690 results about "Emergency control" patented technology

The invention relates to the technical field of energy storage systems, in particular to a source network load storage coordination control method for multi-configuration network type energy storage coordination operation. According to the technical scheme, the source-network-load-storage coordinated control method for multi-construction-network-type energy storage coordinated operation comprises the following steps: generating a new energy output and load change trend through a dynamic prediction model based on historical power data, real-time load requirements and meteorological information; optimization is carried out to obtain a power generation plan containing a clean energy consumption target and economical efficiency constraints; decomposing the power generation plan into a photovoltaic power adjusting instruction, an energy storage charging and discharging instruction and a load control instruction according to the power grid safety priority, wherein the emergency control instruction is executed prior to the economic dispatching instruction; and controlling parallel operation of a plurality of pieces of networking type energy storage equipment, and realizing multi-machine power distribution and circulating current suppression through a virtual synchronous control technology. And through layered optimization scheduling and multi-machine cooperative control, the new energy consumption capability is remarkably improved, and the phenomenon of abandoning light and wind is reduced.

The invention provides an edge calculation traffic light emergency control method and device for a sudden traffic event. The method comprises the following steps: acquiring real-time traffic flow information of a target intersection; determining an emergency response area of the target intersection based on the position identifier of the sudden traffic event, and extracting a dynamic offset between a historical traffic flow feature and a current traffic flow feature in the emergency response area through an edge computing node; inputting the dynamic offset into a pre-trained traffic signal adaptive model, generating a traffic signal lamp control parameter set corresponding to the emergency response area, and sending a control instruction sequence to the traffic signal lamp of the target intersection according to the traffic signal lamp control parameter set, and the execution priority of the control instruction sequence is dynamically adjusted based on the real-time change trend of the vehicle density distribution data and the pedestrian movement track data. According to the invention, the intersection passing efficiency and the safety guarantee capability of traffic participants under the sudden traffic event can be improved.

The invention discloses an expressway emergency management and control method and system, and the method comprises the steps: building a multi-dimensional heterogeneous data fusion model through a time-space diagram neural network according to the traffic flow, meteorological data and accident reports collected by roadside sensing equipment, and carrying out the dynamic prediction of the risk level of a road segment, and obtaining a real-time risk level map of a whole road network; based on the real-time risk level map, outputting a dynamic shunting scheme containing variable lane marks and a speed limiting strategy; according to the dynamic shunting scheme, generating a vehicle trajectory optimization strategy; and outputting an anti-interference optimization control strategy based on a vehicle trajectory optimization strategy in combination with sudden obstacle data polled by the unmanned aerial vehicle in real time. According to the embodiment of the invention, rapid and accurate path adjustment and cooperative control can be carried out, and the emergency management level of the expressway is improved.

The invention belongs to the technical field of digital twinning, and discloses a hydraulic engineering-oriented digital twinning model dynamic construction and risk assessment method, which comprises the steps of dividing a hydraulic engineering into a static basic component area and a dynamic response area, accessing historical hydraulic engineering data, combining BIM and a finite element analysis technology, and carrying out dynamic construction and risk assessment on a digital twinning model. Constructing a structure model of the static basic component area and an agent model of the dynamic response area; combining the structured model with the proxy model to obtain the hydraulic digital twin; state data in the water conservancy digital twinborn body operation process are collected, and a twinborn state sequence is generated; constructing a water conservancy semantic map, and carrying out semantic binding on the water conservancy digital twin, the real-time water conservancy data and the control logic; dynamically updating a twinning state sequence when the node state of the water conservancy semantic map changes by adopting an event-driven strategy; and the response time efficiency and the emergency regulation and control capability of the water conservancy project are further improved.

The invention relates to an intelligent safety protection management method and system. The method comprises the following steps: acquiring behavior data and position data of personnel in an industrial site; analyzing the behavior data and the position data by using a pre-trained personnel behavior model to obtain a behavior recognition result; according to the behavior recognition result and the current operation state of the target equipment, judging a risk level corresponding to the personnel behavior; based on the risk level, a corresponding safety response strategy is matched in the edge computing node, a control instruction is generated according to the safety response strategy, and the control instruction is used for driving the target device to execute a corresponding response action; and the voice interaction module is used for acquiring voice input of an on-site operator, performing semantic recognition on the voice input to obtain a voice recognition result, and executing corresponding emergency control operation to cover a current control instruction when the voice recognition result meets a preset emergency instruction condition. The method has the effect of improving the accuracy of intelligent safety management in the industrial environment.

The invention belongs to the technical field of unmanned aerial vehicle flight control, and particularly relates to an unmanned aerial vehicle intelligent dynamic obstacle avoidance method and system based on ultrasonic frequency self-adaption. The method comprises the following steps: 1, monitoring the position and distance of a static obstacle in real time, and adjusting the ultrasonic emission frequency; the neighborhood environment of the unmanned aerial vehicle is detected in real time through barometer equipment, the attitude, acceleration and angular velocity of the unmanned aerial vehicle are provided through an inertial sensor, and data are preprocessed after the surrounding environment of the unmanned aerial vehicle is comprehensively sensed; 2, performing a dual-stage mode of offline training and online updating through CNN-AE and LSTM decision engines, generating an obstacle avoidance path, and dynamically adjusting a flight strategy according to a real-time environment; 3, adaptively adjusting the reward weight according to the obstacle distance through a dynamic priority reward function, and guiding the unmanned aerial vehicle to make an optimal decision and path optimization in the flight process; and 4, through an emergency control module, triggering a local decision based on a Q value table when communication is interrupted, and ensuring that the unmanned aerial vehicle can still fly safely under an abnormal condition.

The invention discloses a self-adaptive control method for operation of a coupler unhooking robot under multiple working conditions, and relates to the technical field of coupler unhooking, and the method comprises the steps: obtaining a target unhooking robot, and collecting and obtaining an operation environment data flow and a coupler state data flow; working condition sensing and coupler recognition are conducted, and the current working condition and coupler feature information are obtained; performing traversal retrieval and adaptive adjustment in the unhooking strategy database, and determining target unhooking strategy parameters; and executing unhooking operation according to the target unhooking strategy parameters, and performing adaptive closed-loop control and abnormal emergency control on the target unhooking robot based on the unhooking operation state data flow. The technical problems that in the prior art, a car coupler unhooking robot is difficult to adapt to complex and various working conditions, and consequently the unhooking operation accuracy, safety and efficiency are poor are solved, accurate sensing of the working conditions of the car coupler unhooking robot is achieved, and the technical effect of improving the unhooking operation accuracy, safety and efficiency is achieved.

The present invention belongs to the field of smart power grids and power system automation control. Disclosed is a load emergency control method based on a dynamic event triggering mechanism, which method comprises: on the basis of an indicator of safe operation of a system, performing region division on a distribution network; proposing an adaptive load level division method based on user response willingness, and by taking the minimization of the system operation cost of the distribution network as an objective, establishing a precise load control model of the distribution network; and using a dynamic event triggering mechanism to reduce communication between substations and a master station of the distribution network, so as to realize effective exchange and precise execution of load control policy information. The method of the present invention can precisely realize precise control of a load, and can effectively alleviate communication transmission pressure of a distribution network, thereby ensuring the stability of a power grid and the continuous supply of critical loads.

The invention belongs to the field of unmanned aerial vehicle emergency control systems, and relates to a risk identification and emergency method when an unmanned aerial vehicle flies in an airspace adjacent to an expressway, and the method comprises the steps: obtaining the balance state of the unmanned aerial vehicle through constructing a six-degree-of-freedom dynamic model and incorporating environmental factors and control intentions; dynamically comparing the balance state with real-time data to obtain a state deviation, deducing the fault probability of the unmanned aerial vehicle according to the state deviation, and realizing sensitive early warning of possible faults of the unmanned aerial vehicle; besides, the method constructs a double-layer linkage framework of an electromagnetic safety boundary and a physical safety boundary, realizes safety risk identification in combination with a fault probability, and ensures that a safety area between the unmanned aerial vehicle and a motorcade on a highway can be represented by a risk value along with speed, motorcade density and interference intensity; the fault probability of the unmanned aerial vehicle flying in the air is considered, when the fault probability is larger than a preset threshold value, the out-of-control state of the unmanned aerial vehicle is judged, a corresponding control strategy is adopted, and the flight safety of the unmanned aerial vehicle during partial or comprehensive out-of-control is guaranteed.

The invention relates to the technical field of coal mining equipment, and discloses a mining roadway stability real-time monitoring and early warning system which comprises the following steps: S1, multi-source sensor network deployment, S2, data transmission and preprocessing, S3, stability index dynamic calculation, S4, fusion early warning model construction and S5, graded early warning triggering. Roadway surrounding rock deformation, stress, vibration and environmental parameters are collected in real time through a multi-source sensing network, efficient data transmission and preprocessing are achieved in combination with an industrial looped network, surrounding rock strain energy density, displacement convergence rate, support failure coefficient and other key indexes are dynamically calculated, a fusion early warning model is constructed based on machine learning, and the early warning accuracy is improved. According to the method, accurate evaluation of the stability level is achieved, grading alarm and emergency control are automatically triggered when a threshold value is reached, a'perception-analysis-decision-response 'closed loop is formed through the design, the real-time performance of roadway stability monitoring and the early warning reliability are remarkably improved, and accidents such as roof fall and wall caving are effectively prevented.

The invention discloses a reaction condition optimization control method and system for biological aviation kerosene production, and particularly relates to the field of biological aviation kerosene production. The method comprises the following steps: firstly, acquiring parameters such as temperature, pressure, flow, catalyst activity and raw material components of biological aviation kerosene in real time through a sensor module consisting of a temperature sensor, a pressure sensor, a flow sensor and the like, and then carrying out pretreatment operations such as median filtering and wavelet denoising on acquired data; constructing an LSTM-Transformer hybrid model based on the preprocessed data to predict the second-by-second value of each parameter in the future 10 minutes, correcting the predicted value according to a catalyst activity index formula, further optimizing the prediction model by using a shadow model, comparing the predicted value with a preset interval and a threshold value, judging the state of the predicted value, and determining the second-by-second value of each parameter in the future 10 minutes. And finally, generating a fixed fine-tuning, strengthening or emergency control strategy according to a judgment result. According to the method, the biological aviation kerosene production reaction conditions can be accurately predicted, regulated and controlled, and the production stability, safety and product quality are improved.

The invention discloses a source network load storage coordination control system and method for high-capacity multi-network energy storage combined transportation. The system comprises a master station layer which is responsible for receiving a superior scheduling instruction, issuing an emergency control instruction, and performing economic optimization scheduling and rapid coordination control on photovoltaic and energy storage resources; the substation layer is responsible for accessing photovoltaic, load and energy storage resource information and decomposing and issuing superior instructions to realize a local frequency voltage control function; and the terminal layer is used for receiving a generator tripping command or a power regulation command issued by the emergency state monitoring device. The system can effectively improve the network-related performance of a new energy station, enhance the stability and reliability of a power grid, improve the absorption capability of new energy, and optimize the economical efficiency of the system. Through combined operation of the network construction type energy storage equipment and the new energy, effective support for the power grid is realized, the problem of coordination control of parallel operation of multiple voltage sources is solved, oscillation and circulation are avoided, and the overall performance and the power supply guarantee capability of the system are improved.

The invention relates to the technical field of intelligent monitoring, in particular to a hydraulic engineering operation state monitoring method and system. The method comprises the following steps: monitoring corresponding water conservancy dam body stress-strain data, water conservancy dam body osmotic pressure data, water gate opening position data, water area water level data and water area flow velocity data in real time; the method comprises the following steps: acquiring regional meteorological data and regional landform data corresponding to the periphery of a water conservancy project, carrying out dam body displacement analysis and sluice opening statistics, and meanwhile, carrying out water area potential influence mining analysis to obtain corresponding meteorological potential factors and landform potential factors; and performing water conservancy operation risk monitoring and emergency early warning control on the operation facilities corresponding to the water conservancy project based on the water conservancy dam body seepage displacement and the water conservancy gate opening degree in combination with the meteorological potential factors and the terrain potential factors corresponding to the water area of the water conservancy project so as to generate an operation state emergency control plan corresponding to the water conservancy project. The overall operation level of the water conservancy project can be improved.

The invention relates to the technical field of electric power system control, and discloses an emergency control coordination method for power angle stability of an electric power system and related equipment, and by obtaining time domain simulation data of a system test fault and constructing a power angle stability margin, early warning can be performed before the power angle of the system is unstable. The early warning mechanism is helpful for taking measures in advance and preventing the system from entering an unstable state. And when the power angle of the system is indeed unstable, the effects of different control measures can be quickly predicted through the constructed power angle stable sample set and the trained convolutional neural network model, so that quick response is realized, and measures are taken. By constructing the emergency control optimization model considering the control sensitivity, the effects and the sensitivity of various control measures can be comprehensively considered, so that the optimal emergency control strategy is determined, and the control on the system stability is effectively improved according to the optimal emergency control strategy.

The invention discloses a data interaction self-adaptive method for a photovoltaic protocol converter, and particularly relates to the technical field of power grid dispatching cooperative control. The method comprises the following steps: monitoring and calculating a voltage instantaneous change rate of a grid-connected point of a power grid in real time, and comparing the voltage instantaneous change rate with a threshold value; when a threshold value is exceeded, synchronously collecting a current phase and generating a voltage and current phase difference change direction; extracting a voltage high-frequency component, analyzing frequency band energy distribution through wavelet packet decomposition, and calculating a Shannon entropy representing an energy concentration ratio; when the phase difference change direction accords with a preset power grid short-circuit fault feature and the Shannon entropy value is lower than a preset entropy threshold value, determining that a power grid transient event occurs; at the moment, a data caching mechanism of the protocol converter is stopped immediately, and a real-time stream transmission channel is activated; an emergency control instruction issued by a power grid dispatching system is directly transmitted to the photovoltaic inverter through the channel; and when the voltage instantaneous change rate is continuously lower than the preset threshold value for a preset duration, recovering the data caching mechanism of the protocol converter.

The invention relates to the technical field of underground coal mine safety, and discloses an underground coal mine early warning system and method. The method comprises the following steps: collecting multidimensional monitoring data of an underground coal mine environment; performing dynamic window division on the multi-dimensional monitoring data to generate a data fragment set; performing abnormal mode recognition based on the data fragment set, and extracting abnormal feature points exceeding a dynamic threshold in each data fragment; inputting the abnormal feature points into a pre-constructed space-time correlation model, and analyzing diffusion paths of the abnormal feature points in a time dimension and a space dimension; according to the diffusion path, generating an abnormal propagation map containing the propagation direction and the intensity attenuation gradient of the abnormal feature points; hierarchical clustering is carried out on the abnormal propagation atlas, and abnormal clusters with similar propagation characteristics are divided; generating an early warning signal containing a priority label by using the spatial and temporal distribution characteristics of the abnormal cluster; performing synchronous verification on the early warning signal and underground equipment state data, and screening out a target early warning signal needing to be responded; and triggering a corresponding emergency control instruction according to the target early warning signal.

The present application provides a decision-making method and system for emergency frequency control optimization in an off-grid process of a power distribution system, and relates to the technical field of frequency control of the power distribution system. An average system frequency response model of the power distribution system is established; a frequency deviation is approximated as a quadratic function under a reasonable assumption that an increase in active power generation of the system increases approximately linearly with time, to perform open-loop processing on the frequency response model, so as to obtain an open-loop model; decisions are made on control quantities of fast power control resources within the power distribution system, and an emergency frequency control optimization model of the power distribution system is established; and the emergency frequency control optimization model is solved to obtain a decision-making emergency control scheme with a minimum cost of emergency control measures.

The invention discloses a power grid air-ground cooperative emergency control system and method based on unmanned aerial vehicle multi-agent reinforcement learning, and belongs to the technical field of power system emergency control and intelligent cooperation. Comprising the following steps: a central coordination unit obtains a voltage state and a load importance degree of a power grid node and a position, energy and a communication state of an unmanned aerial vehicle cluster in real time, an emergency priority node is identified based on voltage recovery deviation and communication link quality, dynamic clustering is carried out, and a comprehensive communication demand priority of each node cluster is calculated; according to the method, the strong coupling optimization problem of power grid voltage recovery and emergency communication guarantee in a disaster environment is solved, the power supply reliability, the communication connectivity and the emergency response efficiency of the system are improved, the energy utilization of the unmanned aerial vehicle is optimized at the same time, and the energy utilization rate of the unmanned aerial vehicle is improved. The method is suitable for rapid recovery and cooperative scheduling of key infrastructures in extreme scenes such as earthquakes and typhoons.

The invention relates to the technical field of coal underground gasification control, in particular to a stable control method for the gasification process of deep coal passing through dirt band. The gas pressure distribution data and the pore change characteristic data of the deep coal gasification area are collected in real time through the distributed sensor array, the gas dynamic correction permeability is generated, the gas injection pressure is adjusted and dynamically corrected according to the gas dynamic correction permeability, and the gas pressure is kept stable; screening a potential risk area through a main stress direction deviation angle and a stress concentration coefficient in the dirt band layer, analyzing a shear stress threshold value of the potential risk area based on a stress-strain coupling model, and judging a stability evaluation index of the potential risk area; and when the stability evaluation index is lower than a threshold value, a multi-stage emergency regulation and control mechanism is triggered, and a dirt band layer reinforcement intervention scheme is generated. By means of multi-source data fusion and a dynamic feedback mechanism, the limitation of a traditional method for lagging response of the instability risk of the dirt band layer is broken through, and full-closed-loop intelligent stable control over the gasification process is achieved.

The invention relates to the technical field of sewage treatment automatic control, and discloses a control system for a sewage treatment plant, which comprises a multi-modal biosensing module, the multi-modal biosensing module is deployed in an anaerobic zone and an aerobic zone of a biochemical reaction tank, and a cloud edge collaborative data processing module comprises an edge calculation module and a cloud optimization platform. The edge calculation module preprocesses data collected by the multi-mode biosensing module and executes emergency control, the cloud optimization platform operates the multi-target dynamic optimization module and the digital twin model, and the self-adaptive decoupling controller receives control parameters output by the multi-target dynamic optimization module. By deploying the multi-modal biosensing modules in the anaerobic zone and the aerobic zone, the real-time acquisition of biochemical reaction parameters of each zone along the way is realized, and the microbial metabolic activity change in the biological reaction process can be accurately captured in combination with the pretreatment of the edge calculation module and the analysis of the cloud optimization platform.

The invention discloses a tension leg type offshore wind power platform and a tendon dynamic balance adjusting method.The wind power platform comprises a center stand column, side buoys, a floating bridge and tendons, a plurality of ballast tanks are arranged in the floating bridge and the side buoys, and a plurality of emergency water inlets are formed in the bottom of the floating bridge and the tops and the bottoms of the side buoys; a ballast tank communicating opening which can be selectively communicated with the buoy ballast tank is formed in the lower part of the floating bridge ballast tank close to the buoy; and a ballast system is arranged in each ballast tank, and the ballast systems can be used for carrying out pressure discharge on the ballast tanks or selectively transferring water in any ballast tank to other ballast tanks. The internal ballast can be selectively adjusted through a natural flowing mode and / or a mechanical mode based on the tendon tension, the tendon failure position and the tendon failure number can be judged, an emergency control strategy is formulated according to the tendon failure condition, the service life of a mooring system is prolonged, and the safety of the mooring system is improved. And the self-storage performance of the tension leg platform can be improved when the mooring system breaks down.

The invention discloses a gas leakage monitoring system for an environment-friendly ring main unit, and belongs to the technical field of environment-friendly ring main unit monitoring. The system comprises a real-time acquisition looped network supervision platform, and a joint data real-time acquisition and storage module, an external environment gas dynamic analysis module, an internal environment gas risk analysis module and an emergency regulation and control decision processing module which are in communication connection with the real-time acquisition looped network supervision platform; multi-source data fusion monitoring of internal and external environments of the ring main unit is realized through the joint data real-time acquisition and storage module, the one-sidedness problem of single parameter monitoring is solved, and the leakage risk identification accuracy is improved; second-level data processing and grading risk early warning are realized by means of a real-time algorithm, and the fault response time is shortened; a grading emergency response mechanism is established based on the comprehensive risk index, different risks are precisely handled, and the operation and maintenance cost is reduced while the equipment safety is guaranteed.

The invention discloses an unmanned aerial vehicle emergency control management method and system based on digital twinning, and belongs to the technical field of unmanned aerial vehicle control. The system comprises an unmanned aerial vehicle data acquisition module which acquires image data in an emergency area and parameter records of an unmanned aerial vehicle; the virtual scene construction module is used for constructing a virtual scene by using a digital twinning technology, and mapping and dividing a three-dimensional grid in real time; the emergency route analysis module is used for planning a feasible route for each unmanned aerial vehicle in the virtual scene and screening out key routes; the execution scheme planning module is used for analyzing each scheme according to the key route planning scheme so as to set a communication scheme; and the operation visualization module is used for supervising each unmanned aerial vehicle to fly according to the communication scheme and displaying a virtual scene in real time through a visualization page of the command center. According to the invention, through digital twin-driven multi-source sensing fusion, dynamic grid adaptation and nonlinear anti-interference path planning, the environment modeling precision and communication link reliability of the unmanned aerial vehicle group in a disaster environment are improved.

The invention provides a water quality environment detection method and system based on 5G communication, and the method comprises the steps: determining a target detection node through obtaining the spatial distribution data of a mobile detection node in a to-be-detected water area and the water area topographic feature data, and obtaining a detection data set based on the target detection node; heavy metal ion migration tracks in the detection data set are processed, a pollutant diffusion boundary prediction map is generated to simulate and generate a multi-scene diffusion envelope range, and an emergency management and control instruction set is generated based on the multi-scene diffusion envelope range; determining a pollution diffusion trend in combination with the emergency management and control instruction set and the environmental influence factor, and generating a water quality environment detection result based on the pollution diffusion trend; according to the technical scheme, the 5G communication technology and a traditional water quality detection method are effectively combined, automation, refinement and intelligentization of water quality environment detection are achieved, and the water quality management and protection capacity is improved.

The invention discloses a method, a system, equipment and a medium for evaluating stable operation capability of an isolated network of a regional power grid. The method comprises the following steps: acquiring related data of an isolated network system; based on related data of the isolated network system, initial equivalent inertia and initial power deviation are obtained through calculation; based on the frequency deviation value of the isolated network system, operating equipment of the isolated network system is adjusted, and equivalent inertia and power deviation are calculated and updated; calculating a disturbance frequency change rate according to the equivalent inertia and the power deviation; and judging a corresponding relation between the power deviation and the disturbance frequency change rate, and obtaining an evaluation result of the stable operation capability of the isolated network system. According to the isolated network stability quantitative evaluation method constructed based on the frequency change rate, only two core parameters of the system inertia and the new energy proportion are needed, complex modeling and time-consuming simulation are not needed, and the evaluation efficiency is improved through a dynamic parameter updating mechanism of high-frequency generator tripping and low-frequency load shedding in combination with a simplified frequency response model; whether the isolated network is endangered to collapse is determined in real time, and an emergency control decision basis is provided for power grid personnel.

The invention relates to the field of fire safety engineering, and discloses a water pressure transient detection method, system and device for multi-physical quantity fusion and data processing, and the method comprises the following steps: arranging pressure, flow and temperature sensors at key positions of a pipe network, and collecting real-time data; denoising processing is carried out on the collected data, and interference signals are filtered out; fusing the multi-source data by using a Kalman filtering algorithm to obtain an accurate estimated value of each physical quantity; carrying out water pressure transient modeling and state prediction based on the hydrodynamic model; combining a prediction result and sensor data, and adopting a machine learning algorithm to identify an abnormal mode; once an abnormality is detected, local alarm and emergency control response are triggered immediately. Water pressure, flow and temperature data are fused, modeling prediction and intelligent identification are combined, and efficient early warning and response of abnormal water pressure are achieved; the system is high in integration level and has local calculation and control capability, and the accuracy, the real-time performance and the intelligent level of pipe network monitoring are remarkably improved.

The invention relates to the technical field of forestry ecological management, and discloses a forestry jurisdiction ecological management system based on risk prediction. The system comprises an ecological environment monitoring module, a risk prediction analysis module, an emergency regulation and control module, a risk early warning output module and a background management end. The ecological environment monitoring module collects ecological environment parameters in real time through multiple types of sensors and sends the ecological environment parameters to the risk prediction analysis module and the background management end, and the background dynamically displays the parameters. The risk prediction analysis module determines ecological risk factors in combination with the real-time parameters and a historical ecological risk database, calculates regulation and control instructions through a risk prediction model and sends the regulation and control instructions to the emergency regulation and control module. And the emergency regulation and control module executes intervention operation to adjust the ecological state. The risk early warning output module monitors the intervention process, evaluates the operation state of the emergency regulation and control module, generates an intervention normal signal or a risk early warning signal and sends the signal to the background, and the background triggers a prompt when receiving the early warning signal. The system realizes real-time, scientific and closed-loop forestry ecological management.

The invention provides an urban traffic dynamic deduction and real-time planning method and system based on multi-source position data fusion. Time-space references of signaling, MDT and MR data are unified through a dynamic rasterization mechanism, and the problem of data isomerism is solved by adopting anchor point selection of signal weighting and a triple criterion time expansion algorithm; generating a minute-level updated dynamic OD matrix based on the hierarchical road network constraint model; a METANET macroscopic traffic flow model and EKF extended Kalman filtering are fused to realize traffic state deduction, and parameter online calibration is supported; signal timing optimization, path induction and emergency control schemes are generated in combination with real-time deduction results, and a sensing-deduction-decision-evaluation closed loop is formed. The method can improve road network traffic efficiency, and is especially suitable for response of sudden traffic events.

The invention discloses an electric power system emergency control method and system fusing DRL and STGNN. The method comprises the steps that an international standard example IEEE-39 model is built, electric power data are collected, and a data set is built; and performing feature extraction on the data in the data set, inputting the obtained features into the improved DDPG model fused with the DRL, and outputting a generator tripping action vector. And optimizing the generator tripping action vector, and updating network parameters in the model. According to the power system emergency control method and system fusing the DRL and the STGNN provided by the invention, the perception capability of the transient response time-space change trend is effectively improved through the time-space diagram neural network, and the real-time performance and the accuracy of the model are improved. On the basis, through the DRL model, learning of a complex control strategy is achieved, effective actions can be rapidly obtained, and the effectiveness of an emergency control scheme is improved.

The invention provides a hardware-level safety control device of an intelligent robot. The hardware-level safety control device of the intelligent robot comprises a power cut-off execution module, the network destroying module is provided with an isolation assembly capable of physically destroying a robot network communication unit; the independent security protection module integrates a hardware firewall and an encryption communication unit; the emergency control module is electrically connected with the power cut-off execution module and the network destroying module through a hard wire direct connection channel, an encryption communication channel with an external control terminal is established through the independent safety protection module, and a closed-loop safety control system independent of a robot main control system is formed. Through the synergistic effect of the power cut-off execution module and the network destroying module, power output and network communication of the robot are synchronously blocked, the double risks of out-of-control of hardware and data leakage are thoroughly eliminated, and comprehensive safety protection is formed.