2644results about How to "Relieve stress" patented technology

The invention relates to the technical field of big data storage, in particular to a storage control method and device based on big data. The method comprises the following steps: acquiring an original data stream and application demand information; performing data dynamic correlation analysis on the original data flow according to the application demand information to obtain a dynamic update data correlation graph; performing feature vector generation on the dynamic update data association graph to obtain a data feature vector; performing intelligent quality evaluation on the data feature vector to obtain a data quality label; performing timeliness evaluation according to the data feature vector, and performing access popularity evaluation to obtain a timeliness score and an access popularity score; and acquiring system resource load condition information. The storage resource utilization rate, the data access performance and the overall efficiency of the system are improved by solving the limitation of a traditional method in the aspects of static data management and resource allocation.

The invention relates to the technical field of smart power grids, and discloses a distributed renewable energy source and energy storage cooperative scheduling system of Internet of Things data, comprising a data acquisition and monitoring module used for acquiring the running states of distributed energy sources and energy storage units through the Internet of Things technology; the energy supply and demand prediction module is used for predicting energy supply and load demand according to historical data, real-time data and meteorological information and generating basic data of a scheduling strategy; the collaborative scheduling strategy module formulates a collaborative scheduling scheme of the renewable energy and the energy storage unit based on energy supply and demand prediction, and adjusts the charging and discharging time of the energy storage unit; the double-layer optimization decision module is responsible for long-period energy storage planning and short-period real-time scheduling optimization; and the real-time monitoring and feedback module dynamically adjusts a scheduling strategy based on feedback data. According to the invention, through real-time monitoring, supply and demand prediction and cooperative scheduling of renewable energy sources and energy storage equipment, the system can optimize distribution and use of energy to the greatest extent, and energy waste is reduced.

The invention belongs to the technical field of biodegradable materials, and particularly relates to an environment-friendly degradable modified composite material, a preparation method and application. The material comprises PBAT, PBS, PLA, an inorganic mineral filler, natural plant fibers, PBAT-PTMO, nano-silica, an auxiliary agent and a plasticizer. In the preparation process, PLA is prevented from being hydrolyzed in vacuum drying, calcium carbonate and nano silicon dioxide are preheated and activated, natural plant fibers are dispersed through steam explosion and ethanol treatment, and raw material pretreatment comprises high-speed mixing and agglomeration breaking and medium-speed secondary premixing so as to realize uniform distribution. The co-rotating twin-screw extruder accurately controls the temperature, the speed, the rotating speed and the length-diameter ratio, and ensures melting plasticizing, uniform mixing and stable extrusion molding. According to the invention, by adopting accurate proportioning of multiple raw materials and a modification treatment process, the properties of mechanics, degradation, processing and the like of the material are synergistically improved, and the material is widely applied to multiple fields such as packaging bags, disposable tableware and agricultural plastic mulching films.

The invention discloses a crowded automatic warehouse multi-AGV path planning method based on a conflict search algorithm. The method comprises the following steps: constructing a grid map model of an environment where AGVs are located; at the bottom layer of the conflict search algorithm, AGV environment information is obtained according to the grid map model, and a path solution of the AGV and conflict information carried by the path are obtained by using an A * algorithm; according to the top layer of the conflict search algorithm, an improved constraint tree is constructed according to the obtained AGV path solution and conflict information, a node with the minimum loss is selected in the constraint tree for conflict detection, planning succeeds if no conflict exists, corresponding constraints are applied to conflicting AGVs if conflicts exist, and the whole process is circulated till planning succeeds. According to the method, the searching process of corridor conflicts is simplified, the driving direction allowed by the corridor is adaptively determined through searching, the planning process is accelerated by introducing the conflict priority and bypassing the conflicts, the planning time and the quality of a path solution can be considered as much as possible, and the working efficiency of the AGV is effectively improved.

The invention discloses a power decision-making system and method based on cloud side-end coordination, and the system comprises a terminal equipment node which is used for obtaining equipment monitoring data corresponding to power equipment, carrying out the preprocessing of the equipment monitoring data, obtaining target monitoring data, and transmitting the target monitoring data to an edge calculation node; and the edge computing node is used for determining a data analysis result corresponding to the power equipment according to the target monitoring data, and generating a short-time scheduling decision corresponding to the power equipment according to the short-time decision model, the data analysis result and the target monitoring data. Based on the above technical scheme, the equipment monitoring data corresponding to the power equipment is collected, and the edge computing node determines the short-time scheduling decision according to the processed target monitoring data, so that the scheduling decision corresponding to the power equipment is determined at the cloud side end, the decision making efficiency of the power system is improved, and the power system experience is improved. And the data processing pressure of the cloud is reduced.

The invention provides a low-cost preparation method of high-performance titanium-doped iron phosphate, and relates to the technical field of batteries. The low-cost preparation method comprises the following steps: S1, respectively preparing a phosphoric acid solution, a hydrogen peroxide solution, a phosphorus salt solution and a ferrite solution; s2, adding titanium sulfate into the ferrite solution to obtain an iron-titanium mixed solution; s3, directly adding ammonia water and a hydrogen peroxide solution into the phosphorus salt solution to obtain a phosphorus-oxygen mixed solution; s4, the iron-titanium mixed solution is heated, the phosphorus-oxygen mixed solution is put into the iron-titanium mixed solution, and slurry A is obtained; s5, obtaining a filter cake A; s6, adding pure water and a phosphoric acid solution, and heating to obtain slurry B; s7, obtaining anhydrous iron phosphate; the synthesized iron phosphate is compact and compact in morphology, internal pore channels of primary particles are still rich, the compaction density of the lithium iron phosphate material obtained through grinding and sintering reaches 2.613 g / cc, the 0.1 C discharge capacity can still reach 156.35 mAh / g, and the 1C discharge capacity reaches 131.47 mAh / g.

The invention discloses a dynamic power distribution method for a new energy charging module, and relates to the technical field of electric vehicle power distribution, and the method comprises the following steps: S1, determining the charging power distribution of the corresponding priority of an electric vehicle; s2, the charging power distribution of the electric vehicle and the state of the electric vehicle are adjusted in real time; s3, classifying the charged electric vehicles; and S4, dynamically adjusting the power distribution of the charging module. By dividing the charged electric vehicles into controllable electric vehicles and uncontrollable electric vehicles, selective power supply can be carried out on the charging module of the charging pile according to the types of the electric vehicles, for the controllable electric vehicles, the utilization rate of the charging station can be increased while the charging module does not exceed the rated power, and for the uncontrollable electric vehicles, the utilization rate of the charging station can be increased while the charging module does not exceed the rated power. The power output of the charging modules is dynamically adjusted through the alternate distribution strategy, the loss degree of each charging module is reduced, and the stability of the equipment is improved while the user requirements can be greatly met.

The air outlet reversing device comprises a comb head body, an air inlet end and an air outlet end are arranged on the comb head body, an air inlet is formed in the air inlet end, and a left air duct and a right air duct are arranged in the comb head body in a separated mode. The comb head body is internally provided with an air inlet and an air outlet end, the air outlet end is provided with first comb teeth, a left air outlet communicated with the left air duct and a right air outlet communicated with the right air duct, and the comb head body is further internally provided with an air distribution cavity communicated with the air inlet, the left air duct and the right air duct. The movable part is arranged in the air distribution cavity, so that the left air duct or the right air duct can be automatically shielded by means of the gravity action according to the inclination angle of the hair straightening comb, a user does not need to manually adjust the airflow direction when combing hair, and the user experience is improved. And the airflow path can be automatically optimized according to the actual position and action of the comb.

The invention relates to the technical field of resource optimization aggregation regulation and control, and particularly discloses an optimization aggregation regulation and control method and system capable of adjusting load resources, and the method comprises the steps: analyzing the environment state of a to-be-adjusted region, determining a resource aggregation regulation and control deviation factor, analyzing the power grid state and power grid weakness characteristics of the to-be-adjusted region, and determining a resource aggregation regulation and control deviation factor; and obtaining a resource aggregation regulation response factor, determining a resource aggregation regulation response priority category and a response duration category of the to-be-regulated region, obtaining regulation scale data of the to-be-regulated region, and judging whether load peak shifting and load power correction need to be performed on the to-be-regulated region or not. The problems that a traditional centralized regulation and control mode is difficult to adapt to the flexibility and complexity of distributed loads, and an existing regulation and control method is insufficient in consideration of load characteristics and influence characteristics and cannot achieve accurate regulation are solved. The utilization rate of power generation equipment is increased, and efficient utilization of energy is promoted. And new energy power generation fluctuation can be smoothed, and the access proportion of renewable energy sources can be improved.

The invention relates to the technical field of intelligent information management, in particular to an intelligent information management method and system based on cloud computing. The method comprises the following steps: performing load time sequence skewness analysis on enterprise database log data to obtain load fluctuation time sequence skewness data; performing table structure analysis on the enterprise database based on the enterprise database management authority, and performing table structure performance bottleneck analysis to obtain table structure performance bottleneck data; performing asynchronous read-write cache processing on the database table structure according to the table structure performance bottleneck data and the load fluctuation time sequence skewed data to obtain an asynchronous read-write cache database; carrying out compatibility matching on the asynchronous read-write cache database to obtain an asynchronous read-write compatibility cache database; and connecting the asynchronous read-write compatibility cache database to an enterprise database to execute intelligent information management. According to the invention, the intelligent information management technology is optimized, so that the intelligent information management technology is more perfect.

According to the energy storage coupling heat pump steam generation method and system, the mode that the heat pump device and the energy storage device cooperatively operate is adopted, and efficient and economical steam supply is achieved. The method comprises the steps that high-temperature water is prepared and stored in the off-peak electricity period through the heat pump device, and the high-temperature water is further heated through the energy storage device to generate superheated steam for a user to use. The energy storage device comprises a plurality of energy storage modules, and a heat exchange pipeline of the energy storage device can be switched between a parallel connection mode and a series connection mode through switching, so that deep heat release and flexible regulation and control are achieved. According to the method, the energy storage capacity and heat release power of the energy storage module are dynamically adjusted, enthalpy increment distribution of the heat pump and the energy storage device is optimized in combination with load prediction, and diversified steam requirements are met. And meanwhile, preheating or dynamic supplement is conducted on the energy storage module through the heat pump device, waste heat recovery is achieved, and the energy efficiency is improved. According to the method, the operation cost is remarkably reduced, the capacity of the system for adapting to load fluctuation is enhanced, and the method is suitable for industrial steam use scenes and has the advantages of being efficient, stable and flexible.

The invention relates to the technical field of safety management, in particular to a safety management method of Internet of Things equipment, electronic equipment, a medium and a product, and the method comprises the steps: obtaining real-time operation data of each piece of Internet of Things equipment in an Internet of Things system; based on preset hidden danger features, whether abnormal operation data exists in all the real-time operation data is judged, and the abnormal operation data is the real-time operation data containing the preset hidden danger features; if yes, determining a hidden danger type corresponding to each piece of abnormal operation data based on a preset hidden danger feature corresponding to each piece of abnormal operation data; and based on each abnormal operation data and the corresponding hidden danger type, triggering an early warning mechanism of the abnormal Internet of Things equipment corresponding to each abnormal operation data. According to the application, the Internet of Things equipment with potential safety hazards can be found in time, and the Internet of Things equipment can be overhauled or maintained in time, so that the influence on other Internet of Things equipment is reduced.

The invention belongs to the technical field of chronic wound depth analysis, and relates to a chronic wound depth analysis system based on image recognition. According to the method, more comprehensive and richer wound information is provided by acquiring the chronic wound image of the target patient, misdiagnosis and missed diagnosis can be reduced, the depth of the chronic wound can be judged more accurately, and by analyzing the initial depth level of the chronic wound image of the target patient, the accuracy of the chronic wound is improved. The chronic wound in-depth detection method of the target patient is determined, the in-depth detection requirement of the chronic wound of the target patient is judged, a more personalized detection scheme can be formulated, unnecessary examination and treatment are reduced, the economic burden and psychological stress of the patient are reduced, and the detection accuracy is improved by determining the chronic wound in-depth detection method of the target patient and performing detection and correction. The final depth grade of the chronic wound image of the target patient is analyzed, interference factors in the image can be recognized and corrected, the diagnosis accuracy is improved, and an important basis is provided for formulating a personalized treatment scheme.

The invention relates to the technical field of power distribution court autonomy, and discloses a court autonomy method, system, equipment and medium based on new energy coordinated regulation, comprising the steps of: acquiring equipment operation parameters and court load parameters of new energy equipment in a power distribution court in real time, and according to the equipment operation parameters and the court load parameters, calculating the power distribution court autonomy according to the equipment operation parameters and the court load parameters; and regulating and controlling the photovoltaic inverter, the energy storage equipment and the charging pile in the power distribution area by adopting a preset regulation and control strategy, wherein the regulation and control strategy comprises a first regulation and control strategy and a second regulation and control strategy. The running states of the photovoltaic equipment, the energy storage equipment and the charging piles in the transformer area are monitored in real time, the photovoltaic equipment, the energy storage equipment and the charging piles are cooperated to carry out transformer area autonomy in combination with the local control strategy of energy storage, the consumption pressure of distributed photovoltaic is effectively reduced, the optimal charging load regulation control of the transformer area is realized, and the power consumption of the transformer area is reduced. And safe and stable operation of the power distribution area is ensured.

The invention discloses an underwater swimming fish body mass estimation method and system, and relates to the technical field of computer vision, and the method comprises the steps: collecting fish body side view image data through a binocular camera, carrying out the calibration and correction operation, and carrying out the image preprocessing; the method comprises the following steps: extracting two-dimensional features of a fish body target, obtaining a final fish body image disparity map based on an APT-DMR method, extracting corresponding key matching points of a left image and a right image of a fish body based on the final disparity map, obtaining feature point space coordinates according to a triangular geometry principle, and calculating three-dimensional features by using a spatial distance formula; and constructing a fish body quality prediction model based on the MLR, and predicting the fish body quality. According to the method, the fish disparity map is obtained based on the SGBM algorithm, the corresponding key matching points of the left and right images of the fish body are extracted, the coordinates of the three-dimensional space feature points of the fish body are calculated, the three-dimensional features of the fish body target are extracted, the fish body quality prediction model based on the MLR is constructed, the fish body quality is predicted, and the prediction precision and reliability are improved.

The invention discloses a photovoltaic power generation system optimization management system based on intelligent scheduling, and relates to the technical field of renewable energy sources and intelligent power grids. The system comprises the following components: a distributed cooperative control strategy, an information sharing and transaction platform supported by a block chain technology, an intelligent scheduling and optimization engine, intelligent power grid deep integration and a user interaction and visualization interface. Through an innovative distributed cooperative control strategy, comprehensive operation data of a photovoltaic power generation system, a wind energy system, an energy storage system and a micro-grid peripheral energy system can be accurately collected in real time, and an energy supply and demand trend is analyzed and predicted based on big data; therefore, the system can automatically adjust the power generation plan, the energy storage strategy and the load distribution of each system, and the optimal operation of the whole energy system is realized.

The invention discloses a reclaimed oil bio-based plastic modified rubber material and a preparation method thereof, and the reclaimed oil bio-based plastic modified rubber material comprises the following components by weight: 30-70 parts of bio-based plastic, 10-40 parts of natural rubber, 5-25 parts of plant fiber, 5-50 parts of calcium powder, 0.3-1.5 parts of a vulcanizing agent, 0.8-2 parts of zinc oxide, 0.3-0.9 part of an accelerator, and 1-10 parts of a foaming agent. The invention relates to the technical field of rubber materials, in particular to an antibacterial and mildew-proof rubber material. The regenerated oil-based bio-based plastic is innovatively applied to modification of a rubber material, a new application way of the bio-based material in the field of rubber-plastic compounding is developed, a new thought is provided for solving the environmental and resource problems caused by a petroleum-based material, and the selection of the raw materials not only embodies effective utilization of renewable resources, but also has the advantages of environmental protection and environmental protection. The carbon emission is reduced, and the development trend of current green materials is met.

The invention relates to the technical field of data processing, in particular to an equipment cluster multi-modal edge data intelligent processing method based on multi-agent deep reinforcement learning, and the method comprises the steps: firstly classifying data in an equipment cluster according to the characteristics of the data, and dynamically adjusting the priority of data preprocessing according to the importance and access frequency of the data; secondly, a deep reinforcement learning framework is adopted, each edge computing node serves as an independent intelligent agent, self-learning and optimization are conducted through interaction with the environment, the intelligent agents dynamically select computing resource allocation of the edge nodes, instant rewards are obtained according to the data processing efficiency, and the strategy is continuously optimized; the intelligent agents achieve collaborative learning through the shared experience pool, the data processing efficiency is improved, and the load pressure of the central server is relieved. According to the method, the efficiency and real-time performance of equipment cluster multi-modal data processing are effectively improved, flexible scheduling of edge computing nodes is ensured, and therefore the dynamic change requirement is met.

The utility model relates to a sludge treatment device and a sewage sludge co-treatment and resource utilization system, the sludge treatment device comprises a kitchen garbage feeding module, a wet oxidation treatment module and a controller, the kitchen garbage feeding module comprises a storage box and a feeding unit, the storage box comprises a cavity, a first feed port and a first discharge port, and the feeding unit comprises a second feed port and a second discharge port. The first feed port and the first discharge port are respectively communicated with the cavity, the first feed port is used for adding kitchen garbage into the storage box, and the first discharge port is communicated with the charging unit; the wet oxidation treatment module comprises a wet oxidation reaction unit, and the wet oxidation reaction unit is used for performing wet oxidation treatment on a mixture of the sludge and the kitchen garbage to generate a treatment product; the controller is respectively connected with the kitchen garbage feeding module and the wet oxidation treatment module, so that the sludge can be treated, the kitchen garbage can be simultaneously subjected to cooperative treatment, the pressure of kitchen garbage treatment is relieved, and the sludge treatment device is wide in application range.

The invention belongs to the technical field of power system data analysis, and relates to a power utilization habit-based power utilization abnormal behavior real-time analysis method and system, and the method comprises the steps: obtaining a historical power utilization data sample of a charging pile user, and carrying out the calculation to obtain a power utilization behavior habit interval; acquiring real-time power consumption data of the charging pile user according to a preset period, judging whether the real-time power consumption data is in the power consumption behavior habit interval, and if so, not giving an alarm; otherwise, giving an alarm; the advantages of wide coverage, high timeliness and high accuracy of power data are utilized, and the power utilization habit of the user is obtained through data analysis. Real-time power utilization data and historical power utilization habits are compared, abnormal power utilization behaviors are recognized, abnormal power utilization alarms are given out, and a charging pile operator is assisted in effective management, prevention and control; maintenance and upgrade plans of the charging piles are reasonably arranged, and usability of the charging piles is ensured. An electric power company can adjust an electric power supply strategy in advance, optimizes a power grid load, and avoids overlarge power grid pressure caused by a charging peak.

The invention provides an application of a transporter in improving the yield and / or purity of lactose-N-neotetraose (LNnT), and relates to the technical field of genetic engineering. Transporter proteins of different sources are screened, the transporter protein which aims at LNnT synthesis and can achieve efficient transportation is obtained, and a new biological material is provided for LNnT synthesis. Moreover, the efficient transporter obtained by screening is used for transporting the LNnT to the outside of cells, so that the pressure on the cells caused by overhigh concentration of intracellular products is relieved, the conversion of an intermediate product LNT II to the LNnT is improved to the maximum extent, the yield is improved while byproducts are reduced, the yield of a byproduct lactose-N-neohexaose is also reduced, and the separation and purification of later products are facilitated.

The invention belongs to the field of big data, and relates to a file storage method which comprises the steps that access frequency information of a target file in a historical time period is acquired, and the target file is stored in a mechanical hard disk of an object storage system; judging whether the target file is a high-frequency access file or not according to the access frequency information and an access threshold value; if the target file is the high-frequency access file, obtaining file attribute information of the target file, and judging a to-be-stored type of the target file based on the cache strategy and the file attribute information; if the to-be-stored type of the target file is a memory storage type, storing the target file into a memory cache; and if the to-be-stored type of the target file is the standard storage type, storing the target file into a solid state disk cache. The invention further provides a device, equipment and a medium. In addition, the invention also relates to a block chain technology, and the access frequency information and the target file can be stored in a block chain. The method can improve the utilization rate of storage resources.

The invention provides a peak valley adjusting method and system for an alternating current charging pile of an electric vehicle, and belongs to the technical field of data processing. The adjusting method comprises the steps of obtaining data of a to-be-charged electric vehicle and historical data of an alternating current charging pile; calculating a charging urgency value of each to-be-charged electric vehicle; judging whether the charging urgency value of the electric vehicle is greater than a preset charging urgency value or not; if yes, adding to an emergency scheduling queue; otherwise, adding into a normal scheduling queue; taking minimization of the power demand change of the alternating current charging pile in the peak period and maximization of the utilization rate of the alternating current charging pile as targets, constructing a peak-valley adjustment model of the alternating current charging pile, and determining a target function and constraint conditions; under the constraint of the constraint condition, taking the minimum function value of the target function as a target, optimizing the peak-valley adjustment model, and outputting an optimal charging scheduling strategy; and according to the optimal charging scheduling strategy, scheduling the to-be-charged electric vehicle so as to perform peak-valley adjustment of the AC charging pile.

The present invention relates to the field of real-time data processing technology, specifically a distributed real-time data stream processing system and method, the system includes a state mapping modeling module, a load dynamic calculation module, a node task adjustment module, and a resource scheduling execution module. In the present invention, by analyzing the data flow change sequence, identifying the frequency and trend of state switching, realizing dynamic identification and classification of flow states, improving the monitoring and understanding capabilities of real-time data, accurately quantifying node resource pressure in resource occupancy and load range analysis, enhancing the predictability of load balancing, providing a scientific basis for resource scheduling, combining task priority sorting and dynamic task adjustment, optimizing node computing resource utilization and task processing response speed, realizing flexible configuration of memory and computing resources, alleviating peak load pressure, improving data processing efficiency and system stability, and improving the system's adaptability and reliability in processing large-scale data flows.

The invention belongs to the technical field of photovoltaic power generation, and particularly relates to an energy storage management system of distributed photovoltaic power generation equipment, which comprises a photovoltaic module used for converting illumination into direct current; the energy storage module is used for storing direct current; the grid-connected inverter is connected with the energy storage module and is used for converting the direct current into alternating current and supplying power to a load in cooperation with a power grid; the cloud platform is used for predicting the power demand J of the load in the next day and predicting the power generation R of the photovoltaic module in the next day; judging whether the sum of the next-day generating capacity and the remaining capacity meets the next-day power consumption of the load or not based on the next-day power demand, the next-day generating capacity and the remaining capacity by predicting the next-day power demand of the load and the next-day generating capacity of the photovoltaic module and obtaining the remaining capacity of the energy storage module; the decision module controls the power grid and the grid-connected inverter to supply power to the load; the influence on the chemical property of the energy storage battery, the acceleration on the aging of the energy storage battery and the sulfation phenomenon of the energy storage battery due to long-time deficiency of the energy storage battery are prevented.

The invention relates to the technical field of slope protection, and discloses a municipal water supply and drainage construction slope protection device which is mainly composed of a plurality of vertical protection mechanisms and a transverse protection mechanism, and the vertical protection mechanisms are linearly arranged on the surface of a slope body. A transverse protection mechanism is arranged between the two vertical protection mechanisms, and the two ends of the transverse protection mechanism are connected with the connecting mechanisms. The vertical protection mechanism, the connecting mechanism and the transverse protection mechanism are arranged on the slope body, the vertical protection mechanism is movably connected with the transverse protection mechanism through the connecting mechanism, and due to the fact that the transverse protection mechanism is obliquely arranged, when it rains, rainwater is guided by the transverse protection mechanism, flows into the vertical protection mechanism and then is discharged downwards through the vertical protection mechanism; the amount of rainwater flowing on the surface of the slope body is effectively reduced, the impact force of the rainwater on the surface of the slope body is reduced, and therefore water and soil loss is relieved, and protection on the slope body is improved.

The invention discloses a transformer substation unmanned aerial vehicle autonomous inspection system which comprises an unmanned aerial vehicle platform, a three-dimensional modeling module, an inspection route setting module, an autonomous inspection module, a mobile monitoring platform, an image acquisition module, an image processing module, an alarm module, a visualization module, a data storage module and a wireless communication module. Wherein the three-dimensional modeling module comprises laser radar equipment and three-dimensional modeling software, the routing inspection route setting module is used for setting different routing inspection routes according to different routing inspection modes and corresponding routing inspection rules, the autonomous routing inspection module comprises a navigation system and a positioning base station, and the mobile monitoring platform comprises a remote controller and vehicle-mounted charging equipment. The image processing module is used for processing and analyzing different types of collected images and different purposes of collected images by using different algorithms so as to timely discover abnormity and give an alarm; the method has the advantages of being good in inspection abnormity processing effect, good in positioning effect, convenient to use and good in data processing effect.

The invention discloses an emotional support dialogue method based on user belief, which comprises the following steps of: forming a feature vector of a user by using past dialogue information, user characters, emotions and scenes, and then generating a divergent expansion model based on a large language model agent and knowledge graph mode to obtain a user scene vector. On the basis of a consistency algorithm of a mental theory, on the premise of information flow consistency and coherence, a consistency check model is generated, scene vectors are mapped into belief vectors of users, and the belief vectors are added into a belief library. According to the method, from the perspective of generative artificial intelligence, the cognitive process between a person and a system is simulated, and the method is generally divided into three steps of perceiving, guessing and verifying. And after the basic information of the dialogue is dynamically obtained, a divergent expansion model is utilized to generate a detailed description text and a knowledge chain, so that the cognition on the user is enhanced. And the high correlation between the dynamic updating condition of the belief information and the real condition of the user is ensured through a consistency model.

The invention discloses a remote video monitoring data transmission method, and the method comprises the steps: collecting visual video information through a robot camera, and transmitting the visual video information to a remote power plant monitoring center through a HDMI interface, an encoder, a 5G-CPE, a decoder and other links. The 5G-CPE uses MEC, 5G slicing and SRT technologies to adjust resource allocation according to network conditions and requirements, and defines configuration slices and priorities. A network monitoring component is deployed to monitor slice loads in real time, a load threshold value is set for each slice, and a resource adjustment strategy is triggered when the loads exceed the threshold values. And resources are dynamically reallocated after analysis and evaluation, so that sufficient and optimized utilization of high-load slice resources is ensured. Performance is continuously monitored and feedback adjustment is performed, network adaptability and flexibility are improved, key video streams are ensured to be transmitted preferentially, and power plant inspection requirements are met.

The invention belongs to the technical field of turbine tail gas compressor units, and discloses a turbine tail gas centrifugal compressor unit working system which comprises a turbine tail gas centrifugal compressor unit, a compressor unit inlet buffer tank, a compressor unit inlet separator, a first-section cooler, a second-section cooler, a third-section cooler and a fourth-section cooler. A gas outlet of the second-section cooler is communicated with a first-section compression inlet of the low-pressure cylinder to form a first-section anti-surge loop, and a gas outlet of the fourth-section cooler is communicated with a third-section compression inlet of the high-pressure cylinder to form a third-section anti-surge loop. The system can realize undisturbed switching of two process gases, namely desorption gas and low-pressure nitrogen, and recover a large amount of desorption gas, so that the desorption gas emission in the driving process is effectively reduced, the production cost is saved, and the economic benefit is improved.