13results about How to "Realize intelligent distribution" patented technology

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 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 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 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 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.

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 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.

This invention relates to the field of intelligent manufacturing and industrial quality management technology, and in particular to a management system for die-cast housings of new energy vehicles. The system includes a data acquisition module for periodically collecting production data, quality data, and production equipment data of the die-cast housings; a data analysis module for determining the defect type of the die-cast housings within a single cycle based on the average defect density and defect clustering index of the die-cast housings within that cycle; a traceability module for determining different traceability methods based on the defect type of the die-cast housings within a single cycle; and an adjustment module for adjusting the judgment parameters for the defect type of the die-cast housings within a single cycle based on the defect traceability accuracy. This invention, through automatic and accurate defect classification and differentiated traceability, quickly locates the root cause of problems, greatly shortens the problem response time, and reduces the generation of defective products.

This invention discloses a blockchain-based inventory management system for bamboo cellulose raw materials, specifically in the field of on-chain inventory management. It addresses the problems of quality degradation, cross-warehouse transfers, and low intelligence in transaction triggering of traditional bamboo cellulose raw materials during the storage cycle. This invention constructs a digital fingerprint of the raw materials by collecting their core physical characteristics and batch information; it predicts quality changes in the next transaction window based on a dynamic quality degradation model combined with storage environment parameters, thus exposing risks in advance; when the degradation exceeds a threshold, it automatically enters on-chain auction, selecting trading partners based on anonymous bidding and reputation weight; for continuously unsold inventory, it calculates a transfer priority index through a global inventory map and automatically executes cross-warehouse transfers. This mechanism achieves reliable recording, dynamic early warning, and automatic decision-making throughout the entire inventory management process, improving the efficiency of raw material circulation and quality management capabilities under multi-warehouse collaboration.

The invention relates to the technical field of elevator maintenance, in particular to an elevator maintenance method and system, and double improvement of elevator maintenance efficiency and safety is achieved through multi-dimensional data fusion, intelligent algorithm optimization and full-process closed-loop management. The level of the method comprises five core steps of real-time data acquisition, dynamic anomaly detection, fault prediction and early warning, intelligent task allocation and quality tracing. The system layer is integrated with five functional units including a data acquisition module, an anomaly detection module, a fault early warning module, a task distribution module and a quality tracing module. The specific embodiment comprises five embodiments of a cloud intelligent platform, an edge computing node, fault early warning model training, task dynamic scheduling and block chain evidence storage.

This application provides a method, apparatus, storage medium, and electronic device for batch file conversion to online processing. In this application, a batch of files is acquired, including multiple pieces of business data; each piece of business data in the batch file is parsed to obtain multiple business type identifiers, with each piece of business data corresponding to one business type identifier; the online service code of each business type identifier is matched from a preset mapping rule library, which includes the mapping relationship between business type identifiers and online service codes; and the business data corresponding to each business type identifier is distributed to the corresponding online microservice engine for processing according to the online service code. This application solves the problem of low processing efficiency in existing batch file conversion to online processing methods.