2195results about How to "Quick response" patented technology

The invention relates to the technical field of information communication, and discloses a 5G network slice resource scheduling method for a power distribution network, and the method comprises the steps: firstly collecting the geographic coordinates and priority labels of a service request, carrying out the regional division of a service based on the coordinates, and determining the cluster center of each region; then combining the priorities and the areas to which the requests belong, carrying out hierarchical sorting on all the requests to generate a global scheduling sequence; for each request in the sequence, calculating a path distance to each network resource node according to the coordinate of the request and the cluster center, and selecting a shortest path node as a target resource node; and finally, allocating resource quotas from the resource pool of the target node in sequence. According to the 5G network slice resource scheduling method provided by the invention, the resource matching accuracy and locality are effectively improved, the service transmission delay is reduced, the network flow space distribution is optimized, and the more efficient and reliable bearing of the power distribution network service is realized.

The invention relates to the technical field of semantic segmentation, in particular to a night semantic segmentation method based on low illumination enhancement and edge optimization, and the method comprises the steps: inputting an image into a low-light enhancement repair network based on the Retinex theory, local contrast enhancement and adaptive feature fusion, obtaining a denoised and enhanced intermediate image, and carrying out the edge optimization of the intermediate image; inputting the intermediate image into a semantic segmentation network to obtain a category distribution diagram of each pixel; inputting a discriminator embedded with a channel attention module according to the category distribution diagram of each pixel, and optimizing a generator composed of a low light enhancement repair network and a semantic segmentation network through a multi-task joint optimization loss function; and inputting a night image to be detected and segmented into the optimized generator, and outputting a segmentation result. By adopting the method, the low-light enhancement repair network is combined with a local contrast enhancement and channel feature fusion mechanism, so that the overall brightness of the image is improved, the details and edge structures of the image are reserved, and the perception capability and robustness of the model are improved.

The invention discloses a high-efficiency converter for adjusting the voltage of a power grid, and belongs to the technical field of power electronics. The converter comprises a first voltage regulation circuit, a second voltage regulation circuit, a filter circuit, a detection circuit and a control circuit. By detecting the amplitude difference between the power grid voltage and the load voltage, the control circuit automatically switches the Buck working mode or the Boost working mode, and stable alternating current output in a wide input voltage range is achieved. The invention has the advantages of compact structure, high efficiency, fast response, small harmonic wave and the like, and is suitable for industrial and civil occasions with large-range fluctuation and frequent power grid voltage.

The invention discloses a multichannel broadband receiver, and belongs to the technical field of microwave radio frequency and electronic control, the multichannel broadband receiver comprises a multichannel down-conversion assembly, a local oscillator power component, a power interface control panel and a VPX connector, the down-conversion assembly adopts a cavity-divided integrated structure, multiple identical radio frequency links are arranged in the same cavity in parallel, and the VPX connector is connected with the local oscillator power component. Down conversion from a 2-18GHz radio frequency signal to a 1.3-2.3 GHz intermediate frequency signal is realized through two-stage frequency mixing; the power supply interface control board takes an FPGA as a core, integrates the functions of multi-path power supply conversion, driving isolation, state monitoring and the like, and realizes channel gain power failure storage and calling, BIT self-inspection, nanosecond rapid turn-off and multi-parameter real-time monitoring through software and hardware cooperation. Through collaborative innovation of the structure, circuit and control, high integration, high channel consistency, high isolation and high intelligence of the multi-channel receiver are realized, and the multi-channel receiver is suitable for the fields of high-performance radars, electronic countermeasures and the like.

The invention discloses a preparation method of a high-stability photoresponse covalent organic framework membrane and application of the high-stability photoresponse covalent organic framework membrane in selective separation of multiple components. 4-azido azobenzene is prepared by carrying out azido reaction on 4-aminoazobenzene in an acidic aqueous solution, and then a BPTA-TAPB-COF membrane is used as a matrix to prepare the high-stability photoresponse covalent organic framework membrane. 4-azido azobenzene is efficiently grafted to the pore wall of the BPTA-TAPB-COF membrane through a click chemical reaction, the photoresponse covalent organic framework membrane is constructed, and the covalent organic framework membrane can be used for multi-component selective separation and is suitable for multi-component systems with different sizes. The azobenzene group in the pore channel of the prepared Azo-COF membrane is subjected to reversible cis-trans isomerization under the irradiation of ultraviolet / visible light, the response speed is high, and the cycle performance is good; the Azo-COF membrane has good application in the light-operated nanofiltration process, the performance of the Azo-COF membrane is not reduced after the Azo-COF membrane is continuously recycled for 12 days, and the structure of the Azo-COF membrane is kept stable.

The invention relates to the technical field of non-electrical variable control or regulation systems, and discloses an exhaust gas aftertreatment flow channel back pressure dynamic regulation method, which comprises the following steps: acquiring a supply source phase reference signal and establishing cyclic mapping; a fluid channel pressure signal pulse range change rate is extracted to determine a feed-forward factor; determining a pressure signal trough interval as an action window; determining a reference amplitude based on the feedback deviation and using a feed-forward factor for compensation to determine a target adjustment instruction; the adjusting mechanism is driven to move in the action window, so that the response peak value is locked in the trough interval, the adjusting action is locked in the low-energy phase, kinetic energy intervention of fluid pulses on the adjusting mechanism is avoided, and mechanical abrasion is reduced; pulse characteristic feed-forward compensation is utilized to enable an adjusting instruction to sense the trend of a flow field, the response speed is increased while a signal is smoothed, and pressure balance under the transient working condition is maintained.

The invention relates to the technical field of industrial intelligent manufacturing, and discloses a digital factory-oriented dynamic energy price response type production regulation and control system, which comprises a data acquisition module, a data processing module, a model establishment module, a scale regulation and control module, an instruction verification module, a visualization module and a closed-loop optimization module, the dynamic energy price is introduced into production scheduling, so that the comprehensive energy cost is reduced; a multi-agent reinforcement learning model is adopted for real-time response; an optimization strategy is decomposed into long-term, short-term and real-time instructions, macroscopic planning is carried out by using a cloud, and accurate control is executed by relying on edges; three defensive lines of safety, feasibility and stability are set for all control instructions, so that the harm of wrong instructions is effectively prevented; a decision view and a manual intervention interface are provided to ensure the reliability and credibility of the decision; the successful scheduling case is stored in a strategy library, online fine adjustment and offline training are carried out on the core model, and the continuous evolution ability is achieved.

The invention is suitable for the technical field of vehicle dynamics modeling and control, and provides a preview active suspension stiffness control method based on road surface grading and MAP mapping, and the method comprises the steps: collecting a road image through a vehicle-mounted visual sensor, dividing regions, and recognizing the road surface unevenness grade of each region through a convolutional neural network; obtaining the vehicle speed; and according to the current pavement grade and the vehicle speed, a vehicle speed-pavement grade-rigidity mapping MAP table generated in advance is inquired, and the target suspension rigidity is rapidly obtained and adjusted. According to the invention, the dependence on a high-precision sensor and a high-computing-power processor is reduced, and low-cost and fast-response rigidity optimization control of the preview active suspension is realized.

This invention discloses a copper-based ternary chalcogenide semiconductor material, its preparation method, and its applications. The material is prepared by mixing CuSn(OH)6 nanomaterials, thioacetamide, ethylenediaminetetraacetic acid, and water and carrying out a hydrothermal reaction to obtain Cu3SnS4 nanomaterials. This semiconductor material exhibits excellent photoelectrochemical properties. Photoelectrochemical sensors constructed based on this material demonstrate high detection accuracy, fast response speed, low detection limit, and strong stability, enabling rapid and accurate real-time detection of microplastic content. The preparation method is simple, low-cost, and suitable for industrial production.

The invention relates to a cluster unmanned aerial vehicle communication method based on a multi-dimensional key encryption and decryption algorithm. The method comprises the following steps: acquiring unique identifiers of an unmanned aerial vehicle array and marshalling; extracting a single-user key of the unmanned aerial vehicle in the target group, and obtaining a key element by using a multi-dimensional key algorithm; generating an action instruction according to a preset coding rule, encrypting the action instruction, and combining the action configuration classification area to obtain a remote control instruction data packet; transmitting the remote control instruction data packet through a broadcasting mechanism, and receiving the remote control instruction data packet by the unmanned aerial vehicle through a monitoring mechanism; filtering and analyzing the received data packet to obtain a configuration data unit matched with the unmanned aerial vehicle marshalling; extracting a key element based on the configuration data unit, and calculating to obtain an original key; decrypting the action element encryption value to restore the action instruction, and executing the instruction after verification; the execution process of the action instruction is monitored in real time, and abnormal conditions are processed; the cluster unmanned aerial vehicle communication method using multi-dimensional key encryption and decryption is realized.

The invention discloses a multi-agent cooperation method, system and device based on shared memory data, and a medium, mainly relates to the technical field of multi-agents, and aims to solve the problem that a traditional reasoning system cannot recognize semantic similarity between requests and cannot sense a context relationship of agent tasks, so that the efficiency is improved. The intelligent agent system is often deployed at multiple nodes, and the cache result cannot be shared across the nodes. Comprising the steps of obtaining an output result and an intermediate result generated by each path node; caching the semantic signature and the output result to a preset result cache layer; caching an intermediate result generated by each path node as context information to a preset context cache layer; and according to a preset time window, detecting inference frequencies of different semantic signatures generated by all the agents, and according to the inference frequencies, adjusting storage time of output results corresponding to the semantic signatures in a preset result cache layer.

The invention belongs to the technical field of oil and gas pipeline safety monitoring and unmanned aerial vehicle image analysis, and discloses a two-stage oil and gas pipeline occupation pressure monitoring method and system based on unmanned aerial vehicle space perception and deep learning fusion, and the method comprises the steps: obtaining image data and space data of a to-be-monitored region, combining the image data and the space data with a DEM, and obtaining a DEM image; realizing projection of geographic coordinates of the pipeline to image pixel coordinates to obtain a plane image of the pipeline; constructing and deploying a lightweight target detection network DRF-YOLOv8n, performing reasoning on a plane image of the pipeline based on the lightweight target detection network DRF-YOLOv8n, outputting a candidate bounding box, and performing screening and key frame judgment; a Promp-guide SAM pixel level segmentation module is used to realize pixel level segmentation of the key frame, and a candidate pixel mask is generated; and judging whether occupation occurs or not through the intersection of the pipeline projection line and the candidate pixel mask, and outputting alarm information with geographic coordinates.

The invention discloses a distributed photovoltaic panel anomaly detection method under a high-altitude view angle based on a YOLOv8n model, and belongs to the technical field of target detection. The model comprises the following steps: acquiring a distributed photovoltaic panel image data set under a high-altitude view angle, and performing data enhancement and labeling; an improved YOLOv8n model is constructed, and the improvement comprises the steps that a C2fAT module is introduced into a backbone network, and the small target feature extraction capacity is enhanced; an SPPF module is replaced by an SPPF-LSKA module, and complex background interference is suppressed; an EMA attention mechanism is introduced into the neck network, and the multi-scale adaptive capacity is improved; optimizing a training process by adopting a WIoU v3 loss function; and training and optimizing the model by using the training set, and finally outputting a detection result through the test set. According to the invention, the problems of false detection and missing detection of the distributed photovoltaic panel in a high-altitude view angle are effectively solved, the detection precision of the distributed photovoltaic panel is further improved, and inspection personnel are helped to troubleshoot the photovoltaic panel in an abnormal state in the high-altitude view angle.

The invention discloses an intensive culture precise feeding control method based on fuzzy-MPC control, and relates to the technical field of aquaculture intelligent control, and the method comprises the steps: employing a sensing system, collecting multi-source sensing data including fish activity images, healthy growth states and water quality environment data in real time, and forming a comprehensive state data set; and based on the acquired multi-source sensing data, constructing an MTL-LSTM-SAT multi-task learning model. According to the method, the multi-task learning model fusing the LSTM and the soft attention mechanism is constructed, the long-term dependency relationship and dynamic association among the water quality, the feeding and the fish state can be captured, the attention mechanism enables the model to be automatically focused on a key time step, the perception ability of the water quality fluctuation and the feeding influence stage is enhanced, and the accuracy of the water quality fluctuation and feeding influence stage is improved. Meanwhile, double-task collaborative prediction of the growth speed and the disease proportion is achieved through the shared feature layer, a prospective state sequence of the future 7 days is output, and a quantitative and reliable prediction basis is provided for feeding decision making.

This invention discloses an ecological scheduling method and its application based on fish reproductive needs, belonging to the field of environmental protection technology in water conservancy and hydropower engineering. This invention specifically addresses the challenge of protecting fish that lay adhesive eggs. By establishing a population reproductive characteristic adaptation domain model (Ω(pi)), it quantifies for the first time the dynamic response relationship between water level fluctuations (proximal factor) and water temperature and flow velocity (terminal factor), breaking through the limitations of traditional ecological scheduling that only focuses on a single hydrological indicator. It achieves multi-objective collaborative optimization, balancing engineering needs such as flood control, power generation, and water supply with ecological protection through a dynamic adjustment model of ΔH(t). Through proximal factor monitoring and terminal factor feedback, it corrects the water level adjustment ΔH(t) in real time, improving the response speed compared to traditional methods. Furthermore, by dividing the control period according to the key processes of the fish life history, the water level fluctuation limit during the spawning period is more precise, providing an innovative technical method for ecological scheduling in water conservancy projects.

The invention discloses a satellite autonomous task planning method and system based on a ground digital mirror image, and belongs to the technical field of spacecraft measurement and control. Through the states of a satellite-ground link synchronous satellite and a ground digital mirror image, a task request is received in the ground digital mirror image, a planning algorithm is operated, a candidate scheme is generated for high-fidelity simulation deduction and verification, a feasible scheme is evaluated and selected and converted into an instruction sequence to be uploaded to a satellite, the satellite executes an instruction and feeds back the state, and a closed loop is formed. According to the method, a complex planning and verification process is placed in a ground digital mirror image, the efficiency and reliability of task planning are remarkably improved by using the strong computing power of the ground, meanwhile, the autonomous operation capability of a satellite is improved, and the problems that traditional satellite task planning is slow in response and poor in reliability, and the autonomous planning capability of a pure satellite is weak can be solved.

The invention relates to the technical field of antibacterial materials, and provides a light-enzyme-heat synergistic antibacterial nano composite material and a preparation method thereof.The preparation method comprises the steps that 1, a copper-based chalcogenide with a plasma resonance effect serves as a structural template, a transition metal oxide intermediate layer and a bismuth oxyhalide epitaxial layer are sequentially constructed on the surface of the copper-based chalcogenide with the plasma resonance effect through a step-by-step continuous solvothermal method, and the copper-based chalcogenide with the plasma resonance effect serves as the structural template; forming a core-shell heterojunction with Z-type energy band matching; (2) pre-assembling a natural enzyme and a monatomic nano-enzyme in a buffer system to form a composite catalytic unit with an electron transfer channel; and (3) by taking the core-shell heterojunction as a polymerization core, under the precise temperature control condition of 0-10 DEG C, initiating active free radical polymerization through an interface, constructing a thermal response polymer shell layer on the surface of the heterojunction, and encapsulating the composite catalytic unit in a functional microdomain of a polymer network in situ. The anti-bacterial fabric can achieve a better synergistic anti-bacterial effect.

The invention discloses a robot anti-interference control method based on a neural network interference observer, and the method specifically comprises the following steps: 1, building a robot dynamics model containing external interference, and constructing a state space model; step 2, establishing a fixed time interference observer based on a radial basis function neural network, and performing external interference estimation on the robot kinetic model; and step 3, a fixed time sliding mode controller is designed based on the interference estimation result, and fixed time control under the condition of external interference is realized. According to the robot anti-interference control method based on the neural network interference observer, the interference is accurately and rapidly estimated by using the fixed time interference observer, the convergence of the system state in the fixed time is realized by combining the fixed time sliding mode controller, and the feedforward compensation and feedback suppression of the interference are combined, so that the system stability is improved. The method has the advantages of simple implementation mode, high interference estimation precision and high response speed.

The invention discloses a drainage basin source-sink supervision system based on space-space-ground three-dimensional perception. The system comprises a three-dimensional perception module, a water quality fluorescent fingerprint database module and a qualitative traceability analysis module. The three-dimensional perception module is used for collecting multi-source perception data of an air, sky and ground three-dimensional monitoring system in the drainage basin and monitoring water quality indexes of a monitoring section of the drainage basin; the water quality fluorescent fingerprint database module is used for storing water quality fluorescent fingerprints of pollution sources in the drainage basin; and the qualitative traceability analysis module is used for carrying out a water quality fluorescent fingerprint test, carrying out similarity comparison on the water quality fluorescent fingerprint obtained by the test and the water quality fluorescent fingerprint stored in the water quality fluorescent fingerprint database module, and determining a pollution path and a suspected pollution source. According to the system, the pollution path and the suspected pollution source can be rapidly determined under the sudden water pollution condition, and the defects that traditional manual tracing is slow in response, and the pollution source is difficult to find and lock in time are overcome.

The invention discloses a container storage processing method and system based on TIPU, a terminal and a medium, and relates to the technical field of storage virtualization, and the technical scheme is characterized in that storage configuration information of NFS shared file information is encrypted; the method comprises the following steps of: creating a Configumap resource; a persistent storage declaration PVC is created, and a TIPU gateway is triggered to dynamically create virtiofs equipment; a POD is created, and virtiofs equipment is mounted to a container in the POD; the Configumap resource is analyzed, so that a first secret key fragment is injected into the virtiofs file system; and combining to form a complete secret key so as to decrypt the file information. According to the invention, the POD in the Kubernetes environment can be ensured to perceive and directly access the storage resources managed by the TIPU in real time, and efficient and dynamic unloading of the storage load is realized through seamless integration with the TIPU platform.

The invention relates to the technical field of electric power, in particular to a power supply zero-sensing switching method and system based on phase real-time tracking, and the method comprises the following steps: collecting the communication connection state of each inverter node in a micro-grid group, constructing a communication topology model of the micro-grid group, and analyzing a sparse communication connection relationship among the nodes in the communication topology model, and generating a Laplacian matrix reflecting node connectivity according to the sparse communication connection relationship. According to the method, the system state can be comprehensively evaluated from the two dimensions of external alignment precision and internal stability, and misjudgment caused by a single index is avoided. Dual errors are input into a switching stability evaluation model to calculate a stability index, and a switching instruction is generated only when the index exceeds a grid-connected permission threshold value, so that quantitative decision and strict control of a grid-connected opportunity are realized, and the micro-grid and a main grid are highly synchronous in phase and frequency at the moment that a circuit breaker is closed; and transient impact and circulation at the switching-on moment are eliminated.

This application discloses a corner module steering mechanism based on a rolling screw pair, comprising: a drive motor fixedly mounted on the vehicle body; a steering knuckle connected to the wheel hub, the steering knuckle having a steering arm and a lower connection point formed thereon, a steering tie rod connected to the steering arm, and the lower connection point being the lower point of the kingpin; and a rolling screw pair connected to the vehicle body, comprising a screw, a nut, and rolling elements, the nut being fitted onto the screw, the rolling elements being disposed between the nut and the screw, the nut being connected to the output end of the drive motor, and one end of the screw being connected to the steering tie rod, the screw being configured to move linearly only along the axial direction of the nut; when the wheel steers, the drive motor drives the nut to rotate and transmits the rotation through the rolling elements, causing the screw to move axially, which in turn drives the steering knuckle to rotate around the kingpin via the steering tie rod. This application eliminates the complex piping and pump structure of the hydraulic system, resulting in a simple and compact structure, and eliminating the possibility of hydraulic oil leakage.

The application relates to a proportional valve control method, system, device and storage medium, which comprises the following steps: obtaining the opening degree of the proportional valve; judging whether the opening degree change of the proportional valve belongs to a critical stage based on the change trend of the opening degree of the proportional valve, wherein the critical stage is a stage in which the opening degree of the proportional valve changes between being closed and being critically opened or a stage in which the opening degree of the proportional valve changes between a maximum opening degree and a critical maximum opening degree; when the opening degree change of the proportional valve belongs to the critical stage, a preset fixed duty ratio and a frequency change signal are used to control the opening degree of the proportional valve; and when the opening degree change of the proportional valve does not belong to the critical stage, a preset fixed frequency and a duty ratio change signal are used to control the opening degree of the proportional valve. The application can solve the problem of reduced control precision caused by flow hysteresis difference in the opening degree control of the proportional valve in the prior art.

The utility model discloses a kind of chemical fibre recycled material pretreatment reaction kettle, belong to spinning equipment technical field, this kind of chemical fibre recycled material pretreatment reaction kettle, including kettle body and electromagnetic heating control cabinet, the kettle body is three-layer structure, its inner layer is provided with pressure vessel layer, the pressure vessel layer directly contacts material, the intermediate layer of kettle body is provided with electromagnetic heating coil, and the electromagnetic heating coil is electrically connected in electromagnetic heating control cabinet, the outermost layer of kettle body is provided with heat preservation protective shell, and the front, middle and rear of kettle body are provided with temperature measuring probe. Heating is carried out to reaction kettle using electromagnetic induction coil cooperation electromagnetic heating control cabinet, heat loss is reduced in heating process, energy consumption cost is lower, and the response speed of heating is faster, without preheating and waiting, the temperature of reaction kettle is measured in real time by temperature measuring probe, cooperate electromagnetic heating control cabinet accurate temperature control, with better use effect.

The present application belongs to the technical field of geotechnical engineering test, and relates to a system and method for rapidly determining the permeability coefficient of low-permeability soil in situ, which comprises an inner sleeve, an outer sleeve, a pressurizing device and a pore water pressure sensor. The inner and outer sleeves are simultaneously driven into the soil to a specified depth, and then the outer sleeve is further pressed to form a sealed test cavity; water is injected into the inner sleeve and the top is closed, and a stable air pressure is applied through the pressurizing hole to accelerate the permeation; the pore water pressure sensor pre-embedded at the bottom of the outer sleeve is used to monitor the transient change data of the pore water pressure at the soil permeation interface in real time and in situ, instead of the traditional external water level change. Based on the monitored pressure decay data, the soil parameters can be calculated. Compared with the prior art, the present application discards the unreliable water level observation link, shortens the test time from several days to several hours, fundamentally avoids the errors introduced by the capillary effect and hysteresis effect, and realizes the rapid and high-precision test of low-permeability soil in situ.

This invention relates to the field of power grid management technology, specifically to a platform for energy consumption monitoring, analysis, and operation and maintenance of typical indoor substations in cold regions. The platform includes: an energy consumption change analysis module, an energy consumption cycle identification module, a power adaptability analysis module, a low-temperature impact assessment module, a fault risk identification module, and an equipment lifespan management module. This invention improves the accuracy of predicting power consumption trends and the speed of operational response by analyzing environmental data and energy consumption records of typical indoor substations in cold regions. By combining analysis of the relationship between temperature, wind speed, and energy consumption, it accurately predicts energy consumption changes and adjusts the power grid, matching seasonal and weather changes. Combined with real-time environmental data analysis, it improves the accuracy of assessing the impact of low temperatures in winter, optimizes the stability of the power system under extreme conditions, reduces losses caused by faults and unplanned outages, extends equipment lifespan, and improves operational efficiency.

The application relates to a water quality change trend rapid prediction method based on multi-source data fusion and physical constraints, and specifically comprises the following steps: step 1: synchronously collecting data such as spectrum information, DO, COD, temperature and pH at key monitoring sites, constructing a water dynamics-water quality coupling equation, and simulating the space-time dynamic distribution of water quality parameters; step 2: outputting a water quality sensitive area through a water dynamics-water quality model, screening sensor layout points by combining information entropy evaluation and spatial clustering, realizing low-cost water quality sensor network deployment through a multi-objective optimization algorithm, and calculating a water body global water quality distribution map by adopting a spatial interpolation method; step 3: analyzing main pollution sources according to the synchronous collection of spectrum information at key monitoring sites, and adopting principal component analysis and an attention mechanism neural network; step 4: based on real-time optical characteristic value-DO data, combining a spatial topological network, a water quality gradient and a cross-region covariance to capture the spatial correlation of water quality parameters between different points, and constructing an optical characteristic value-DO-COD dynamic prediction model; combining pollution tracing and spectrum characteristic correction to correct the COD prediction value, adopting ensemble Kalman filtering to assimilate multi-source data, and improving the model accuracy.

The present application relates to the technical field of plunger pump, in particular to a variable stroke double cavity plunger pump, which comprises a shell and a driving motor, two delivery pipes are arranged in the shell, two groups of crankshaft assemblies are arranged on the output shaft of the driving motor, the shell is connected with the corresponding delivery pipe through the crankshaft assembly, and a first one-way valve and a second one-way valve are symmetrically arranged in the delivery pipe along the axis of the crankshaft assembly; the one-way valve comprises a reset assembly, a sealing assembly and a clamping assembly arranged in sequence from top to bottom, the sealing of the sealing assembly is realized by the elastic extension of the reset assembly and the adhesion of the clamping assembly; the sealing assembly on the first one-way valve is provided with a first negative pressure assembly, the sealing assembly on the second one-way valve is provided with a second negative pressure assembly, and the first negative pressure assembly and the second negative pressure assembly are oppositely arranged; by arranging the negative pressure disc and the connecting pipe, the stress area of the sealing ball under the negative pressure condition is increased, the opening speed is accelerated, and the fluid passing efficiency is improved.

The utility model belongs to temperature monitoring technical field discloses a kind of lithium battery temperature real-time monitoring equipment, including shell, shell inner wall is connected with lithium battery group, the center position of lithium battery group one end is connected with heat conduction block, and the outer end of lithium battery group is connected with multiple ducts, the scheme is in lithium battery group outside along the length direction of battery Multiple fitting ducts are laid out, and heat-conducting oil is filled in duct interior, the joint action of heat-conducting oil and heat block, the heat generated by battery surface local is quickly, evenly guided to heat conduction block and thermistor, the efficient real-time monitoring of whole battery temperature is realized, the structure can greatly improve the response speed to local overheating phenomenon, reduce the error caused by point measurement delay or measuring point offset, with fast thermal response, high thermal coupling degree, strong adaptability Advantage, significantly enhance the safety and stability of lithium battery system under complex working conditions.

The application relates to a kind of port entry and exit special goods risk identification methods based on knowledge graph construction and entity linking, comprising: according to the risk identification demand of port entry and exit special goods in advance, constructing hierarchical risk factor knowledge graph;Obtain the declaration material of risk to be identified, carry out entity extraction from the declaration material, retrieve historical similar cases according to the extracted entity, build enhanced context containing declaration material and its historical similar cases, and carry out overall vectorization processing;Adopt three-granularity matching strategy: first, through Top-K screening, to match special goods subclass with coarse granularity;Then through threshold filtering, to match risk factor with medium granularity, finally, fine-grained matching risk feature node, to obtain the risk identification result of port entry and exit special goods.Compared with the prior art, the present application has the advantages of more precise risk feature expression, explicit risk knowledge audit, and realizes accurate matching from declaration material to knowledge graph node.