35results about How to "Realize intelligent distribution" patented technology

The invention provides an oil depot tank field inspection robot task allocation method and system based on the Internet of Things, and relates to the technical field of the Internet of Things. Constructing a multi-target collaborative scheduling model, extracting features by adopting a space-time attention mechanism, establishing a task priority evaluation and path planning sub-model, and generating an optimal task allocation strategy; and an inspection task instruction is issued, the execution condition is monitored in real time, and when abnormity is detected, the emergency module is started for optimization adjustment. According to the invention, intelligent and collaborative routing inspection task distribution is realized, and the routing inspection efficiency and safety are improved.

The invention discloses a cooling cooperative control method, and the method comprises the steps: obtaining a temperature parameter, a load state parameter and a cooling system parameter of a transformer, and forming a parameter set; constructing a gating circulation unit model, and predicting thermal load distribution of each region of the transformer by adopting the parameter set through the gating circulation unit model; and performing real-time distribution on cooling resources by adopting a dynamic region distribution algorithm. According to the cooling cooperative control method, temperature and load changes of all areas of the transformer are predicted in real time through a gating circulation unit model; intelligent distribution of cooling resources is achieved through a dynamic area distribution algorithm, the cooling cooperative control method can dynamically adjust the flow speed of a cooling medium and the rotating speed of a fan according to real-time temperature and load changes, it is ensured that all areas of a transformer obtain appropriate cooling resources, and extra cooling is preferentially provided for areas with the temperature abnormally increased; and a cooling strategy is optimized through multiple iterations in combination with historical operation data, so that the response speed and accuracy of the cooling system are remarkably improved.

The invention provides a high-efficiency intelligent teaching resource scheduling algorithm and an implementation method thereof, and the method comprises the steps: constructing a judgment matrix according to a learner capability difference evaluation result, cooperation efficiency analysis data, knowledge graph coverage rate statistics and learning style matching degree score, carrying out the calculation to obtain a group heterogeneity index, solving the weight of each index through a feature value method, and carrying out the calculation of the group heterogeneity index. Carrying out weighted summation to obtain a group complementarity comprehensive index; acquiring a historical learning data sequence of a learner, extracting time sequence features, combining a current individual progress deviation monitoring result, individual resource demand evaluation and individual learning content suitability analysis, constructing an individual development trajectory prediction model, and predicting a future individual learning performance curve; and aiming at the group complementarity comprehensive index and a future individual learning performance prediction result, constructing a multi-objective optimization model of resource allocation, setting a group complementarity objective function and an individual satisfaction objective function, and solving to obtain a resource allocation scheme for balancing group and individual benefits.

The invention discloses a data center infrastructure operation and maintenance management system and method, and relates to the technical field of data center management. Comprising a data collection module which is responsible for collecting basic information and operation state data of various facilities in a data center; the feature analysis and label generation module is used for performing feature analysis on each facility based on the collected data and generating a corresponding feature label; each facility corresponds to a plurality of feature tags, including equipment types, performance indexes and fault histories; and the maintenance personnel capability evaluation module is used for establishing a capability model of the maintenance personnel and setting various capability scores for each maintenance personnel according to skill levels and working experience factors of the maintenance personnel. According to the invention, data is collected and analyzed in real time, and managers are helped to know system conditions in time and make better management decisions; according to the condition of the maintenance personnel and the matching degree with the equipment condition, the appropriate maintenance personnel are selected to execute the maintenance operation, so that targeted processing is realized, and the maintenance efficiency is improved.

The invention relates to a wireless network communication method and system, and belongs to the technical field of communication. The method comprises the following steps: integrating channel monitoring, data acquisition and primary processing functions, and realizing real-time sensing and data preprocessing of an environment; adaptive power control and resource allocation functions are fused, and dynamic adjustment of transmitting power and intelligent allocation of network resources are realized through cross-level optimization decision; the edge computing capability is utilized to share system architecture optimization tasks, dynamic scheduling computing and communication resources; and resources are dynamically configured by adopting a virtualization technology, and the overall architecture of the system is centrally managed. Through comprehensive application of cross-level collaborative optimization, adaptive power control and edge computing technologies, the energy efficiency and communication quality of the system are remarkably improved, and efficient utilization of resources and flexible management of network architecture are realized.

The invention relates to the technical field of batteries, and discloses a battery self-adaptive safety protection method and system based on data driving, and the method comprises the steps: extracting parameter features of a transient segment, a steady segment and a fluctuation segment after segmentation, constructing a comprehensive feature matrix based on the parameter features, all environmental factors of the battery are screened based on the environmental influence model, the working condition of the battery is determined based on the working condition identification model, the environmental influence factors and the state feature sequence, the working condition is verified based on historical data, and a corresponding monitoring strategy is selected based on the verified working condition or the re-determined working condition. And the acquisition interval is adjusted based on the monitoring strategy, the risk direction of the battery is determined based on the relationship between the standard state feature sequence and the state feature sequence, and whether power-off protection is performed on the battery is judged based on the association relationship of all the risk directions. According to the invention, through data driving of historical data, the flexibility and reliability of battery safety protection are ensured.

The invention relates to the technical field of display control, and discloses a control method and device of a mobile intelligent display terminal, equipment and a storage medium. The method comprises the following steps: performing system initialization and hardware self-inspection on a main controller of the mobile intelligent display terminal to obtain a terminal initialization data packet; performing network quality evaluation on the terminal initialization data packet through the network set top box to obtain a transmission protocol parameter; content distribution is carried out through the network set top box and the transmission protocol parameters, cache management is carried out through the display control chip, and a multi-level cache data structure is obtained; carrying out decoding and quality enhancement processing on the video data through the display control chip to obtain an enhanced video frame; performing dynamic power consumption management on the enhanced video frame through the display control chip to obtain a target display parameter; and performing anomaly detection and automatic correction on the target display parameter through the display control chip to obtain the display control instruction, thereby optimizing the video transmission and display process and improving the user experience.

The invention discloses a resource dynamic allocation method based on cloud computing. The method comprises the following steps: step 1, realizing sub-region division and labeling through grid and map data; 2, realizing user order prediction by establishing a regional taxi-taking order prediction model; 3, predicting a user order to minimize the empty driving time of a driver; 4, order priority ranking is carried out, user feedback is carried out, a taxi-taking order prediction and delivery optimization module is used for establishing a taxi-taking order prediction model of a region level, and the utilization rate of the driver vehicle is improved through an optimized delivery algorithm; the intelligent distribution and real-time optimization module is used for minimizing the empty driving time of a driver through an intelligent order dispatching algorithm, and realizing intelligent distribution and real-time optimization of orders in combination with a real-time order demand map, traffic information and a dynamic adjustment strategy; the method has the characteristics of improving the vehicle utilization rate and the taxi taking experience of the user.

This invention relates to the field of automotive battery management technology, specifically to a non-intrusive parallel safety control device and method for auxiliary batteries in electric vehicles. The device includes a three-terminal parallel connection component, a boost converter module, a dual 12V signal detection module, a control module, and a power switch array. The three-terminal component reuses the original vehicle's high-voltage bus, the boost module adapts to the low-voltage auxiliary battery, and uses optocoupler isolation to detect charging and ignition signals. The control module executes electrically independent control logic, only turning on the power switch array during charging and discharging to achieve coordinated operation, and disconnecting it at other times to maintain electrical independence between the main and auxiliary batteries. This application eliminates the safety hazards of long-term parallel connection of new and old batteries without modifying the original vehicle's protocol and circuitry, ensuring the original manufacturer's warranty, and achieving intelligent range expansion and charging management.

The invention discloses a charging pile control method and device and a charging pile, and belongs to the field of new energy charging piles, and the charging pile control method and device comprises the steps that charging demand information of multiple to-be-charged vehicles connected with multiple charging guns is acquired, and the charging demand information at least comprises the battery charge state, the battery capacity and the charging duration preset by a user; according to the charging demand information, the charging priority and the demand power of each vehicle are calculated; generating a power distribution strategy according to the charging priority and the required power, and dynamically distributing a plurality of power modules in the charging pile to a plurality of charging guns; controlling the on-off state of the power distribution matrix according to a power distribution strategy so as to establish electric connection between the power supply module and the charging gun; in the charging process, the actual charging power and the battery state of each vehicle are monitored in real time, the on-off state of the power distribution matrix is dynamically adjusted according to the monitoring result, the power modules are redistributed, and the charging efficiency is maximized on the premise that the requirement for charging multiple vehicles at the same time is met.

The invention relates to a pico base station memory allocation method and device, an electronic device and a storage medium, and the method comprises the steps: dividing a memory region in a pico base station into a plurality of memory blocks; obtaining a preset main line memory pool and a branch line memory pool; wherein to-be-allocated memory blocks in the memory blocks are stored in the main line memory pool, and to-be-used memory blocks in the memory blocks are stored in the branch memory pools; detecting use information of the to-be-used memory blocks stored in the branched memory pool, and determining available memory blocks of the to-be-used memory blocks based on the use information; and based on a comparison result between the number of the available memory blocks and a preset memory block number threshold, generating a memory resource allocation result of the pico base station. Through application of the method and the device, the problem of how to allocate the memory resources of the base station in a balanced manner to ensure that each cell under the base station can meet the processing of the current data volume and achieve the optimal performance is solved, intelligent allocation and recovery of the memory blocks are realized, the utilization rate of the memory is improved, and the waste of the memory resources is avoided.

The invention discloses an event-driven adaptive sampling and hierarchical transmission method based on a data change rate. The event-driven adaptive sampling and hierarchical transmission method specifically comprises the steps that S1, an equipment end collects industrial equipment operation data at a fixed frequency and generates a data frame; s2, the server side calculates the data change rate of adjacent data frames from the same equipment, and generates an abnormal score based on the change rate; s3, the server side divides the data frame into event levels at least including a heartbeat level, a conventional level, an abnormal level and an accident snapshot level according to the abnormal score Score; s4, the server performs adaptive adjustment on an issuing strategy to the client according to the event level; s5, the server triggers an accident snapshot level event, and reliably transmits and issues the accident snapshot level event to the client through a TCP; and S6, the server side enables the data of different event levels to enter different priority queues and dispatches and issues the data according to the priorities. According to the invention, through event grading, sampling self-adaption and grading transmission, priority arrival of key abnormal data and complete reservation of accident data are realized.

The present invention provides a train braking control method and system, the system includes: a train braking control module, a vehicle braking electronic control module, a vehicle braking air control module, a mode switching module and a control loop, the train braking control module is used to send a braking command to the vehicle braking electronic control module through a braking control network, and send a corresponding voltage or current signal to the vehicle braking electronic control module through a braking control hard line according to the target braking force of the vehicle, so that the vehicle braking electronic control module controls the vehicle brake cylinder, and is also used to send an emergency braking signal on the emergency braking hard line when the train is in emergency braking, so that the vehicle braking electronic control module controls the mode switching module to switch the braking mode, and the vehicle braking air control module generates the vehicle brake cylinder control pressure. The present application can improve the synchronization of braking, reduce the impulse of the train, and can also achieve perfect stage braking and stage relief, and also improve the safety and reliability of braking.

The invention relates to the technical field of operation control, in particular to a textile delivery inspection control system, which comprises a data acquisition module, an inspection task generation module and an inspection distribution module, the data acquisition module is used for automatically acquiring basic information and shipment requirements of to-be-detected textiles; the inspection task generation module dynamically generates an inspection task according to the basic information of the textiles and shipment requirements, and the inspection task comprises an inspection standard and an inspection process; and the inspection distribution module distributes corresponding inspection personnel according to the inspection standard and the inspection process, provides a work station for the inspection personnel, and supports the inspection personnel to execute the inspection task according to the established standard, and the work station comprises all related information of the textile to be inspected, the inspection standard and the inspection process guidance. According to the invention, not only is the accuracy of inspection task generation significantly improved, but also each inspection work is ensured to highly meet the actual situation and market demand of textiles.

The invention provides a mobile office method and system applied to river and lake secret visit, and relates to the field of water resource management and environmental protection, and the method comprises the steps: after a new problem clue is received, carrying out the severity grade classification and influence range grade classification of the problem clue through an intelligent algorithm, and obtaining a classification result; according to the position information corresponding to the problem clues and the classification result, determining a priority order of the problem clues in a patrol queue; in the process that the worker carries out evidence collection according to the priority ranking, obtaining field evidence data corresponding to each problem clue through mobile equipment carried by the worker; and generating an investigation report according to the investigation template corresponding to the problem clue and the field evidence data. By implementing the method, intelligent allocation and mobile office of problem clues are realized, so that resource allocation is optimized, and response time delay of report generation is reduced.

The invention relates to an intelligent distribution system for logistics order resources. The intelligent distribution system comprises an information acquisition part, a data capture part, a multi-layer building mechanism, a prediction processing mechanism, a store configuration mechanism, a prediction processing mechanism, a store configuration mechanism and the like. The logistics management level can be improved.

The application discloses a drill-and-blast tunnel dynamic geological modeling method, medium, equipment and product, relates to the technical field of tunnel geological modeling, and comprises the following steps: according to the tunnel length and the hole diameter range of different construction periods, a tunnel three-dimensional geological model with different precision and resolution is constructed, the tunnel three-dimensional geological model is constructed in the following process: based on geological exploration data and drilling data, a stratum interface three-dimensional model is constructed; based on drilling core data, advanced drilling lithology information and geophysical prospecting data, lithology information is coupled to the stratum interface three-dimensional model to form a lithology three-dimensional distribution; the physical and mechanical parameters of rock-soil bodies are associated with the lithology three-dimensional distribution to realize three-dimensional assignment of the physical and mechanical parameters and form an attribute parameter field model; and the tunnel three-dimensional geological model is dynamically incrementally updated along with construction progress. The application adopts hierarchical models, takes into account the high-precision requirement of a current construction section and the efficiency requirement of a long-term planning section, incrementally updates the models, and improves the working efficiency of the whole modeling process.

The invention provides a waste heat application method, system and device for a photovoltaic curtain wall, a controller and a medium, and the system comprises a plurality of photovoltaic modules, the back surfaces of which are installed against a wall body; the photovoltaic module is installed between the back of the photovoltaic module and a wall body; the heat exchanger is arranged on the back of the photovoltaic module relative to the fan; one end of the heat exchange water pipe communicates with the heat exchanger through a wall; the other end of the heat exchange water pipe is communicated with the water storage tank; each water supply pipe is further communicated with one external device, and the multiple external devices are arranged in the same smart home environment; the controller is electrically connected with the fan and the water storage tank, when the photovoltaic module works, the fan is controlled to blow hot air generated by the photovoltaic module to the heat exchanger to complete cooling of the photovoltaic module, and the heat exchanger heats water in the water storage tank through the heat exchange water pipe by means of heat in the hot air. And the water storage tank is controlled to convey the heated water to external equipment through the water conveying pipe according to preset requirements so as to supply hot water to the external equipment.

The invention provides an edge cloud collaborative data processing system and method based on deep learning, and relates to the technical field of edge cloud collaboration, and the method comprises the steps: extracting a task feature vector of edge terminal equipment from a data task flow; constructing a task dependency graph, and determining an allocation label during sub-task processing through the task dependency graph and the resource allocation granularity of the sub-tasks in the data task flow; carrying out confidence adjustment on each distribution label to obtain execution confidence of the subtasks on the edge terminal equipment, and further carrying out load transfer analysis on the edge terminal equipment to obtain load transfer quantity of the edge terminal equipment; when the load transfer amount is smaller than a preset load transfer threshold value, the subtasks in the data task flow are asynchronously executed in the edge terminal device, and otherwise, the data task flow in the edge terminal device is sent to the cloud server through the edge cache server for batch processing. The task load between the edge terminal device and the cloud server can be divided under the condition that heterogeneous computing resources are limited.

The invention provides an online data flow monitoring optimization method and device, equipment and a medium, and the method comprises the steps: obtaining an application program, dividing the application program into a plurality of groups, then pre-distributing a first bandwidth, obtaining a hotspot comment, setting a second bandwidth based on the hotspot comment, and setting the second bandwidth based on the hotspot comment; and finally, setting the bandwidth of each group based on the first bandwidth and the second bandwidth. The method has the beneficial effects that intelligent allocation and dynamic adjustment of the bandwidth are realized, the utilization efficiency of network resources is improved, and the network experience of a user is also improved. Meanwhile, through subsequent monitoring and optimization measures, the rationality and effectiveness of bandwidth allocation are ensured.

The utility model provides a kind of master-slave adaptive multi-channel bluetooth detection device, the device includes shell, MCU master control unit and the power module, RS232-TTL module and bluetooth test unit connected with it are equipped in shell;The RS232-TTL module is used to complete the bidirectional conversion between TTL level and RS-232 level, and is communicated with MCU master control unit by serial port;The bluetooth test unit is composed of multiple independent bluetooth modules, each bluetooth module is connected with MCU master control unit by serial port, for executing the scanning and communication task on specified bluetooth channel.The utility model's master-slave adaptive multi-channel bluetooth detection device adopts multiple independent bluetooth detection module, and each bluetooth module detection is responsible for the scanning work of one bluetooth channel, greatly improves detection efficiency and signal capture probability.

This invention relates to the field of shared equipment security monitoring technology, and discloses a remote security monitoring method and system for shared power bank cabinets. The method includes: collecting and preprocessing operational data; extracting peak temperature rise and usage duration to group equipment status; screening abnormal equipment and extracting abnormal temperature rise intervals, calculating the correlation characteristics between temperature and current, and generating a preliminary abnormal list; acquiring historical and real-time fluctuation sequences and calculating correlation strength scores; calculating a comprehensive risk index based on the scores and fluctuation amplitudes, and generating a priority monitoring list; increasing the data collection frequency and analyzing dynamic health status; when the health status remains abnormal, generating and verifying alarm signals to trigger equipment control commands; executing commands and updating the risk index to generate a high-risk equipment monitoring list. This invention achieves accurate early warning and closed-loop management of security risks in shared power bank cabinets through multi-dimensional data analysis and dynamic risk assessment.

The present invention discloses a vehicle-mounted power supply and discharge system control method based on Petri net. The vehicle-mounted power supply and discharge system includes a vehicle-mounted generator, a vehicle-mounted energy storage system, a power supply control system, a power distribution control system and a power load; the vehicle-mounted generator includes an original vehicle generator and a backup generator; the vehicle-mounted energy storage system is composed of multiple battery clusters connected in parallel. The vehicle-mounted power supply and discharge system power supply control process based on Petri net established by the present invention can realize system power supply safely and quickly. As long as the power supply and load meet the conditions, the token can be obtained to change and enter the power transmission and distribution system; when the power supply or load fails, the token can also be obtained to change and exit the power transmission and distribution system. And these changes are real-time, which can realize the real-time distribution of electric energy.

The embodiment of the invention provides a signature data processing method and device, equipment and a storage medium. The signature data processing method comprises the steps of obtaining to-be-signed data; inputting the to-be-approved data into the approval process prediction model to obtain feature information of the to-be-approved data, the feature information including an approval path and approval time; the signing and auditing path comprises signing and auditing steps required for signing and auditing the data to be signed and auditing; when the signing and auditing time is up, signing and auditing the data to be signed and auditing according to signing and auditing steps required for signing and auditing the data to be signed and auditing; according to the method, the signing and auditing path and the signing and auditing time are determined through the prediction model, so that the signing and auditing efficiency and accuracy are improved, intelligent distribution of the signing and auditing tasks is realized, and the workload of signing and auditing personnel is relieved.

The present invention relates to the technical field of power equipment management, and specifically to an intelligent monitoring, management and operation and maintenance system for power equipment based on cloud computing, comprising an equipment comparison power module, which is used to evaluate the equipment operation status of power equipment under different powers to obtain the equipment comparison power of the power equipment; an equipment fault data module, which is used to analyze the equipment status of power equipment under different equipment operation data to obtain target equipment fault data of the power equipment; an electricity consumption prediction module, which is used to predict the electricity consumption of a power consumption area in a current cycle to obtain predicted electricity consumption data of the power consumption area; a target power data module, which is used to analyze the energy consumption status and work efficiency of power equipment under different powers to obtain target power data of the power equipment; and an intelligent operation and maintenance module, which is used to monitor the equipment status of power equipment in the current cycle and perform intelligent operation and maintenance on power equipment in a power grid.

The invention provides a communication module power consumption and performance parallel test method and system, and relates to the technical field of communication module tests.The specific scheme comprises the steps that power consumption data and communication performance data of a communication module are obtained, and a multi-dimensional vector matrix is formed through discretization processing; based on the multi-dimensional vector matrix of the communication modules, calculating dynamic association between the communication modules, and constructing a multi-dimensional dynamic association matrix; estimating the interaction influence between the communication modules by using the multi-dimensional dynamic incidence matrix, and adjusting the resource allocation proportion between the communication modules according to the interaction influence; after resource allocation is completed, a final comprehensive test result is generated according to the performance of power consumption and communication performance in an actual test; according to the invention, the mutual influence and interaction relationship between the two are considered, the communication module is comprehensively tested, and the test efficiency and accuracy are improved.

The invention discloses a ponding monitoring and early warning system based on edge intelligent processing. The ponding monitoring and early warning system comprises a data acquisition module, an edge intelligent processing unit and a decision module. The data acquisition module is configured at an accumulated water monitoring point and is used for acquiring accumulated water depth, water flow velocity and rainfall intensity data; the edge intelligent processing unit is arranged in the monitoring equipment and is used for locally extracting accumulated water depth change rate and change acceleration characteristics, evaluating data priority, identifying accumulated water state abnormity and dynamically deciding a data transmission strategy based on the priority and an abnormal mark; and the decision-making module generates multi-level early warning information according to the received data and can issue an instruction to adjust the transmission priority of the edge equipment. According to the system, real-time analysis and intelligent early warning of ponding characteristics are realized, the early warning timeliness is effectively improved through edge side data processing and dynamic transmission strategies, the data transmission quantity is reduced, and the stability and adaptability of the system in a complex environment are enhanced.

This invention provides a method and system for dynamic processing of intermodal ticketing based on load forecasting and implicit customer data. It solves the technical obstacles that lead to inaccurate pricing decisions and user complaints due to reliance on a single, delayed, or erroneous external data source; the inability of fixed-discount intermodal tickets to adapt to real-time market supply and demand, resulting in revenue loss; the inability of discount strategies to differentiate customers during off-peak periods, leading to wasted discount resources; and the inability to quantify inventory data, resulting in a crude intermodal cooperation mechanism and difficulty in fairly measuring the contributions of all parties. This invention introduces a system load rate model for each time window, remapping any valid continuous pass scenario for any train into a series of discrete time windows for calculating expected load data. It achieves forward-looking perception of market demand and adaptive price generation, thereby realizing dynamic adjustment of fares, precise guidance of demand, and intelligent allocation of revenue; enabling the intermodal ticketing system to truly possess intelligent revenue management capabilities.

The utility model belongs to the technical field of low-temperature concentration, and particularly relates to a low-temperature concentration device for processing birch juice, which comprises a vacuum concentration unit for evaporating and concentrating birch juice in a low-temperature environment; the raw material storage device is used for storing birch raw material juice; a preheating cavity and a heating source cavity are formed in the preheater; the liquid level sensor is used for monitoring the liquid level of the birch juice in the evaporator; the condenser is used for condensing the steam which is not utilized by the heating source cavity into liquid water; the control valves comprise a first control valve mounted on the first ventilation pipeline and a second control valve mounted on the second ventilation pipeline; the controller controls starting and stopping of the first liquid supply pump and the second liquid supply pump according to the liquid level, monitored by the liquid level sensor, of birch juice in the evaporator, and the on-off state of the first control valve and the on-off state of the second control valve and the running state of the condenser are synchronously adjusted. According to the device, the steam flow direction is dynamically switched through the controller according to the liquid level of the evaporator, juice overheating caused by continuous preheating is avoided, and the follow-up evaporation load is reduced.