96results about How to "Improve emergency response capabilities" patented technology

The invention discloses a power transmission and transformation equipment fault early warning system based on online monitoring, and the system comprises the following modules: a multi-parameter sensor module which is used for collecting data in real time; the wireless sensor network module is used for transmitting the data to the data processing center for processing; the data fusion module is used for generating a comprehensive health score of the equipment by adopting a multi-modal data fusion algorithm based on a self-evolution nested network; the trend prediction module introduces an adaptive residual module to carry out trend prediction based on a nonlinear time sequence analysis technology of a generative adversarial adaptive residual network; the early warning threshold value adjusting module is used for dynamically adjusting an early warning threshold value by adopting a self-adaptive evolutionary algorithm of meta reinforcement learning; the maintenance suggestion generation module is used for generating maintenance suggestions; and the power grid dispatching linkage module is used for automatically linking a power grid dispatching system and detecting and adjusting an equipment load. According to the invention, a multi-parameter fusion and generative adversarial network method is adopted, and an adaptive residual module is introduced, so that accurate early warning of faults of power transmission and transformation equipment is realized.

The invention discloses an intelligent mine management and control platform for mine management, and relates to the technical field of mine management, a mine is divided into different monitoring areas, detailed classification is carried out according to the personnel density, and the personnel density of the monitoring areas is improved. Key data such as ground stress fluctuation amplitude and communication channel electromagnetic interference index are acquired in real time by using a preset sensor, and a data test model is constructed to evaluate the stability of the intelligent mine management and control platform in combination with a sensor acquisition frequency deviation proportion; according to the evaluation result, the area is divided into different out-of-control risk levels, in-depth stability prediction is carried out on the high-out-of-control risk area, and a corresponding emergency management plan is made; the monitoring precision and the emergency response efficiency of mine operation under complex and extreme environment conditions are remarkably improved, and the possibility of safety accidents and operation interruption caused by out-of-control risks is reduced.

The invention discloses a multi-mode mountain torrent disaster in-situ early warning threshold value dynamic demarcation method and system, and the method comprises the steps: collecting the topographic data of a research region, setting the DEM precision, automatically recognizing a river in the research region, recognizing grid abnormal points, and dividing the research region into a molecular basin; the method comprises the following steps: extracting historical rainfall data of a research area, constructing a rainfall scene random construction model based on prior distribution of historical rainfall, generating a rainfall scene of the research area, inputting the rainfall scene into a pre-constructed distributed hydrological model, and simulating to obtain confluence time, a rainfall cover range and a rainfall harvesting area; constructing a mountain torrent forecasting model, inputting the rainfall scenes of the plurality of research areas into the constructed mountain torrent forecasting model, simulating and extracting disaster scenes, inputting the disaster scenes into a pre-constructed Seq2Seq model, and training; historical mountain torrent data of a research area are collected, historical mountain torrent scenes of the research area are input into the Seq2Seq models corresponding to the seven built early warning combinations, the mountain torrent disaster process is obtained through simulation, early warning thresholds of the seven early warning combinations are calculated, and the mountain torrent disaster in-situ early warning threshold is obtained through combination.

The invention relates to the technical field of data processing, in particular to a hoisting state intelligent sensing and early warning system, method and equipment, and the system comprises an environment interference early warning module, a hoisting equipment abnormity early warning module, a hoisting operation abnormity early warning module and a hoisting system database, according to the intelligent sensing and early warning system, method and equipment for the hoisting state, the influence of environment interference, hoisting equipment abnormity and hoisting state abnormity on hoisting operation is comprehensively analyzed, and a comprehensive hoisting operation abnormity evaluation system is formed; the evaluation system not only can monitor the environmental interference degree of a hoisting operation site in real time, but also can perform analysis and early warning on hoisting equipment abnormity and hoisting state abnormity, and through comprehensive evaluation and early warning on hoisting operation, the emergency response capability of hoisting operation can be improved, and the safety of hoisting operation is improved. And therefore, the hoisting operation can still be kept stable and safe under the emergency condition.

The invention relates to the technical field of material storage management, in particular to a BIM-based construction site material monitoring management method and system. The method comprises the following steps: obtaining a construction project drawing; performing drawing information extraction on the construction project drawing to obtain construction project material information data and construction project structure data; performing construction project three-dimensional modeling on the construction project material information data and the construction project structure data to generate construction project three-dimensional modeling data; obtaining total construction material data; and carrying out material information modeling on the total construction material data by using a BIM technology to generate total construction material modeling data. According to the invention, accurate three-dimensional modeling, intelligent marking, regionalized storage and real-time allocation of the construction site materials are realized through the BIM technology, and the accuracy of construction site material monitoring management and the emergency response real-time performance are improved.

The invention discloses a mountain torrent disaster early warning method and system based on multi-mode combination optimization. According to the method, a comprehensive adaptability index screening framework method is adopted to identify mountain torrent disaster indexes, a key mountain torrent disaster index set is constructed, index weights of the key mountain torrent disaster index set are calculated, and a pre-constructed mountain torrent disaster forecasting model is configured; the method comprises the following steps: extracting a rainwater collecting area and confluence time corresponding to each historical mountain torrent disaster from historical mountain torrent disaster data of a research area, fitting distribution of the rainwater collecting area and the confluence time respectively, constructing joint distribution of the rainwater collecting area and the confluence time, and randomly sampling to obtain a plurality of mountain torrent scenes; fitting the mountain torrent disaster-causing process and inputting the mountain torrent disaster-causing process into a pre-constructed early warning combination optimization model, solving the model to obtain an optimal early warning combination corresponding to each mountain torrent scene and fitting the mountain torrent disaster-causing process, calculating key mountain torrent disaster index values and inputting the key mountain torrent disaster index values into a constructed mountain torrent disaster forecasting model, and solving the model to obtain mountain torrent disaster forecasting; according to the method, accurate mountain torrent disaster early warning and forecasting changing along with actual conditions can be provided.

The invention discloses a large model training and application method and system based on a city brain, and relates to the technical field of artificial intelligence and smart city management. Comprising the steps of 1, collecting and preprocessing data, 2, training a large-scale language model, 3, utilizing the trained large-scale language model to understand and predict city dynamics, and utilizing the large-scale language model to carry out semantic understanding and relation reasoning on city data, and 4, displaying a model analysis and prediction result by using a visual interface, and performing interactive question and answer by using the visual interface. And 5, continuously learning and updating the large-scale language model according to the feedback: continuously learning and improving the large-scale language model according to the newly acquired city data and the user feedback, regularly evaluating the performance of the model, and adjusting the structure and parameters of the model according to the evaluation result.

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 discloses a fire-fighting alarm receiving and processing digital management system, and the system obtains real-time environment parameter data through employing a distributed sensor, carries out the data preprocessing of the real-time environment parameter data, and obtains target environment parameter data. Inputting the target environment parameter data into a preset early warning identification model for identification to obtain an accident state type; analyzing the accident state type by using a path planning algorithm to obtain fire-fighting vehicle planning information; analyzing the accident state type by using a fire-fighting resource allocation model to obtain firefighter allocation information; and according to the fire-fighting vehicle planning information and the firefighter distribution information, unified scheduling of vehicles and persons is carried out, and real-time scheduling adjustment is carried out according to real-time conditions. The optimal path can be planned for the fire-fighting vehicle in a short time, resources are reasonably allocated, the police time is shortened, and the alarm response speed is increased.

The invention discloses an enterprise safety production joint control information management system, which relates to the technical field of production joint control information management and comprises a collection module, a data processing module, a safety management module and a response module. And selectable. According to the invention, dynamic assessment of the safety risk is realized, intelligent early warning is carried out according to the change trend and severity of the risk, the accuracy and timeliness of early warning are improved, quantitative analysis of the degree of dispersion of the safety risk is realized, a scientific basis is provided for emergency response, rapid response and intelligent scheduling are realized, the accident processing efficiency is improved, and the safety risk is protected. According to the method and the system, the real-time monitoring of the wind speed and the flow velocity data is realized, the quantitative evaluation of the emergency response capability is realized, accurate guidance is provided for the formulation and implementation of emergency measures, the accuracy and effectiveness of emergency processing are improved, dynamic early warning and accurate positioning of a risk source can be realized by using the real-time monitored wind speed and flow velocity data, and the accuracy and timeliness of early warning are improved.

The invention relates to the field of remote monitoring, and discloses a safety inspection method and system applied to intelligent security, and the method comprises the steps: calculating a potential risk coefficient of a scene element; marking risk nodes of the intelligent security scene, analyzing risk indexes of the risk nodes, defining multi-modal inspection equipment of the risk nodes, and analyzing inspection resistance of the multi-modal inspection equipment to the risk nodes; configuring a mobile inspection device of the risk node, capturing an abnormal behavior of the risk node, locking an abnormal target of the intelligent security scene, analyzing target characteristics of the abnormal target, and constructing a multi-modal tracking path of the multi-modal inspection device and the mobile inspection device; the abnormal development state of the abnormal target is analyzed, when the abnormal development state accords with a preset abnormal development threshold value, the abnormal level of the abnormal target is determined, and abnormal alarm of the intelligent security scene is executed based on the abnormal level. According to the invention, the automatic test efficiency of the X86 tablet interface can be improved.

The invention relates to the technical field of intelligent fire rescue, and discloses a small self-sensing intelligent special vehicle and a control method.The small self-sensing intelligent special vehicle is characterized in that a plurality of supporting foot devices are connected to the outer side face of a lower bottom plate, a gearbox is connected to the terminal of the top of the lower bottom plate, plunger pumps are connected to the output ends of the gearbox, and the number of the plunger pumps corresponds to that of the supporting foot devices; the top of the upper top plate is connected with a recognition device, and a spraying device corresponding to the fire extinguishing agent storage box is arranged at the front end of the top of the upper top plate; one side of the top end of the middle plate is connected with a fire extinguishing agent storage box, and the middle end of the top face of the middle plate is connected with a steering assembly. According to the device, the change of a fire source can be recognized in time in a complex environment, and accurate and effective fire extinguishing measures are taken. According to the device, a brand new thought and method are brought to forest fire fighting, the fire source checking and extinguishing efficiency is improved, secondary reburning of the fire is avoided, and the overall safety and emergency response capacity of fire fighting operation are improved.

The application provides a kind of campus security risk prevention and control cloud service platform, it is related to cloud platform technical field, including: data processing and transmission module, for based on cloud platform architecture data storage, processing and secure transmission, and support the automatic reconnection and concurrent control of data transmission;Safety assurance module, connect data processing and transmission module, for the digital management of the civil air defense, physical protection and technical support information of campus;Security risk prevention and control module, connect data processing and transmission module and safety assurance module, for the information processing and linkage of campus safety management, safety education and safety emergency process;Joint defense and control module, connect security risk prevention and control module, for based on the processing result of security risk prevention and control module, realize the data linkage and emergency response command between multi-level education management department and school. By constructing the campus security risk prevention and control cloud service platform, the intelligentization and collaboration level of campus safety management is significantly improved.

The present invention discloses a complete set of mining machinery application analysis system based on BIM technology in the field of mining machinery technology, including a model building subsystem for constructing a three-dimensional model by inputting the original data of the complete set of mining machinery applications; an information management subsystem for informatization processing of the model; a data acquisition subsystem including a sensor integration module, a data preprocessing module and a data transmission module; a data analysis subsystem for in-depth analysis of the collected data and pipeline collision inspection; a BIM model and visualization subsystem and a decision support subsystem. The complete set of mining machinery application analysis system based on BIM technology adopted by the present invention can improve efficiency, enhance collaborative operations, optimize decision support, reduce costs and enhance safety. This helps to ensure the safe, stable and efficient operation of the complete set of mining machinery applications.

The invention discloses a distributed multi-node remote sensing satellite multi-mode integrated scheduling method, and belongs to the field of remote sensing satellite ground task management and control. The method comprises the following steps: a main center performs overall management on various remote sensing satellites of each node, performs demand preprocessing, multi-type satellite joint task planning and proper scheduling mode decision aiming at various observation demands, and performs multi-type satellite node task integrated scheduling according to different scheduling modes; and sending the scheduling task order to each corresponding satellite node to perform observation task planning and satellite control implementation, collecting task order states to perform demand state feedback and tracking closed-loop management, and performing iterative scheduling on non-closed-loop demands. According to the method, joint application of multi-type satellite node resources, advantage complementation and sharing service, online scheduling and rapid task implementation are realized, the use efficiency of multi-type remote sensing resources is greatly improved, and the demand timeliness and the observation effect are improved.

The utility model relates to the field of tunnel construction emergency, and discloses a tunnel construction emergency early warning system. According to the invention, through integration of an informatization technology and a mechanical device, the emergency response capability of a construction scene is significantly improved. According to the system, a multi-module linkage mechanism is adopted, the abnormal state in the hole can be sensed in real time, early warning can be triggered synchronously, and the problems of delay and information transmission errors existing in traditional manual early warning are effectively solved. When a sudden dangerous case occurs, the wireless communication and intelligent control module can quickly cover a hole opening, the interior of the hole and an adjacent tunnel with a signal, and it is ensured that an operator receives an evacuation instruction at the first time through multi-dimensional warning means such as sound and light, voice and traffic signals. Meanwhile, due to intervention of the fixing support and automatic equipment, the posture of the construction trolley can be stabilized, the safety risk of manual operation is avoided, and the probability of secondary disasters caused by instability of the equipment is reduced fundamentally.

This invention discloses a control system for an intelligent inspection robot for stormwater and sewage pipelines, comprising a microcontroller unit, a multi-sensor module, an image acquisition module, a communication module, and a power module. Through multi-sensor collaborative perception and intelligent decision-making mechanisms, it integrates multi-dimensional data such as images, distance, and environmental data, and employs adaptive path planning and obstacle avoidance algorithms, making it suitable for autonomous inspection tasks in complex pipeline environments. The image acquisition module integrates a high-definition camera and a WiFi module; the distance detection unit combines ultrasonic and infrared ranging sensors to achieve complementary ranging and improve detection accuracy; the environmental monitoring unit uses gas sensors to detect the concentration of toxic and flammable gases such as ammonia and sulfides in the pipeline in real time, and automatically triggers an early warning when the concentration exceeds the standard. This effectively solves the problems of existing pipeline robots, such as single sensor detection methods, poor environmental adaptability, and insufficient intelligence, improving inspection efficiency and system reliability, and reducing manual maintenance costs.

The invention relates to the technical field of medical instruments, in particular to a shoulder arthroscopy lateral position abduction traction frame which comprises a main frame, a traction rod and a traction rope, a sliding rail is vertically and fixedly installed on the main frame, a lifting block is vertically and slidably installed on the sliding rail, one end of the traction rope is fixedly connected with the lifting block through a traction assembly, and the other end of the traction assembly is fixedly connected with the traction rod. A water tank is fixedly installed on the main frame, a water outlet pipe is installed at the bottom end of the water tank, a water inlet pipe is installed at the upper end of the weight box, the water outlet pipe and the water inlet pipe are communicated through a connecting water pipe, and a water level window is formed in the side face of the weight box. And water level scales are arranged on the water level window. A medical worker can control the traction force on the arm by controlling the water level in the weight box, the situation that the traction force is too large or too small, and consequently the operation progress is affected is prevented, it is guaranteed that the operation effect is better, and the disease of a patient is thoroughly solved.

The application discloses a building cross-subsystem data sharing and dynamic permission allocation method based on Internet of Things, and relates to the technical field of building cross-subsystem data processing. Specifically, the analysis of the analysis timeliness and analysis processing capacity of building cross-subsystem data in the sharing process is carried out, the analysis result is used as a benchmark to quantize the adaptation of permission allocation, the analysis capacity is adapted to dynamic load and permission decision, the data quality and communication state are matched, the timeliness and resource utilization efficiency of permission allocation in the building scene are balanced, and therefore, the accuracy of the permission allocation result is improved.

A three-way valve body with an emergency sealing structure belongs to the technical field of three-way valve bodies and comprises a valve body, a sealing partition plate A and two sealing partition plates B are fixedly mounted in the valve body and divide an inner cavity of the valve body into an air inlet cavity and a mixing cavity, two through holes are formed in the upper surface of the sealing partition plate A in a penetrating mode, and the two through holes are communicated with the air inlet cavity and the mixing cavity. The two ports are used for communicating with the corresponding air inlet cavities correspondingly, electric execution power sources are installed in the air inlet cavities in a penetrating mode correspondingly, pressing plates are fixedly installed on the lower surfaces of the electric execution units correspondingly, sealing rings are fixedly installed on the lower surfaces of the pressing plates, and sealing bases are fixedly installed at the ports in the upper surface of the sealing partition plate A; a plurality of contact rings are integrally formed on the upper surface of the sealing base, a plurality of adaptive grooves are formed in the lower surface of the sealing ring, the conical contact rings and the adaptive grooves can be utilized to form multi-stage sealing of multiple contact surfaces, and compared with a traditional single sealing ring, the pressure resistance and the sealing performance of the sealing structure are greatly improved.

The application provides a kind of surface deformation measurement method and system based on different imaging mode SAR data, comprising: obtaining different imaging mode SAR image data;Register SAR image data, obtain the slant range difference of main and auxiliary images, resampled main image and registered auxiliary image;Obtain the main and auxiliary images after downsampling;Interferometric processing obtains surface deformation information and outputs.The application constructs the end-to-end processing framework of different imaging mode SAR data, effectively reduces the spatial baseline incoherence risk of different imaging mode SAR system, ensures the space-time correlation of different star data;Through the whole link innovation of orbit design, joint registration, spectrum matching and terrain residual suppression, the cross-platform data interference incoherence bottleneck is broken, the registration error problem caused by spectrum shift and resolution difference of different imaging mode data is solved, and a systematic solution is provided for high-frequency and high-precision surface deformation monitoring;Through terrain phase separation technology, terrain residual is effectively suppressed.

The application discloses a self-adaptive multi-modal data fusion bridge health monitoring method and system, generates a response sample database through establishment of a bridge nonlinear dynamics equation, pre-processes bridge sensor data and trains a deep learning model to extract damage features, and self-adaptively optimizes model parameters; based on model output, real-time and historical data are combined to perform bridge health evaluation, and a monitoring strategy is dynamically adjusted or early warning is triggered; an edge computing device is deployed to perform pre-processing and damage identification, and long-term trend analysis is realized in cooperation with a cloud platform; macro-structure damage and micro-crack data are fused through cross-scale feature extraction; an artificial intelligence algorithm is used to generate a bridge health evaluation result, a bridge maintenance and repair scheme and a decision-level early warning signal. The application combines nonlinear dynamics modeling, self-adaptive deep learning, edge cloud collaborative computing and cross-scale analysis, improves complex damage identification precision and monitoring intelligent level, and is suitable for large-scale traffic network bridge monitoring management.

The embodiment of the application provides a kind of route dependence evaluation method and device, comprising: according to the route information obtained, construct route prefix path dictionary;According to the domain name list information obtained, the comprehensive weight of each domain name in domain name list is calculated;According to the comprehensive weight of each domain name, the route prefix weight of the route prefix corresponding to each domain name is determined, and the route prefix and the corresponding route prefix weight are saved in route prefix weight dictionary;Based on route prefix path dictionary and route prefix weight dictionary, determine route dependence.This application can accurately evaluate the dependence degree of AS on key application service, effectively identify key AS, ensure the continuous availability of key application service, improve the resilience and emergency response capability of network, provide protection for network security management and application service.

This invention provides a campus hardware and software integrated management method and system supporting remote operation via mobile devices. It collects status parameters and business data from heterogeneous devices in the campus teaching, security, and logistics domains, synchronizes them with a hybrid clock, and pushes them to a campus digital twin virtual model incorporating geographic information, achieving full-domain resource virtual-real mapping and 3D visualization. A sliding time window combined with a business weight correction mechanism is used to determine adaptive warning thresholds and cross-device linkage strategies based on device operating time and business scenarios. Mobile devices access the system via an end-to-end encrypted link, enabling remote hierarchical handling based on dynamic hierarchical permissions. Hierarchical warnings are generated when a single parameter exceeds limits or multi-dimensional correlation anomalies are detected. If remote handling is ineffective, maintenance work orders are automatically generated and resources are intelligently scheduled, forming a closed-loop management process. This solution breaks down campus hardware and software data silos, enabling deep mobile control and intelligent operation and maintenance, significantly improving campus management efficiency and emergency response capabilities.

The invention belongs to the technical field of fire-fighting systems, and particularly relates to a fire-fighting control system and method for a thermal power plant based on image processing, and the system comprises a central control room, a detection alarm system, and a fire-fighting equipment inspection system. The detection alarm system is composed of a fire detection system, an alarm and linkage control system, an emergency broadcast and telephone system and a fire-fighting area integrated cabinet. The alarm and linkage control system is internally provided with an information acquisition unit, an evacuation plan unit, an information sending unit, a navigation generation unit, a disaster area fire extinguishing / fire fighting facility starting unit and a blocking plan unit, and the evacuation plan unit is internally provided with an evacuation information generation unit, an evacuation route generation unit and an edge updating feedback unit. According to the invention, the problems of false alarm and missing alarm caused by equipment failure or aging can be reduced, a scheme for hindering fire spreading and an emergency operation scheme for emergency treatment are provided, and the emergency operation scheme can guarantee the passing of safety officers as much as possible.

The present application belongs to the technical field of nuclear power plant physical simulation and simulation, and particularly relates to a nuclear power plant core instrument bay equipment simulation body and a simulation method. The simulation body comprises a driving unit, a group selector assembly and a path selector assembly, the driving unit is connected to the path selector assembly through the group selector assembly, the cable outlet end of the driving unit is connected to the group selector inlet end through a stainless steel pipe and a sleeve joint, and the group selector outlet end of the group selector assembly is connected to the path selector inlet end of the path selector assembly through a stainless steel pipe and a sleeve joint. The present application has the beneficial effect of improving training effect and efficiency, the RIC system simulation body can simulate the real operating environment of the nuclear power plant core, so that the trainees can learn and operate in a work scene close to the actual one, thereby more intuitively understanding the working principle and operation process of the core measurement system.

The application provides a rural power distribution substation low-voltage interconnection uninterrupted power transfer method, comprising the following steps: enabling an intelligent circuit breaker as a tie switch type according to a basic electrical connection, combining a built-in overload and short circuit protection module to realize a millisecond-level fast on-off response, determining a controllable switching state of a low-voltage interconnection line, and obtaining a response parameter of the controllable switching state; collecting the response parameter of the controllable switching state and monitoring data for access feasibility judgment, embedding a switching state mutual exclusion control program to form a two-stage linkage locking logic, judging a safety constraint condition of a power transfer operation, and obtaining a satisfaction symbol of the safety constraint condition; monitoring data changes of a current and voltage collection port in real time through a load power transfer path, dynamically adjusting an on-off state of the intelligent circuit breaker in combination with feedback information of a voltage frequency real-time monitoring unit, and obtaining a final execution result of target substation load uninterrupted power transfer.

This utility model proposes an AC / DC operation training circuit for urban rail transit, including an AC circuit 1 and an AC circuit 2 configured with an interlocked backup relationship, a busbar connected to AC circuit 1 and AC circuit 2, an emergency lighting circuit connected to the busbar, a first simulated fault switch, and a second simulated fault switch. AC circuit 1 includes an AC circuit 1 incoming switch, an AC circuit 1 contactor, and a first contactor; AC circuit 2 includes an AC circuit 2 incoming switch, an AC circuit 2 contactor, and a second contactor. The AC circuit 1 incoming switch is connected to the three phase lines of a three-phase power supply, and the AC circuit 1 contactor coil is connected between two of the three phase lines. The AC circuit 2 incoming switch is also connected to the three phase lines of a three-phase power supply, and the AC circuit 2 contactor coil and the first normally closed contact of the AC circuit 1 contactor are connected in series between two of the three phase lines. This utility model can meet the needs of efficient and safe training in various scenarios.

This invention discloses a collaborative optimization method, system, and medium for intelligent power grid emergency repair based on a closed-loop perception-decision-execution system. The method first collects meteorological data, resource allocation data, power grid data, and road traffic data from the disaster-stricken area, integrating them into multi-source perception data. This data is then input into a two-layer optimization model for calculation. The outer layer model combines the fault location, road conditions, and load levels to generate the optimal repair path decision, while the inner layer model outputs a fault recovery decision based on the power grid topology and load priority. Finally, the two types of decisions are converted into emergency repair resource scheduling instructions and power grid control instructions, respectively, and emergency repair operations and load restoration operations are executed simultaneously. This invention effectively solves the problems of difficult path selection, information asymmetry, and slow response speed faced by power grid repair and restoration when power failures are caused by natural disasters or accidents, significantly improving the emergency response capability and power supply restoration speed of the power grid, and effectively ensuring power supply stability and security.

The application discloses a diver handheld navigation sonar cross-modal navigation method and system, and relates to the technical field of underwater navigation. It aims to solve the problems of low navigation recognition, high power consumption and cross-modal fusion deviation in low visibility environment. The application includes synchronously collecting underwater acoustic, visual and positioning data; correcting the physical field of acoustic and visual data based on a fluid dynamics model and an electromagnetic wave propagation model; extracting geometric and texture features from the corrected data, while detecting acoustic anomalies and visual anomalies, and comprehensively outputting obstacle information; matching the extracted features with a pre-stored feature library for similarity, and outputting fusion features; generating a basic path based on the fusion features through a dynamic weight cost function, correcting the generated final path using positioning data, and planning a detour route; and superimposing and displaying the path, the detour route and the obstacle information, and giving a warning when the distance of the obstacle is less than a safety threshold. The technical scheme significantly improves the navigation recognition and reduces the power consumption in low visibility.