520results about How to "Reduce accident rate" patented technology

The invention discloses an intelligent navigation system and method for a ship in the technical field of ship navigation, and the system comprises a sensing module which is used for collecting the surrounding environment information and the state information of the ship in real time; the data processing and fusing module is used for preprocessing, calibrating and fusing the surrounding environment information and the self state information of the sensing module; the route optimization module is used for formulating a navigation plan and a collision avoidance strategy; the navigation control module is used for autonomously controlling the ship according to the output of the ship route optimization module; and the communication monitoring module monitors the navigation state of the ship and the change of the surrounding environment through real-time communication between the ship and a shore-based control center, other ships and a maritime affair management department. According to the method, data of different sensing units are associated, and the associated data are fused, so that mutual verification and complementation can be realized, and the accuracy and reliability of target identification are improved.

The invention discloses a random field theory-based deformation analysis method for a shield to pass through an existing shield tunnel, and the method comprises the following steps: 1, building a shield construction three-dimensional refined numerical model, and exporting central point coordinates of all entity units; 2, determining a statistical characteristic value of the spatial variability of the elastic modulus of the stratum; 3, constructing a three-dimensional random field model of the stratum elastic modulus; 4, importing the three-dimensional random field model of the stratum elasticity modulus into the three-dimensional refined numerical model, and carrying out numerical calculation and analysis; 5, vertical displacement, caused by shield construction, of the stratum at the axis position of the existing shield tunnel is extracted; 6, deformation of the existing shield tunnel is calculated; and 7, calculating the mean value and the standard deviation of the maximum vertical deformation of the tunnel. According to the analysis method, spatial variability characteristics of stratum mechanical parameters are considered, the random field theory and the Monte Carlo strategy are adopted to predict existing shield tunnel deformation caused by shield construction, and the analysis result is more accurate.

The invention provides a wind power industry equipment state on-line monitoring system and a fault analysis method, and the system comprises a signal collection module, a direct monitoring module, an indirect monitoring module, an impact pulse and vibration analysis module, a multi-trend analysis module, a comprehensive diagnosis module, and an analysis report module. Vibration, impact pulse and phase data of a main shaft, a gear box and the like are collected, a phase information matching fault library is fused to evaluate damage, and the actual change rate is calculated to judge the stable state. Time-frequency domain analysis is carried out to identify the shafting problem, and multi-dimensional analysis is carried out to draw an operation map. Feedback of all the modules is integrated, the fault diagnosis module comprehensively evaluates, an analysis report is finally generated, and accurate monitoring and fault early warning of the wind power equipment are achieved.

The invention discloses an electrical energy monitoring method and system, and particularly relates to the technical field of energy monitoring. The method comprises the following steps: monitoring target parameters of power equipment in real time, extracting load volatility characteristics and sampling interval deviation characteristics, calculating a synchronization accuracy value of equipment data in each time period, comparing and analyzing with a gradient standard threshold value, dividing synchronization accuracy into different grades, and implementing corresponding processing measures according to different conditions, so that the accuracy of the power equipment is improved. For accuracy synchronization, the system keeps normal operation; for inaccurate synchronization, the system triggers early warning and starts a self-diagnosis and calibration program; for incompletely accurate synchronization, fault diagnosis errors caused by data asynchronization are effectively avoided by predicting the severity of synchronization errors, adjusting an alarm threshold value in advance and taking corresponding maintenance measures, the safety of power equipment and the reliability of a monitoring system are improved, and the accident risk is reduced.

The invention relates to the field of electric power engineering construction safety management, and particularly discloses an electric power engineering construction safety management system based on multiple sensors. By monitoring the relative deviation distance and direction of the gravity center point, the transfer speed and direction of the gravity center point, the inclination angle and direction of the body and the number and the supporting area of supporting framework joint points corresponding to various postures of the overhead working personnel in the electric power engineering construction process, the falling risk of the overhead working personnel is recognized; monitoring the distance between each easily-impacted part of the body of the aerial working personnel and an object adjacent to the part and the activity coefficient of the object adjacent to each easily-impacted part in the electric power engineering construction process, and identifying the collision risk of the aerial working personnel; the distance between high-altitude operation personnel and all surrounding electrified bodies in the electric power engineering construction process is monitored, the electric shock risk of the high-altitude operation personnel is recognized, recognition and evaluation of various safety risks of the high-altitude operation personnel in the electric power engineering construction process are achieved, and personnel safety is guaranteed.

The invention relates to the technical field of bridge monitoring, in particular to an intelligent bridge structure health monitoring and early warning device which comprises a monitoring base, a supporting mechanism is arranged at the center of the top of the monitoring base, a monitoring top plate is arranged above the supporting mechanism, and a vibration monitoring module is arranged at the top of the supporting mechanism. A distance monitoring module is arranged in the supporting mechanism, an offset monitoring module is arranged on the outer side of the monitoring base, and a protection module is arranged on the outer side of the monitoring base. The vibration sensor, the first infrared distance measuring sensor and the second infrared distance measuring sensor are arranged in the monitoring device, the distance change and the relative position deviation between the bridge support and the bridge deck system are monitored, the vibration condition of the bridge deck system is monitored, the structural health condition of a bridge is comprehensively monitored, and the monitoring efficiency is improved. Therefore, tiny damage and abnormal change of the bridge structure can be found in time, and the bridge accident rate is reduced.

The invention discloses an intelligent monitoring system for the running state of a water turbine. The intelligent monitoring system comprises a data acquisition module, a real-time data pushing module, a data storage module, a state evaluation module and a man-machine interaction module. The data acquisition module is used for acquiring vibration, throw, pressure pulsation and key phase information by using various sensors; the real-time data pushing module is used for distinguishing data types and pushing the data through WebSocket and HTTP protocols; the data storage module adopts a Redis and MySQL double-layer framework; the state evaluation module constructs an evaluation index system, determines a weight by using an entropy weight method and an improved analytic hierarchy process, and determines an operation state through deterioration degree analysis and fuzzy comprehensive evaluation; the man-machine interaction module displays monitoring data and evaluation results, provides a real-time monitoring, data query and state evaluation interface, has the advantages of being fast in data updating, convenient to query, visual in display and the like, can comprehensively monitor the operation state of the water turbine, and provides powerful guarantee for safe and efficient operation of a hydropower station.

The invention relates to the technical field of construction site risk identification, and particularly discloses an infrastructure line construction site environment risk identification system. The system is provided with a three-dimensional distance measurement risk grade determination module, a natural environment risk grade determination module, a construction state risk grade determination module, an environment risk initial evaluation grade determination module and a construction site environment risk judgment module. The problems that monitoring of the safety area and the safety distance of high-risk operation is low in precision, low in efficiency, greatly affected by the environment and difficult to meet the requirement of a modern infrastructure line construction site for safety management exist in the prior art are solved, the construction site can be dynamically monitored under different environments and construction conditions, and through a comprehensive and efficient risk identification and early warning system, the safety management efficiency is improved. The accident rate of a construction site can be reduced, and construction quality and project progress are guaranteed.

The invention discloses a construction site inspection method, inspection system and equipment and a nonvolatile storage medium, and relates to the technical field of intelligent construction, and the method specifically comprises the steps: carrying out the inspection planning according to the inspection requirements of a construction site; based on the inspection plan, executing an inspection task, and obtaining inspection data of a target area; and analyzing the inspection data by constructing a deep learning algorithm model, and carrying out risk event classification based on an analysis result. According to the invention, a closed-loop processing mechanism of data in a platform-nest-unmanned aerial vehicle-platform is driven through control of the unmanned aerial vehicle cruise by the intelligent construction transportation and management platform for construction engineering, and a mobile supervision mode for engineering quality and safety is innovated.

The invention discloses an intelligent automobile path tracking system for urgent danger avoidance, and particularly relates to the technical field of intelligent automobiles, the system comprises an environment sensing module, the output end of the environment sensing module is connected with a danger assessment module, and the output end of the danger assessment module is connected with a path planning module. The output end of the path planning module is connected with a decision planning module, the output end of the decision planning module is connected with a vehicle control module, and the output end of the vehicle control module is connected with a communication and interaction module. Through cooperative work of all the modules, perception of the surrounding environment of the vehicle, danger assessment, path planning, decision making, vehicle control and communication interaction with the outside are achieved, under the dangerous condition, the system can make a response rapidly, effective danger avoiding measures are taken, the driving safety of the vehicle and the accuracy of path tracking are ensured, and the driving safety of the vehicle is improved. And a comprehensive and reliable guarantee is provided for safe driving of the intelligent automobile.

The invention relates to the technical field of highway traffic safety assessment, and provides a highway traffic safety state assessment method and system. Comprising the following steps: acquiring highway historical accident data and road alignment data, and matching the accident data with the road alignment data; the accident rate under each time index and the road alignment index is counted, and a time-space risk index scoring standard is formulated based on the accident rate; calculating the subjective weight of the time index by adopting an analytic hierarchy process, and calculating the objective weight of the road alignment index by adopting an entropy weight method; and constructing a space-time risk index model by integrating the risk score of each index and the weight coefficient, and clustering the space-time risk index based on a K-means clustering algorithm, and dividing the space-time risk index into four safety risk levels. According to the method, the highway traffic safety state can be accurately evaluated, the accident high-incidence period and the accident frequent-incidence period can be identified, it is ensured that targeted management and control measures are formulated at the first time when the high-risk state occurs in the road traffic, and therefore the highway traffic safety level is improved.

The invention provides a V2X-based traffic situation early warning method, system and device, and the method comprises the steps: obtaining traffic data collected by a plurality of data sources, and carrying out the preprocessing of the received traffic data; corresponding traffic indexes are determined according to the preprocessed traffic data, and the traffic indexes at least comprise the vehicle pedestrian flow, the vehicle average speed and the lane traffic situation; wherein the lane traffic situation at least comprises a corresponding grade representing a road congestion condition in a preset time period, and the corresponding grade at least comprises one of unblocked, mild congestion, moderate congestion and serious congestion; and evaluating a corresponding traffic situation condition according to the traffic index, and if the traffic situation condition is abnormal, outputting corresponding risk early warning information. Through the real-time data monitoring technology, the urban traffic management efficiency is improved, the traffic jam problem is relieved, and the comprehensiveness and accuracy of information are ensured.

The invention discloses an intelligent port comprehensive management system based on big data, and relates to the technical field of port energy management, and the system comprises a data collection and integration module which is used for deploying a plurality of sensors in each key region of a port, and a data collection device which is used for collecting the data of the ship position, the cargo flow, the device state and the environmental condition in real time, and through real-time data collection and integration, management personnel can quickly know the operation condition of the port. The intelligent port comprehensive management system based on big data has the advantages of real-time data collection and integration, intelligent scheduling and operation optimization, and the system can quickly respond to port operation requirements and adjust resource configuration and operation strategies in real time, so that the waiting time of ships and cargoes is shortened, the loading and unloading operation and prediction analysis are optimized, and the management efficiency is improved. The resource utilization rate and the efficiency of the operation process are remarkably improved, and managers can make decisions more accurately according to the data analysis result, so that the operation cost is reduced, and the customer satisfaction is improved.

The invention provides an on-line detection system and method for oil leakage of a transformer, and the method comprises the steps: an oil pressure detection module detects the oil pressure of the transformer, and transmits the oil pressure data to a microprocessor for processing; the microprocessor converts the oil pressure of the transformer into the oil level of the oil conservator, and when the oil level of the oil conservator is lower than the oil level at the lowest oil temperature all the year round, an over-low oil level alarm is given; the temperature detection module is used for detecting the oil temperature of the transformer and sending oil temperature data to the microprocessor for processing; the microprocessor records an oil level-temperature curve of the transformer, calculates the theoretical oil level h2 of the oil conservator through the oil temperature detected by the temperature detection module, compares the theoretical oil level h2 with the oil level h1 of the oil conservator calculated through the pressure detected by the oil pressure detection module, and gives out an over-low or over-high oil level alarm when the deviation is too large.

The invention relates to the technical field of 3D printing, in particular to a method for cleaning a waste barrel of a purification box and the purification box. The method for cleaning the waste barrel of the purification box comprises the following steps: providing a closed space, and placing the purification box in the closed space; the barrel body and the barrel cover of the waste barrel are separated through the driving mechanism; the moving device moves the barrel body to a grabbing position; the grabbing mechanism grabs the barrel body and moves the barrel body to a rotating position, the grabbing mechanism turns over the barrel body so that a barrel opening of the barrel body faces downwards, and the barrel body is vibrated so that metal powder in the barrel body can be poured out; the moving device moves the barrel body to the cleaning position, the cleaning mechanism cleans the barrel body, automatic cleaning of the waste barrel is achieved, and the cleaning efficiency of the waste barrel is improved; the safety of workers is well guaranteed, and the accident rate is greatly reduced. The purification box can adopt the method for cleaning the waste barrel of the purification box, the cleaning efficiency of the waste barrel is improved, the safety of workers is guaranteed, and the accident rate is reduced.

The invention discloses a vehicle anti-collision method and device for a mining area intersection based on the C-V2X technology in the technical field of intelligent traffic, and the method comprises the steps: obtaining the vehicle information of a vehicle, and judging whether the vehicle enters an area around the intersection or an intersection area or not according to the vehicle information of the vehicle; after the vehicle drives into the surrounding area of the intersection, vehicle information of a nearby vehicle is obtained through V2V communication; after the vehicle is driven into the intersection area, judging whether a nearby vehicle is driven into the intersection area or not according to the vehicle information of the nearby vehicle; if there is an adjacent vehicle entering the intersection area, predicting driving tracks of the own vehicle and the adjacent vehicle in the intersection area according to the vehicle information of the own vehicle and the adjacent vehicle; and performing anti-collision processing according to the driving tracks of the own vehicle and the adjacent vehicle in the intersection area. According to the invention, the traffic safety of the intersection of the mining area can be obviously improved.

The invention belongs to the technical field of railway foundation pit construction safety monitoring, and discloses an intelligent monitoring and analyzing system for railway construction safety. Comprising a supporting structure safety analysis module, a geologic structure safety analysis module, a self-structure safety analysis module, an external factor data analysis module, a foundation pit safety problem identification module, an influence area data acquisition module and an influence area abnormity identification module. According to the method, the structure safety is comprehensively evaluated by integrating the supporting structure safety, the geologic structure safety and the self structure safety, and meanwhile, the abnormal conditions of external factors of the target foundation pit are analyzed by monitoring other behaviors influencing railway driving; the invention further relates to monitoring of construction equipment in the possible influence area of the target foundation pit, and further analysis of the construction safety abnormal condition of the influence area of the target foundation pit, so that the foundation pit construction safety management level and the overall construction efficiency are improved, smooth foundation pit construction is effectively guaranteed, and potential risk hazards are reduced.

The invention discloses an intelligent scheduling system for tunnel construction operation objects, and the system is characterized in that the construction system comprises a data collection module, a data processing module, a scheduling decision module, an execution and feedback module, and a user interface module; through highly integrated data acquisition, processing and decision making modules, the system can respond to the change of a construction site in real time and optimize scheduling decisions, so that the construction efficiency and the resource utilization rate are remarkably improved. Through the real-time monitoring and dynamic adjustment functions of the execution and feedback module, the scheduling system can respond to onsite emergencies in time, project delay and overhigh cost are reduced, and the construction progress and quality are guaranteed. The user interface module provides a visual and easy-to-operate interaction platform, so that a dispatcher can effectively monitor and manage the whole construction process, and the operation convenience and the decision accuracy are improved. The risk assessment and management function of the system strengthens the construction safety, and by predicting and preventing potential risks, the accident rate is obviously reduced, and the safety of personnel and equipment is guaranteed.

The invention discloses a driving strategy dynamic adjustment method and system based on driving style recognition. The method comprises the following steps: establishing a driving style classification model; monitoring the behavior data of the driver in real time, completing the confirmation of the driving style of the driver by using a data-driven adaptive algorithm, and dynamically updating the driving style classification model; on the basis of the driving style of the driver, specific behaviors of the driver in different situations are considered, and a scene-driven self-adaptive control strategy is applied to output a current driving strategy of the vehicle; and optimizing the current driving strategy of the vehicle through the interactive feedback of the driver in the driving process. The method can assist the automatic driving system in providing a driving experience mode more conforming to the personal preference of the driver, and improves the comfort and satisfaction of the driver in combination with an intelligent interaction and strategy closed-loop mechanism, and meets the individuation and dynamic adaptability of the automatic driving system.

The present invention discloses a method and system for monitoring fall prevention safety of aerial work, the method includes obtaining physiological sign data and operation behavior data of aerial work personnel, use status data of fall prevention devices and environmental data; determining human risk index, equipment risk index and environmental risk index; judging whether there is a situation where the risk value among human risk index, equipment risk index and environmental risk index is greater than a first preset threshold value; if so, triggering an alarm prompt and generating a first operation guide to push to the aerial work personnel; if not, determining the fall risk value according to the human risk index, equipment risk index and environmental risk index, and when it is greater than a second preset threshold value, triggering an alarm prompt and generating a second operation guide to push to the aerial work personnel. The present invention takes into account more comprehensive risk factors, so that the fall risk value can be accurately predicted, and different operation guides are provided for different risks, thereby improving the energy efficiency of aerial work safety monitoring.

The invention provides an efficient waste steel slag treatment process, and relates to the technical field of waste steel slag treatment. The device based on efficient waste steel slag treatment comprises the following steps that S1, large steel slag is subjected to crushing, iron separation and grinding, and steel slag powder is obtained; s2, the steel slag powder is matched with a leaching agent for pulping leaching, and in the leaching process, CaO and a small amount of MgO components in the slag are decomposed and subjected to a chemical reaction with ammonium chloride; s3, carrying out solid-liquid separation to dissolve main alkaline components in the steel slag, and improving the separation efficiency by adopting a plate-and-frame pressure filtration method; through the process technical design, in the treatment process of the waste steel slag, the effects that the reaction temperature is low, the energy consumption is low, the dielectric loss is small, a medium does not react with FeO, the iron loss is small, the concentration of calcium and magnesium ions in a leached solution is high and the like can be achieved, and meanwhile a large amount of CO2 can be consumed; through a leaching process, a leaching reactor and a quantum ring activation process are adopted, so that the later reaction time can be shortened by about 70%, and the accident rate can be reduced by 80%.

The invention provides a vehicle motor control method and device, a vehicle and a storage medium, the method is applied to the technical field of motor control, and the method comprises the steps that the rotation period of a steering actuator motor and output current change information of the steering actuator motor are obtained; determining a duty ratio based on the rotation period and the output current change information; generating a pulse width modulation (PWM) signal based on the duty ratio and the rotation period; and adjusting the torque of the road sensing motor based on the PWM signal. The method can improve the reliability and safety of vehicle driving.

The invention discloses a supervision and management method for construction operation and a pre-class education supervision system, and relates to the technical field of data processing. Firstly, learning videos corresponding to all construction workers in the supervision and management system are obtained through matching, and then progress data in learning hosts of all the construction workers are analyzed, so that the safety awareness of the construction workers can be evaluated; and then the safety data of each construction work subordinate sub-region and the behavior characteristic data of each construction worker are analyzed, so that the pre-class education learning effect of the construction worker in the actual work process can be analyzed, potential safety hazards can be identified, the working strategy can be adjusted in time, the accident risk is reduced, and the working efficiency is improved. And finally, comprehensively analyzing to obtain a learning effect evaluation value of the supervision and management method for the construction operation, and further adjusting the supervision and management method, so that the management process can be continuously optimized, and the safety awareness of construction personnel is further improved.

The invention relates to the technical field of traffic safety management, in particular to an expressway emergency response blocking device, system and method, which are arranged on a preset road section, and comprises the following steps: a road detection system monitors data of key indexes of vehicles and road conditions in real time; the remote control system receives the data, transmitted by the data transmission system, of the road detection system, judges the road condition according to the data, activates corresponding emergency measures automatically or through manual instructions according to the road condition, and dispatches and guides starting and stopping of the warning system and the physical interception system; the guiding and warning system is used for guiding and warning; when the physical interception system is activated, an entity or virtual barrier is formed to block a road; the road section information feedback system carries out information transmission with an external user system and information transmission between the expressway emergency response blocking devices of different road sections. According to the scheme, the safety and the emergency response efficiency of the expressway are greatly improved, the accident rate is reduced, and secondary accidents are minimized.

The invention discloses an energy storage system insulation detection method based on artificial intelligence, and the method comprises the steps: collecting the electric digital data and text data of an energy storage system, and carrying out the vectorization processing of the text data based on a BERT model, so as to facilitate the subsequent modeling analysis, then, key features related to the insulation state are extracted from the electrical digital data and the vectorized text data through a GBDT algorithm; based on the selected features, constructing a GBDT model for predicting the insulation state of the energy storage system; preprocessing the collected data, and dividing the data into a training set and a test set; adopting a K-fold cross validation and grid search method to train the GBDT model; and evaluating the trained model by using test set data, and selecting MAE and Ras evaluation indexes. According to the invention, the accuracy and prediction capability of insulation detection are obviously improved, preventive maintenance is realized, the service life of equipment is prolonged, and the overall safety management level of the energy storage system is enhanced.

The invention discloses a direct-current power transmission system EM lightning arrester zinc oxide resistor disc selecting and balancing method, and belongs to the technical field of lightning arrester disc selecting and matching. The disc selecting method comprises the steps that S1, direct-current parameter testing is carried out, and damped and aged resistor discs are removed based on the direct-current parameter testing result; s2, applying lightning and operation impact to the resistor discs, measuring residual voltage, calculating a voltage ratio based on the residual voltage, and rejecting the resistor discs of which the voltage ratio deviation is not within a set voltage ratio threshold range; s3, carrying out square wave energy testing on the resistor discs, and removing the damaged resistor discs in the testing process; s4, performing long-wave residual voltage test on the resistor discs one by one by using the test square wave, recording a long-wave residual voltage value obtained by the test, and removing the resistor discs which are subjected to breakdown, flashover and aluminum surface burning in the test; calculating long-wave residual voltage deviation of the resistor discs under square wave excitation, and removing the resistor discs with the long-wave residual voltage deviation exceeding a set long-wave residual voltage deviation threshold value; and the sheet selection scheme of the EM lightning arrester is perfected, and the accident rate is reduced.

The invention discloses a road risk simulation avoidance system and method based on multi-mode Internet of Things perception, and belongs to the technical field of intelligent traffic, and the method comprises the following steps: collecting the road condition information and road section characteristic parameters of a current road section in real time; screening out a plurality of monitoring vehicles; extracting historical driving behavior data and road condition characteristics of the plurality of monitored vehicles; constructing a historical driving behavior model, and constructing a scene model; extracting historical traffic road condition information, and extracting static feature data through the scene model; constructing a spatial feature matrix, and constructing a spatial-temporal feature matrix; performing feature weighted fusion on the spatial feature matrix and the spatial-temporal feature matrix to obtain a multi-model fusion evaluation result, and calculating a vehicle collision probability; and a vehicle owner is prompted to avoid danger and adjust steering, and an auxiliary steering avoiding function is started through the intelligent danger avoiding module. The problems that a traditional monitoring function cannot achieve risk modeling early warning and risk avoidance and lacks a multi-vehicle collision real-time prediction function are solved.

A sequential control simulation method and system of a centralized control station simulation system comprises the following steps: establishing a primary wiring diagram and an interval diagram through the simulation system, and collecting data information; establishing an equipment switch disconnecting link association table; associating equipment of the simulation system with a switch and a disconnecting link associated with the equipment, and establishing an index; decomposing the operation state of the equipment according to the association of the equipment, the switch and the disconnecting link to obtain the operation state of the switch; based on a switch operation state, establishing an indexed equipment switch disconnecting link association table, and modeling a scheduling instruction ticket; on the basis of the obtained scheduling instruction ticket model, the simulation system automatically generates an operation instruction ticket according to the initial state and the target state according to the equipment state recorded by the equipment switch disconnecting link association table with the established index; analyzing the operation instruction ticket according to a time sequence to form an event set, and inserting a to-be-executed event list of the simulation system; and the simulation system carries out analysis according to the time sequence and feeds back corresponding states including operation success or operation failure, and one-key sequential control is completed.

The present invention relates to the field of performance monitoring technology, specifically to an online monitoring system for shield tunnels, the system comprising: a real-time data acquisition module collects data on shield machine cutter disc wear and geological conditions in real time based on the cutter disc wear state and geological data, analyzes the wear mode of the contact between the cutter disc and the rock and soil, identifies the current construction environment, and obtains real-time geotechnical mechanical parameters and construction conditions. In the present invention, through real-time monitoring and refined geological condition analysis, it is possible to accurately grasp the key parameters in the tunnel excavation process, optimize the construction strategy, and enhance the adaptability to complex geological changes. The risk assessment and early warning mechanism can timely discover and respond to possible safety issues, thereby reducing the accident rate and ensuring the safety of construction personnel and equipment. By analyzing the predicted geological conditions, the excavation path is adjusted to adapt to the geological difficulties that may be encountered in the future, thereby achieving greater flexibility in project management and reducing potential economic losses.

The invention relates to the technical field of building geological data management and decision making, and discloses a virtual reality-based building geological data management and decision making system, which comprises the following steps of: establishing a two-dimensional coordinate system on the ground by taking the position of a tower body of a tower crane on the ground as an original point; executing a dangerous area dynamic calculation strategy, and calculating the range of the dangerous area in real time; executing a constructor position prediction strategy, and predicting the position of each constructor at a future moment; according to the predicted position of each constructor at the future moment, a constructor danger judgment strategy is executed, if it is predicted that the constructor enters the dangerous area at the moment, a personnel moving direction planning strategy is executed, a new moving direction is planned for the constructor entering the dangerous area, and a cargo moving path planning strategy is executed; and the position of the goods at the moment is planned, and the decision process of tower crane goods transportation is optimized, so that the construction site safety and the working efficiency are improved.