182 results about "Control measure" patented technology

The invention discloses a liquefied natural gas (LNG) early warning system and method for dynamically monitoring an LNG ship, and the method comprises the steps: collecting the output amount, cabin pressure, environment temperature and pump operation parameters in real time, combining a multi-factor correction model to dynamically calculate the actual evaporation rate, and reversely setting an allowable evaporation rate threshold according to the maximum capability of a BOG processing system; the evaporation rate is ensured to be within a safe range through a grading alarm mechanism and safety regulation and control measures; the problem that in the prior art, static testing cannot reflect evaporation rate changes in real time is solved. Liquefied natural gas whole life cycle monitoring and performance degradation early warning of the LNG ship are achieved.

The invention discloses a real-time emergency prevention and control system and method for an electrochemical energy storage system based on digital twinning, and belongs to the field of energy storage safety. The system comprises a multi-source sensing unit, a digital twin deduction unit and a visual emergency decision unit. The sensing unit collects multi-source data to form a state vector; the deduction unit outputs a future thermal runaway evolution path containing a temperature field, a gas concentration field and a fire blast risk probability and uncertainty measurement thereof in real time through a pre-trained Gaussian process regression agent model; and the decision-making unit performs three-dimensional visual rendering, jointly determines a high-confidence risk area based on the risk level and the uncertainty level, and generates an emergency prevention and control instruction with accurate spatial positioning. The problems that in the prior art, disaster evolution paths cannot be predicted in real time, and prevention and control measures are extensive are solved, millisecond-level online deduction and accurate active prevention and control of the thermal runaway process are achieved, and the safety of an energy storage system is remarkably improved.

The invention provides a subway tunnel water disaster risk evaluation method under extreme rainfall based on multi-source data, and belongs to the technical field of urban rail transit disaster prevention. The method comprises the following steps: establishing a grading evaluation system on the basis of field rainstorm monitoring data, hydrogeological parameters, field geological exploration, rock-soil physical and mechanical parameters, monitoring data of a tunnel lining structure and material strength parameters of a tunnel site area in combination with a plurality of developed tests, dividing corresponding grades and determining an influence index-; and S4, respectively carrying out weight calculation on the influence index-by adopting an analytic hierarchy process and an entropy weight method, then calculating a dynamic weight of the influence index-, correcting an abnormal dynamic weight, generating a comprehensive score, dividing risk grades, matching graded prevention and control measures, and optimizing and adjusting the prevention and control measures in real time through a parameter risk grade dynamic judgment and construction method matching mechanism. According to the method, minute-level accurate interpretation of a disaster evolution mechanism and dynamic optimization adaptation of a prevention and control scheme are realized.

The invention provides a bridge health monitoring and intelligent control method and system based on machine learning, and the method comprises the steps: carrying out the distributed sensing data collection of a bridge structure, generating a structure monitoring data set, carrying out the spatial-temporal feature extraction, and obtaining a vibration response feature sequence and a traffic load feature sequence of the bridge structure; performing correlation analysis on the two sequences, generating a structural damage sensitive feature matrix, performing damage evolution trend prediction based on the structural damage sensitive feature matrix, generating damage development probability distribution of the bridge key component, and generating a dynamic traffic control instruction according to the damage development probability distribution. The dynamic traffic control instruction comprises a vehicle passing parameter dynamically adjusted based on a damage degree quantitative index, and sending the dynamic traffic control instruction to a traffic management system. According to the invention, the accuracy of bridge health monitoring and the dynamic adaptability of control measures can be improved.

The invention discloses an early warning grade evaluation method based on an urban pollution industrial site, relates to the technical field of industrial site early warning evaluation, and solves the technical problems of incomplete overall evaluation and lack of systematic analysis process and data processing correction caused by analysis of a single evaluation index. According to the method, pollution factor indexes are integrated in a three-dimensional mode through the pollutant standard exceeding multiple mean value, the specific pollutant toxicity coefficient and the pollution plume diffusion area proportion, the pollution intensity is reflected, toxicity hazards and spatial diffusion risks are considered, the soil pollution area is calculated through the Kriging interpolation method, the groundwater pollution plume area is predicted through the MODFLOW model, and the groundwater pollution plume area is predicted through the MODFLOW model. The overlapping area is processed through a maximum area method, repeated statistics is avoided, the accuracy of pollution range data is improved, different threshold values are set, standardized matching of comprehensive indexes and early warning levels is achieved, corresponding management and control measures are defined for all the early warning levels, abstract comprehensive indexes are converted into specific practical operation guidance, and hierarchical management and control can be conveniently carried out.

The invention discloses an operation machine safe operation control method and device based on a three-dimensional electronic fence, and belongs to the technical field of operation machine control. The method comprises the steps of setting a three-dimensional electronic fence based on an actual working environment of a working area; acquiring a first dynamic parameter of the working machine, wherein the first dynamic parameter comprises first three-dimensional position data and first attitude data when the working machine works; calculating a key point coordinate on the operation machine according to the first dynamic parameter; calculating the minimum boundary distance between the key point and the three-dimensional electronic fence according to the coordinates of the key point; and determining and executing a safety control measure according to the minimum boundary distance. According to the method, the relative position relation between the key point of the operation machine and the three-dimensional electronic fence can be accurately determined when the position of the operation machine changes, manual recalibration and confirmation are not needed, dynamic position self-adaption of the operation machine is achieved, misoperation or collision accidents are avoided, and construction safety is remarkably improved.

The invention discloses an argillaceous siltstone geological anchorage deep foundation pit construction method, which relates to the technical field of building construction, and comprises the following steps: collecting stratum structure data, hydrogeological data and surrounding environment data of an anchorage area; determining an integral foundation pit form; a supporting scheme is designed, and a supporting structure type, a construction process and safety prevention and control measures are determined; verifying the stability of the supporting structure; construction resource investment, construction period and risk assessment data of different support schemes are collected, cost-benefit comparative analysis is carried out, and an optimal construction scheme is screened; the construction state is fed back in real time; and the anti-collapse, anti-seepage and anti-disturbance construction requirements under the muddy siltstone geological scene are met. According to the deep foundation pit construction method, a deep foundation pit construction full-process solution matched with the geological scene is formed by adopting double-row secant pile supporting, a targeted cast-in-situ bored pile and anchor cable construction technology and a near-high-rise special monitoring and inner supporting optimization technology.

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 coal mine safety mining and rock stratum control, and discloses a deep roadway surrounding rock multi-parameter dynamic regulation and control method which comprises the following steps: firstly, dividing a monitoring area and collecting gas pressure, surrounding rock displacement, gas release amount and stress data in real time; then calculating a gas pressure influence index and a surrounding rock stress response coefficient representing multi-field coupling characteristics based on the collected data; inputting the characteristic indexes into a pre-trained multiple regression model, and calculating to generate a surrounding rock stability evaluation coefficient of each region; and finally, dynamically dividing the monitoring area into a stable area, an early warning area or an unstable area according to a comparison result of the evaluation coefficient and a set threshold interval, and respectively executing differentiated support regulation and control measures such as current situation maintenance, support strength increase or grouting reinforcement. According to the method, dynamic accurate evaluation and active fine management of the stability of the surrounding rock of the deep roadway are realized by quantifying the coupling effect of a gas field, a stress field and a displacement field.

The invention discloses an intelligent construction site vulnerability identification and prevention and control method based on sensing terminal data, and particularly relates to the technical field of safety risk management and control. The method comprises the following steps of: acquiring and preprocessing multi-source sensing terminal data to construct standardized monitoring data; constructing a unified space-time association layer based on the standardized monitoring data, identifying a function dependency relationship and a space association mode between different construction processes, and determining a key resource occupation relationship and a space interaction mode; identifying dynamic cascade effect characteristics caused by construction rhythm fluctuation between construction procedures; and finally, fusing the space and time sequence coupling strength, determining a key vulnerability conduction path, and formulating a corresponding grading early warning strategy and active prevention and control measures based on the risk grade of the conduction path, thereby realizing accurate identification and active management and control of the vulnerability risk of the intelligent construction site. The prevention and control efficiency and the active response capability of the construction site risk are improved, and safe and stable operation of the intelligent construction site is guaranteed.

The invention discloses an intelligent stability control method, system and device for a red soil slope, and relates to the technical field of monitoring control, and the method comprises the steps: S1, constructing a multi-scale hydraulic-mechanical coupling model and a special parameter library for red soil; s2, monitoring and collecting data information in real time; s3, the seepage-deformation coupling behavior of the slope and the shearing strength of unsaturated soil are analyzed; s4, dynamically predicting an air inlet value parameter alpha (t) and slope suction evolution, and updating a safety coefficient; s5, predicting seepage and deformation response of the side slope; s6, correcting the parameters of the special parameter library for the red layer soil, and returning to S2; s7, triggering a dynamic control module according to the safety coefficient; s8, adjusting the control measures according to the safety coefficient; s9, an executing mechanism corresponding to the dynamic control module works according to the adjusted control measures, and the step S2 is executed again; according to the method, the slope stability evaluation precision and the control efficiency are remarkably improved, and an efficient, intelligent and sustainable solution is provided for red soil slope disaster prevention and control.

The invention discloses a wind power plant icing disaster sensing and early warning method and system. The method comprises the following steps: acquiring SCADA multi-source data of a satellite, a ground station and a wind power plant; performing data noise reduction and feature extraction; inputting the feature data into a physical mechanism model and a data-driven machine learning model in parallel, and fusing the outputs of the physical mechanism model and the data-driven machine learning model by adopting a dynamic weight distribution strategy to obtain an icing thickness predicted value; and early warning information is generated and prevention and control measures are triggered. The system comprises corresponding function modules. According to the method, through multi-source data fusion and mechanism-data driven dual-core model coupling, high-precision prediction and closed-loop prevention and control of the whole cycle from icing formation, growth to ablation are achieved, and the early warning timeliness and accuracy and the operation safety and economic benefits of the wind power plant are remarkably improved.

The invention discloses a tunnel mud burst and water burst intelligent early warning method and system based on multi-modal data, relates to the technical field of tunnel engineering safety monitoring, and solves the problems that in the prior art, the early warning precision is low, the false alarm rate is high, and prevention and control measures are difficult to dynamically match risk positions. According to the technical scheme, the method is characterized in that geological and hydrological multi-modal data are fused to construct a three-dimensional geological and water flow model, and a space-time registration engine is adopted to eliminate positioning errors and guarantee data timeliness; dynamically calculating an inrush risk value in combination with a construction disturbance factor, and quantifying a disaster chain triggering mechanism; according to the risk grade and the space coordinate, automatically mapping a grading prevention and control instruction to realize accurate resource allocation; and the lithology identification rule and the permeability coefficient calculation model are optimized in real time through an event feedback mechanism so as to improve the model precision. The effects that the false alarm rate is remarkably reduced through global accurate early warning, the response speed is increased through dynamic cooperation of prevention and control measures and risks, and construction safety is guaranteed are achieved.

The invention relates to a risk management and control method and device for a power transmission line, computer equipment, a medium and a product. The method comprises the following steps: acquiring real-time monitoring data related to a power transmission line; the real-time monitoring data comprises monitoring data corresponding to multiple risk types; calling a preset risk analysis model corresponding to the risk type, analyzing the monitoring data corresponding to the risk type, and outputting a risk analysis result corresponding to the risk type; the risk analysis result at least comprises a risk level; generating a risk management and control plan corresponding to the risk type based on the risk level and a preset risk management and control measure library; and pushing the risk management and control plan to a risk management and control platform to instruct the risk management and control platform to perform risk management and monitoring. Comprehensive risk analysis is performed on the power transmission line by integrating multiple paths of resource data, and the risk management and control plan corresponding to each risk type is generated and pushed to the risk management and control platform, so that efficient operation and maintenance management of the power transmission line is realized, and the risk management and control efficiency and the management and control effect of the power transmission line are improved.

The application provides a full-chain meat safety knowledge graph construction method and retrieval device, which has the following characteristics: steps S1-S2, entity and relationship extraction is performed on all meat safety standard files; step S3, meat product nodes and corresponding subordinate nodes are constructed and relationships are set; steps S4-S6, corresponding multistage nodes are set for each subordinate node; step S7, the extracted entities and relationships are assigned to the corresponding nodes; step S8, CCP selection nodes including specific hazards and corresponding control measures are set according to the HACCP principle; steps S9-S10, non-directly connected nodes are directly connected as needed through artificial relationships. In summary, the method can construct a more comprehensive meat safety knowledge graph, and the retrieval device can more quickly, conveniently and accurately retrieve and display the data of the meat safety knowledge graph.

The present application relates to the technical field of engineering construction management, in particular to a quality and safety management method and system for water conservancy construction engineering. The present application obtains multi-source heterogeneous data of construction engineering and builds a knowledge graph containing physical domain and non-physical domain nodes, and establishes a dynamic causal model integrating physical causal layer and situational causal layer. The model can be dynamically reconstructed and incrementally learned according to the changes of construction stages and the inflow of new data. When the deviation between the predicted value and the actual value of the model exceeds the threshold value, the system determines it as a risk event, and traces back to the root cause from the physical domain anomaly point to the non-physical domain through hierarchical causal tracing. Finally, the expected impact of different control measures on the construction risk index is evaluated through forward-looking deduction, and the optimal control measures are generated and issued, solving the problem that the prior art cannot perform deep causal attribution, dynamic adaptation and quantitative decision-making.

The invention provides a slope stability evaluation and control method based on multi-factor deformation analysis, and belongs to the technical field of geotechnical engineering.The slope stability evaluation and control method comprises the following steps that S1, multiple monitoring parameters of a slope are obtained; s2, predicting the deformation trend of the slope by using an adaptive depth hybrid prediction model based on the monitoring parameters to obtain a deformation trend probability prediction result; s3, synchronously with the prediction step, performing real-time evaluation on the slope stability by using a stability dynamic evaluation model based on the monitoring parameters to obtain a slope stability coefficient F; s4, performing risk judgment according to the deformation trend probability prediction result and the slope stability coefficient F, and determining the current risk level of the slope; and S5, triggering a corresponding hierarchical control measure based on the current risk level, and carrying out advanced control on the slope stability. The problem that according to a traditional scheme, after monitoring data reach a threshold value, a control measure is started, the slope which starts to deform is controlled, and the optimal intervention period is missed is solved.

The invention discloses a multi-dimensional monitoring and control method and system for a new energy stability control execution station, and the method comprises the steps: configuring two sets of stability control devices at the new energy stability control execution station, and collecting the operation state information of a current collection line; each set of stability control device judges the reliability in real time, issues the data information of the device to another device, and receives the data information of the other device; each set of stable control device sets the cutting priority on line based on the operation state information of each current collection line, calculates the total cuttable capacity and sends the total cuttable capacity to a superior station; after the new energy stability control execution station receives the amount needing to be cut sent by the superior station, undercut amount judgment is sequentially conducted from high to low according to the cutting priority sequence of all the current collection lines till the undercut amount is not larger than an undercut fixed value or traversal of the cuttable elements is finished, and the stability control device acts to cut off the corresponding current collection lines. Accurate calculation of collected and uploaded information and accurate execution of stability control measures of the new energy stability control execution station are realized.

The invention relates to a risk early warning method and device based on new energy output fluctuation and a storage medium, which are applied to the technical field of power system dispatching, and comprise the following steps: obtaining the output deviation level of a generator set under a dispatching output plan through historical data, quantifying behavior deviation and incorporating the behavior deviation into a risk model, the risk assessment result is closer to the physical reality and market environment, and the accuracy and reliability of imbalance risk early warning are remarkably improved; accurate risk early warning is provided before a scheduling plan is executed, so that scheduling personnel can identify potential system imbalance risks in advance and have sufficient time to take preventive control measures, and therefore, occurrence of large-scale imbalance events can be effectively avoided, and safe and stable operation of a power grid can be guaranteed; accurate risk early warning helps to reduce unnecessary standby capacity configuration and emergency control cost, avoids sharp fluctuation of spot market price caused by large-scale output deviation at the same time, and helps to maintain stable and economical and efficient operation of the power market.

The invention discloses a bridge two-dimensional over-limit partition monitoring and early warning and safety risk control method, device, equipment, medium and product, and relates to the field of bridge safety risk control, and the method comprises the steps: carrying out the bi-two-dimensional safety evaluation according to a finite element simulation value of a to-be-evaluated bridge structure state and a real bridge monitoring value, determining the technical condition and the evaluation grade of the to-be-evaluated bridge; determining a plurality of over-limit vehicle load grades based on bridge technical conditions and evaluation grades thereof; determining a load range corresponding to each over-limit vehicle load grade according to the vehicle critical load in the normal use limit state and the bearing capacity limit state; based on this, determining a load upper limit corresponding to the current structure state; and according to the determined load upper limit, determining a current over-limit vehicle load grade from the plurality of over-limit vehicle load grades so as to determine a current early warning grade and a current safety risk control measure, and carrying out early warning and safety risk control on the to-be-evaluated bridge. According to the invention, quantitative evaluation of the bridge safety risk is realized.

The utility model provides a multifunctional recyclable measurement control point protection device, which belongs to the technical field of engineering measurement control points or monitoring references and comprises a foundation connecting layer, a standard connecting layer, a control measurement layer, a rainproof energy storage ceiling and an anti-collision early warning system which are detachably connected. A protective ladder stand is arranged on the side face of the standard connecting layer and the side face of the basic connecting layer, a measuring instrument is erected in the control measuring layer, the anti-collision early warning system comprises a radar anti-collision system and a security monitoring system, and the basic connecting layer, the standard connecting layer, the control measuring layer and the rainproof energy storage ceiling are mechanically connected through bolts. A protection locking device is arranged at the joint of each layer, and the problems that a traditional measurement control point is long in dismantling period, cannot be recycled, pollutes the environment after being dismantled, and is incomplete in security and protection, and the levelness is not easy to master during platform installation are solved.

The invention belongs to but is not limited to the technical field of natural language processing and risk management, and discloses a PPO-RAG-based chemical risk field management and control measure generation method and system, and the method comprises the step of providing a PPO-RAG-based management and control measure generation method. In order to solve the problem that LLM has knowledge hysteresis and insufficient user preference adaptability in a management and control measure generation task, a PPO-RAG framework is established by adopting a mode of combining RAG and reinforcement learning based on human feedback. The framework aims to improve the timeliness and speciality of LLM generation management and control measures, so that the LLM generation management and control measures can better meet diversified requirements in actual application scenes. A final experiment result shows that the method effectively improves the comprehensive capability of LLM generation management and control measures. According to the embodiment of the invention, high-quality management and control measure recommendation service can be provided for the user aiming at the characteristics of high professional property and high complexity of the management and control measures in the risk field.

The invention discloses a goaf disaster simulation and prevention technology verification platform and method, and relates to the field of mine safety and disaster prevention. The verification platform comprises an experiment box body, a variable-angle supporting mechanism, a multi-medium injection system, a sensing monitoring system and a central control cabinet, wherein a heterogeneous porosity goaf is arranged in the experiment box body. The variable-angle supporting mechanism can drive the box body to rotate so as to simulate different inclination angles. The multi-medium injection system can inject gas to simulate disasters and inject media such as liquid nitrogen, inert gas and foam for prevention and treatment through multiple ports such as top, side wall, bottom and working face drag pipes. The sensing monitoring system monitors a temperature field, a concentration field and a pressure field in real time. The method comprises the steps of model preparation, environment initialization, disaster simulation, prevention and control medium injection and effect evaluation on a verification platform. According to the method, goaf multi-field coupling disasters can be reproduced in a high-simulation mode, the effectiveness of various prevention and control measures is quantitatively verified, and data support is provided for mine fire prevention and extinguishing.

The invention discloses a construction method for a shield to pass through an existing pile foundation, which belongs to the technical field of interval shield tunnel underpass, and comprises four parts of pile foundation underpinning design, pile foundation underpinning automatic monitoring and precision control, shield active direct grinding crossing and shield crossing automatic monitoring and cooperative control. According to the pile foundation underpinning design, the stratum disturbance influence of shield crossing is fully considered, and the strength, rigidity and node design of an underpinning structure are optimized; an automatic monitoring system is adopted for pile foundation underpinning and shield crossing, synchronous transmission and fusion analysis of monitoring data are achieved, high-precision control measures are combined, the construction state is fed back in real time, and automatic deviation correction is achieved. The method has the advantages that the problems that in the prior art, shield crossing influences are not considered in pile foundation underpinning design, the passive cutting risk of shield crossing is high, and cooperative control over the two is insufficient are solved, the construction safety, reliability and efficiency are improved, and the method is suitable for shield crossing pile foundation engineering in urban dense building areas.

The application discloses a ground pressure management system suitable for deep mining of underground mines, and relates to the technical field of mine safety monitoring and intelligent control, comprising a perception and collection layer, a transmission and communication layer, a data processing and analysis layer, a risk assessment and early warning layer and a linkage control layer; by arranging multiple types of monitoring units at key parts of the stope, roadway and support, multi-source data such as surrounding rock stress, deformation, dynamic response, support state and environmental disturbance are obtained, and after unified processing by an edge gateway, the data are transmitted to the analysis layer for fusion modeling and abnormality identification. Based on multiple indexes, a comprehensive risk evaluation system is constructed, and dynamic weights are used to realize risk grading and trend prediction, and generate early warning information. The system further links pressure relief, support, mining adjustment and personnel and equipment control measures, and realizes parameter self-adaptive correction through a feedback mechanism, forming a closed-loop management. The system improves the ground pressure monitoring precision, early warning accuracy and disposal efficiency of deep mines.

The application discloses a locust line detection and bias vector alternating light illumination induced thermal magnetic strengthening type direct current electric field killing device, which comprises a system support mechanism, a locust thermal magnetic strengthening type high-voltage direct current electric field killing system, a line detection and bias vector alternating rotation implementation system, a heterogeneous wave spectrum specific frequency flash light source system and a sliding collection system. The thermal magnetic strengthening type high-voltage direct current electric field killing system implements high-voltage direct current electric field killing and excitation strengthening type thermal electric shock killing locust functions. Under the action of the line detection and bias vector alternating rotation implementation system, the wave spectrum frequency flash line detection and bias alternating light illumination induced effect is realized. Under the action of thermal diffusion effect, the magnetic strengthening type locusts gather and the light-thermal-magnetic control locusts are strengthened, which can be used for the suppression and intelligent monitoring of disaster locusts, and can be arranged in a large range in a locust disaster outbreak area and cooperated with other control measures to kill and control locusts in a field and grassland.

The invention discloses a multi-device cooperative inspection safety conflict detection method and system, and belongs to the technical field of intelligent inspection and robot control. According to the method, a UWB positioning base station and a wired interconnected WIFI networking router are deployed in a tunnel, high-precision three-dimensional positioning is carried out on a robot dog, an unmanned aerial vehicle and intelligent wearable equipment which carry UWB tags and WIFI modules, and position and state information is returned in real time; and the ground station terminal dynamically calculates a dynamic safety distance between any two pieces of equipment based on equipment motion parameters and personnel operation states, evaluates a conflict risk probability in combination with an actual distance, and triggers corresponding graded early warning and control measures according to risk grades. According to the invention, high-precision cooperation and intelligent safety conflict prevention and control of multiple types of inspection main bodies in a closed environment are realized, the safety and reliability of inspection operation are remarkably improved, and the method is suitable for complex scenes such as hydropower station tunnels, urban underground pipe galleries and mine roadways.

The application discloses a transient stability prevention control measure generation method and a related system, including the following steps: in a predicted fault scenario, a machine learning model is used to predict the transient stability of the current operation mode of a power system, the input of the machine learning model including various electrical characteristics related to the transient stability of the power system; the operation mode predicted as unstable is taken as an explained sample, a model explanation method is used to determine the influence degree of each electrical characteristic in the explained sample on the transient stability; candidate control units are determined according to the influence degree, and the candidate control units are adjusted, and the machine learning model is used to predict the transient stability of the adjusted operation mode until an operation mode predicted as stable is obtained, so that transient stability prevention control measures are generated. The method improves the explainability of the data-driven transient stability analysis model, the overall scheme requires a short time, and is suitable for online application.

The present application relates to the technical field of slope intelligent monitoring, and particularly relates to a slope prevention and treatment measure generation method and system based on multi-source monitoring data, which comprises: acquiring slope multi-source monitoring data, extracting multi-dimensional monitoring features from the slope multi-source monitoring data; based on the monitoring features, acquiring future time sequence features by using a time sequence prediction model; based on the monitoring features and the future time sequence features, judging the stability grade of the slope and generating corresponding prevention and treatment measures by using a multi-modal fusion model. The method extracts multi-dimensional monitoring features based on multi-source monitoring data, realizes forward-looking prediction of slope stability relying on a time sequence prediction model, synchronously determines the stability grade by means of a multi-modal fusion model and generates measures, forms an intelligent decision-making closed loop, improves the adaptability and accuracy of the scheme, reduces the risk of instability, and has both engineering safety and economy.

The invention discloses an expressway collaborative management and control method, device and equipment and a storage medium. Comprising the steps that constraint conditions and a tool set issued by an operation side are acquired, the constraint conditions are used for constraining behavior boundaries of management and control measures of the operation side, and the tool set comprises management and control measures of economic dimensions; obtaining a constraint condition and a management and control measure set of the operation side, fusing the constraint condition of the operation side with the constraint condition of the operation side to obtain a collaborative constraint condition, and fusing the tool set of the operation side with the management and control measure set of the operation side to obtain a collaborative management and control measure set; in response to a to-be-handled event occurring on the highway, performing optimization solution based on event related information, a collaborative constraint condition and a collaborative management and control measure set, and generating a joint optimization decision; and executing a joint optimization decision, and handling the event. According to the invention, real-time cooperation of operation management and control and operation targets is realized, and the overall consistency and comprehensive benefits of disposal decisions are improved.