Bridge foundation deformation analysis method and system for bridge foundation rotary excavating pile construction based on BIM

Abstract

The invention relates to the technical field of data processing, and discloses a BIM-based bridge foundation deformation analysis method and system for bridge foundation rotary excavating pile construction. The method comprises the steps that three-dimensional scanning modeling is conducted on a construction site, a BIM model is established, a multi-source sensor is arranged to collect data, deformation characteristic parameters are extracted to construct a propagation model, space-time correlation analysis is conducted to generate prediction data, the deformation process is displayed in the BIM model in a multi-view mode, and construction parameters are optimized in combination with historical cases to form a control scheme. Accurate deformation analysis and intelligent construction control in the bridge foundation rotary excavating pile construction process are achieved.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular to a bridge foundation deformation analysis method and system for bridge foundation rotary drilling pile construction based on BIM. Background Art

[0002] The existing deformation monitoring of rotary bored pile construction of bridge foundation mainly relies on traditional surveying and mapping methods and single sensor monitoring methods, such as using total station measurement and inclinometer monitoring to obtain the displacement data of the bridge foundation. Although these methods can obtain basic deformation data, due to the lack of a unified data management platform and intelligent analysis methods, it is difficult to effectively integrate and fully utilize the monitoring data. At the same time, the application of existing BIM technology in bridge engineering is mainly limited to visual display and engineering quantity statistics, and has not yet been deeply integrated with real-time monitoring data, making it difficult to play the guiding role of BIM technology in the engineering construction process.

[0003] However, these traditional methods have the following shortcomings: First, the collection and processing of monitoring data lacks systematicity, and the data from various sensors cannot be effectively linked, making it difficult to timely discover potential construction safety hazards; second, existing deformation analysis methods often ignore the relationship between the stress transfer path of the soil and the deformation development, and cannot accurately predict the deformation development trend; third, the adjustment of construction parameters mainly relies on the experience and judgment of construction personnel, lacks scientific data support, and can easily lead to low construction efficiency or safety hazards; finally, traditional monitoring methods cannot achieve real-time early warning and dynamic optimization during the construction process, and it is difficult to meet the requirements of large-scale bridge projects for construction safety and quality control. Summary of the invention

[0004] The present application provides a bridge foundation deformation analysis method and system for bridge foundation rotary drilling pile construction based on BIM, which is used to organically combine BIM technology with multi-source sensor monitoring data to achieve accurate deformation analysis and intelligent construction control during bridge foundation rotary drilling pile construction.

[0005] In the first aspect, the present application provides a bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM, and the bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM includes: performing three-dimensional scanning modeling on the construction site, establishing a BIM model containing geological information and pile foundation characteristics, setting monitoring reference points in the BIM model, and obtaining monitoring reference data; deploying multi-source sensors according to the positions of the monitoring reference points, edge processing the collected raw data to form an effective monitoring data set, and establishing a corresponding relationship between the effective monitoring data set and the BIM model; based on the effective monitoring data set, extracting the rotary drilling data set, and obtaining the monitoring reference data set. The deformation characteristic parameters during pile construction are combined with the soil stress transfer path analysis to construct a deformation propagation model and output standardized characteristic data; a spatiotemporal correlation analysis is performed on the standardized characteristic data to establish a mapping relationship between rotary drilling construction parameters and bridge foundation deformation, generate deformation prediction data, and conduct a credibility assessment on the prediction results; based on the deformation prediction data, the bridge foundation deformation process is displayed in the BIM model, and multi-perspective dynamic switching display is achieved to form real-time rendered deformation effect data; based on the deformation effect data, the correlation between rotary drilling parameters and deformation is analyzed in combination with the historical case library, the rotary drilling construction parameters are optimized, and a construction control plan is output.

[0006] In a second aspect, the present application provides a bridge foundation deformation analysis system for bridge foundation rotary drilling pile construction based on BIM, and the bridge foundation deformation analysis system for bridge foundation rotary drilling pile construction based on BIM includes:

[0007] A scanning module is used to perform three-dimensional scanning modeling on the construction site, establish a BIM model containing geological information and pile foundation characteristics, set monitoring benchmark points in the BIM model, and obtain monitoring benchmark data;

[0008] A processing module, used to deploy multi-source sensors according to the positions of the monitoring reference points, perform edge processing on the collected raw data to form an effective monitoring data set, and establish a corresponding relationship between the effective monitoring data set and the BIM model;

[0009] An analysis module is used to extract deformation characteristic parameters during the construction of rotary piles based on the effective monitoring data set, build a deformation propagation model in combination with soil stress transfer path analysis, and output standardized characteristic data;

[0010] Establishing a module for performing spatiotemporal correlation analysis on the standardized characteristic data, establishing a mapping relationship between rotary drilling construction parameters and bridge foundation deformation, generating deformation prediction data, and conducting credibility assessment on the prediction results;

[0011] A display module is used to display the deformation process of the bridge foundation in the BIM model based on the deformation prediction data, realize dynamic switching display of multiple perspectives, and form real-time rendering deformation effect data;

[0012] The output module is used to analyze the correlation between rotary drilling parameters and deformation according to the deformation effect data and in combination with the historical case library, optimize the rotary drilling construction parameters, and output the construction control plan.

[0013] In the technical solution provided by the present application, accurate terrain data and geological information are obtained by three-dimensional scanning modeling of the construction site, and a three-dimensional model containing complete pile foundation features is established in combination with BIM technology, which provides accurate basic data for subsequent deformation analysis. By setting monitoring reference points in the BIM model, accurate monitoring of key positions is achieved. At the same time, multi-source sensors are arranged according to the monitoring reference points, and the original data is processed by edge processing technology, which effectively improves the quality and reliability of the monitoring data. In the process of deformation feature extraction, the deformation propagation model is constructed in combination with the analysis of soil stress transfer path, which not only accurately reflects the development law of soil deformation, but also reveals the inherent mechanism of deformation transfer. The time-space correlation analysis of standardized feature data is carried out, and the mapping relationship between rotary excavation construction parameters and bridge foundation deformation is established, and the accuracy of the prediction results is ensured by credibility assessment. The multi-perspective dynamic switching display function in the BIM model enables engineering personnel to intuitively observe and analyze the deformation development process, improving the efficiency of construction monitoring. By analyzing the correlation between rotary excavation parameters and deformation in combination with the historical case library, a scientific and reasonable construction control plan is formulated to achieve accurate control and optimization adjustment of construction parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0015] Figure 1 It is a schematic diagram of an embodiment of a bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM in an embodiment of the present application;

[0016] Figure 2 It is a schematic diagram of an embodiment of a bridge foundation deformation analysis system for bridge foundation rotary drilling pile construction based on BIM in an embodiment of the present application. DETAILED DESCRIPTION

[0017] The embodiment of the present application provides a method and system for analyzing the deformation of a bridge foundation for rotary excavation pile construction based on BIM. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described here can be implemented in an order other than that illustrated or described here. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0018] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 In the embodiment of the present application, an embodiment of a bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM includes:

[0019] Step S101, perform three-dimensional scanning modeling on the construction site, establish a BIM model including geological information and pile foundation characteristics, set monitoring benchmark points in the BIM model, and obtain monitoring benchmark data;

[0020] Step S102: deploy multi-source sensors according to the locations of monitoring reference points, perform edge processing on the collected raw data to form an effective monitoring data set, and establish a corresponding relationship between the effective monitoring data set and the BIM model;

[0021] Step S103: Based on the effective monitoring data set, the deformation characteristic parameters in the rotary pile construction process are extracted, and the deformation propagation model is constructed in combination with the soil stress transfer path analysis to output the standardized characteristic data;

[0022] Step S104: performing a spatiotemporal correlation analysis on the standardized feature data, establishing a mapping relationship between rotary drilling construction parameters and bridge foundation deformation, generating deformation prediction data, and conducting a credibility assessment on the prediction results;

[0023] Step S105: Based on the deformation prediction data, the deformation process of the bridge foundation is displayed in the BIM model, and dynamic switching display of multiple perspectives is realized to form real-time rendered deformation effect data;

[0024] Step S106: Analyze the correlation between rotary drilling parameters and deformation based on the deformation effect data and in combination with the historical case library, optimize the rotary drilling construction parameters, and output a construction control plan.

[0025] It is understandable that the execution subject of the present application can be a bridge foundation deformation analysis system for bridge foundation rotary pile construction based on BIM, or a terminal or a server, which is not limited here. The present application embodiment is described by taking a server as the execution subject as an example.

[0026] Specifically, the construction site is scanned by a three-dimensional laser scanner to obtain point cloud data. The point cloud data contains the spatial position information of the site terrain and objects. The noise points and duplicate points are removed by data cleaning to form preliminary terrain data. At the same time, combined with the soil layer distribution information in the geological drilling report, a three-dimensional model containing geological information is constructed in the BIM software. The BIM model not only contains geological stratification data, but also includes the geometric characteristic parameters of the pile foundation, such as pile diameter, pile length and other information. In the constructed BIM model, monitoring benchmark points are marked at key node positions according to the characteristics of the project. These monitoring benchmark points include soil displacement monitoring points around the pile foundation, hole wall deformation monitoring points and bridge foundation pedestal deformation monitoring points. The initial position data of these monitoring benchmark points are obtained by spatial coordinate calibration. After obtaining the monitoring benchmark point data, various sensors are arranged at the corresponding positions according to the spatial distribution of the monitoring points, including inclinometers, strain gauges, displacement meters, etc. The raw data collected by these sensors are preprocessed by edge computing devices. The edge processing mainly includes three steps: data denoising, outlier removal and data standardization. The processed valid data is indexed according to time series and spatial position, and a corresponding relationship is established with the components in the BIM model, so that the monitoring data can be associated with the specific location in the three-dimensional model.

[0027] Based on the processed effective monitoring data, the deformation characteristics during the construction process are extracted. The deformation characteristics include parameters such as displacement, displacement rate, and stress change. The soil stress transfer path analysis calculates the stress distribution field, tracks the changes in the main direction of stress, and determines the propagation law of stress in the soil. The deformation propagation model is based on the stress transfer path, establishes the relationship between stress change and deformation development, considers the deformation characteristics of the soil, and calculates the deformation influence range and propagation speed. When performing spatiotemporal correlation analysis on standardized characteristic data, the deformation data is first organized according to the time and space dimensions to construct a deformation data matrix. By analyzing the deformation development laws at different time points and different spatial positions, the main influencing factors of deformation are identified. At the same time, the deformation data is correlated with the rotary drilling construction parameters to establish a mapping relationship between construction parameters (such as drilling speed, wall protection mud density, etc.) and deformation development.

[0028] When displaying the deformation process of the bridge foundation in the BIM model, the predicted deformation data is mapped to the three-dimensional model, and the deformation trend is intuitively displayed through the deformation magnification factor. Multi-view dynamic switching display By setting different observation viewpoints, such as plane view, section view, stereo view, etc., and switching smoothly between these views, engineers can observe the deformation development from multiple angles. Finally, based on the deformation effect data obtained in real time, the relationship between rotary drilling parameters and deformation under similar working conditions in the historical case library is compared and analyzed to optimize the current construction parameters. The historical case library stores construction parameters and corresponding deformation data under different geological conditions and different pile types. Through case retrieval and similarity matching, the most suitable construction parameter combination for the current working conditions is found.

[0029] For example, during the construction of rotary piles for the foundation of a bridge, the point cloud data obtained by 3D laser scanning showed that the surface elevation of the site varied between 23.5 meters and 25.6 meters. The geological survey data showed that the site consisted of silty clay layer, sandy soil layer and strongly weathered rock layer from top to bottom. The monitoring data of the deployed inclinometer showed that when the rotary excavation reached a depth of 15 meters, the soil 2 meters away from the pile hole produced a horizontal displacement. Through the analysis of the soil stress transfer path, it was found that this displacement was related to the sinking of the casing and the release of soil stress during the rotary excavation process. After the time-space correlation analysis, it was found that when the drilling speed exceeded 0.5 meters per minute, the deformation rate of the surrounding soil increased significantly. According to this correlation, the development of soil deformation was controlled by adjusting the drilling speed and the density of the wall slurry. The data processing in the whole process reflects the complete chain from raw data acquisition, deformation feature extraction to parameter optimization, ensuring the safety and efficiency of the construction process.

[0030] In the embodiment of the present application, by performing three-dimensional scanning modeling on the construction site, accurate terrain data and geological information are obtained, and a three-dimensional model containing complete pile foundation features is established in combination with BIM technology, which provides accurate basic data for subsequent deformation analysis. By setting monitoring reference points in the BIM model, accurate monitoring of key positions is achieved. At the same time, multi-source sensors are arranged according to the monitoring reference points, and the original data is processed using edge processing technology, which effectively improves the quality and reliability of the monitoring data. In the process of deformation feature extraction, the deformation propagation model is constructed in combination with the analysis of soil stress transfer path, which not only accurately reflects the development law of soil deformation, but also reveals the inherent mechanism of deformation transfer. The time-space correlation analysis of standardized feature data is carried out, and the mapping relationship between rotary excavation construction parameters and bridge foundation deformation is established, and the accuracy of the prediction results is ensured by credibility assessment. The multi-perspective dynamic switching display function in the BIM model enables engineering personnel to intuitively observe and analyze the deformation development process, thereby improving the efficiency of construction monitoring. By analyzing the correlation between rotary excavation parameters and deformation in combination with the historical case library, a scientific and reasonable construction control plan is formulated, which realizes accurate control and optimization adjustment of construction parameters.

[0031] In a specific embodiment, the process of executing step S101 may specifically include the following steps:

[0032] (1) Collect the original point cloud data of the construction site, remove the noise points in the original point cloud data, and generate preliminary terrain data;

[0033] (2) The preliminary topographic data are layered according to geological information, and drilling records are integrated to generate layered geological data;

[0034] (3) Combine the layered geological data with the pile foundation characteristics to construct a construction site coordinate system and form positioning benchmark data;

[0035] (4) Divide the deformation monitoring network according to the positioning reference data, set monitoring reference points at the key component positions, and output the monitoring point layout data;

[0036] (5) Import the monitoring point layout data into the BIM model, establish the relationship between the monitoring points and the model components, and generate point corresponding data;

[0037] (6) Set the sampling frequency and warning threshold for the corresponding data of the point, associate the monitoring parameters with the displacement changes, and obtain the monitoring benchmark data.

[0038] Specifically, a 3D laser scanner is used to scan the construction site in all directions to obtain the original point cloud data. The original point cloud data is a data set consisting of a large number of spatial coordinate points, each of which contains three-dimensional coordinate values ​​(X, Y, Z) and reflection intensity information. Due to the influence of environmental factors during the scanning process, there are noise points in the original point cloud data, such as interference points caused by suspended dust, raindrop reflection, etc. The original point cloud data are cleaned by calculating the spatial distance between each point and the surrounding points, identifying discrete points that are obviously deviated from the main body, eliminating these noise data, and merging repeated sampling points that are too close, and finally forming preliminary topographic data that accurately reflects the topographic characteristics of the site. The obtained preliminary topographic data are integrated with the geological drilling records, which contain geological parameters such as soil properties, thickness, and strength at each depth. By matching the elevation information of the point cloud data with the depth data of the drilling record, the topographic data are marked and classified according to different soil layer types. Each soil layer is given a unique identifier, and its physical and mechanical properties, such as internal friction angle, cohesion, compression modulus and other parameters are recorded to form layered geological data containing geological information.

[0039] In the process of combining stratified geological data with pile foundation characteristics, the design parameters of the pile foundation need to be imported into the data processing system. Pile foundation characteristics include geometric parameters such as pile diameter, pile length, pile position coordinates, and material parameters such as concrete strength and steel bar configuration. By establishing a unified three-dimensional coordinate system, the geological stratification information and pile foundation characteristics are spatially registered so that the two types of data can accurately correspond in the same coordinate system, thereby forming positioning reference data. Based on the positioning reference data, the monitoring network is divided according to the needs of deformation monitoring. Monitoring sections are arranged radially around the pile foundation, and the layout of the monitoring sections takes into account the characteristics of soil layer changes and construction process requirements. Encrypted monitoring points are set at key component locations such as the abutment and pile body. Each monitoring point is equipped with a unique spatial coordinate and number, and its corresponding monitoring purpose is recorded, such as horizontal displacement, vertical displacement or tilt angle monitoring, so as to output the monitoring point layout data.

[0040] The monitoring point layout data needs to be imported into the BIM model. During the import process, the coordinate information of each monitoring point is spatially associated with the components in the BIM model. The spatial registration algorithm is used to ensure the accurate positioning of the monitoring points in the model. At the same time, each monitoring point is associated with its component information, including component type, material properties, etc., to generate point corresponding data. The point corresponding data is further processed to set corresponding sampling frequencies for different types of monitoring points. The setting of the sampling frequency is determined according to the characteristics of deformation development, such as increasing the sampling frequency for areas with faster deformation rates. At the same time, based on engineering experience and specification requirements, a graded warning threshold is set, and different levels of warning values ​​are associated with monitoring parameters. Monitoring parameters include displacement, deformation rate, tilt angle, etc., and monitoring benchmark data are obtained through parameter association calculation.

[0041] For example, the point cloud data obtained by 3D laser scanning covers the entire construction site. When processing the data, a large number of abnormal points suspended in the air and repeated points caused by ground reflection are first identified, and these interfering data are eliminated through spatial clustering analysis. Then, the different soil layer information shown in the geological drilling report is combined with the terrain data to clarify the distribution boundary of the soil layer. In the positioning data processing, the pile foundation parameters and geological data are unified in the engineering coordinate system to ensure the spatial consistency of the data. When laying out the monitoring points, the main survey line is laid out in four directions around the pile foundation, and multiple monitoring points are set on each survey line. The position of the monitoring point is determined according to the characteristics of soil layer changes. These monitoring points are accurately located in the BIM model and a corresponding relationship is established with the model components. Finally, different sampling frequencies are set according to the importance of different monitoring points. High-frequency sampling is used for key points on the main survey line, and multi-level warning thresholds are set to achieve comprehensive monitoring of deformation during pile foundation construction.

[0042] In a specific embodiment, the process of executing step S102 may specifically include the following steps:

[0043] (1) Displacement sensors, stress sensors, and settlement sensors are configured according to the location of the monitoring reference point, the data sampling frequency is recorded, and a sensor layout plan is generated;

[0044] (2) Import the sensor deployment plan into the data acquisition system, mark the spatial coordinates of each sensor, and generate equipment deployment data;

[0045] (3) Perform marginal processing on the collected raw data, eliminate outliers and interference signals, and output preliminary monitoring data;

[0046] (4) Perform time calibration and coordinate transformation on the preliminary monitoring data to eliminate acquisition delay and spatial deviation and form an effective monitoring data set;

[0047] (5) Classify and organize effective monitoring data sets according to monitoring indicator types, establish data retrieval indexes, and generate data management plans;

[0048] (6) Map the effective monitoring data set to the BIM model based on the data management plan and establish a corresponding relationship between the effective monitoring data set and the BIM model.

[0049] Specifically, multiple types of sensors are deployed according to the location of the monitoring benchmark. Displacement sensors mainly include horizontal displacement sensors and vertical displacement sensors, which are used to monitor the displacement changes of soil bodies; stress sensors include earth pressure boxes and pore water pressure sensors, which are used to monitor the changes in the stress state of soil bodies; settlement sensors monitor the settlement changes of surface and deep soil bodies through hydraulic levels and inclinometers. Each type of sensor is set with a specific sampling frequency. The displacement sensor is set to sample 6 times per hour, the stress sensor is set to sample 12 times per hour, and the settlement sensor is set to sample 4 times per hour. These sampling frequencies are set based on the deformation development rate and monitoring accuracy requirements to form a sensor deployment plan. When the sensor deployment plan is imported into the data acquisition system, it is necessary to mark the accurate spatial coordinates for each sensor. The determination of spatial coordinates is obtained through total station measurement. The spatial position of each sensor corresponds to the engineering coordinate system, including the installation depth, azimuth and tilt angle of the sensor. The sensor spatial information after marking constitutes the equipment deployment data, which records the specific installation location, monitoring direction and data transmission channel of the sensor. Marginalization processing is the process of preliminary filtering and processing of raw monitoring data. An edge computing unit is set up at the data acquisition end to process the data collected by the sensor in real time. First, outliers that exceed the range are eliminated, such as sudden changes in displacement sensor data or jumps in stress sensor readings; then, noise signals caused by external electromagnetic interference and mechanical vibration are removed through digital filtering; finally, data standardization is performed to unify the data of different sensors to the same metric standard and output preliminary monitoring data. Timing calibration and coordinate transformation are key steps in forming an effective monitoring data set. Since there is a time delay in data acquisition from different sensors, the data needs to be synchronized in time. Through timestamp alignment, the monitoring data at the same time is combined. Coordinate transformation converts the data in the local coordinate system of each sensor into a unified engineering coordinate system, eliminating installation errors and posture deviations, and ensuring the spatial consistency of the data.

[0050] The classification and organization of effective monitoring data sets are carried out according to the type of monitoring indicators. Displacement data, stress data and settlement data are classified separately, and an independent data table is established for each type of data, including fields such as time, spatial location, and monitoring value. At the same time, a data retrieval index is established to quickly locate specific data through time index and spatial index, which is convenient for subsequent analysis and use. The data management plan defines the storage format, update rules and access rights of the data. A mapping relationship is established between the effective monitoring data set and the BIM model. Through the spatial registration algorithm, the spatial coordinates of the monitoring data are matched with the component positions in the BIM model. The data of each monitoring point is associated with a specific model component to achieve dynamic association between data and model. This correspondence enables the monitoring data to be intuitively displayed in the BIM model, which is convenient for engineering personnel to understand and analyze the development of deformation.

[0051] For example, 24 monitoring points are set up around the pile foundation, and each monitoring point is equipped with different types of sensors. During the sensor data collection process, a large amount of raw data is processed by the edge computing unit. The displacement sensor data shows the changing trend of horizontal displacement, the stress sensor data reflects the redistribution process of soil stress, and the settlement sensor data records the development of surface settlement. After time series calibration, these data clearly show the spatiotemporal evolution of soil deformation during pile foundation construction. When the displacement value of a monitoring point exceeds the warning threshold, the system immediately marks the location in the BIM model and displays the data changes of surrounding monitoring points in a linked manner, helping engineering personnel to promptly discover and deal with potential construction risks.

[0052] In a specific embodiment, the process of executing step S103 may specifically include the following steps:

[0053] (1) The effective monitoring data set is layered according to the location of the monitoring points, the soil displacement and hole wall stress values ​​are extracted, and layered monitoring data are generated;

[0054] (2) Correlate the layered monitoring data with the soil stress data during rotary excavation, calculate the stress change gradient of each monitoring point, and form stress change data;

[0055] (3) Determine the principal stress direction of stress change data, identify soil deformation trend and stress transfer direction, and construct soil stress transfer path analysis data;

[0056] (4) Based on the soil stress transfer path analysis data, the corresponding relationship between the stress diffusion range and the deformation is established to form the stress propagation parameters;

[0057] (5) Numerical analysis of the deformation transfer law is performed based on the stress propagation parameters, the spatial attenuation law of soil deformation is determined, and a deformation propagation model is constructed;

[0058] (6) The calculation results of the deformation propagation model are processed by data standardization, the measurement units and measurement standards are unified, and standardized feature data are output.

[0059] Specifically, the effective monitoring data set is processed in layers according to the spatial position. The data at each monitoring point is segmented in depth, corresponding to the monitoring data of different soil layers. The soil displacement data, including horizontal displacement and vertical displacement, are extracted in each layer, and the radial stress and tangential stress values ​​recorded by the hole wall stress sensor are read at the same time. These data are sorted according to the depth mark to form layered monitoring data, which reflects the deformation and stress state of soil layers at different depths. The layered monitoring data needs to be associated with the soil stress data collected in real time during the rotary excavation process. The soil stress data during the rotary excavation process comes from stress sensors buried in different positions, which record the dynamic changes of the soil stress field during the rotary excavation construction process. The stress change gradient is obtained by calculating the ratio of the stress difference between adjacent monitoring points to the spatial distance. The stress change gradient reflects the rate of change of stress in space, and these data are integrated to form stress change data.

[0060] Determining the direction of principal stress is a key step in analyzing the deformation mechanism of soil. The direction of principal stress is calculated by the following formula:

[0061]

[0062] Among them, θ p represents the principal stress direction angle, τ xy represents the shear stress, σ x represents the normal stress in the x direction, σ y Represents the positive stress in the y direction. The determination of the principal stress direction directly indicates the development trend of soil deformation. Combined with the stress transfer direction, the soil stress transfer path analysis data is constructed.

[0063] The corresponding relationship between stress diffusion range and deformation amount is established by the following formula:

[0064]

[0065] Among them, Δ d represents the deformation, λ f represents the elastic coefficient of soil, β r represents the attenuation coefficient, ρ represents the distance from the rotary drilling center, ω s represents the stress diffusion angle, γ m represents the soil bulk density, φ k Represents the internal friction angle of soil. Through this relationship, the deformation prediction of each point within the stress diffusion range is established to form the stress propagation parameter. According to the stress propagation parameter, the deformation transmission law is numerically analyzed to determine the attenuation law of soil deformation with increasing distance. By analyzing the deformation data at different depths and directions, a deformation propagation model in three-dimensional space is established, which describes how the deformation diffuses and decays in space.

[0066] The calculation results of the deformation propagation model are standardized, and the measurement units of various data are unified, such as displacement is unified to millimeters, stress is unified to kilopascals, and data of different dimensions are converted into dimensionless standard values, and standardized characteristic data are output.

[0067] For example, the strata from top to bottom are silt layer, silty clay layer and gravel layer. The stress sensors arranged in the silt layer detected that the stress field of the soil changed significantly with the increase of rotary drilling depth. Applying the principal stress direction determination formula, it is calculated that the principal stress direction within 2 meters around the pile is inclined at 45 degrees and points to the direction of the pile hole, indicating that the soil is deforming in the direction of the pile hole. Combined with the stress diffusion model, the variation law of the deformation influence range with depth is predicted. In the silt layer, the deformation influence range is large and the stress transmission distance is long; in the gravel layer, due to the high strength of the soil, the deformation influence range is significantly reduced.

[0068] In a specific embodiment, the process of executing step S104 may specifically include the following steps:

[0069] (1) Arrange the deformation amounts in the standardized feature data according to time series and spatial position to obtain a deformation data matrix;

[0070] (2) Analyze the deformation data matrix in the time dimension, extract the deformation development rate and acceleration factor, and form time series characteristic data;

[0071] (3) Correlate the time series feature data with the rotary drilling parameters, analyze the influence of the construction parameter adjustment on the deformation, and generate parameter sensitivity data;

[0072] (4) Establish the bridge foundation deformation prediction index based on the parameter sensitivity data, calculate the deformation trend weight of each monitoring point, and output the deformation prediction data;

[0073] (5) Compare and verify the deformation prediction data with the historical monitoring data, calculate the error range between the predicted value and the measured value, and generate error distribution data;

[0074] (6) The probability of deformation prediction is statistically calculated based on the error distribution data, and the credibility level of the prediction results is divided to form a prediction credibility evaluation result.

[0075] Specifically, the standardized characteristic data are sorted and organized according to the time dimension and the space dimension. The time dimension reflects the change process of the deformation of each monitoring point over time, and the space dimension reflects the deformation distribution at different positions at the same time. These data are organized into a deformation data matrix, the rows of the matrix represent different time points, and the columns represent different spatial monitoring point positions. When the deformation data matrix is ​​analyzed in the time dimension, the difference in deformation between adjacent time points is calculated to obtain the deformation rate, and then the change in the rate is calculated to obtain the acceleration factor. The deformation rate reflects the speed of deformation development, and the acceleration factor indicates the trend change of deformation development. These time series characteristic data describe the dynamic characteristics of deformation development.

[0076] The time series characteristic data and rotary drilling construction parameters are correlated and analyzed to study the influence of changes in construction parameters (including rotation speed, downforce, and lifting speed) on deformation development. By comparing the deformation development before and after parameter adjustment, the influence of each parameter on the deformation is calculated to generate parameter sensitivity data. Parameter sensitivity data reflects the importance of different construction parameters to deformation control.

[0077] The deformation trend weight of each monitoring point is calculated using the following formula:

[0078]

[0079] Among them, W d represents the deformation trend weight, q i represents the monitoring point distance impact factor, h i Indicates the cumulative value of historical deformation, u i Indicates the current deformation rate, v i represents the geological condition coefficient, r i Denotes the depth influence coefficient, c i represents the constraint coefficient, j i represents the load distribution coefficient, and n represents the number of influencing factors. The weight value calculated according to the formula is combined with the parameter sensitivity data to output the deformation prediction data. The predicted deformation data is compared and analyzed with the historical measured data to calculate the difference between the predicted value and the measured value. These difference data are statistically analyzed to obtain the distribution law of the error, including the mean, standard deviation and distribution characteristics of the error, and form the error distribution data.

[0080] Based on the error distribution data, the accuracy of deformation prediction is statistically calculated, and the prediction results are divided into three levels according to accuracy: high credibility, medium credibility and low credibility. High credibility means small prediction error and good stability, medium credibility means moderate prediction error, and low credibility means large prediction error or instability, forming the final prediction credibility evaluation result.

[0081] For example, the deformation data of multiple monitoring points are analyzed and processed. The deformation data matrix contains sampling data once an hour within 24 hours, as well as spatial distribution data of 12 monitoring points arranged around the pile. Through time dimension analysis, it is found that in the initial stage of rotary drilling, the deformation rate is large and the acceleration is positive, indicating that the deformation is accelerating; as the construction progresses, the deformation rate gradually decreases and the acceleration turns negative, indicating that the deformation tends to stabilize. In the parameter sensitivity analysis, it is found that the drilling speed has the most significant effect on the development of deformation, followed by the density of the wall mud. Based on these analysis results, the deformation trend weights of each monitoring point are calculated, focusing on the monitoring points with larger weight values. Comparing the prediction results with the actual monitoring data, it is found that the prediction accuracy is high in the stable deformation stage, which belongs to the high credibility level; while in the rapid development stage of deformation, the accuracy of the prediction results is relatively low and is classified as medium credibility level.

[0082] In a specific embodiment, the process of executing step S105 may specifically include the following steps:

[0083] (1) The deformation prediction data is converted into deformation node data according to the spatial coordinate system, the corresponding relationship between the deformation amount and the BIM component is established, and the component deformation data is generated;

[0084] (2) setting three reference perspectives of front view, side view and top view for the component deformation data, calculating the rotation matrix of the perspective conversion, and forming perspective parameter data;

[0085] (3) Convert the viewing angle parameter data into the observation point coordinate system, divide the observation distances into three: near view, middle view and far view, and output the viewpoint transformation data;

[0086] (4) Establish rendering priorities under different viewing angles based on viewpoint transformation data, calculate component occlusion relationships and display order, and generate view rendering data;

[0087] (5) Update the view rendering data in real time, calculate the component displacement according to the deformation development process, and form a dynamic display sequence;

[0088] (6) Combine the dynamic display sequence with the rendering engine parameters, integrate the lighting, material and shadow effects, and output real-time rendered deformation effect data.

[0089] Specifically, the predicted deformation data is mapped to the corresponding nodes in the BIM model through coordinate transformation, and each node contains spatial position and deformation information. These nodes establish a corresponding relationship with the components in the BIM model, record the geometric characteristics, material properties and deformation state of the components, and generate component deformation data. When performing multi-view display processing on the component deformation data, three reference perspectives are first established: the front view reflects the front deformation state of the component, the side view shows the lateral deformation distribution, and the top view shows the plane deformation law. For each perspective, the corresponding rotation matrix is ​​calculated to determine the spatial orientation and observation angle of the view. These perspective parameters are recorded in the perspective parameter data.

[0090] The viewing angle parameter data needs to be converted to the observation point coordinate system. The conversion formula is:

[0091]

[0092] Among them, P view is the point coordinate in the observation point coordinate system, M vp is the projection matrix, R vh is the horizontal rotation matrix of the viewing angle, T vc is the viewpoint translation matrix.

[0093] The world coordinate system coordinates are divided into near view (0-5 meters), middle view (5-15 meters) and far view (more than 15 meters) according to the observation distance to form viewpoint transformation data.

[0094] Based on the viewpoint transformation data, the rendering priority of components under different viewing angles is sorted. The depth sorting algorithm is used to calculate the occlusion relationship between components and determine the display order. Components in the near view area are rendered first to show more details; components in the distant view area can be appropriately simplified to improve rendering efficiency. These rendering parameters and display order information constitute the view rendering data. During the real-time update process, the displacement change of the component at each moment is calculated according to the time sequence of the deformation development. The continuous deformation process is obtained through interpolation calculation, including the translation, rotation and deformation of the component. These change sequences are arranged in chronological order to form a dynamic display sequence.

[0095] Finally, the dynamic display sequence is combined with the rendering engine to add lighting effects, material textures, and shadow projection. The lighting calculation takes into account ambient light, diffuse light, and specular light, the material properties include color, transparency, and reflectivity, and the shadow effect is achieved through the ray tracing algorithm. These rendering effects are combined to form the deformation effect data for real-time rendering.

[0096] For example, during the construction process, deformation prediction data showed that the soil around the piles had uneven deformation. These deformation data were first converted into the BIM model coordinate system and associated with components such as pile foundations and caps. The horizontal displacement distribution of the soil around the pile foundation was observed in the front view, the side view reflected the deformation gradient in the depth direction, and the top view showed the distribution range of surface settlement. By adjusting the viewing angle, engineers can clearly observe the deformation development process: the close-up view shows the contact deformation between the pile wall and the soil in detail, the mid-view view shows the expansion of the deformation influence range, and the long-range view reflects the overall deformation trend. As the rotary drilling depth increases, the dynamic display sequence is updated in real time, showing the gradual development of soil deformation. By adding lighting and shadow effects, the spatial position relationship of the deformation area is made more intuitive, which helps to timely discover potential construction risks.

[0097] In a specific embodiment, the process of executing step S106 may specifically include the following steps:

[0098] (1) Classify and label the deformation effect data according to geological conditions, pile diameter, pile length, and deformation range, establish data retrieval standards, and generate feature index data;

[0099] (2) Based on the feature index data, similar working condition information is extracted from the historical case library, and the corresponding relationship between rotary drilling parameters and deformation is statistically analyzed to form parameter mapping data;

[0100] (3) Perform multi-dimensional analysis on the parameter mapping data, calculate the correlation coefficients among the rotation speed, downforce, lifting speed and deformation, and output parameter correlation data;

[0101] (4) Convert parameter correlation data into construction condition constraints, determine the safety threshold range of each parameter, and generate parameter control data;

[0102] (5) Construct a construction process parameter optimization plan based on parameter control data, set parameter adjustment strategies for each stage, and form a segmented control sequence;

[0103] (6) Combine the segmented control sequence with geological stratification information to formulate drilling parameters and protective measures for different soil layers and generate a construction control plan.

[0104] Specifically, the deformation effect data is first classified according to geological conditions, including geological parameters such as soil layer type, water content, and density; secondly, it is classified according to pile foundation characteristics, including geometric parameters such as pile diameter and pile length; finally, it is classified according to deformation range, including deformation characteristics such as horizontal deformation range and vertical deformation range. Retrieval criteria are established for each type of data, and weight values ​​are assigned to each feature to generate feature index data. These index data will be used for subsequent case retrieval and parameter matching. Based on the generated feature index data, similar working conditions are retrieved in the historical case library. The similarity judgment is based on the matching degree of geological conditions, the similarity of pile type parameters, and the proximity of deformation characteristics. The rotary drilling parameters in the historical cases that meet the conditions are extracted, including drill bit speed, downforce, and lifting speed, and the corresponding relationship between these parameters and the actual deformation amount is statistically analyzed to form parameter mapping data.

[0105] Perform multi-dimensional analysis on parameter mapping data, focusing on the correlation between construction parameters and deformation. The relationship between rotation speed and horizontal deformation reflects the degree of influence of rotary drilling disturbance, the relationship between downforce and vertical deformation reflects the load transfer characteristics, and the relationship between lifting speed and hole wall stability shows the stress release law of soil. Through the analysis of these relationships, calculate the correlation coefficient between each parameter and deformation, and output parameter correlation data. Convert parameter correlation data into specific construction constraints. According to engineering safety standards and specifications, determine the safety threshold range of rotation speed, downforce and lifting speed. Set the parameter adjustment range under different working conditions, consider the influence of geological conditions, construction environment and other factors, and generate parameter control data.

[0106] Based on the parameter control data, formulate a parameter optimization plan during the construction process. Divide the entire construction process into multiple stages, such as the initial drilling stage, the stable hole formation stage, and the final hole stage. According to the characteristics of each stage, set the corresponding parameter adjustment strategy, including the parameter adjustment direction, adjustment step and adjustment frequency, to form a segmented control sequence. Finally, combine the segmented control sequence with the geological stratification information, and formulate corresponding drilling parameters and protective measures according to the engineering characteristics of different soil layers. Add wall protection measures in soft soil layers, adjust drilling parameters in hard soil layers, and take special protective measures in special strata to finally form a construction control plan.

[0107] For example, the geological conditions of the construction site are silt layer, silty clay layer and sand and gravel layer from top to bottom. According to previous construction experience, silt layer is prone to collapse, silty clay layer is prone to mud skin, and sand and gravel layer has large drilling resistance. By searching the historical case library, construction cases under similar geological conditions were found. These cases show that when constructing in silt layer, when the rotation speed exceeds a certain value, the hole wall is prone to instability; in silty clay layer, it is necessary to increase the downforce appropriately to prevent the formation of mud skin; in sand and gravel layer, it is necessary to reduce the rotation speed and increase the flushing fluid flow. Based on these empirical data, layered construction parameters were formulated: in silt layer, a parameter combination of low rotation speed and low downforce was used, combined with mud wall protection; in silty clay layer, a combination of medium rotation speed and large downforce was used, and attention was paid to controlling the drilling speed; in sand and gravel layer, a combination of low rotation speed and large downforce was used to strengthen flushing. During the construction process, the drilling rig operator carried out the construction according to these parameter guidance and effectively controlled the soil deformation. The effectiveness of the parameter control scheme was verified through real-time monitoring data analysis, and the soil deformation was controlled within the expected range.

[0108] The above describes the bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM in the embodiment of the present application. The following describes the bridge foundation deformation analysis system for bridge foundation rotary drilling pile construction based on BIM in the embodiment of the present application. Figure 2 In the embodiment of the present application, an embodiment of a bridge foundation deformation analysis system for bridge foundation rotary drilling pile construction based on BIM includes:

[0109] Scanning module 201 is used to perform three-dimensional scanning modeling on the construction site, establish a BIM model containing geological information and pile foundation characteristics, set monitoring benchmark points in the BIM model, and obtain monitoring benchmark data;

[0110] The processing module 202 is used to deploy multi-source sensors according to the positions of the monitoring reference points, perform edge processing on the collected raw data to form an effective monitoring data set, and establish a corresponding relationship between the effective monitoring data set and the BIM model;

[0111] The analysis module 203 is used to extract deformation characteristic parameters during the construction of rotary piles based on the effective monitoring data set, build a deformation propagation model in combination with soil stress transfer path analysis, and output standardized characteristic data;

[0112] Establishing module 204, for performing spatiotemporal correlation analysis on the standardized characteristic data, establishing a mapping relationship between rotary drilling construction parameters and bridge foundation deformation, generating deformation prediction data, and conducting credibility assessment on the prediction results;

[0113] A display module 205 is used to display the deformation process of the bridge foundation in the BIM model based on the deformation prediction data, realize dynamic switching display of multiple perspectives, and form real-time rendering deformation effect data;

[0114] The output module 206 is used to analyze the correlation between rotary drilling parameters and deformation according to the deformation effect data and in combination with the historical case library, optimize the rotary drilling construction parameters, and output a construction control plan.

[0115] Through the cooperation of the above components, accurate terrain data and geological information are obtained by three-dimensional scanning and modeling of the construction site, and a three-dimensional model containing complete pile foundation features is established in combination with BIM technology, providing accurate basic data for subsequent deformation analysis. By setting monitoring benchmarks in the BIM model, accurate monitoring of key locations is achieved. At the same time, multi-source sensors are arranged according to the monitoring benchmarks, and the original data is processed using edge processing technology, which effectively improves the quality and reliability of the monitoring data. In the process of deformation feature extraction, the deformation propagation model is constructed in combination with the analysis of soil stress transfer path, which not only accurately reflects the development law of soil deformation, but also reveals the internal mechanism of deformation transfer. The spatiotemporal correlation analysis of standardized feature data is carried out, and the mapping relationship between rotary excavation construction parameters and bridge foundation deformation is established, and the accuracy of the prediction results is ensured through credibility evaluation. The multi-perspective dynamic switching display function in the BIM model enables engineering personnel to intuitively observe and analyze the deformation development process, improving the efficiency of construction monitoring. By analyzing the correlation between rotary excavation parameters and deformation in combination with the historical case library, a scientific and reasonable construction control plan is formulated to achieve accurate control and optimization adjustment of construction parameters.

[0116] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM, characterized in that: The bridge foundation deformation analysis method for bridge foundation rotary excavation pile construction based on BIM includes: Conduct three-dimensional scanning and modeling of the construction site, establish a BIM model containing geological information and pile foundation characteristics, set monitoring benchmark points in the BIM model, and obtain monitoring benchmark data; Deploy multi-source sensors according to the positions of the monitoring reference points, perform edge processing on the collected raw data to form an effective monitoring data set, and establish a corresponding relationship between the effective monitoring data set and the BIM model; Based on the effective monitoring data set, the deformation characteristic parameters in the rotary pile construction process are extracted, and the deformation propagation model is constructed in combination with the soil stress transfer path analysis to output standardized characteristic data; Performing a spatiotemporal correlation analysis on the standardized characteristic data, establishing a mapping relationship between rotary drilling construction parameters and bridge foundation deformation, generating deformation prediction data, and conducting a credibility assessment on the prediction results; Based on the deformation prediction data, the deformation process of the bridge foundation is displayed in the BIM model, and dynamic switching display of multiple perspectives is realized to form real-time rendering deformation effect data; According to the deformation effect data, the correlation between rotary drilling parameters and deformation is analyzed in combination with the historical case library, the rotary drilling construction parameters are optimized, and the construction control plan is output.

2. The bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM according to claim 1 is characterized in that: The three-dimensional scanning and modeling of the construction site is performed to establish a BIM model including geological information and pile foundation characteristics, and monitoring benchmark points are set in the BIM model to obtain monitoring benchmark data, including: Collect the original point cloud data of the construction site, remove the noise points in the original point cloud data, and generate preliminary terrain data; Processing the preliminary topographic data in layers according to the geological information, integrating drilling records, and generating layered geological data; Combining the layered geological data with the pile foundation characteristics to construct a construction site coordinate system and form positioning reference data; Dividing the deformation monitoring network according to the positioning reference data, setting the monitoring reference points at the key component positions, and outputting the monitoring point layout data; Importing the monitoring point layout data into the BIM model, establishing an association relationship between the monitoring points and the model components, and generating point corresponding data; The sampling frequency and the early warning threshold are set for the data corresponding to the point positions, and the monitoring parameters are associated with the displacement changes to obtain the monitoring reference data.

3. The bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM according to claim 1 is characterized in that: The multi-source sensors are arranged according to the positions of the monitoring reference points, the collected raw data are marginalized to form an effective monitoring data set, and a corresponding relationship between the effective monitoring data set and the BIM model is established, including: Displacement sensors, stress sensors and settlement sensors are configured according to the positions of the monitoring reference points, data sampling frequencies are recorded, and a sensor layout plan is generated; Importing the sensor deployment plan into a data acquisition system, marking the spatial coordinates of each sensor, and generating equipment deployment data; Performing marginalization processing on the collected raw data, eliminating abnormal values ​​and interference signals, and outputting preliminary monitoring data; Performing time series calibration and coordinate transformation on the preliminary monitoring data to eliminate acquisition delay and spatial deviation, thereby forming the effective monitoring data set; Classify and sort the effective monitoring data sets according to the monitoring indicator types, establish data retrieval indexes, and generate data management plans; The effective monitoring data set is mapped to the BIM model according to the data management solution, and a corresponding relationship between the effective monitoring data set and the BIM model is established.

4. The bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM according to claim 1 is characterized in that: Based on the effective monitoring data set, the deformation characteristic parameters in the rotary pile construction process are extracted, and the deformation propagation model is constructed in combination with the soil stress transfer path analysis to output standardized characteristic data, including: The effective monitoring data set is layered according to the location of the monitoring points, soil displacement and hole wall stress values ​​are extracted, and layered monitoring data is generated; Correlating the layered monitoring data with soil stress data during rotary drilling, calculating the stress change gradient of each monitoring point, and forming stress change data; Determine the principal stress direction of the stress change data, identify the soil deformation trend and stress transfer direction, and construct the soil stress transfer path analysis data; Based on the soil stress transfer path analysis data, a corresponding relationship between the stress diffusion range and the deformation amount is established to form a stress propagation parameter; Numerical analysis is performed on the deformation transmission law according to the stress propagation parameters, the spatial attenuation law of soil deformation is determined, and the deformation propagation model is constructed; The calculation results of the deformation propagation model are subjected to data standardization processing, the measurement units and measurement standards are unified, and the standardized feature data are output.

5. The bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM according to claim 1 is characterized in that: The time-space correlation analysis is performed on the standardized characteristic data, a mapping relationship between rotary drilling construction parameters and bridge foundation deformation is established, deformation prediction data is generated, and a credibility assessment is performed on the prediction results, including: Arranging the deformation amounts in the standardized feature data according to time series and spatial positions to obtain a deformation data matrix; Performing time dimension analysis on the deformation data matrix, extracting deformation development rate and acceleration factor, and forming time series characteristic data; Associating the time series characteristic data with rotary drilling working condition parameters, analyzing the influence of construction parameter adjustment on deformation, and generating parameter sensitivity data; Establishing a bridge foundation deformation prediction index based on the parameter sensitivity data, calculating the deformation trend weight of each monitoring point, and outputting the deformation prediction data; Compare and verify the deformation prediction data with the historical monitoring data, calculate the error range between the predicted value and the measured value, and generate error distribution data; The probability of deformation prediction is statistically calculated based on the error distribution data, and the credibility levels of the prediction results are divided to form a prediction credibility evaluation result.

6. The bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM according to claim 1 is characterized in that: Based on the deformation prediction data, the deformation process of the bridge foundation is displayed in the BIM model, and dynamic switching display of multiple perspectives is realized to form real-time rendering deformation effect data, including: The deformation prediction data is converted into deformation node data according to the spatial coordinate system, a corresponding relationship between the deformation amount and the BIM component is established, and component deformation data is generated; Setting three reference viewing angles of the front view, the side view and the top view for the component deformation data, calculating the rotation matrix of the viewing angle conversion, and forming viewing angle parameter data; Convert the viewing angle parameter data into an observation point coordinate system, divide the observation distances into three: near view, middle view and far view, and output the viewpoint transformation data; Based on the viewpoint transformation data, the rendering priorities under different viewing angles are established, the component occlusion relationship and display order are calculated, and the view rendering data is generated; The view rendering data is updated in real time, and the displacement of the component is calculated according to the deformation development process to form a dynamic display sequence; The dynamic display sequence is combined with rendering engine parameters, and lighting, material and shadow effects are integrated to output the real-time rendered deformation effect data.

7. The bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM according to claim 1 is characterized in that: The method of analyzing the correlation between rotary drilling parameters and deformation based on the deformation effect data and combining with the historical case library, optimizing the rotary drilling construction parameters, and outputting the construction control plan includes: Classify and mark the deformation effect data according to geological conditions, pile diameter, pile length, and deformation range, establish data retrieval standards, and generate feature index data; Based on the feature index data, similar working condition information is extracted from the historical case library, and the corresponding relationship between the rotary drilling parameters and the deformation amount is counted to form parameter mapping data; Perform multi-dimensional analysis on the parameter mapping data, calculate the correlation coefficients among the rotation speed, downforce, lifting speed and deformation, and output parameter correlation data; Convert the parameter correlation data into construction condition constraints, determine the safety threshold range of each parameter, and generate parameter control data; Based on the parameter control data, a construction process parameter optimization scheme is constructed, and a parameter adjustment strategy for each stage is set to form a segmented control sequence; The segmented control sequence is combined with geological stratification information to formulate drilling parameters and protective measures for different soil layers and generate the construction control plan.

8. A bridge foundation deformation analysis system for bridge foundation rotary drilling pile construction based on BIM, used to implement the bridge foundation deformation analysis method for bridge foundation rotary drilling pile construction based on BIM as described in any one of claims 1 to 7, characterized in that: The bridge foundation deformation analysis system for bridge foundation rotary excavation pile construction based on BIM includes: A scanning module is used to perform three-dimensional scanning modeling on the construction site, establish a BIM model containing geological information and pile foundation characteristics, set monitoring benchmark points in the BIM model, and obtain monitoring benchmark data; A processing module, used to deploy multi-source sensors according to the positions of the monitoring reference points, perform edge processing on the collected raw data to form an effective monitoring data set, and establish a corresponding relationship between the effective monitoring data set and the BIM model; An analysis module is used to extract deformation characteristic parameters during the construction of rotary piles based on the effective monitoring data set, build a deformation propagation model in combination with soil stress transfer path analysis, and output standardized characteristic data; Establishing a module for performing spatiotemporal correlation analysis on the standardized characteristic data, establishing a mapping relationship between rotary drilling construction parameters and bridge foundation deformation, generating deformation prediction data, and conducting credibility assessment on the prediction results; A display module is used to display the deformation process of the bridge foundation in the BIM model based on the deformation prediction data, realize dynamic switching display of multiple perspectives, and form real-time rendering deformation effect data; The output module is used to analyze the correlation between rotary drilling parameters and deformation according to the deformation effect data and in combination with the historical case library, optimize the rotary drilling construction parameters, and output the construction control plan.

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