corresponding to each pile hole; Process identification module: Automatically identify the working state of the pile hole process of each pile; Parameter warning module: Real-time monitor the collected construction parameters and compare them with the threshold values. If the collected construction parameters are not within the threshold values, the parameter warning module will issue an alarm to relevant technical personnel and display the specific pile position number, warning reason, and specific construction time where the abnormality occurs.

7. The digital construction control system for bored cast-in-place piles according to claim 6, wherein, It also includes Visualization module: Visually display the overall situation and completion status of the project and the construction progress of the current construction pile positions. For the working conditions of hole formation, steel cage lowering, and concrete pouring, respectively display the corresponding 3D digital twin models to visualize the concealed works. Log push module: After the completion of each pile process, automatically push information such as the duration and energy consumption of the process to the construction management personnel; automatically push the construction log to the construction management personnel every day to display the quantities of hole formation, steel cage lowering, and concrete pouring completed at the construction pile positions on the current day.

8. The digital construction control system for bored cast-in-place piles according to claim 7, characterized in that, It also includes Auxiliary decision-making module: Based on the actual drilling parameters collected for the project, and based on the NSGA-III multi-objective optimization algorithm and the constraint conditions of hole formation efficiency, hole formation verticality, and hole formation energy consumption, give dynamic optimization decisions for drilling parameters. Enterprise management module: Used for the enterprise to collect data on project work efficiency, cost, and quality, comprehensively evaluate the bored pile construction of different project departments, and establish a database of enterprise construction parameters for bored piles and a quota library for bored cast-in-place piles of the enterprise to provide data support for the subsequent calculation of project duration and cost.

Images