623 results about "Construction management" patented technology

The invention relates to the technical field of engineering construction management and control, in particular to an engineering construction management and control method and system based on digital twinning. The method comprises the following steps: acquiring real-time construction engineering data and regional environment data, identifying a real-time structured construction state and generating a three-dimensional simulation model, then acquiring a target construction engineering plan and performing process node positioning to calculate a real-time engineering progress deviation, performing compensation simulation based on the deviation, and determining an engineering construction development trend. And then environment constraint mapping and resource conflict analysis are performed to generate corresponding data, and an optimized construction path conforming to environment constraint and resource conditions is screened out through construction optimization path mining of the simulation model, so that the construction efficiency and the management level are improved. According to the invention, the competitiveness and sustainable development capability of the building industry are enhanced, and an efficient and transparent engineering management system is finally formed.

The invention discloses a method and system for managing expressway construction based on a BIM technology. The method comprises the following steps: acquiring multi-modal data in expressway construction; constructing an environment-load-response multi-modal data fusion risk matrix by using a space-time correlation model; constructing an AI prediction model by using bridge motion signals and humidity and CO2 concentration data in the multi-modal data; dynamic risk early warning and hierarchical response are realized; the bridge vibration signals and thermal infrared imager data are utilized to analyze and identify invisible faults in highway construction; constructing a fault and health management scheme based on dynamic risk early warning, hierarchical response and invisible faults; performing construction simulation, conflict elimination and extreme working condition deduction by using the digital twin environment of the BIM technology; and according to a deduction result, carrying out highway construction abnormal area management through VR visualization. According to the scheme of the invention, the safety early warning, fault prediction and health management levels of highway construction can be improved.

The invention relates to the technical field of decoration construction management, and discloses a BIM-based decoration construction scene resource consumption simulation analysis method. The method comprises the following steps: firstly, creating a multi-dimensional BIM resource model, and integrating building information model data, real-time construction data flow and historical resource consumption records; identifying resource consumption characteristics through the model, and generating an initial resource allocation strategy set comprising material allocation, equipment scheduling and process priority schemes; receiving a user interaction instruction, and dynamically adjusting the initial strategy set; and finally, executing the adjusted strategy, and updating the multi-dimensional BIM resource model based on a result. Wherein the resource consumption feature comprises construction stage division, resource node dynamic weight calculation and space correlation correction operation. According to the method, by integrating multi-dimensional data and dynamically analyzing a resource consumption rule, real-time optimization of a resource allocation strategy is realized, and the accuracy and flexibility of decoration construction resource management can be improved.

The invention discloses an intelligent building construction operation management method based on big data, and belongs to the technical field of building construction management. Comprising the following steps: step 1, real-time data acquisition of construction site personnel, equipment and environment is realized, and a dynamic information database is established; 2, preprocessing and feature extraction are carried out on the collected multi-source heterogeneous data, and fusion and intelligent analysis of real-time data are achieved; step 3, accurately identifying risk factors and implementing refined early warning and intelligent intervention aiming at a single risk; 4, construction resource configuration is dynamically optimized, the resource utilization efficiency is improved, and meanwhile the cost and the safety risk are reduced; step 5, constructing a block chain data sharing mechanism, and realizing data tracing and intelligent management of a construction full life cycle; and step 6, forming a self-adaptive closed-loop feedback mechanism, and promoting intelligent transformation of construction management from passive response to active prediction.

The invention discloses a photovoltaic power station distributed construction management method and system based on load analysis, and the method comprises the steps: outputting a dynamic load intensity thermodynamic diagram according to the terrain elevation data, meteorological historical data and assembly mechanical parameters of a photovoltaic power station planning region; based on the dynamic load strength thermodynamic diagram, generating a construction zoning scheme for wind pressure resistance optimization; outputting a conflict-free construction resource allocation matrix according to the construction partitioning scheme; on the basis of the construction resource allocation matrix, construction parameters are dynamically corrected by adopting an adaptive particle swarm optimization algorithm, and an anti-deformation construction instruction set is generated; and driving the construction machinery to execute operation according to the anti-deformation construction instruction set, and iteratively updating the global load distribution map by using the reinforcement learning model to form a closed-loop construction management link. By utilizing the embodiment of the invention, the balance of construction precision and efficiency in a complex environment can be realized by fusing multi-source data, optimizing partition planning, intelligently scheduling equipment and controlling closed-loop quality.

The invention belongs to the technical field of smart city construction and intelligent construction management, and particularly relates to an intelligent scheduling and cooperation system and method for the whole life cycle of city reconstruction. The system comprises an edge sensing layer, a digital twinning network module, a space-time brain module, a block chain collaborative trust layer and an XR collaborative interaction layer. The system collects multi-source data of a construction site in real time through a 5G edge device, realizes fusion modeling of BIM, GIS and TIN models by using a graph convolutional neural network, and performs multi-target scheduling optimization in combination with meta reinforcement learning and a dynamic graph neural network; and meanwhile, construction task verification and fund payment linkage is realized through a block chain smart contract, and immersive cooperation and visual acceptance are provided in cooperation with an AR / VR platform. According to the method, the problems of model splitting, scheduling response lagging, low data collaboration efficiency, insufficient credibility of the performance process and the like in the urban reconstruction project are solved, and the intelligence, transparency and automation level of the construction process is remarkably improved.

The invention relates to the technical field of digital engineering, and particularly provides a BIM-based engineering construction dynamic three-dimensional visual management method and system, and the method comprises the steps: collecting construction multi-dimensional data, carrying out the correlation mapping with an initial BIM model component after preprocessing, and forming a structured construction element data set; dynamically reconstructing an initial BIM model based on the data set, generating a three-dimensional dynamic twinborn body, and dynamically displaying information such as superposition progress, quality, resources and environment; a prediction analysis model is called to generate progress prediction, quality early warning and resource optimization suggestions, and a final scheme is determined after visual simulation verification; and updating the data set and the twin according to an execution result, and iteratively optimizing the prediction model. According to the scheme, dynamic integration and visual management of construction total elements are achieved, the timeliness, accuracy and intelligent level of construction management are effectively improved through intelligent prediction and closed-loop optimization, the construction efficiency is improved, and the management cost is reduced.

The invention relates to the technical field of construction stage management, in particular to a BIM-based road construction digital management system, which comprises a component parameter acquisition module, a process topology construction module, a state trigger mapping module, a logic conflict judgment module and a scheduling path adjustment module. According to the method, through continuous collection and analysis of the component state, dynamic monitoring of the connection state, geometric intersection and contact time is achieved, the construction change sensing capacity is improved, the dependency relationship is constructed in combination with component space adjacency and time overlapping, the dispatching path and field matching degree is enhanced, and through linkage updating of the component state and model attributes, the construction efficiency is improved. According to the method, the execution state is visual and controllable, scheduling reconstruction is carried out after time dependence conflicts are recognized, synchronous updating of model views is completed, a closed-loop dynamic scheduling mechanism is formed, the task allocation accuracy, the flow connection efficiency and the field scheduling response capability are integrally improved, and the real-time performance and the intelligent level of construction management are enhanced.

The invention relates to the technical field of bridge construction, in particular to an intelligent construction management system based on urban cross-railway bridge anti-collision guardrail construction, and aims to solve the problems that space-time modeling cannot be performed on personnel, equipment and obstacles on a construction site, a multi-agent collaborative decision-making mechanism cannot be constructed by combining reinforcement learning and game theory, and the construction efficiency is low in the prior art. Conflicts cannot be dynamically recognized according to the spatial distance to generate a low-conflict path, and the construction safety and efficiency are reduced. According to the method, space-time modeling is carried out on personnel, equipment and obstacles on a construction site based on a graph neural network through a space conflict detection module, behavior characteristics are extracted by fusing multi-source data, a multi-agent collaborative decision-making mechanism is constructed by combining reinforcement learning and the game theory, node representation is optimized through comparative learning, and the decision-making efficiency is improved. The cooperation capability is enhanced by using the communication graph and the credit score, conflicts are dynamically identified according to the spatial distance to generate a low-conflict path, and the construction safety and efficiency are improved.

The invention relates to a multi-modal data-driven rail transit construction potential safety hazard identification method and system, and solves the problem that the accuracy and real-time performance of potential hazard identification are insufficient due to the fact that multi-source data cannot realize deep collaboration, and the method comprises the following steps: obtaining multi-modal data containing a BIM + GIS model, an unmanned aerial vehicle image stream and Internet of Things data; according to an edge end-cloud architecture, by taking BIM + GIS coordinates as a reference, the edge end associates and binds data and cleans and transmits the data to the cloud, and the cloud corrects and generates a standardized data set; and the comprehensive risk index is calculated by using an entropy weight method, and a report is generated and pushed to a construction management terminal. The method has the following effects: the multi-modal data barrier is broken, the integrated accurate identification of the hidden hidden danger of the rail transit construction is realized, and the accuracy and efficiency of the construction safety management and control are fundamentally improved.

The invention discloses a water conservancy project construction management informatization platform, and relates to the technical field of water conservancy project management, and the platform comprises an evaluation form generation module, a form filling verification module, an intelligent approval module, a classification filing module and a safety management module. According to the invention, a whole-user, full-service and full-life-cycle construction management standardization system is constructed; automatic filling and real-time verification are realized by means of a natural language processing technology and machine learning, and data entry experience and accuracy are improved; decision support is provided through big data analysis, a filling strategy and an approval path are recommended through a model, and process management is optimized; digitized upgrading of form full-life-cycle management is realized, and the method is suitable for a water conservancy project construction management scene with a complex approval process; the state evolution trend of hidden danger points or major hazard sources in a future period of time is simulated, and early warning and plan generation are carried out based on the state evolution trend.

The invention provides a metro section parameterized linear digital model construction method based on Revit and Dynamo, and the method comprises the steps: building a three-dimensional space control reference through analyzing track line design data, and constructing a metro section model in a manner of combining parameterized modeling with an intelligent algorithm; the contact network and pipeline models are ensured to meet the standard requirements through real-time verification of the conductor height change rate and the turning radius-pipe diameter matching matrix; space coordinate unification and interface matching precision control are achieved through a multi-professional model cooperation system, and a parameter linkage updating mechanism is established to respond to design changes; and finally, outputting an LOD400 precision BIM model and associating construction data for dynamic correction, and supporting RVT / IFC format conversion and engineering quantity automatic statistics. The method is mainly used for efficient collaborative design and construction management and control of metro sections, the modeling precision and the multi-specialty coordination efficiency can be improved, and the design error rate is reduced.

The invention provides a subway construction management method and device in a complex sensitive environment, and relates to the technical field of subway construction management, and the method comprises the steps: obtaining first information which comprises construction region shield propulsion parameter time sequence data, building settlement monitoring data, underground pipeline distribution data and micro-seismic sensor array data; preprocessing the first information to obtain a three-dimensional geological influence map fusing underground structure-stress response-dynamic disturbance; performing semi-variation function modeling and spectrogram co-training clustering algorithm joint optimization on the three-dimensional geological influence map to generate a multi-layer heterogeneous map structure; performing dynamic graph convolutional network and graph integral propagation model co-evolution on the multilayer heterogeneous graph structure to generate a risk cascade prediction model; and solving the prediction model to obtain a global management scheme of subway construction. According to the invention, subway construction full-life-cycle management with controllable risk, timely response and dynamic strategy adjustment is realized.

The present application relates to the technical field of project management, and discloses an integrated management system and method for a large-scale project. The system comprises: a budget subsystem, used for obtaining target project information, and carrying out multi-level classification processing and coding processing on the target project information to obtain budget codes; a contract management subsystem, used for decomposing the target project information, generating a plurality of project contracts and associating the plurality of project contracts with the budget codes; a construction management and control subsystem, used for splitting the project contracts to obtain unit projects, encoding the unit projects to obtain unit codes, and associating quantity data corresponding to the unit projects with a preset construction drawing list; and a joint control subsystem, used for carrying out joint control on the project cost, the project progress and the project quality on the basis of a measurement visa so as to carry out integrated management on a large-scale project. The present application realizes integrated management of large-scale project construction.

The invention discloses a construction management system and method based on multi-source data analysis, and relates to the technical field of building construction informatization and intelligent management and control, and the method comprises the steps: capturing a front path task completion signal and a subsequent task starting instruction; obtaining preposed task completion time, a dynamic condition type and a threshold parameter; executing time logic verification based on the dynamic condition type, and judging a construction dynamic context ready state; bIM design coordinates, field positioning coordinates and space tolerance parameters of the construction machinery are obtained, and space logic verification is executed by calculating space deviation; when both the time verification and the space verification pass, subsequent task state conversion is allowed, and otherwise, blocking is carried out; and finally generating a structured report containing all verification parameters and results.

The invention relates to the technical field of building engineering construction management, and discloses a house steel building construction prediction progress and deployment system based on deep learning. According to the system, periodic stable paragraphs and non-periodic fluctuation paragraphs are recognized by analyzing the time sequence form of construction flow data, and construction links are stripped accordingly. And performing cross mapping on the hoisting event sequence in the link and the environmental monitoring reading of the associated link to generate a link toughness spectrogram representing the construction robustness. And determining a resource demand based on the spectrum graph, and forming a multi-dimensional resource demand vector, so as to drive a graph convolutional network to construct a dynamic construction deduction graph. And carrying out message passing and neighborhood aggregation on the graph, analyzing a key bottleneck path, and iteratively generating a progress prediction and resource allocation scheme. According to the method, the construction dynamic toughness can be evaluated, and accurate positioning and dynamic optimization of resource bottlenecks are realized.

The invention discloses a construction site three-dimensional modeling method based on multi-sensor fusion. The method comprises the following steps: synchronously acquiring data by using a laser radar, a camera, an infrared sensor, a GPS (Global Positioning System) and an IMU (Inertial Measurement Unit); the method comprises the following steps of: performing denoising and filtering operation on collected original data, aligning a timestamp and a space of the collected data, fusing the collected multi-source data, and aligning and fusing the processed multi-source point cloud data through a point cloud registration and fusion algorithm to generate a complete three-dimensional point cloud model; generating a grid model by using a surface reconstruction algorithm based on the point cloud data, and performing texture mapping in combination with texture information collected by a camera; the model is simplified and the precision of the model is improved through a model optimization technology, and a reliable three-dimensional visualization foundation for construction management and analysis is formed; real-time detection and modeling of dynamic targets such as mobile equipment and workers on a construction site are realized, and the real-time response capability of the system in a complex construction site environment is ensured through combination of a lightweight neural network architecture and an edge computing technology.

The invention relates to the technical field of intelligent construction, and discloses an intelligent construction collaborative management platform and method based on digital twinning, and the method comprises the steps: firstly obtaining the practical operation data of a target engineering machine, analyzing the data safety level of the practical operation data to generate a distributed storage path, extracting storage node identifiers in the path, and deploying the storage node identifiers to a digital twinning platform; analyzing a node storage state index, querying a data backup demand and constructing a storage backup framework; then identifying an access request of the storage security framework, verifying a user identity, calculating an authority level index, analyzing an access range, and determining a platform multi-layer access regulation; then monitoring a permission change event, collecting a log, identifying a risk access behavior and calculating an access risk index; and finally, adjusting node encryption configuration according to the risk index, identifying an authority control key, and generating a self-adaptive security policy of the target engineering machinery on the platform. According to the invention, the integrity and safety of construction management can be improved.

The invention belongs to the technical field of construction management, and particularly relates to a construction data processing method and system based on big data, and the system comprises a data collection and editing preprocessing module, a time-space correlation modeling module, a multi-dimensional risk deduction module, a decision feedback optimization module and a construction supervision terminal. Multi-source heterogeneous data are efficiently accessed and processed through the data collecting and editing preprocessing module, the efficiency and accuracy of data processing are improved, the space-time correlation modeling module constructs dynamic digital twinborn bodies of construction elements, real-time mapping and correlation analysis of a physical space and a digital space are achieved, powerful support is provided for risk prevention and control, and the method is suitable for large-scale popularization and application. The multi-dimensional risk deduction module carries out risk quantitative evaluation and scene simulation based on the digital twinborn body, potential risks can be found in advance and early warning signals can be generated, the decision feedback optimization module converts risk early warning into a specific disposal scheme, the construction supervision difficulty can be reduced, and a powerful guarantee is provided for smooth proceeding of a construction project.

The invention discloses a BIM / CIM-based engineering design whole-process auxiliary decision-making method, relates to the technical field of engineering design, and discloses a BIM / CIM-based engineering design whole-process auxiliary decision-making method, which comprises the following steps: responding to a project red line range, obtaining geographic space data, and carrying out preprocessing, model reconstruction and lightweight processing on the geographic space data to obtain a project red line range; generating a macroscopic current situation scene; obtaining at least two candidate schemes, and performing spatial registration and fusion on the BIM models corresponding to the candidate schemes and the macroscopic current situation scene to generate a corresponding fusion decision scene; based on the fusion decision-making scene, carrying out collaborative decision-making on the candidate schemes, and determining a bid-winning scheme; and packaging the BIM model corresponding to the bid winning scheme and associated data, and transmitting the packaged BIM model and associated data to a downstream construction management system through an interface. The scheme collaborative decision-making efficiency is effectively improved, the information fault problem in the design and construction stages is solved, and the whole-process decision-making closed loop of the engineering project is achieved.

The invention discloses a tunnel process realistic management system based on real-time data acquisition and intelligent analysis, and belongs to the technical field of tunnel engineering construction management. Comprising a hardware layer, a data layer and an application layer, all the layers cooperatively achieve real-time realistic management of the tunnel process, and the hardware layer is used for collecting data of the whole process and comprises the steps that an Internet of Things terminal with a GPS and a sensor interface is installed on tunnel construction equipment, and equipment start-stop time, working parameters and position information are collected; the data layer is used for data real-time transmission and structured storage; and the application layer realizes a realistic management function and comprises a real-time realistic panel, an intelligent report generation module, a tracing query function module and a permission and collaborative management module. According to the invention, multi-terminal cooperative acquisition of "UWB positioning card + equipment + material" is adopted, and through accurate binding of space positioning and time nodes, process data is upgraded from "manual recording" to "space-time linkage realistic", and the problem that traditional equipment is difficult to accurately associate personnel and processes is solved.

The invention relates to the technical field of electric power construction management, in particular to a full-chain-number intelligent construction collaborative management method and system based on electric power production. The method comprises the following steps: constructing a construction actual measurement parameter reverse mapping path, and reversely synchronizing a construction actual measurement data set to a design platform; structuring the change information in the debugging event log into measuring point mapping change data, and constructing a debugging change information reverse synchronization path based on a point construction loop three-way binding structure; constructing a dynamic transformer area operation portrait, introducing a transformer area deviation attribution identification model to compare the dynamic transformer area operation portrait with the static archive data to generate a transformer area operation deviation matrix, and dynamically adjusting a reactive power compensation control strategy and a load prediction model parameter; and performing unified archiving on the construction actual measurement data set, the measurement point mapping change data and the dynamic court operation portrait in real time. According to the invention, the reverse closed-loop collaborative management method for the whole life cycle of power production and construction is realized.

The invention relates to the technical field of computers, and provides a cross-platform installation package automatic adaptation method and system, and the method comprises the steps: obtaining a unified description file and an operating system fingerprint of each target platform; based on the operating system fingerprints of the target platforms and the installation package adaptation parameters, matching is carried out, and dependency trees of the target platforms are generated; and generating an adaptive installation package based on the dependency tree of each target platform and the installation package adaptation parameter. According to the cross-platform installation package automatic adaptation method, specific parameters and shared parameters of the platform are managed in a centralized mode through unified description files, environment intelligent perception is achieved and the dependency tree of the platform is generated in combination with dynamically obtained operating system fingerprints, and the adaptive installation package is generated through analysis of the installation package adaptation parameters of the platform and the dependency tree. The problems of low adaptation efficiency, high configuration error rate, high maintenance cost and the like are solved; in addition, a unified construction management mechanism realizes cross-platform centralized management and control, and the accuracy and efficiency of cross-platform installation package adaptation are improved.

The invention relates to the technical field of environment control of earth excavation, in particular to an earth excavation construction flying dust suppression method and system.The earth excavation construction flying dust suppression method comprises the steps that construction intensity prediction is conducted, specifically, the construction activity intensity and duration in a specific time period in the future are predicted by accessing a construction management system; vehicle information acquisition and fusion: identifying and classifying incoming and outgoing vehicles to obtain accurate vehicle passing frequency and type distribution; raising dust risk assessment and grade determination: establishing a raising dust risk assessment model based on the predicted construction intensity, real-time vehicle passing data and meteorological parameters, and performing grade determination on raising dust risks of different areas; and the regional dynamic spraying control module is used for dividing the construction site into a plurality of independent control regions according to the dust raising risk level and the wind direction information, dynamically adjusting the start-stop time sequence, the water quantity and the spraying angle of a spraying device in each region, and realizing regional and differentiated dust raising suppression. On the premise of saving water and electricity, the problem of flying dust pollution in earth excavation operation is solved.

The invention provides a needle beam trolley construction digital management method, and relates to the technical field of digital management, and the method comprises the steps: employing a laser scanner to scan the wall surface of a to-be-constructed tunnel; acquiring position information of a plurality of working windows of the needle beam trolley; carrying out operation sequence enumeration by taking the maximum number of cooperative work windows as a constraint, and generating a plurality of work window operation sequences; based on the tunnel wall face three-dimensional model, with the requirement for the expected construction quality as the constraint and the requirement for maximizing the construction efficiency as the target, according to the multiple working window operation sequences, casting parameter and vibration parameter optimization is conducted, an optimal construction scheme is output, and digital construction management is conducted on the needle beam trolley. The technical problem of low construction efficiency caused by unreasonable operation sequence and non-uniform resource distribution in the construction process is solved, spatial perception is performed on the to-be-constructed tunnel through three-dimensional modeling, multi-aspect optimization is realized in combination with digital management, and the construction efficiency and precision of the needle beam trolley are improved.

The invention relates to a tool path planning method, device and equipment for a pumped storage power station construction site, a storage medium and a program product, and relates to the technical field of construction site path planning. The method can improve the construction management efficiency and the construction safety. The method comprises the following steps: constructing an environment model of a pumped storage power station construction site through a grid method according to environment information of the pumped storage power station construction site; determining path length cost, gradient cost and path smoothness of the environment model, and setting an objective function of the environment model; setting constraint conditions of the environment model according to the path passing constraint, the gradient constraint and the path smoothing constraint of the construction equipment; and under the condition that constraint conditions are met, iterative optimization is carried out by taking minimization of the objective function as a target through a Latin hypercube sampling, Levy distribution strategy and stable development change-based Heman optimization algorithm to obtain an optimal solution of the objective function, and an optimal path planning scheme of the construction equipment is obtained according to the optimal solution.

The invention relates to an intelligent construction management method for an intelligent beam field, and the method comprises the steps: collecting multi-source data of a field beam field control system in a preset target period, and carrying out the preprocessing of the multi-source data into standardized input data; substituting the standardized input data into a productivity prediction model trained according to historical multi-source data, and generating a corresponding productivity interval; on the basis of a constrained optimization algorithm, generating a corresponding production scheduling result according to a pre-acquired production scheduling plan and a production capacity interval, and driving a field beam field control system to execute corresponding scheduling operation according to the production scheduling result; and when interference factors are detected, a new production scheduling result is dynamically adjusted based on the productivity prediction model, so that beam manufacturing, beam storage and beam discharging form a closed-loop collaborative management chain, thereby improving the precision and flexibility of a production plan, reducing resource waste and construction conflicts, and improving the overall operation efficiency and scheduling response capability.

The invention relates to the technical field of remote monitoring, in particular to a TBM remote monitoring method based on a multi-level collaborative management architecture, which is applied to a remote comprehensive monitoring platform. The platform comprises a construction operation layer, a construction management and control layer and a decision support layer, each monitoring scene forms a local block chain ring by a plurality of construction surface nodes, and an integral block chain ring is integrally formed. The method comprises the steps of collecting construction state data, performing standardization processing, and inputting the data to an equipment risk identification model and a geological evaluation model for construction state analysis; based on local anomaly detection, deducing an anomaly propagation path, calculating the reverse coverage capability of each non-abnormal local circle, and determining a decision block chain circle; and performing node locking and decision switching through the abnormal isolation control smart contract, and generating a decision instruction based on a multi-objective optimization algorithm. According to the method, the abnormal self-healing capability and the dynamic decision-making efficiency of the TBM construction monitoring system are improved.

The invention relates to the technical field of hoisting construction risk management and control, and discloses a building peripheral frame construction management and control method and system based on an unmanned aerial vehicle and a storage medium. Then determining a hoisting risk coefficient according to the obstacle type and the state parameter; and when the risk coefficient exceeds a threshold value, according to the obstacle state parameter, determining an estimated time length for the obstacle to arrive at the hoisting rope, and correcting the estimated time length in combination with the hoisting rope following motion parameter and the environment characteristic parameter to obtain a target pre-collision time length. And finally, implementing graded coping according to the target pre-collision duration: accelerating take-off and hovering if the pre-collision time is sufficient, and triggering a lifting hook to be separated from a lifting rope if the pre-collision time is urgent. According to the technical scheme, the actual requirements of efficient and intelligent construction can be met.

The invention discloses an expressway differential settlement prediction and regulation system based on machine learning, and belongs to the technical field of intelligent traffic infrastructure construction and maintenance. According to the system, a closed-loop system including multi-source data fusion acquisition, spatial-temporal characteristic engineering, physical constraint spatial-temporal diagram network prediction, reinforcement learning reverse regulation and control and visual decision early warning is constructed for solving the problem of differential settlement control in alluvial plain deep and thick soft soil area highway reconstruction and extension projects. According to the system, Biot consolidation theory constraints are embedded in a geological weighted graph network, so that the problems of over-fitting and physical consistency deficiency of a pure data driven model under complex geological conditions are effectively solved; meanwhile, the reinforcement learning strategy network is used for replacing artificial experience, and global optimization regulation and control of construction parameters are achieved on the premise that the differential settlement control requirement is met. The method is mainly used for precise settlement prediction and intelligent construction management of highway reconstruction and extension projects.