Automatic arrangement method and device for steel pipe pile foundation

Abstract

The present invention relates to the field of building construction and discloses a method and device for automatically arranging steel pipe pile foundations. The method comprises: collecting construction site data to form a site information database, the data including topographic maps, geological reports, and site dimensions; dividing the site into regions according to pile foundation arrangement requirements and identifying factors influencing the arrangement of each region; planning the pile foundation arrangement based on these factors to obtain an arrangement reference target; setting key influencing factors, identifying historical construction site information, and obtaining a historical reference arrangement through data analysis; and combining the arrangement reference target and the historical reference arrangement to determine a predicted pile foundation arrangement target. The present invention can control deviations in areas with greater engineering volume flexibility, optimize arrangement plans, and improve construction efficiency and accuracy.

Description

Technical Field

[0001] The present invention relates to the field of building construction, and in particular to a method and device for automatically arranging steel pipe pile foundations. Background Art

[0002] In modern engineering construction, steel pipe pile foundations are essential foundational components, and their layout and design play a crucial role in the stability and durability of the project. Traditional steel pipe pile foundation layout methods rely primarily on the experience and expertise of engineers, who manually analyze project requirements, site conditions, and potential risks to plan the pile foundation layout. However, as engineering projects expand in scale and complexity, this manual approach suffers from inefficiency, subjectivity, and limitations, making it difficult to meet the high efficiency and precision requirements of modern engineering.

[0003] In the process of implementing the embodiments of the present invention, the inventors found that there are at least the following problems or defects in the prior art: the traditional layout method cannot quickly adapt to the complex and changeable construction site conditions, lacks effective use of historical construction data, and is insufficient in automation and intelligence, resulting in the inability to achieve automation and optimization of steel pipe pile foundation layout. Summary of the Invention

[0004] The embodiments of the present invention aim to provide a method and device for automatically arranging steel pipe pile foundations to solve the technical problems raised in the prior art.

[0005] The embodiments of the present invention solve the technical problems by adopting the following technical solutions:

[0006] In a first aspect, a method for automatically arranging a steel pipe pile foundation is provided, comprising:

[0007] Collecting construction site data to form a site information database, wherein the construction site data includes a topographic map, a geological report, and corresponding site dimension data;

[0008] Divide the construction site into zones according to the arrangement requirements of the steel pipe pile foundation, and identify factors affecting the arrangement of the steel pipe pile foundation for different zones of the construction site;

[0009] Planning the arrangement of the steel pipe pile foundation based on the influencing factors of the steel pipe pile foundation arrangement to obtain an arrangement reference target;

[0010] Setting key influencing factors for sites of the same type based on the influencing factors of the steel pipe pile foundation arrangement, identifying historical construction site information of the same type based on the key influencing factors, and then obtaining historical reference arrangements of steel pipe pile foundations for the same type of historical construction sites through data analysis;

[0011] And determining a steel pipe pile foundation arrangement prediction target according to the arrangement reference target and the historical reference arrangement of the steel pipe pile foundation.

[0012] Furthermore, after determining the steel pipe pile foundation arrangement prediction target, the method further includes:

[0013] Combined with regional decomposition, the steel pipe pile foundation design layout of different regions is compared with the predicted target of the steel pipe pile foundation layout to determine their deviations and impact ratios, and regions with greater engineering volume flexibility are adjusted first to control the deviations within a pre-set error range;

[0014] The automatic arrangement method of steel pipe pile foundation is used to predict the design arrangement of steel pipe pile foundations in different types of construction sites.

[0015] Furthermore, according to the arrangement requirements of the steel pipe pile foundation, the construction site is divided into regions, and the factors affecting the arrangement of the steel pipe pile foundation are identified for different regions of the construction site, including:

[0016] Determining the layout requirements of the construction site according to the topographic map;

[0017] Decomposing the civil engineering portion of the construction site into a pile foundation area, a bearing platform area, a superstructure area, and ancillary facilities area according to the layout requirements of the construction site;

[0018] And identify the influencing factors of the steel pipe pile foundation layout in the pile foundation area, pedestal area, superstructure area and ancillary facilities area of ​​the construction site, including geographical location, topography, environment, wind speed, temperature, geology, pile diameter, pile length, pile spacing, pedestal size, superstructure load, and ancillary facilities requirements.

[0019] Furthermore, the layout of the steel pipe pile foundation is planned based on the factors affecting the layout of the steel pipe pile foundation, and the layout reference targets include:

[0020] Separately planning the steel pipe pile foundation layout of the pile foundation area, the platform area, the superstructure area, and the ancillary facilities area of ​​the construction site to obtain the steel pipe pile foundation layout in different areas;

[0021] The steel pipe pile foundation arrangements in the different areas are superimposed to obtain the total steel pipe pile foundation arrangement of the construction site as the arrangement reference target.

[0022] Furthermore, identifying historical construction site information of the same type based on the key influencing factors includes:

[0023] Based on the key influencing factors, all sample data are searched and K-means clustering algorithm is applied to find the objective function.

[0024]

[0025] The minimum number of clusters k and the corresponding cluster center μ i . Among them, x represents sample data, C i represents the i-th cluster, μ i Represents the i-th cluster center, J represents the objective function, whose value is the sum of the squares of the distances from each sample data to the cluster center to which it belongs.

[0026] Furthermore, the final determination of the categories of the sample data and the centers of each category according to the K-means clustering algorithm further includes:

[0027] Given the number of cluster categories k, initialize the cluster center μ i , assign the sample data to the category to which the nearest cluster center belongs, recalculate the cluster center, and repeat the above steps until the cluster center no longer changes.

[0028] Furthermore, historical reference arrangements of steel pipe pile foundations at historical construction sites of the same type were obtained through data analysis, including:

[0029] Calculate the median, upper quartile, lower quartile, maximum value, minimum value, sample mean and sample variance of sample data;

[0030] A box plot is used to remove outliers to perform an outlier analysis on the sample data, wherein the outlier is not less than the lower quartile QL minus 1.5 times the interquartile range QIQR and greater than the upper quartile QU plus 1.5 times the interquartile range QIQR;

[0031] According to the 3σ principle, at least 99.7% of the statistics fall within the interval middle;

[0032]

[0033] Wherein, μ is the average value of the sample data, is the standard deviation of the sample data; the reasonable interval of the steel pipe pile foundation arrangement is finally obtained as

[0034] μ-k1σ≤x≤μ+k1σ

[0035] The historical reference layout of steel pipe pile foundations at the same type of historical construction site is calculated using the following formula

[0036] CKLP:CKLP=μ

[0037] Among them, μ represents the mean of the sample data, k1 is the coefficient, and σ is the standard deviation of the sample data.

[0038] Furthermore, determining a predicted target for steel pipe pile foundation arrangement based on the arrangement reference target and the historical reference arrangement of the steel pipe pile foundation includes:

[0039] The steel pipe pile foundation layout prediction target is determined by the following formula:

[0040] PG=(μ+CKYC) / 2

[0041] Wherein, PG is the predicted target of the construction site, CKYC is the layout reference target constructed in combination with influencing factors, and μ represents the average value of the sample data.

[0042] Furthermore, planning the arrangement of the steel pipe pile foundation based on the influencing factors of the arrangement of the steel pipe pile foundation to obtain an arrangement reference target includes: planning the arrangement of the steel pipe pile foundation based on the influencing factors of the arrangement of the steel pipe pile foundation using a neural network-based model to obtain an arrangement reference target, wherein the neural network model processes the input data through the connection and activation function of neurons, and the output is the processed result.

[0043] In a second aspect of the present invention, there is provided an automatic arrangement device for steel pipe pile foundations, comprising:

[0044] A data acquisition module, configured to collect construction site data to form a site information database, wherein the construction site data includes topographic maps, geological reports, and corresponding site dimension data;

[0045] An influencing factor identification module is used to divide the construction site into regions according to the office layout requirements of the steel pipe pile foundation, and identify the influencing factors of the steel pipe pile foundation layout in different areas of the construction site;

[0046] A target planning module plans the arrangement of the steel pipe pile foundation based on the influencing factors of the arrangement of the steel pipe pile foundation to obtain an arrangement reference target;

[0047] a historical layout acquisition module, configured to set key influencing factors for the same type of construction site based on the influencing factors of the steel pipe pile foundation layout, identify historical construction site information of the same type based on the key influencing factors, and then obtain a historical reference layout of the steel pipe pile foundation for the same type of historical construction site through data analysis;

[0048] and a prediction target acquisition module, which is used to determine the steel pipe pile foundation arrangement prediction target based on the arrangement reference target and the historical reference arrangement of the steel pipe pile foundation.

[0049] The above-mentioned embodiments of the present invention have at least the following beneficial effects: the automatic arrangement method of steel pipe pile foundations described in the present invention collects detailed data of the construction site and forms a site information database, divides the construction site into regions based on the arrangement requirements of the steel pipe pile foundation, and identifies the factors affecting the arrangement of the pile foundation in each region. By comprehensively considering these factors, the method can scientifically plan the arrangement of the steel pipe pile foundation and obtain a more reasonable arrangement reference target. In addition, the method can also analyze historical construction site data, extract key influencing factors, and use data analysis to obtain historical reference arrangements, thereby providing a more accurate arrangement prediction target for the new construction site. The application of this method can significantly improve the efficiency and accuracy of pile foundation arrangement, reduce engineering costs and construction time.

[0050] Furthermore, this automated steel pipe pile foundation layout method, by combining regional decomposition with historical data, can compare the designed layout of steel pipe pile foundations in different regions with the predicted target, determine deviations and impact ratios, and prioritize adjustments to areas with greater engineering flexibility to keep deviations within a preset error range. This method can optimize construction plans, reduce resource waste, and improve project safety and reliability. Furthermore, the method can be extended to different types of construction sites, enhancing the versatility and adaptability of layout plans and providing an innovative automated solution for the construction industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] One or more embodiments are exemplarily illustrated by the figures in the corresponding drawings. These exemplifications do not constitute limitations on the embodiments. Elements with the same reference numerals in the drawings are represented as similar elements. Unless otherwise stated, the figures in the drawings do not constitute proportional limitations.

[0052] Figure 1 1 is a flow chart of a method for automatically arranging steel pipe pile foundations according to an embodiment of the present invention;

[0053] Figure 2 A schematic structural diagram of an automatic arrangement device for steel pipe pile foundations according to an embodiment of the present invention;

[0054] Figure 3 The figure schematically shows the structure of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0055] For ease of understanding of the present invention, the present invention will be described in more detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that when an element is described as "connected" to another element, it can be directly on another element, or there can be one or more centered elements therebetween. The orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", "upper end", "lower end", "top" and "bottom" used in this specification is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0056] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0057] The following combination Figure 1 , the automatic arrangement method 100 of the steel pipe pile foundation provided in the embodiment of the present application is described in detail through specific examples.

[0058] Figure 1 The figure is a flow chart of the automatic arrangement method of steel pipe pile foundation provided by the present invention. The automatic arrangement method of steel pipe pile foundation provided by one embodiment of the present invention includes:

[0059] Step 101: collecting construction site data to form a site information database, wherein the construction site data includes a topographic map, a geological report, and corresponding site dimension data;

[0060] Step 102: Divide the construction site into regions according to the arrangement requirements of the steel pipe pile foundation, and identify factors affecting the arrangement of the steel pipe pile foundation for different regions of the construction site;

[0061] Step 103, planning the arrangement of the steel pipe pile foundation based on the influencing factors of the arrangement of the steel pipe pile foundation to obtain an arrangement reference target;

[0062] Step 104: setting key influencing factors for sites of the same type based on the influencing factors of the steel pipe pile foundation arrangement, identifying historical construction site information of the same type based on the key influencing factors, and then obtaining historical reference arrangements of steel pipe pile foundations for the same type of historical construction sites through data analysis;

[0063] Step 105 , determining a predicted target for steel pipe pile foundation arrangement based on the arrangement reference target and the historical reference arrangement of the steel pipe pile foundation.

[0064] It's important to note that this automated layout method first involves collecting construction site data to form a site information database. This means systematically organizing and recording the details of the construction site. Here, construction site data refers to all relevant information about the construction site, including but not limited to topographic maps, geological reports, and corresponding site dimensions. The site information database is a system that stores this data, either electronically or in paper format, to facilitate query and analysis.

[0065] Specifically, construction site data can be collected through a variety of methods, such as field surveys, satellite remote sensing, and historical data inquiries. Topographic maps show the contours of the ground, while geological reports provide detailed analysis of subsurface conditions such as soil composition and rock structure. Site dimensional data refers to specific measurements such as the length, width, and height of the construction area. This data is then entered into a site information database, which can be a cloud-based storage system or a local server. The key is to ensure secure and efficient data access.

[0066] The site information database should preferably be managed using a Structured Query Language (SQL) database management system to facilitate complex queries and data analysis. In practice, a Geographic Information System (GIS) can be used to store and analyze topographic maps and site dimension data, while geological reports can be converted into records in the database to extract geological characteristics of a specific area. Furthermore, the database can include additional information on local climate, hydrology, and other factors, which are also crucial for the placement of steel pipe pile foundations.

[0067] In some embodiments, after determining the steel pipe pile foundation arrangement prediction target, the method further includes:

[0068] Combined with regional decomposition, the steel pipe pile foundation design layout of different regions is compared with the predicted target of the steel pipe pile foundation layout to determine their deviations and impact ratios, and regions with greater engineering volume flexibility are adjusted first to control the deviations within a pre-set error range;

[0069] The automatic arrangement method of steel pipe pile foundation is used to predict the design arrangement of steel pipe pile foundations in different types of construction sites.

[0070] It should be noted that after determining the predicted target for steel pipe pile foundation layout, this embodiment further includes a step of comparing the steel pipe pile foundation design layouts for different regions with the predicted target using regional decomposition. Regional decomposition refers to dividing the construction site into several regions so that the pile foundation design layout for each region can be analyzed and adjusted separately. The predicted target for the layout is the expected target for the pile foundation layout for the entire construction site, derived from the previous steps.

[0071] Specifically, regional decomposition can be performed based on the construction site's topography, geological conditions, and specific project requirements. For example, a topographic map can be used to divide the site into flat areas, sloped areas, and water areas, with each area receiving a different pile foundation design layout tailored to its specific characteristics. During the comparison process, key parameters such as pile spacing, depth, and diameter can be set to assess whether the design layouts for different areas meet the predicted objectives. Environmental factors, construction costs, and deadlines can also be considered.

[0072] The comparison process can also include an assessment of deviations and impact ratios. This means that for each area's pile foundation layout, we not only compare its deviation from the predicted target but also assess the impact of this deviation on the overall project. For example, areas with greater project volume flexibility, such as ancillary facilities, can be prioritized for adjustments to ensure that the overall pile foundation layout remains within a pre-set tolerance.

[0073] Furthermore, in actual operation, statistical methods or machine learning models can be used to predict and evaluate these parameters, enabling more precise control and adjustment. Furthermore, simulation software can be used to simulate the pile foundation design layout in different areas to verify its consistency with the predicted targets and optimize accordingly.

[0074] In some embodiments, the construction site is divided into regions according to the arrangement requirements of the steel pipe pile foundation, and factors affecting the arrangement of the steel pipe pile foundation are identified for different regions of the construction site, including:

[0075] Determining the layout requirements of the construction site according to the topographic map;

[0076] Decomposing the civil engineering portion of the construction site into a pile foundation area, a bearing platform area, a superstructure area, and ancillary facilities area according to the layout requirements of the construction site;

[0077] And identify the influencing factors of the steel pipe pile foundation layout in the pile foundation area, pedestal area, superstructure area and ancillary facilities area of ​​the construction site, including geographical location, topography, environment, wind speed, temperature, geology, pile diameter, pile length, pile spacing, pedestal size, superstructure load, and ancillary facilities requirements.

[0078] It's important to note that the construction site is divided into zones based on pile foundation layout requirements, and factors influencing steel pipe pile foundation layout are identified for each zone. Zone division refers to dividing the site into several areas based on specific conditions, such as topography and geology, to facilitate more targeted pile foundation layout. Influencing factors encompass all natural conditions and engineering parameters that may affect steel pipe pile foundation layout.

[0079] Specifically, regional divisions can be based on natural boundaries shown on topographic maps, such as rivers and hillsides, or on different geological structures mentioned in geological reports. Identified factors influencing the layout of steel pipe pile foundations may include geographic location, topography, environment, wind speed, temperature, geology, pile diameter, pile length, pile spacing, cap dimensions, superstructure loads, and ancillary facility requirements. These factors can be determined through site surveys, historical data, and expert experience, and specific parameter ranges must be established, such as pile diameter, pile depth, and pile spacing.

[0080] Preferably, different layout strategies can be adopted for each region based on its specific influencing factors. For example, in soft soil areas, the depth and number of piles may need to be increased to ensure stability, while in hard rock areas, the number of piles may need to be reduced to save costs.

[0081] Furthermore, a geographic information system (GIS) can be used to assist in identifying and analyzing these influencing factors, and through layer overlay analysis, the optimal regional division and pile foundation layout can be determined. In actual operation, these parameters can also be adjusted and optimized based on field test data to ensure that the steel pipe pile foundation layout is both scientific and economical.

[0082] In some embodiments, the steel pipe pile foundation arrangement is planned based on the factors affecting the arrangement of the steel pipe pile foundation, and the arrangement reference target is obtained, including:

[0083] Separately planning the steel pipe pile foundation layout of the pile foundation area, the platform area, the superstructure area, and the ancillary facilities area of ​​the construction site to obtain the steel pipe pile foundation layout in different areas;

[0084] The steel pipe pile foundation arrangements in the different areas are superimposed to obtain the total steel pipe pile foundation arrangement of the construction site as the arrangement reference target.

[0085] It's important to note that planning the steel pipe pile foundation layout based on factors influencing it yields a layout reference target. This means systematically planning the steel pipe pile foundation layout for each area based on the various factors previously identified, such as geographic location and topography. The layout reference target refers to a reference goal or standard developed based on these factors to guide actual construction.

[0086] Specifically, the planning process can include separate planning for the layout of steel pipe pile foundations in the pile foundation area, bearing area, superstructure area, and ancillary facilities area of ​​the construction site. This means that we need to develop a specific layout plan for each area, including the type, quantity, location, and depth of the piles. The setting of specific parameters will depend on the specific conditions of the site and the needs of the project. For example, the pile foundation area may require deeper and more dense pile foundations to support the weight of the structure; while the ancillary facilities area may need to consider the specific needs of the facilities to determine the layout of the pile foundation. Conceptually, the planning of these areas should take into account structural safety, cost-effectiveness, and construction feasibility.

[0087] Ideally, after the steel pipe pile foundation layouts for different areas are planned, they can be superimposed to obtain a master steel pipe pile foundation layout for the entire construction site, which serves as a reference for the layout. This superposition process can be assisted by specialized engineering software capable of processing large amounts of data and providing visual layout results. For example, Building Information Modeling (BIM) technology can be used to integrate the pile foundation layouts for each area and detect potential conflicts or optimize space.

[0088] Furthermore, the effectiveness of each area layout plan can be evaluated by simulating different construction scenarios, ensuring that the final layout reference target not only meets project requirements but is also practical. In some cases, the initial plan can be adjusted based on feedback during construction to adapt to changing site conditions.

[0089] In some embodiments, identifying historical construction site information of the same type based on the key influencing factors includes:

[0090] Based on the key influencing factors, all sample data are searched and K-means clustering algorithm is applied to find the objective function.

[0091]

[0092] The minimum number of clusters k and the corresponding cluster center μ i . Among them, x represents sample data, C i represents the i-th cluster, μ i Represents the i-th cluster center, J represents the objective function, whose value is the sum of the squares of the distances from each sample data to the cluster center to which it belongs.

[0093] It's important to note that identifying historical construction site information of the same type based on key influencing factors refers to using identified key factors, such as geographic location and geological conditions, to search historical databases for projects similar to the current construction site. Key influencing factors, as used here, are those that significantly impact the placement of steel pipe pile foundations; identifying them can help us find similar historical cases. Historical construction site information refers to data records from past projects, which can be used to assist in planning and decision-making for current projects.

[0094] Specifically, the identification process can be performed by comparing construction site data stored in a historical database with the key influencing factors of the current project. For example, if the geological conditions of the current project are the primary key influencing factor, parameters can be set to filter out historical projects with similar geological conditions. This may involve a detailed analysis of geological reports and matching geological parameters recorded in historical projects. It can also include analyzing parameters such as pile diameter and length used in historical projects to identify cases that are most similar to the current project.

[0095] Preferably, the identification process based on key influencing factors can be automated using data mining and machine learning techniques. For example, a K-means clustering algorithm can be applied to classify historical data to find historical construction sites that best match the current project conditions.

[0096] Furthermore, during implementation, algorithm parameters, such as the number of clusters and the distance metric, can be adjusted to optimize clustering results. Alternatively, other clustering algorithms, such as hierarchical clustering or DBSCAN, can be considered to improve clustering effectiveness and accuracy. In practice, expert experience and statistical analysis can be combined to validate clustering results and adjust algorithm parameters accordingly.

[0097] In some embodiments, finally determining the categories of sample data and the centers of each category according to the K-means clustering algorithm further includes:

[0098] Given the number of cluster categories k, initialize the cluster center μ i , assign the sample data to the category to which the nearest cluster center belongs, recalculate the cluster center, and repeat the above steps until the cluster center no longer changes.

[0099] It should be noted that the K-means clustering algorithm is used to ultimately determine the sample data categories and the centers of each category. This refers to using the K-means clustering algorithm to classify the sample data and determine the center point of each category, or cluster center. Here, the K-means clustering algorithm is an algorithm that divides data points into K clusters, making the points within a cluster as similar as possible and the points between clusters as different as possible. The sample data refers to data collected from historical construction site information and is used to train and apply the clustering algorithm.

[0100] Specifically, when implementing the K-means clustering algorithm, the number of cluster categories, K, must first be specified. This parameter can be set based on the specific problem and data characteristics. Cluster centers can be initialized by randomly selecting K sample points as initial cluster centers, or by using more advanced initialization methods such as k-means++ to improve clustering quality and stability. Next, each sample data point is assigned to the category to which the nearest cluster center belongs, and the cluster center for each category is recalculated. This process is repeated until the cluster center no longer changes or the preset number of iterations is reached.

[0101] Preferably, optimization measures can be incorporated into the clustering algorithm to improve efficiency and effectiveness. For example, a threshold can be set to determine whether the change in cluster center is sufficiently small, thereby deciding whether to stop iteration. In addition, to avoid local optimal solutions, multiple initializations and selecting the best result can be used.

[0102] More specifically, the elbow rule can be used to determine the optimal number of cluster categories, K. This involves observing how the sum of squared errors (SSE) within clusters changes as K increases to select a suitable value. In practice, clustering algorithm parameters and processes can be adjusted based on business knowledge and the opinions of domain experts to achieve clustering results that better meet practical needs.

[0103] In some embodiments, obtaining a historical reference arrangement of steel pipe pile foundations of the same type of historical construction sites through data analysis includes:

[0104] Calculate the median, upper quartile, lower quartile, maximum value, minimum value, sample mean and sample variance of sample data;

[0105] A box plot is used to remove outliers to perform an outlier analysis on the sample data, wherein the outlier is not less than the lower quartile QL minus 1.5 times the interquartile range QIQR and greater than the upper quartile QU plus 1.5 times the interquartile range QIQR;

[0106] According to the 3σ principle, at least 99.7% of the statistics fall within the interval middle;

[0107]

[0108] Wherein, μ is the average value of the sample data, is the standard deviation of the sample data; the reasonable interval of the steel pipe pile foundation arrangement is finally obtained as

[0109] μ-k1σ≤x≤μ+k1σ

[0110] The historical reference layout of steel pipe pile foundations at the same type of historical construction site is calculated using the following formula

[0111] CKLP:CKLP=μ

[0112] Among them, μ represents the mean of the sample data, k1 is the coefficient, and σ is the standard deviation of the sample data.

[0113] It's important to note that historical reference layouts for steel pipe pile foundations at similar historical construction sites are obtained through data analysis. This means using statistical and data analysis techniques to process historical data to extract valuable steel pipe pile foundation layout information for current projects. Data analysis refers to the process of processing and interpreting data using mathematical and computer techniques, while historical reference layouts refer to layout plans derived from historical data that can serve as reference.

[0114] Specifically, the data analysis process involves calculating statistics such as the median, upper quartile, lower quartile, maximum, minimum, sample mean, and sample variance of the sample data. These statistics can help us understand the distribution and changing trends of the data. For example, the median is the value that divides a dataset into two equal parts, while the upper and lower quartiles represent the ranges of values ​​within which 75% and 25% of the data points in the dataset fall, respectively. The sample mean is the average of all data points, while the sample variance measures the dispersion of the data points relative to the mean. Furthermore, boxplots can be used to identify and remove outliers to ensure the accuracy of the analysis results.

[0115] Preferably, the data analysis process can also include further processing and verification of the data. For example, the 3σ principle can be used to determine the reasonable range of the data. This principle states that in the case of a normal distribution, approximately 99.7% of the data should fall within three standard deviations of the mean. Specifically, the reasonable range for the layout of steel pipe pile foundations can be calculated as the mean ± 3 standard deviations.

[0116] Furthermore, the historical reference layout can be obtained by calculating the mean and standard deviation of the sample data and then applying the following formula:

[0117] P=μ+ασ

[0118] Here, μ represents the mean of the sample data, σ represents the standard deviation of the sample data, and α is a coefficient that can be determined based on the specific requirements and risk appetite of the project. In practice, the value of coefficient α can also be adjusted based on expert experience and the success rate of historical cases to obtain a more accurate historical reference layout.

[0119] In some embodiments, determining a predicted target for steel pipe pile foundation arrangement based on the arrangement reference target and the historical reference arrangement of the steel pipe pile foundation includes:

[0120] The steel pipe pile foundation layout prediction target is determined by the following formula:

[0121] PG=(μ+CKYC) / 2

[0122] Wherein, PG is the predicted target of the construction site, CKYC is the layout reference target constructed in combination with influencing factors, and μ represents the average value of the sample data.

[0123] It should be noted that the predicted steel pipe pile foundation layout target is determined based on the layout reference target and the historical reference layout of steel pipe pile foundations. This refers to predicting the layout target of the current project's steel pipe pile foundation by combining the planning target of the current project (the layout reference target) with data from historical similar projects (the historical reference layout of steel pipe pile foundations). Here, the layout prediction target refers to the expected results of the steel pipe pile foundation layout predicted based on historical data and current project conditions.

[0124] Specifically, the predicted placement target is determined by calculating the average of the reference placement target and the historical reference placement, and then taking the midpoint of these two averages as the predicted target. In this process, the reference placement target is based on current project conditions, while the historical reference placement is derived from historical data analysis. For example, if the reference placement target is 100 piles and the historical reference placement is 120 piles, the predicted target could be the average of these two values, or 110 piles. This calculation process provides a data-based prediction for the placement of steel pipe pile foundations.

[0125] Preferably, the process of determining the predicted target for steel pipe pile foundation placement can also include calculating a weighted average. This means that different weights can be assigned to the reference placement target and the historical reference placement based on the specific conditions of the project. For example, if the geological conditions of the current project differ significantly from those of the historical project, the reference placement target can be given a higher weight.

[0126] More specifically, the following formula can be used to determine the prediction target for steel pipe pile foundation layout:

[0127]

[0128] Among them, PG is the predicted target of the construction site, CKYC is the layout reference target constructed by combining influencing factors, represents the average value of the sample data, and β is the weighting coefficient used to adjust the influence of the historical reference arrangement.

[0129] Furthermore, in practice, the value of β can be adjusted based on the project's risk assessment and cost budget to obtain a forecast target that better meets actual needs. Furthermore, more statistical methods, such as Monte Carlo simulation, can be introduced to account for uncertainty and variability, thereby obtaining a prediction interval rather than a single prediction value.

[0130] In some embodiments, planning the steel pipe pile foundation arrangement based on the influencing factors of the steel pipe pile foundation arrangement to obtain an arrangement reference target includes:

[0131] Based on the influencing factors of the steel pipe pile foundation arrangement, a neural network-based model is used to plan the steel pipe pile foundation arrangement to obtain an arrangement reference target, wherein the neural network model processes input data through neuron connections and activation functions, and outputs the processed result.

[0132] It should be noted that planning the steel pipe pile foundation layout based on factors influencing its placement and obtaining a reference layout target involves employing a neural network model. A neural network model, as used here, mimics the connections and information processing of neurons in the human brain. It predicts or determines the reference layout target by learning the relationship between input data and desired output. This model can handle complex nonlinear relationships and is therefore suitable for optimizing steel pipe pile foundation placement.

[0133] Specifically, the construction of the neural network model involves determining the network structure, such as the number of layers, the number of neurons in each layer, and the selection of the activation function. The input data is the factors affecting the layout of the steel pipe pile foundation, and the output is the reference target for the planned layout.

[0134] More specifically, when training a neural network, you need to set certain parameters, such as the learning rate, batch size, and number of iterations, which affect the model's learning efficiency and ultimate performance. In addition, you need to choose a suitable loss function to evaluate the difference between the model's predictions and the actual placement targets, and adjust the model's weights and biases based on this loss function.

[0135] Preferably, the neural network model can be trained using various optimization algorithms, such as gradient descent and the Adam optimizer, to accelerate model convergence and improve accuracy. More specifically, regularization techniques, such as L1 or L2 regularization, can be used to prevent overfitting and ensure good generalization of the model to new construction site data.

[0136] Furthermore, in actual operations, you can also consider using transfer learning, that is, using a model pre-trained on similar tasks as a starting point and further fine-tuning it on the current specific task. This can reduce the demand for training data and speed up the training process.

[0137] Furthermore, different types of neural network architectures, such as convolutional neural networks (CNNs) or recurrent neural networks (RNNs), can be explored to select the most appropriate model structure based on the specific characteristics of the steel pipe pile foundation arrangement and data properties.

[0138] The above-described embodiments of the present invention have the following beneficial effects: The automatic steel pipe pile foundation layout method described in the present invention can significantly improve construction efficiency and accuracy. By comprehensively analyzing data such as the construction site's topographic map, geological report, and site dimensions, the method can identify key factors affecting the layout of steel pipe pile foundations and, based on this, conduct scientific regional division and planning, thereby obtaining a more reasonable layout reference target. The application of this method can not only reduce reliance on the engineer's personal experience and expertise, and reduce errors and deviations caused by human factors, but also improve design efficiency, shorten project cycles, reduce project costs, and enhance the safety and reliability of pile foundation projects.

[0139] Furthermore, the automated layout method can analyze historical construction data to extract key influencing factors and use these factors to predict and plan new construction sites. This approach can optimize construction plans, reduce resource waste, and improve project adaptability and flexibility. This method can predict the design and layout of steel pipe pile foundations for different types of construction sites, further improving the level of engineering intelligence and automation, and bringing revolutionary progress to the field of construction.

[0140] like Figure 2 As shown, some embodiments of an automatic arrangement device 200 for steel pipe pile foundations include:

[0141] The data acquisition module 201 is used to collect construction site data to form a site information database, wherein the construction site data includes topographic maps, geological reports and corresponding site dimension data;

[0142] An influencing factor identification module 202 is used to divide the construction site into regions according to the office layout requirements of the steel pipe pile foundation, and identify influencing factors of the steel pipe pile foundation layout for different regions of the construction site;

[0143] A target planning module 203 plans the arrangement of the steel pipe pile foundation based on the influencing factors of the arrangement of the steel pipe pile foundation to obtain an arrangement reference target;

[0144] A historical layout acquisition module 204 is configured to set key influencing factors for the same type of construction site based on the influencing factors of the steel pipe pile foundation layout, identify historical construction site information of the same type based on the key influencing factors, and then obtain a historical reference layout of the steel pipe pile foundation for the same type of historical construction site through data analysis;

[0145] And a prediction target acquisition module 205 is used to determine the steel pipe pile foundation arrangement prediction target based on the arrangement reference target and the steel pipe pile foundation historical reference arrangement.

[0146] It is understandable that the modules described in the steel pipe pile foundation automatic arrangement device 200 are similar to those described in the reference Figure 1 Therefore, the operations, features and beneficial effects described above for the automatic arrangement method of steel pipe pile foundations are also applicable to the automatic arrangement device 200 of steel pipe pile foundations and the modules contained therein, and will not be repeated here.

[0147] Reference below Figure 3 , which shows a schematic structural diagram of a structure 300 of an electronic device suitable for implementing some embodiments of the present invention. The electronic devices in some embodiments of the present invention may include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 3 The terminal device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0148] like Figure 3 As shown, the electronic device 300 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage device 308 into a random access memory (RAM) 303. Various programs and data required for the operation of the electronic device 300 are also stored in the RAM 303. The processing device 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0149] Typically, the following devices may be connected to the I / O interface 305: an input device 306 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 308 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 309. The communication device 309 may allow the electronic device 300 to communicate with other devices wirelessly or by wire to exchange data. Figure 3 The electronic device 300 is shown with various devices, but it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed instead. Figure 3 Each block shown in the figure may represent one device, or may represent multiple devices as needed.

[0150] Furthermore, the storage medium of the embodiment of the present application stores program instructions that can implement all the above methods, wherein the program instructions can be stored in the above storage medium in the form of a software product, including a number of instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or a terminal device such as a computer, a server, a mobile phone, or a tablet.

[0151] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Under the idea of ​​the present invention, the technical features in the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of different aspects of the present invention as above, which are not provided in detail for the sake of simplicity. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in this field should understand that they can still modify the technical solutions described in the above 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 scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for automatically arranging steel pipe pile foundations, characterized in that: include: Collecting construction site data to form a site information database, wherein the construction site data includes a topographic map, a geological report, and corresponding site dimension data; Divide the construction site into zones according to the arrangement requirements of the steel pipe pile foundation, and identify factors affecting the arrangement of the steel pipe pile foundation for different zones of the construction site; Planning the arrangement of the steel pipe pile foundation based on the influencing factors of the steel pipe pile foundation arrangement to obtain an arrangement reference target; Setting key influencing factors for sites of the same type based on the influencing factors of the steel pipe pile foundation arrangement, identifying historical construction site information of the same type based on the key influencing factors, and then obtaining historical reference arrangements of steel pipe pile foundations for the same type of historical construction sites through data analysis; and determining a steel pipe pile foundation arrangement prediction target based on the arrangement reference target and the steel pipe pile foundation historical reference arrangement; The construction site is divided into regions according to the arrangement requirements of the steel pipe pile foundation, and the factors affecting the arrangement of the steel pipe pile foundation are identified for different regions of the construction site, including: Determining the layout requirements of the construction site according to the topographic map; Decomposing the civil engineering portion of the construction site into a pile foundation area, a bearing platform area, a superstructure area, and ancillary facilities area according to the layout requirements of the construction site; and identifying factors influencing the arrangement of the steel pipe pile foundation in the pile foundation area, the cap area, the superstructure area, and the ancillary facilities area of ​​the construction site, wherein the factors influencing the arrangement of the steel pipe pile foundation include geographical location, topography, environment, wind speed, temperature, geology, pile diameter, pile length, pile spacing, cap size, superstructure load, and ancillary facilities requirements; The layout of the steel pipe pile foundation is planned based on the factors affecting the layout of the steel pipe pile foundation, and the layout reference targets include: Separately planning the steel pipe pile foundation layout of the pile foundation area, the platform area, the superstructure area, and the ancillary facilities area of ​​the construction site to obtain the steel pipe pile foundation layout in different areas; The steel pipe pile foundation arrangements in the different areas are superimposed to obtain the total steel pipe pile foundation arrangement of the construction site as the arrangement reference target.

2. The automatic arrangement method of steel pipe pile foundation according to claim 1, characterized in that: After determining the steel pipe pile foundation layout prediction target, it further includes: Combined with regional decomposition, the steel pipe pile foundation design layout of different regions is compared with the predicted target of the steel pipe pile foundation layout to determine their deviations and impact ratios, and regions with greater engineering volume flexibility are adjusted first to control the deviations within a pre-set error range; The automatic arrangement method of steel pipe pile foundation is used to predict the design arrangement of steel pipe pile foundations in different types of construction sites.

3. The automatic arrangement method of steel pipe pile foundation according to claim 2, characterized in that: Identifying historical construction site information of the same type based on the key influencing factors includes: Based on the key influencing factors, all sample data are searched and the K-means clustering algorithm is applied to find the number of clusters that minimizes the objective function. And the corresponding cluster centers ; in, represents sample data, Indicates the clusters, Indicates the Cluster centers, Represents the objective function, whose value is the sum of the squares of the distances from each sample data to the cluster center to which it belongs.

4. The automatic arrangement method of steel pipe pile foundation according to claim 3, characterized in that: The final determination of the categories of sample data and the centers of each category based on the K-means clustering algorithm further includes: Given the number of cluster categories , initialize the cluster center , assign the sample data to the category to which the nearest cluster center belongs, recalculate the cluster center, and repeat the above steps until the cluster center no longer changes.

5. The automatic arrangement method of steel pipe pile foundation according to claim 1, characterized in that: The historical reference layout of steel pipe pile foundations of the same type of historical construction sites obtained through data analysis includes: Calculate the median, upper quartile, lower quartile, maximum value, minimum value, sample mean and sample variance of sample data; A box plot is used to remove outliers to perform an outlier analysis on the sample data, wherein the outlier is not less than the lower quartile QL minus 1.5 times the interquartile range QIQR and greater than the upper quartile QU plus 1.5 times the interquartile range QIQR; According to 3 In principle, at least 99.7% of the statistics fall within the range middle; in, is the average value of the sample data, is the standard deviation of the sample data; the reasonable interval of the steel pipe pile foundation arrangement is finally obtained as: The historical reference layout of steel pipe pile foundations for the same type of historical construction sites is calculated using the following formula: in, represents the mean value of the sample data, is the coefficient, is the standard deviation of the sample data.

6. The automatic arrangement method of steel pipe pile foundation according to claim 5, characterized in that: Determining a predicted target for steel pipe pile foundation arrangement based on the arrangement reference target and the historical reference arrangement of the steel pipe pile foundation includes: The steel pipe pile foundation layout prediction target is determined by the following formula: Among them, PG is the predicted target of the construction site, CKYC is the layout reference target constructed in combination with influencing factors, Represents the mean of the sample data.

7. The automatic arrangement method of steel pipe pile foundation according to claim 1, characterized in that: Planning the arrangement of the steel pipe pile foundation based on the influencing factors of the steel pipe pile foundation arrangement to obtain an arrangement reference target includes: planning the arrangement of the steel pipe pile foundation based on the influencing factors of the steel pipe pile foundation arrangement using a neural network-based model to obtain an arrangement reference target, wherein the neural network model processes input data through neuron connections and activation functions, and outputs the processed result.

8. An automatic arrangement device for steel pipe pile foundation, characterized in that: include: A data acquisition module, configured to collect construction site data to form a site information database, wherein the construction site data includes topographic maps, geological reports, and corresponding site dimension data; The influencing factor identification module is used to divide the construction site into areas according to the office layout requirements of the steel pipe pile foundation, and identify the influencing factors of the steel pipe pile foundation layout in different areas of the construction site, including: Determining the layout requirements of the construction site according to the topographic map; Decomposing the civil engineering portion of the construction site into a pile foundation area, a bearing platform area, a superstructure area, and ancillary facilities area according to the layout requirements of the construction site; and identifying factors influencing the arrangement of the steel pipe pile foundation in the pile foundation area, the cap area, the superstructure area, and the ancillary facilities area of ​​the construction site, wherein the factors influencing the arrangement of the steel pipe pile foundation include geographical location, topography, environment, wind speed, temperature, geology, pile diameter, pile length, pile spacing, cap size, superstructure load, and ancillary facilities requirements; The target planning module plans the arrangement of the steel pipe pile foundation based on the influencing factors of the steel pipe pile foundation arrangement to obtain an arrangement reference target, including: Separately planning the steel pipe pile foundation layout of the pile foundation area, the platform area, the superstructure area, and the ancillary facilities area of ​​the construction site to obtain the steel pipe pile foundation layout in different areas; and superimposing the steel pipe pile foundation arrangements in the different areas to obtain a total steel pipe pile foundation arrangement of the construction site as the arrangement reference target; a historical layout acquisition module, configured to set key influencing factors for the same type of construction site based on the influencing factors of the steel pipe pile foundation layout, identify historical construction site information of the same type based on the key influencing factors, and then obtain a historical reference layout of the steel pipe pile foundation for the same type of historical construction site through data analysis; and a prediction target acquisition module, which is used to determine the steel pipe pile foundation arrangement prediction target based on the arrangement reference target and the steel pipe pile foundation historical reference arrangement.

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