Civil engineering early warning method and system based on data analysis

Abstract

The invention discloses a civil engineering early warning method and system based on data analysis, and relates to the technical field of civil engineering management. Comprising the steps of constructing a three-dimensional virtual project based on project design data, performing progress deduction mapping in combination with project promotion arrangement, and generating a deduction expression sequence changing along with time; scanning a field project by using an unmanned aerial vehicle, recording propulsion conditions of different position nodes, and forming a field scanning record sequence; mapping to a preset tree model based on the engineering propulsion record information, and constructing a tree model representation sequence; aligning the three-dimensional virtual engineering deduction sequence, the field scanning record sequence and the tree model expression state sequence, analyzing latest time section data, and performing real-time expression mapping on the three-dimensional virtual engineering; comparing the real-time performance with the deduction performance, and determining that the project progress is abnormal; according to the invention, through multi-source data integration and dynamic analysis, accurate detection and early warning of progress deviation are realized, and civil engineering management efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of civil engineering management, and in particular to a civil engineering early warning method and system based on data analysis. Background Art

[0002] With the increasing scale and complexity of modern civil engineering projects, traditional engineering management methods have gradually exposed their shortcomings in progress monitoring, abnormal warning and resource optimization. As a systematic work involving multiple disciplines and multiple links, the smooth implementation of civil engineering not only depends on scientific design and reasonable planning, but also requires real-time supervision of progress, quality and safety during the construction process. However, in actual operation, traditional management methods usually rely on manual records, regular inspections and empirical judgments. This method is not only inefficient, but also easily affected by subjective factors, resulting in data update lags, error accumulation, and abnormal situations that are difficult to be discovered and handled in a timely manner. For example, deviations in project progress may be ignored due to the lack of real-time monitoring, and eventually evolve into construction delays or cost overruns, bringing irreversible negative impacts to the entire project. Therefore, how to achieve efficient, accurate and intelligent management of civil engineering progress has become one of the key issues that need to be urgently solved in the current engineering field.

[0003] Under the traditional management model, the data sources involved in civil engineering are diverse and scattered, including drawings and parameters in the design phase, field records in the construction phase, and promotion plans in the management phase. These data often exist in different formats, and the update frequency and collection methods are also different. For example, design data is usually stored in the form of static two-dimensional drawings or three-dimensional models, while the on-site construction conditions may be recorded through manual measurement or text reports, and the project promotion plan is presented in the form of a timetable or log. The characteristics of this multi-source heterogeneous data make it difficult for managers to integrate it into a unified analysis framework, which in turn limits the comprehensive grasp of the overall status of the project. In addition, traditional methods also have significant deficiencies in anomaly detection. Due to the lack of systematic data comparison and quantitative analysis methods, managers can often only judge whether the progress is normal through experience or sampling inspection, which is not only time-consuming and labor-intensive, but may also miss key issues due to limited detection coverage. Especially in large-scale civil engineering projects, there are many construction links and a wide range of areas involved, and abnormal situations are more concealed, which further increases the difficulty of manual management. Summary of the invention

[0004] The purpose of the present invention is to provide a civil engineering early warning method and system capable of accurately monitoring the progress of civil engineering projects.

[0005] The present invention discloses a civil engineering early warning method based on data analysis, comprising: Step S100, obtaining engineering design data, and constructing a three-dimensional virtual engineering based on the engineering design data, obtaining an engineering progress schedule, and based on the engineering progress schedule, performing a progress deduction and mapping of the three-dimensional virtual engineering to obtain a three-dimensional virtual engineering deduction and performance sequence that changes over time; Step S200, using a drone to scan the on-site project, determine the progress of the project at different location nodes, and record the corresponding time nodes in a relevant manner to form an on-site scanning record sequence; Step S300, obtaining the engineering progress record information, and mapping the engineering progress record information on the preset engineering progress tree model to obtain the tree model expression state of the engineering progress tree model, and constructing the tree model expression state into a tree model expression state sequence based on the time sequence relationship; Step S400, aligning the three-dimensional virtual engineering simulation sequence, the on-site scanning record sequence and the tree model representation state sequence in time, and analyzing the sequence units of the latest time segment in the on-site scanning record sequence and the tree model representation state respectively, and based on the analysis results, performing real-time representation mapping on the three-dimensional virtual engineering to obtain a real-time three-dimensional virtual engineering representation; Step S500, comparing the real-time three-dimensional virtual engineering performance with the corresponding three-dimensional virtual engineering simulation performance, and determining whether there is any abnormality in the civil engineering progress based on the comparison result.

[0006] In some embodiments disclosed in the present invention, a method for performing progress deduction and mapping on a three-dimensional virtual project includes: Step S101, gridding the three-dimensional virtual project, defining the advancement direction of the grid in the three-dimensional virtual project based on the project advancement arrangement, and performing deduction and mapping in a time advancement manner, including: Step S1011, establishing a first time schedule for the project advancement arrangement, and setting a number of time reference nodes for the first time schedule; Step S1012, based on the project advancement arrangement, determine the project conditions that need to be completed at different time reference nodes, and associate them with each other, and mark the ongoing grids in the three-dimensional virtual project in turn based on the project conditions corresponding to different first time reference nodes on the first time progress line; Step S1013, comparing the marked grid groups between adjacent first time reference nodes, and determining the grid group boundaries between the two, and determining the directions of the grid group boundaries between the two as the grid delineation advancement direction.

[0007] In some embodiments disclosed in the present invention, a method for mapping on a preset engineering advancement tree model based on engineering advancement record information includes: Step S301, constructing a second time progress line for the project progress record information, setting a number of second time reference nodes for the second time progress line, and setting a time reference interval for each second time reference node; Step S302, analyzing the time stamps of the record information monomers in the engineering progress record information, determining the time reference interval to which each record information monomer belongs, and combining the record information monomers according to the time reference interval to obtain a record information monomer group; Step S303: Analyze the record information monomers in each record information monomer group, determine the corresponding engineering sub-project work completion amount, and adjust the corresponding engineering sub-project nodes on the preset engineering advancement tree model.

[0008] In some embodiments disclosed in the present invention, the method for constructing an engineering advancement tree model includes: Step S304, based on the project advancement arrangement, determine the project sub-projects to be completed, and determine the order of each project sub-project and the parallel relationship; Step S305, construct an engineering project sub-node for each work sub-project, and connect the engineering sub-project nodes in sequence based on the sequence relationship of the engineering sub-projects. If there are engineering sub-project nodes that can be parallel to each other, the corresponding engineering sub-project nodes will be connected in parallel, wherein the length of the connection line between the engineering sub-project nodes is determined by the amount of work required to complete the engineering sub-project nodes.

[0009] In some embodiments disclosed in the present invention, a method for real-time performance mapping of a three-dimensional virtual project includes: Step S401, determining the field scanning record of the latest time segment in the field scanning record sequence, and determining the corresponding mapping block on the three-dimensional virtual project based on the scanning position block corresponding to the field scanning record, and adjusting the mapping block based on the shape characteristics of the scanning position block; Step S402, based on the project progress schedule, determine the project sub-projects to be completed, and divide the three-dimensional virtual project into sub-project three-dimensional blocks based on the corresponding part of each project sub-project in the project; Step S403, determining the tree model expression state of the latest time segment in the tree model expression state sequence, and adjusting the expression of the corresponding sub-project 3D block based on the completion feature of each engineering sub-project node in the tree model expression state.

[0010] In some embodiments disclosed in the present invention, a method for comparing a real-time 3D virtual engineering performance with a corresponding 3D virtual engineering simulation performance includes: Step S501, configuring weight coefficients for each sub-project 3D block in the 3D virtual engineering, and determining a first mapping volume of each sub-project 3D block in the real-time 3D virtual engineering performance, and a second mapping volume of each sub-project 3D block in the 3D virtual engineering deduction performance; Step S502, calculating the mapping volume difference between the second mapping volume and the first mapping volume corresponding to each sub-project 3D block, and determining the engineering progress difference characteristic parameter between the real-time 3D virtual engineering performance and the 3D virtual engineering simulation performance in combination with the weight coefficient corresponding to the sub-project 3D block; Step S503, calculating the sum of all first mapping volumes to obtain a first total mapping volume, calculating the sum of all second mapping volumes to obtain a second total mapping volume, and calculating a total mapping volume difference between the second total mapping volume and the first total mapping volume; Step S504, combining the total mapping volume difference and the engineering progress difference characteristic parameter, determines the abnormality degree of the real-time three-dimensional virtual engineering performance, and issues an early warning if the abnormality degree is greater than or equal to a preset value.

[0011] In some embodiments disclosed in the present invention, a method for using a drone to scan an on-site project and determine the progress of the project at different location nodes includes: Step S201, determining the key location nodes of the project, and planning the flight path of the UAV based on the key location nodes; Step S202, using drones to collect engineering progress status data at different key location nodes, including the geometric shape and identification of the engineering progress area.

[0012] In some embodiments disclosed in the present invention, a civil engineering early warning system based on data analysis is also disclosed, including: The first module is used to obtain engineering design data, build a three-dimensional virtual project based on the engineering design data, obtain the project progress schedule, and perform progress deduction and mapping on the three-dimensional virtual project based on the project progress schedule to obtain a three-dimensional virtual project deduction and performance sequence that changes over time; The second module is used to use drones to scan on-site projects, determine the progress of projects at different location nodes, and record the corresponding time nodes in a relevant manner to form a sequence of on-site scan records; The third module is used to obtain the engineering progress record information, and based on the engineering progress record information, map it on the preset engineering progress tree model to obtain the tree model expression state of the engineering progress tree model, and construct the tree model expression state into a tree model expression state sequence based on the time sequence relationship; The fourth module is used to align the three-dimensional virtual engineering simulation sequence, the on-site scanning record sequence and the tree model representation sequence in time, and analyze the sequence units of the latest time segment in the on-site scanning record sequence and the tree model representation respectively, and based on the analysis results, perform real-time representation mapping on the three-dimensional virtual engineering to obtain real-time three-dimensional virtual engineering representation; The fifth module is used to compare the real-time three-dimensional virtual engineering performance with the corresponding three-dimensional virtual engineering simulation performance, and based on the comparison results, determine whether there are any abnormalities in the progress of the civil engineering project.

[0013] The invention discloses a civil engineering early warning method and system based on data analysis, and relates to the technical field of civil engineering management; the method comprises: constructing a three-dimensional virtual engineering based on engineering design data, and performing progress deduction and mapping in combination with the engineering advancement arrangement, and generating a deduction performance sequence that changes with time; utilizing an unmanned aerial vehicle to scan the on-site engineering, and recording the advancement status of nodes at different positions, and forming an on-site scanning record sequence; mapping the engineering advancement record information to a preset tree model, and constructing a tree model performance state sequence; aligning the three-dimensional virtual engineering deduction sequence, the on-site scanning record sequence, and the tree model performance state sequence, analyzing the latest time segment data, and performing real-time performance mapping on the three-dimensional virtual engineering; comparing the real-time performance with the deduction performance, and determining the abnormality of the engineering progress; the invention realizes the accurate detection and early warning of progress deviation through multi-source data integration and dynamic analysis, and improves the efficiency of civil engineering management.

[0014] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A method step diagram of a civil engineering early warning method based on data analysis disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The technical solution of the present invention is further described below through the accompanying drawings and embodiments.

[0017] The following will be combined with the accompanying drawings and specific embodiments to clearly and completely describe the technical solution of the present invention. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention and cannot be understood as limiting the scope of protection of the present invention. Those skilled in the art in this field can make some non-essential improvements and adjustments based on the content of the present invention described below. In the present invention, unless otherwise clearly specified and limited, the technical terms used in the present invention should be the common meanings understood by the technical personnel described in the present invention.

[0018] Example: The present invention discloses a civil engineering early warning method based on data analysis, see Figure 1 ,include: Step S100, obtaining engineering design data, and constructing a three-dimensional virtual engineering based on the engineering design data, obtaining the engineering progress schedule, and based on the engineering progress schedule, performing progress deduction and mapping on the three-dimensional virtual engineering to obtain a three-dimensional virtual engineering deduction and performance sequence that changes over time.

[0019] The principle of step S100 is to convert the engineering design data into a three-dimensional virtual engineering model, and combine it with the engineering progress schedule to perform progress deduction mapping, so as to generate a time-varying deduction performance sequence, thereby providing an ideal benchmark reference for subsequent real-time monitoring and anomaly detection. Specifically, this step first obtains engineering design data (such as architectural drawings, structural parameters, etc.), and uses three-dimensional modeling technology to build a virtual engineering model. This model not only reflects the spatial structure of the project, but also provides a digital basis for dynamic simulation. Next, the project progress schedule (i.e., construction plan and schedule) is obtained, and the progress deduction mapping of the three-dimensional virtual project is performed based on this. The key to this process lies in the grid deduction method of sub-step S101: by dividing the three-dimensional virtual project into multiple grid units (S101), and setting the first time progress line and several time reference nodes (S1011) based on the project progress schedule, a structured framework is provided for deduction in the time dimension. Subsequently, according to the completion of the engineering tasks corresponding to different time reference nodes (S1012), the grid is delineated and marked in the direction of advancement, the grid state is gradually updated, and the advancement direction is determined by comparing the grid group boundaries of adjacent time nodes (S1013), forming a deduction performance sequence that evolves over time. This sequence is essentially a dynamic simulation of the ideal progress of the project, and each frame performance corresponds to the expected state at a time point. Combined with the overall technical solution, the role of step S100 is not only to build the initial model, but also to provide a comparison basis for subsequent steps: the output deduction performance sequence will be aligned with the on-site scanning record sequence and the tree model performance state sequence in step S400 for real-time mapping (S401-S403); in step S500, the deviation is quantified and the abnormality is judged by comparing with the real-time three-dimensional virtual engineering performance (S501-S504). In addition, the precision of gridded simulation provides support for the division of three-dimensional blocks of sub-projects (S402) and weight configuration (S501), and the setting of time reference nodes corresponds to the construction of the second time schedule line in step S300 (S301) in the time dimension. The whole process combines static design data with dynamic plans, and with the help of grid technology and time series analysis, realizes the digital transition from design to simulation, laying a theoretical and practical foundation for multi-source data integration and abnormal warning. Its core advantage lies in converting complex construction plans into visual and quantitative virtual expressions, providing a key first step for the intelligent management of civil engineering.

[0020] Step S200, using a drone to scan the on-site project, determine the progress of the project at different location nodes, and record the corresponding time nodes in a correlated manner to form an on-site scanning record sequence.

[0021] The principle of step S200 is to use drone technology to scan the civil engineering site efficiently and accurately, collect construction progress data of different position nodes, and generate a dynamic on-site scanning record sequence through time association, which provides a key basis for reflecting the actual situation for subsequent real-time mapping and anomaly detection. Specifically, this step uses the automated data collection capability of the drone to carry out scanning work on the key position nodes of the engineering site. First, determine the key position nodes of the project (such as main structural components, construction demarcation points, etc., step S201). These nodes are usually representative areas of engineering progress and directly affect the evaluation of the overall construction status. Based on these nodes, plan the flight path of the drone to ensure that the scan covers all key areas and avoid data omissions. The high-precision equipment (such as laser radar or high-resolution camera) carried by the drone can quickly obtain the advancement status data of the site, including the geometric shape of the construction area (such as boundaries, volume changes) and identification information (such as material stacking, equipment location, step S202). After collection, these data are recorded in association with the corresponding time nodes to form a sequence of on-site scanning records. This sequence not only captures the static state of the site at a certain moment, but also reflects the dynamic characteristics of the construction progress over time through continuous timestamps, providing real-time support for subsequent analysis. The core of the entire process is to convert the physical construction site into quantifiable digital information, overcoming the shortcomings of traditional manual measurement, which is low efficiency, strong subjectivity, and limited coverage.

[0022] Step S300, obtain the project progress record information, and based on the project progress record information, map it on the preset project progress tree model to obtain the tree model expression state of the project progress tree model, and based on the time sequence, construct the tree model expression state into a tree model expression state sequence.

[0023] The principle of step S300 is to obtain the project progress record information and map it to the preset project progress tree model to construct a structured expression state sequence to systematically reflect the dynamic changes of the actual construction progress and provide a logically clear analysis basis for subsequent real-time mapping and anomaly detection. Specifically, this step first obtains the project progress record information (such as construction logs, task completion reports, etc.), which usually contain the implementation details and time stamps of the project sub-projects. Then, based on these record information, a second time progress line is constructed, and several second time reference nodes are set, each of which is associated with a time reference interval (step S301), providing a framework for the temporal classification of data. By analyzing the timestamp of each record information monomer (step S302), it is classified into the corresponding time reference interval to form a record information monomer group, and then the monomers in each group are analyzed to extract the corresponding project sub-project work completion amount (step S303), and the corresponding sub-project node state in the preset tree model is adjusted accordingly. The construction of the tree model (steps S304-S305) is based on the project progress arrangement, determines the order and parallel relationship of the sub-projects, and converts each sub-project into a node. The length of the connection line between the nodes reflects the workload, thus forming a hierarchical and logically rigorous structure. By mapping the record information to this model, the expression state of the tree model is obtained, and the expression state sequence is constructed according to the time sequence. This sequence intuitively shows the dynamic evolution of the project progress. The core of the whole process is to convert scattered construction records into structured tree expressions, and use time reference intervals and node adjustments to achieve quantification and visualization of actual progress.

[0024] Step S400, aligning the three-dimensional virtual engineering simulation sequence, the on-site scanning record sequence and the tree model representation sequence in time, and analyzing the sequence units of the latest time segments in the on-site scanning record sequence and the tree model representation respectively, and based on the analysis results, performing real-time representation mapping of the three-dimensional virtual engineering to obtain a real-time three-dimensional virtual engineering representation.

[0025] The principle of step S400 is to dynamically map multi-source data to the three-dimensional virtual engineering through time alignment of the three-dimensional virtual engineering deduction sequence, the on-site scanning record sequence and the tree model expression state sequence, and based on the analysis results of the latest time segment, generate a real-time performance reflecting the current construction status, and provide a comprehensive basis for subsequent anomaly detection. Specifically, this step first aligns the deduction performance sequence (ideal progress) generated by step S100, the on-site scanning record sequence (actual spatial data) generated by step S200, and the tree model expression state sequence (actual record progress) generated by step S300 on the time axis to ensure the consistency of the three in the time dimension. Next, the sequence units of the latest time segment in the on-site scanning record sequence and the tree model expression sequence are extracted for analysis: for the on-site scanning data, the scanning position block is determined by using the scanning record of the latest segment, and the corresponding mapping block of the three-dimensional virtual project is adjusted based on its shape characteristics (step S401) to achieve real-time spatial update; for the tree model data, based on the completion characteristics of each engineering sub-project node in the latest expression, the three-dimensional blocks divided by sub-projects of the three-dimensional virtual project are expressed and adjusted (steps S402-S403) to reflect the progress details of the actual construction. This process dynamically maps the actual construction status to the virtual model by integrating the spatial information scanned by the drone and the structured records of the tree model to form a real-time three-dimensional virtual engineering expression. The core of the entire step lies in the collaborative analysis and mapping of multi-source data: the deduction sequence provides an ideal benchmark, the on-site scanning provides a basis for actual measurement, and the tree model provides record supplements. The combination of the three ensures the comprehensiveness and accuracy of the real-time expression.

[0026] Step S500, comparing the real-time three-dimensional virtual engineering performance with the corresponding three-dimensional virtual engineering simulation performance, and determining whether there is any abnormality in the civil engineering progress based on the comparison result.

[0027] The principle of step S500 is to systematically compare the real-time three-dimensional virtual engineering performance generated in step S400 with the corresponding three-dimensional virtual engineering deduction performance generated in step S100, quantify the deviation between the two, and judge whether there is an abnormality in the progress of the civil engineering project based on the scientific computing model, so as to achieve an accurate early warning function. Specifically, this step first configures a weight coefficient for each sub-project stereo block in the three-dimensional virtual engineering (step S501) to reflect the difference in importance of different sub-projects in the overall project, and calculates the first mapping volume (actual progress) of each sub-project block in the real-time performance and the second mapping volume (expected progress) in the deduction performance. Then, by comparing the second mapping volume of each sub-project block with the first mapping volume, the mapping volume difference is obtained, and the engineering progress difference characteristic parameter is calculated in combination with the weight coefficient (step S502), which reflects the impact of local deviation on the whole. At the same time, the sum of the first mapping volume (first total mapping volume) and the sum of the second mapping volume (second total mapping volume) of all sub-project blocks are calculated respectively, and the total mapping volume difference between the two is obtained (step S503) to evaluate the deviation of the overall progress. Finally, the degree of abnormality is calculated by combining the total mapping volume difference and the engineering progress difference characteristic parameters using a preset abnormality degree expression (step S504), where the expression combines the influence of overall deviation, local difference and adjustment coefficient. If the degree of abnormality exceeds a preset threshold, an early warning is triggered.

[0028] In some embodiments disclosed in the present invention, a method for performing progress deduction and mapping on a three-dimensional virtual project includes: Step S101, gridding the three-dimensional virtual project, defining the advancement direction of the grid in the three-dimensional virtual project based on the project advancement arrangement, and performing deduction and mapping in a time advancement manner, including: Step S1011, establishing a first time schedule for the project advancement arrangement, and setting a number of time reference nodes for the first time schedule.

[0029] Step S1012, based on the project progress schedule, determine the project conditions that need to be completed at different time reference nodes, and make associations between them. Based on the project conditions corresponding to different first time reference nodes on the first time progress line, mark the ongoing grids in the three-dimensional virtual project in turn.

[0030] Step S1013, comparing the marked grid groups between adjacent first time reference nodes, and determining the grid group boundaries between the two, and determining the directions of the grid group boundaries between the two as the grid delineation advancement direction.

[0031] In some embodiments disclosed in the present invention, a method for mapping on a preset engineering advancement tree model based on engineering advancement record information includes: Step S301, constructing a second time progress line for the project progress record information, setting a number of second time reference nodes for the second time progress line, and setting a time reference interval for each second time reference node.

[0032] Step S302 , analyzing the time stamps of the record information monomers in the engineering progress record information, determining the time reference interval to which each record information monomer belongs, and combining the record information monomers according to the time reference interval to obtain a record information monomer group.

[0033] Step S303: Analyze the record information monomers in each record information monomer group, determine the corresponding engineering sub-project work completion amount, and adjust the corresponding engineering sub-project nodes on the preset engineering advancement tree model.

[0034] In some embodiments disclosed in the present invention, the method for constructing an engineering advancement tree model includes: Step S304, based on the project progress schedule, determine the project sub-projects to be completed, and determine the sequence relationship and parallel relationship of each project sub-project.

[0035] Step S305, construct an engineering project sub-node for each work sub-project, and connect the engineering sub-project nodes in sequence based on the sequence relationship of the engineering sub-projects. If there are engineering sub-project nodes that can be parallel to each other, the corresponding engineering sub-project nodes will be connected in parallel, wherein the length of the connection line between the engineering sub-project nodes is determined by the amount of work required to complete the engineering sub-project nodes.

[0036] In some embodiments disclosed in the present invention, a method for real-time performance mapping of a three-dimensional virtual project includes: Step S401, determining the field scan record of the latest time segment in the field scan record sequence, and based on the scan position block corresponding to the field scan record, determining the corresponding mapping block on the three-dimensional virtual project, and adjusting the mapping block based on the shape characteristics of the scan position block.

[0037] Step S402, based on the project progress schedule, determine the project sub-projects to be completed, and divide the three-dimensional virtual project into sub-project stereo blocks based on the corresponding part of each project sub-project in the project.

[0038] Step S403, determining the tree model expression state of the latest time segment in the tree model expression state sequence, and adjusting the expression of the corresponding sub-project 3D block based on the completion feature of each engineering sub-project node in the tree model expression state.

[0039] In some embodiments disclosed in the present invention, a method for comparing a real-time 3D virtual engineering performance with a corresponding 3D virtual engineering simulation performance includes: Step S501, configure weight coefficients for each sub-project 3D block in the 3D virtual engineering, and determine the first mapping volume of each sub-project 3D block in the real-time 3D virtual engineering performance, and the second mapping volume of each sub-project 3D block in the 3D virtual engineering deduction performance.

[0040] Step S502, calculate the mapping volume difference between the second mapping volume and the first mapping volume corresponding to each sub-project 3D block, and determine the engineering progress difference characteristic parameters between the real-time 3D virtual engineering performance and the 3D virtual engineering simulation performance in combination with the weight coefficient corresponding to the sub-project 3D block.

[0041] Step S503: calculating the sum of all first mapping volumes to obtain a first total mapping volume, calculating the sum of all second mapping volumes to obtain a second total mapping volume, and calculating a total mapping volume difference between the second total mapping volume and the first total mapping volume.

[0042] Step S504, combining the total mapping volume difference and the engineering progress difference characteristic parameter, determines the abnormality degree of the real-time three-dimensional virtual engineering performance, and issues an early warning if the abnormality degree is greater than or equal to a preset value.

[0043] The principle of steps S501 to S504 is to quantify the deviation between the actual construction status and the ideal plan by systematically comparing the real-time three-dimensional virtual engineering performance with the corresponding three-dimensional virtual engineering deduction performance, and determine the abnormal degree of the engineering progress based on a scientific calculation model, so as to achieve an accurate early warning function. Specifically, the process starts with step S501, and a weight coefficient is configured for each sub-project three-dimensional block in the three-dimensional virtual engineering. This coefficient is set according to the importance of the sub-project in the overall project (such as tasks or resource-intensive links on the critical path) to reflect the difference in its impact on the overall progress. At the same time, the first mapping volume of each sub-project three-dimensional block in the real-time three-dimensional virtual engineering performance (from the mapping result of step S400), that is, the actual completed volume, and the second mapping volume of the corresponding block in the three-dimensional virtual engineering deduction performance (from the ideal deduction of step S100), that is, the expected completed volume. The calculation of these two volumes is based on the spatial division of the sub-project three-dimensional blocks (step S402), which provides a quantitative basis for subsequent difference analysis. Next, in step S502, the difference between the second mapped volume and the first mapped volume of each sub-project three-dimensional block is calculated. This difference reflects the degree of deviation of local construction. Combined with the weight coefficients of each block, the characteristic parameter of engineering progress difference is obtained through weighted processing. This parameter integrates the distribution and importance of local deviations and provides a fine-grained perspective for abnormal evaluation. Subsequently, in step S503, the sum of the first mapped volume (first total mapped volume) and the sum of the second mapped volume (second total mapped volume) of all sub-project blocks are calculated respectively, and the total mapped volume difference between the two is obtained. This indicator measures the deviation between the actual progress and the plan from the overall level, supplementing the global perspective of local analysis. Finally, in step S504, the abnormal degree of real-time three-dimensional virtual engineering performance is calculated using a preset abnormal degree expression in combination with the total mapped volume difference and the characteristic parameter of engineering progress difference. This expression optimizes the calculation results by adjusting coefficients and constants (such as sub-project difference characteristics affecting the adjustment coefficients and constants) to ensure the scientificity and sensitivity of the abnormal degree. If the abnormal degree is greater than or equal to the preset threshold, an early warning is triggered to prompt the manager to take intervention measures.

[0044] Among them, the expression for calculating the degree of abnormality is: .

[0045] in, For abnormal degree, is the abnormality conversion coefficient, is the second total mapping volume, is the first total mapping volume, For the The second mapping volume corresponding to the sub-project three-dimensional block, For the The first mapping volume corresponding to the sub-project stereo block, For the The weight coefficient corresponding to each sub-project stereo block, Adjust constants for the influence of differences in the characteristics of the three-dimensional blocks of the sub-projects. It is the adjustment coefficient affected by the difference characteristics of the three-dimensional blocks of the sub-project.

[0046] In some embodiments disclosed in the present invention, a method for using a drone to scan an on-site project and determine the progress of the project at different location nodes includes: Step S201, determine the key location nodes of the project, and plan the flight path of the drone based on the key location nodes.

[0047] Step S202, using drones to collect engineering progress status data at different key location nodes, including the geometric shape and identification of the engineering progress area.

[0048] In some embodiments disclosed in the present invention, a civil engineering early warning system based on data analysis is also disclosed, including: The first module is used to obtain engineering design data, build a three-dimensional virtual project based on the engineering design data, obtain the project progress schedule, and perform progress deduction and mapping on the three-dimensional virtual project based on the project progress schedule to obtain a three-dimensional virtual project deduction and performance sequence that changes over time; The second module is used to use drones to scan on-site projects, determine the progress of projects at different location nodes, and record the corresponding time nodes in a relevant manner to form a sequence of on-site scan records; The third module is used to obtain the engineering progress record information, and based on the engineering progress record information, map it on the preset engineering progress tree model to obtain the tree model expression state of the engineering progress tree model, and construct the tree model expression state into a tree model expression state sequence based on the time sequence relationship; The fourth module is used to align the three-dimensional virtual engineering simulation sequence, the on-site scanning record sequence and the tree model representation sequence in time, and analyze the sequence units of the latest time segment in the on-site scanning record sequence and the tree model representation respectively, and based on the analysis results, perform real-time representation mapping on the three-dimensional virtual engineering to obtain real-time three-dimensional virtual engineering representation; The fifth module is used to compare the real-time three-dimensional virtual engineering performance with the corresponding three-dimensional virtual engineering simulation performance, and based on the comparison results, determine whether there are any abnormalities in the progress of the civil engineering project.

[0049] The invention discloses a civil engineering early warning method and system based on data analysis, and relates to the technical field of civil engineering management; the method comprises: constructing a three-dimensional virtual engineering based on engineering design data, and performing progress deduction and mapping in combination with the engineering advancement arrangement, and generating a deduction performance sequence that changes with time; utilizing an unmanned aerial vehicle to scan the on-site engineering, and recording the advancement status of nodes at different positions, and forming an on-site scanning record sequence; mapping the engineering advancement record information to a preset tree model, and constructing a tree model performance state sequence; aligning the three-dimensional virtual engineering deduction sequence, the on-site scanning record sequence, and the tree model performance state sequence, analyzing the latest time segment data, and performing real-time performance mapping on the three-dimensional virtual engineering; comparing the real-time performance with the deduction performance, and determining the abnormality of the engineering progress; the invention realizes the accurate detection and early warning of progress deviation through multi-source data integration and dynamic analysis, and improves the efficiency of civil engineering management.

[0050] Through the description of the above implementation methods, those skilled in the art can clearly understand that the present invention can be implemented by hardware, or by software plus a necessary general hardware platform. Based on such an understanding, the technical solution of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each implementation scenario of the present invention.

[0051] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A civil engineering early warning method based on data analysis, characterized in that: include: Step S100, obtaining engineering design data, and constructing a three-dimensional virtual engineering based on the engineering design data, obtaining an engineering progress schedule, and based on the engineering progress schedule, performing a progress deduction and mapping of the three-dimensional virtual engineering to obtain a three-dimensional virtual engineering deduction and performance sequence that changes over time; Step S200, using a drone to scan the on-site project, determine the progress of the project at different location nodes, and record the corresponding time nodes in a relevant manner to form an on-site scanning record sequence; Step S300, obtaining the engineering progress record information, and mapping the engineering progress record information on the preset engineering progress tree model to obtain the tree model expression state of the engineering progress tree model, and constructing the tree model expression state into a tree model expression state sequence based on the time sequence relationship; Step S400, aligning the three-dimensional virtual engineering simulation sequence, the on-site scanning record sequence and the tree model representation state sequence in time, and analyzing the sequence units of the latest time segment in the on-site scanning record sequence and the tree model representation state respectively, and based on the analysis results, performing real-time representation mapping on the three-dimensional virtual engineering to obtain a real-time three-dimensional virtual engineering representation; Step S500, comparing the real-time three-dimensional virtual engineering performance with the corresponding three-dimensional virtual engineering simulation performance, and determining whether there is any abnormality in the civil engineering progress based on the comparison result.

2. The civil engineering early warning method based on data analysis according to claim 1 is characterized in that: Methods for mapping the progress of three-dimensional virtual engineering include: Step S101, gridding the three-dimensional virtual project, defining the advancement direction of the grid in the three-dimensional virtual project based on the project advancement arrangement, and performing deduction and mapping in a time advancement manner, including: Step S1011, establishing a first time schedule for the project advancement arrangement, and setting a number of time reference nodes for the first time schedule; Step S1012, based on the project advancement arrangement, determine the project conditions that need to be completed at different time reference nodes, and associate them with each other, and mark the ongoing grids in the three-dimensional virtual project in turn based on the project conditions corresponding to different first time reference nodes on the first time progress line; Step S1013, comparing the marked grid groups between adjacent first time reference nodes, and determining the grid group boundaries between the two, and determining the directions of the grid group boundaries between the two as the grid delineation advancement direction.

3. The civil engineering early warning method based on data analysis according to claim 1 is characterized in that: Based on the engineering progress record information, the method of mapping on the preset engineering progress tree model includes: Step S301, constructing a second time progress line for the project progress record information, setting a number of second time reference nodes for the second time progress line, and setting a time reference interval for each second time reference node; Step S302, analyzing the time stamps of the record information monomers in the engineering progress record information, determining the time reference interval to which each record information monomer belongs, and combining the record information monomers according to the time reference interval to obtain a record information monomer group; Step S303: Analyze the record information monomers in each record information monomer group, determine the corresponding engineering sub-project work completion amount, and adjust the corresponding engineering sub-project nodes on the preset engineering advancement tree model.

4. The civil engineering early warning method based on data analysis according to claim 1 is characterized in that: Methods for constructing an engineering advancement tree model include: Step S304, based on the project advancement arrangement, determine the project sub-projects to be completed, and determine the order of each project sub-project and the parallel relationship; Step S305, construct an engineering project sub-node for each work sub-project, and connect the engineering sub-project nodes in sequence based on the sequence relationship of the engineering sub-projects. If there are engineering sub-project nodes that can be parallel to each other, the corresponding engineering sub-project nodes will be connected in parallel, wherein the length of the connection line between the engineering sub-project nodes is determined by the amount of work required to complete the engineering sub-project nodes.

5. The civil engineering early warning method based on data analysis according to claim 1 is characterized in that: Methods for real-time performance mapping of three-dimensional virtual engineering include: Step S401, determining the field scanning record of the latest time segment in the field scanning record sequence, and determining the corresponding mapping block on the three-dimensional virtual project based on the scanning position block corresponding to the field scanning record, and adjusting the mapping block based on the shape characteristics of the scanning position block; Step S402, based on the project progress schedule, determine the project sub-projects to be completed, and divide the three-dimensional virtual project into sub-project three-dimensional blocks based on the corresponding part of each project sub-project in the project; Step S403, determining the tree model expression state of the latest time segment in the tree model expression state sequence, and adjusting the expression of the corresponding sub-project 3D block based on the completion feature of each engineering sub-project node in the tree model expression state.

6. A civil engineering early warning method based on data analysis according to claim 5, characterized in that: The method of comparing the real-time 3D virtual engineering performance with the corresponding 3D virtual engineering simulation performance includes: Step S501, configuring weight coefficients for each sub-project 3D block in the 3D virtual engineering, and determining a first mapping volume of each sub-project 3D block in the real-time 3D virtual engineering performance, and a second mapping volume of each sub-project 3D block in the 3D virtual engineering deduction performance; Step S502, calculating the mapping volume difference between the second mapping volume and the first mapping volume corresponding to each sub-project 3D block, and determining the engineering progress difference characteristic parameter between the real-time 3D virtual engineering performance and the 3D virtual engineering simulation performance in combination with the weight coefficient corresponding to the sub-project 3D block; Step S503, calculating the sum of all first mapping volumes to obtain a first total mapping volume, calculating the sum of all second mapping volumes to obtain a second total mapping volume, and calculating a total mapping volume difference between the second total mapping volume and the first total mapping volume; Step S504, combining the total mapping volume difference and the engineering progress difference characteristic parameter, determines the abnormality degree of the real-time three-dimensional virtual engineering performance, and issues an early warning if the abnormality degree is greater than or equal to a preset value.

7. The civil engineering early warning method based on data analysis according to claim 5 is characterized in that: Methods for using drones to scan on-site projects and determine the progress of projects at different locations include: Step S201, determining the key location nodes of the project, and planning the flight path of the UAV based on the key location nodes; Step S202, using drones to collect engineering progress status data at different key location nodes, including the geometric shape and identification of the engineering progress area.

8. A civil engineering early warning system based on data analysis, characterized in that: A civil engineering early warning method based on data analysis for executing any one of claims 1 to 7, comprising: The first module is used to obtain engineering design data, build a three-dimensional virtual project based on the engineering design data, obtain the project progress schedule, and perform progress deduction and mapping on the three-dimensional virtual project based on the project progress schedule to obtain a three-dimensional virtual project deduction and performance sequence that changes over time; The second module is used to use drones to scan on-site projects, determine the progress of projects at different location nodes, and record the corresponding time nodes in a relevant manner to form a sequence of on-site scan records; The third module is used to obtain the engineering progress record information, and based on the engineering progress record information, map it on the preset engineering progress tree model to obtain the tree model expression state of the engineering progress tree model, and construct the tree model expression state into a tree model expression state sequence based on the time sequence relationship; The fourth module is used to align the three-dimensional virtual engineering simulation sequence, the on-site scanning record sequence and the tree model representation sequence in time, and analyze the sequence units of the latest time segment in the on-site scanning record sequence and the tree model representation respectively, and based on the analysis results, perform real-time representation mapping on the three-dimensional virtual engineering to obtain real-time three-dimensional virtual engineering representation; The fifth module is used to compare the real-time three-dimensional virtual engineering performance with the corresponding three-dimensional virtual engineering simulation performance, and based on the comparison results, determine whether there are any abnormalities in the progress of the civil engineering project.

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