383 results about "Construction management" patented technology

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 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 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 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 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 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.

The invention relates to the technical field of concrete performance detection, and discloses a concrete condensation state prediction and maintenance method based on multi-sensor fusion. The method aims at solving the problems that an existing concrete condensation state judgment method is destructive and cannot reflect the real state in a structure in real time, and maintenance measures cannot dynamically adapt to actual working condition changes. The method comprises the following steps: deploying a multi-sensor combination in concrete to collect data in real time, pre-processing the data, inputting the pre-processed data into a long-short-term memory network model, and predicting a condensation state and early strength; and the maintenance equipment is automatically controlled according to the prediction result. According to the method, feedback optimization is also performed on the model by utilizing the final actual measurement intensity. Lossless and real-time monitoring and accurate prediction of the internal state of the concrete are realized, automatic and refined closed-loop regulation and control can be performed on the maintenance operation, and the scientificity and efficiency of construction management are improved.

The invention discloses an intelligent construction site multi-dimensional collaborative management method based on BIM and Internet of Things, and the method comprises the steps: carrying out the grouping processing of data through employing a clustering algorithm according to a unified data set after fusion, classifying the data of similar processes, and carrying out the recalculation through adjusting a clustering center if a grouping result shows that the data distribution is not uniform, determining an inter-process logic dependency relationship graph; the method comprises the following steps: acquiring real-time field update data as input through a complex coupling process sequence, predicting the completion time of each process in the sequence by adopting a neural network model, judging whether a prediction deviation is within an allowable range or not, and obtaining an accurate progress prediction result; and deducing a result through a final dynamic resource demand, generating a summary report for a project end process, carrying out mapping display on the result by adopting a visual tool, judging whether a construction period requirement is met or not, and obtaining complete construction management output.

The invention relates to the technical field of building engineering construction, in particular to a construction general level management method based on fitting of a BIM technology and a surveying and mapping technology, and the method comprises the steps: carrying out the butt joint of a point cloud and a BIM model, determining a contour through analyzing a space error, generating a site reference layer, comparing real-time data, judging the layout deviation, and generating a monitoring layer, and analyzing the deviation type to calibrate the non-compliance area and generate a judgment layer, further analyzing resource occupation judgment conflicts and generating a list, finally dynamically updating the resource layout state, and obtaining a construction general level management situation map. According to the method, a reference layer is established through spatial error analysis, a contour basis is formed, spatial offset comparison is performed in combination with a real-time acquisition state, layout differences are dynamically captured, change records are generated, functional area data are compared to identify non-compliance areas, a judgment result is formed, conflict areas are revealed in combination with resource occupation conditions, and a list is generated. And dense and conflict positions are marked in the situation map, so that the site is visualized, and the resource scheduling and construction management efficiency is improved.

The invention relates to the technical field of intelligent construction management, and discloses a construction collaborative management system and method based on robot actual measurement data, and the system comprises a building information model module which stores a BIM model containing a process logic chain; the measurement robot cluster performs actual measurement according to the process logic chain and generates an actual measurement data set; the data twin engine is used for comparing the measured data set with the BIM model, generating a deviation matrix and constructing a collaborative health degree model; the collaborative decision-making module is used for hierarchically generating a local correction instruction or a global dynamic adjustment instruction set according to the health degree index; and the collaborative management terminal is used for visual display. The method corresponds to the system. According to the invention, automatic acquisition, intelligent analysis and dynamic collaborative decision-making of construction quality data are realized, the problems of low efficiency, insufficient coverage and feedback lag of a traditional method are solved, and the automation and intelligent level of construction collaborative management is improved.

The invention provides a construction informatization management method and system, relates to the technical field of informatization management, and is characterized in that an independent work point is used as a unified space and management unit, and static management information in a building information model and project planning data is converted into static management information; and integrating and associating with real-time dynamic data from heterogeneous systems of personnel, equipment, environment, video monitoring and the like, and automatically judging and visually displaying the comprehensive execution state of each independent work site based on a preset rule. The core step of the method is that a construction site is finely divided into independent work points with independent working procedures and management responsibility, and dynamic and static data deep fusion and state evaluation are carried out by taking the independent work points as basic units, so that the problems of information islands and fuzzy responsibility in traditional construction management are effectively solved. And a real-time, transparent and traceable global command view is provided for project managers, so that the refined and intelligent management level of the construction process is remarkably improved.

The invention relates to a road construction project supervision construction real-time state monitoring method and system based on big data. The method comprises the following steps: analyzing multi-source monitoring data to obtain a field matrix set and an adjacent set; feature parameters are extracted based on the field matrix set, and clustering processing is carried out on the feature parameters to obtain a soil property partition set; performing initial risk calculation according to the set, calculating a risk propagation coefficient based on the set and an adjacent set, and constructing a dynamic risk field in combination with an initial risk calculation result; and evaluating the dynamic risk field to obtain a comprehensive evaluation result, and generating a corresponding control instruction according to the result. According to the method, the real-time performance of road construction project supervision construction state monitoring, the accuracy of risk assessment and the refinement level of construction management and control can be improved through data structural processing, soil property partition accurate division, dynamic risk field construction and the like.

The invention relates to the technical field of engineering safety monitoring and intelligent construction management, in particular to a slope deformation automatic identification and risk early warning system and method in the earthwork construction process, and the method comprises the following steps: collecting slope image data and sensor monitoring data, and carrying out the time synchronization processing of the data; extracting deformation characteristics of the slope surface, and generating a risk assessment index threshold in combination with historical data; performing feature analysis on the synchronized monitoring data on a short-term and long-term dual-time scale, and extracting a deformation rate and an accumulated trend index; setting a scene gating factor; calculating a comprehensive risk score; eliminating short-time interference influence; and judging the risk level, and executing early warning response of the corresponding level in a linkage manner, including sound-light alarm and engineering control measures. According to the method, the problems of space-time non-uniformity and insufficient continuity of the sensing layer, insufficient evolution description of the cognitive layer and weak closed loop and edge-cloud collaboration of the execution layer are solved.

The invention relates to the technical field of construction management, in particular to a BIM (Building Information Modeling)-based engineering supervision management system and method.According to the BIM-based engineering supervision management system and method, spatial positions and states of construction machinery, vehicles and personnel are captured in real time through a sensor network deployed on site, and a core dynamic spatial conflict calculation module is used for calculating the safety of the construction machinery, the vehicles and the personnel according to a preset safety rule base; and millisecond-level conflict detection and prediction are carried out on the real-time dynamic safety envelope lines of the moving objects. And after potential risks are found, the system sends early warning of different levels from prompting to forced intervention to related personnel, so that a complete management closed loop from active perception and intelligent prediction to co-processing is constructed. Therefore, through pre-virtual simulation and in-process real-time intervention, the risk of major safety accidents such as collision and overturning caused by space conflicts is greatly reduced, and life safety is guaranteed. And by optimizing the construction space and logistics planning, shutdown and rework caused by conflicts are reduced, and the construction efficiency and the project management refinement level are improved.

The invention relates to the technical field of power infrastructure construction management, and discloses a constructor ability assessment method and system based on an intelligent model, and the method sequentially comprises a multi-source data collection and preprocessing step, an intelligent assessment model construction and training step, and a dynamic early warning mechanism triggering step. The system corresponds to the method. According to the construction personnel capability assessment method and system based on the intelligent model, the multi-dimensional capability associated data is collected and subjected to standardized processing, the traditional data dispersion barrier is broken through, and a high-quality data basis is provided for assessment; secondly, an evaluation result is generated through three-level quantitative transmission, and the limitation that traditional evaluation depends on subjective experience is broken; besides, risk possibilities are output and signals are pushed by constructing an early warning model, so that risk prospective prevention and control are realized, and the actual requirements of electric power infrastructure construction on accurate capability assessment and safety management and control of constructors are met.

The invention relates to the technical field of building construction management, and discloses an intelligent building engineering construction management method based on big data, which is used for solving the problem that the cost benefit evaluation of building engineering cannot be dynamically adjusted in real time according to the project progress in a traditional method. The method comprises the following steps: firstly, collecting construction engineering project progress data, and transmitting the data to a central data processing platform for classification through a wireless network; integrating the collected data, and cleaning and fusing the multi-source data to form a comprehensive data set; updating the cost-benefit evaluation framework based on the data set, and adjusting parameters and weights; calculating an investment and income quantitative index by using an updating framework, and reviewing the initial investment; a budget allocation scheme is adjusted according to the quantitative indexes, priority ranking and resource reallocation are carried out, and a budget plan is generated; outputting a management decision report, and converting the scheme into an executable instruction; real-time dynamic adjustment of cost benefit evaluation is realized, and the construction engineering management efficiency and the resource utilization rate are improved.

The invention provides an intelligent iron tower construction process simulation and optimization method based on digital twinning, which is applied to the technical field of intelligent iron tower construction, and comprises the following steps: obtaining a human intervention event sequence and a construction execution state transition sequence corresponding to each construction stage in a construction process, the human intervention event sequence at least comprises a manual confirmation trigger moment, an unplanned pause trigger type and a manual intervention duration, and the construction execution state transition sequence at least comprises a construction step start-stop state, a state duration and a state switching result; according to the method, the causal influence of human intervention behaviors before and after construction execution state transition is quantified, the causal influence weight is constructed, and the construction sequence is optimized in combination with digital twin construction simulation, so that the problems that construction sequence optimization in the prior art lacks quantifiable constraint parameters and results are unstable are solved; the construction steps are sensitive and stable, the construction sequence can be predicted and executed, and the reliability of construction management decisions and the risk controllability of the construction process are improved.

The invention is suitable for the technical field of unmanned aerial vehicle routing inspection, and provides a water conservancy and hydropower building construction self-adaptive routing inspection unmanned aerial vehicle path planning method and system, and the method comprises the following steps: building a dynamic four-dimensional environment model based on an airborne multi-source sensor of an unmanned aerial vehicle and construction plan data; based on the dynamic four-dimensional environment model, a preset key inspection point and a path fitting algorithm, generating a three-dimensional space path matched with the surface form of the terrain building; when the unmanned aerial vehicle executes an inspection task, sensing environment change in real time, and when an unforeseen obstacle is recognized or dynamic update sent by a construction BIM management system is received, performing local path re-planning based on a composite cost function; according to the invention, the environment information and the construction plan data acquired by the airborne multi-source sensor of the unmanned aerial vehicle can be fused in real time, and the dynamic change of the construction environment is accurately reflected. And local path re-planning is carried out based on the composite cost function, so that the unmanned aerial vehicle can avoid obstacles in time, and smooth completion of an inspection task is ensured.

The invention relates to the technical field of building engineering construction management of the Internet of Things, and provides a multi-modal data fusion-based reinforcing steel bar loss rate dynamic accounting method, which comprises the following steps of: acquiring multi-modal original data, serializing the multi-modal original data into structured entries, identifying corresponding points of video frames and weighing events, selecting the corresponding points as calibration anchor points, and calculating the loss rate of reinforcing steel bars according to the calibration anchor points. The timestamps of all the devices are mapped to a unified timeline through multi-point fitting; splitting according to a blanking rule to form a consumption baseline of component granularity, carrying out quantitative scoring on candidate components, screening accounting units, and obtaining a residual error by solving the difference between the actual consumption amount and the consumption baseline; searching multi-modal evidences in a corresponding time window for the residual exceeding the tolerance, calculating the effectiveness score of each evidence, defining an evidence support weight matrix for each candidate attribution category, multiplying and summing to obtain a candidate category confidence coefficient, and automatically attributing according to the confidence coefficient; and summarizing attribution statistical data indexes according to process dimensions, and checking and analyzing the indexes and historical baselines to identify anomalies.

The invention relates to a BIM-based building complex node construction scheme dynamic simulation method and system, and relates to the technical field of constructional engineering informatization construction management, and the method comprises the steps: carrying out the construction region self-adaptive division of a node BIM model based on multi-dimensional feature clustering, and defining a heterogeneous substrate unit based on a self-adaptive division result; according to the heterogeneous substrate unit, the construction scheme parameters are dynamically divided based on the influence mode, and a bipartite construction parameter set is obtained; and according to the bipartite construction parameter set, performing two-stage dynamic simulation on the construction scheme in combination with the heterogeneous base unit and the node BIM model to obtain a node construction simulation result. The method solves the problems that in traditional complex node construction simulation, complex nodes are not effectively deconstructed, so that the overall simulation precision is insufficient, fixed-time quota is depended, the simulation process is not flexible, influences of different schemes are difficult to quickly evaluate, and scheme comparison, selection and optimization are difficult.

The invention discloses a photovoltaic station construction period main project investment cost collection method, and particularly relates to the technical field of photovoltaic station construction management, and the method comprises the following steps: 1, building a standard division rule of cost collection items, and determining a cost collection list; step 2, establishing an association relationship between the cost collection list and each type of business data; 3, executing automatic collection of the investment cost on the cost collection item to obtain an automatic collection list; 4, performing quality verification on the target collection items in the automatic collection list, and summarizing obtained quality verification results to obtain a quality verification list; 5, matching each item of quality verification with a preset construction acceptance policy form, and executing a construction acceptance policy; the system can achieve the comprehensive management, monitoring and automatic collection of the investment cost of the main project in the construction period of the photovoltaic station, facilitates the improvement of the project management level and management efficiency, guarantees the completion of the project according to the quality, and achieves an expected target.

The invention relates to the technical field of traffic construction management, in particular to a construction management and control system for an intelligent bridge fabrication machine of a railway bridge. The system is deployed based on an industrial cloud platform, construction parameters of the bridge fabrication machine are monitored in real time through a multi-dimensional sensing network, and key indexes such as cantilever construction line shape, load and progress are digitally controlled in combination with an intelligent scheduling algorithm and a resource dynamic allocation model. The core technology of the system comprises a multi-source data fusion construction parameter real-time acquisition module, a digital twinning-based process intelligent scheduling engine, a supply and demand balanced resource dynamic allocation system, a cross-terminal interconnected remote management and control platform, a multi-level early warning safety guarantee mechanism and a whole-process data tracing system. The problems of parameter monitoring lagging, low working procedure collaboration efficiency, unbalanced resource allocation and the like in traditional bridge fabrication machine construction are solved, visual, intelligent and refined management of the construction process is achieved, the construction efficiency is improved, the safety risk is reduced, and the method is suitable for various railway bridge cantilever construction scenes.

The invention relates to the technical field of elevators, in particular to an elevator construction management system and method.The elevator construction management system comprises a data acquisition module used for acquiring operation parameters and environment parameters in the elevator construction process in real time; the data twinning module is used for updating an elevator construction twinning model according to the operation parameters and the environment parameters; the data processing module is used for processing the current elevator construction data reflected by the elevator construction twinning model and generating an optimized construction scheme according to a processing result; and the safety monitoring module is used for generating a construction safety state according to the operation parameters, the environment parameters and the current elevator construction data and generating construction early warning information based on the construction safety state, so that early discovery and active intervention of safety risks are realized. And finally, the core problems of potential safety hazard identification lagging and low transportation efficiency in a traditional mode are solved.

The invention discloses a traffic engineering construction management method and system based on intelligent perception, and belongs to the technical field of construction management. The system comprises an environment sensing module, an intelligent analysis module, a risk assessment module and an early warning prompt module. The environment sensing module is used for collecting GIS map and environment data, azimuth parameters of operation objects in a construction area and operation parameters of moving objects in a road area, and constructing a three-dimensional scene; the intelligent analysis module analyzes the state of the operation object according to the azimuth parameters and sets equivalent points in the three-dimensional scene; analyzing and calculating a weight coefficient of the moving object in combination with the environment data and the operation parameters; the risk assessment module sets detection points for the equivalent points, analyzes the parameters of the driven-in moving object, calculates the risk coefficient of the equivalent points and the risk index of the operation object in combination with the weight coefficient, marks the operation object and sets a safety point; the early warning prompt module gives out acousto-optic early warning through the helmet, and voice prompt marks that the operation object immediately moves to a safety point for danger avoiding.

The invention provides a construction site project intelligent management method based on digital twinning, and the method comprises the steps: collecting construction state data through deploying a sensor array at a construction site, generating twinning input data through space-time alignment and adaptive weighted fusion, and triggering the re-collection calibration when the data fluctuation exceeds a threshold value. Constructing a digital twinborn platform based on the fused data; calculating a progress deviation index to evaluate a construction state; filtering and smoothing short-term fluctuation through a sliding window; predicting a progress trend by using an LSTM model and early warning when a plan is deviated; the emergency degree and the work area contribution degree are comprehensively considered when the scheduling priority is set, a multi-objective optimization algorithm is applied to evaluate resource requirements and dynamically monitor inventory, and finally, an improved ant colony algorithm is adopted to optimize a resource scheduling scheme, so that dynamic management and control of the construction process are realized. The construction management efficiency can be improved, and the resource waste and construction period delay risk can be reduced.

The invention provides an anti-falling device for building construction management, which structurally comprises balance blocks, positioning blocks, locking bodies, grooves and a protective structure, the balance blocks are arranged at the upper and lower positions of the positioning blocks, the positioning blocks are mounted on a building through the locking bodies, and the positioning blocks are connected with the two ends of the protective structure through the grooves; on the basis of the stainless steel positioning block and the locking body, the two ends of the anti-rust body can be positioned through the grooves, then the anti-rust body is fixed through a rebound frame, a rubber block and a magnetic attraction block, the effect of convenient disassembly and assembly is achieved, and then building falling objects can be effectively received and positioned through a rebound net and an elastic block in a receiving groove; and an original pure wood support and an independent rebound net are replaced, so that the durability is improved, the situation that the whole rebound net is punctured due to impact force is prevented, and the actual use strength of the anti-falling object can be improved.

The application discloses a tunnel construction command management method and system based on Internet of Things, and relates to the technical field of tunnel construction management and intelligent construction. The position data of construction personnel and equipment is collected in real time; based on a multi-dimensional rule base, the equipment gathering area, equipment behavior mode and personnel cooperation characteristics are analyzed to identify the current construction process; the start time, end time and actual time consumption of the process are recorded, and a visual progress report is generated; the actual time consumption of the process is compared with a preset standard threshold value to trigger an overtime alarm and hierarchical push; a resource optimization model is constructed to optimize and schedule the approach order of construction personnel, equipment and materials. The scheme deeply combines the Internet of Things positioning data with construction management business logic, realizes automatic identification of the tunnel construction process, real-time monitoring of the progress, active early warning of risks and intelligent cooperation of the process, and effectively improves the fine, automation and intelligent level of construction management.

The utility model discloses a safety belt for preventing high hanging by utilizing a liquid level height difference principle, which relates to the field of building construction and comprises a safety rope, a safety belt is arranged at one end of the safety rope, a hanging part for hanging is arranged at the other end of the safety rope, and a detection device is arranged in the safety rope and is used for detecting the height difference of two ends of the safety rope. An alarm device is arranged on the side, close to the hanging part, of the safety rope, when the detection device detects that the end, connected with the safety belt, of the safety rope is higher than the end, connected with the hanging part, of the safety rope, the alarm device is triggered and sends an alarm signal to a construction manager in time, and the construction manager supervises corresponding workers to correct and improve in time. A power supply assembly is arranged on the side, close to the hanging part, of the safety rope and used for providing electric energy for the detection device and the alarm device. The safety belt has the effect of improving the use safety of the safety belt.

The invention relates to the technical field of bridge engineering, and discloses a cable force optimization and linear control method in the construction process of a cable-stayed bridge, and the method comprises the steps: constructing a finite element model capable of reflecting the physical characteristics of a structure and a construction risk potential model capable of quantifying the construction constraint; on the basis of weather forecast, structure disturbance potential energy caused by environmental factors in the bridge in a future control period is predicted prospectively; constructing a multi-objective optimization problem taking energy hedging residue minimization and total construction risk potential minimization as objectives, and solving to obtain a time-sequenced cable force adjustment operation sequence; after the cable force adjustment operation is executed on site, the actual response of the structure is monitored through the sensor network. According to the method, future environment disturbance can be resisted prospectively, construction management constraints are brought into optimization decision, adaptive evolution and emerging risk identification of the model are realized through closed-loop feedback, and the accuracy, safety and intelligent level of cable-stayed bridge construction control are improved.