15results about How to "Break down information barriers" patented technology

The application is particularly applied to a security risk dynamic evaluation and early warning system for information integrated monitoring, relates to the technical field of information security and industrial internet monitoring, and comprises a disaster energy capture and transient conversion module, a threshold triggering module, a terminal signal generation and emission module and a gradient heat insulation and anti-destroying protection module.In the application, the plug-in protocol adaptation and space-time synchronization alignment technology can access monitoring data and business system data of multiple types and multiple protocols without distinction, break the information barrier between different systems, provide a comprehensive, accurate and space-time unified data basis for risk evaluation, avoid risk omissions caused by one-sided data, and at the same time, build a hierarchical dynamic risk evaluation system, realize accurate quantification of risks and evolution trend prediction through adaptive weight adjustment and risk dynamic deduction.

The invention relates to the technical field of intelligent logistics management, and discloses an EWTMS full-link intelligent warehouse distribution management system. According to the system, digital mirror image mapping composed of a storage physical space mirror image and a distribution process network mirror image is established, and historical data is used for driving dynamic twinborn evolution of the system. And based on an evolution result, coupling the identified physical efficiency bottleneck region and the flow delay sensitive node, and generating a full-link dynamic vulnerability topological graph. The system further drives the topological graph to perform instant reconstruction according to real-time cargo movement data and equipment state signals, and dynamically generates a warehouse allocation instruction by analyzing reconstruction differences. According to the scheme, deep collaboration and overall vulnerability visualization of storage and distribution links are realized, adaptive strategy adjustment based on real-time data is supported, and the overall efficiency and response agility of a full-link warehouse distribution system are improved.

The invention discloses a control method of a multi-piezoelectric ceramic vibration exciter parallel combination system, and relates to the technical field of vibration control and piezoelectric driving, and the method comprises the steps: synchronously collecting the working time sequence waveform of each vibration exciter and the energy consumption flow data of the system, calibrating the waveform, and carrying out the spectrum purity analysis of the energy consumption data to extract the fundamental wave and harmonic wave components. And performing time-frequency domain alignment fusion on the calibrated time sequence waveform and the energy consumption spectrum component, and constructing a system state fusion tensor. And based on the tensor, identifying phase coherence and energy coupling strength among excitation units in the system, and further deducing a global vibration mode and a local instability risk area of the system. And making a dynamic balance control plan according to a deduction result, redistributing output energy of each vibration exciter and coordinating action phases of the vibration exciters. According to the invention, accurate diagnosis and risk prediction of the internal interaction state of the parallel vibration exciter system are realized, and the stability and controllability of cooperative work of the system are improved.

The application provides an artificial intelligence-based call center data analysis method, and relates to the field of call center data processing.The method collects real-time call audio and pre-processes it, extracts mel-frequency spectrum features and text data with timestamps;uses an analysis model integrating acoustic layer, text layer, cross-modal fusion layer and multi-task analysis head layer to obtain multi-dimensional analysis results such as emotional state, service compliance, service quality score and customer intent.In model training, an adversarial gradient reversal layer and an acoustic environment discriminator are introduced to eliminate environmental noise interference, and a timing risk encoder and a contrast learning are used to enhance the risk evolution capture capability.Based on the analysis results, a comprehensive risk index is calculated, an intervention strategy is matched and real-time pushing is performed, and a comprehensive analysis report is generated after the call is completed.The application realizes cross-environment adaptive purification and multi-modal fusion analysis, effectively improving the service quality monitoring and risk early warning efficiency of the call center.

The invention relates to the field of logistics packaging, and discloses a fragile product logistics packaging suite with a damage early warning function, the fragile product logistics packaging suite comprises a composite buffer cabin body, a main control circuit cabin and a box cover, the composite buffer cabin body comprises a flexible lining layer, an inflatable supporting pad and a box body from inside to outside, the inflatable supporting pads are symmetrically arranged between the flexible lining layer and the inner side face of the box body, the center of the bottom face in the box body is fixedly connected with a hollow columnar connecting body, the top end of the hollow columnar connecting body is fixedly connected with an object bearing platform, and a sensor sealing cabin is suspended in an inner cavity of the hollow columnar connecting body; the passive packaging system aims at solving the technical problems that due to the fact that existing passive packaging cannot monitor, early warn and record the state of the transportation environment in real time, the responsibility of goods damage is unclear, and the risk is uncontrollable. The passive packaging system aims at solving the technical problems that due to the fact that the existing passive packaging system cannot monitor, early warn and record the state of the transportation environment in real time.

The present application relates to the field of oilfield ignition intelligent control, more particularly to an oilfield ignition intelligent control system and method based on multi-source data, comprising a multi-source data acquisition module for acquiring multi-source data and storing the same in an oilfield ignition database; an ignition condition analysis module for calling data in the oilfield ignition database, training a model to generate a control strategy containing gas supply, ignition energy and combustion air ratio, and storing the control strategy in an ignition scheme library according to scenarios; an ignition scheme generation module for calling the ignition scheme library, screening out an adapted ignition scheme and marking the priority of the scheme; and an ignition execution scheduling module for displaying the matched ignition scheme to field operators to ensure the standardization of ignition operation; the present application provides precise data support for the whole process of oilfield ignition by integrating four types of multi-source data, effectively solves the problem of extensive strategy caused by scattered data in traditional ignition, and thus improves the safety and energy efficiency of ignition operation.

This application discloses an artificial intelligence-based method and device for processing Flash particle test data. The method includes: collecting particle response behavior data from Flash storage particle test tasks and extracting time-series correlation logic information; creating a dynamic reasoning model based on an adapted behavior sequence analysis algorithm to mine the evolutionary patterns under different instruction requests and generate hidden evolutionary trajectories; deriving the degradation trend prediction results through particle performance evolution characteristics, converting trend features into semantic knowledge nodes and establishing a semantic mapping relationship with failure types; and generating a structured test knowledge graph by combining test log data. This application breaks through the limitations of traditional single feature judgment, provides a new dimension for Flash particle lifetime prediction, and breaks down the information barrier between test data and design optimization, enabling efficient transformation from data to decision-making.

The present disclosure relates to a data storage method and device, storage medium and electronic equipment, and relates to the technical field of computers. The method comprises: first acquiring initial image data collected by an inspection instrument for a user and related information of the user, matching the related information of the user using a preset mapping relationship, determining image feature information corresponding to the initial image data, determining a target storage format and a target storage location indicated by the image feature information based on a preset partition storage strategy, converting the initial image data into a target image file according to the target storage format, and storing the target image file in the target storage location. In this way, the storage strategy is determined according to the feature information of the acquired image data, which can avoid the problem of long transmission time caused by directly storing the image file, thereby avoiding the waste of transmission resources, ensuring the diversified storage demand of the image file, and improving the transmission efficiency of the image file.

This invention discloses a method, apparatus, and non-volatile storage medium for constructing a digital twin of a power grid. The method includes: collecting real-world data and historical operational data corresponding to multiple levels; establishing a three-dimensional model of the power grid based on the real-world data corresponding to each level; constructing fault prediction models corresponding to each level based on the historical operational data corresponding to each level; obtaining a target power grid three-dimensional model according to a preset equipment hierarchy; performing fault propagation analysis on multiple levels based on the target power grid three-dimensional model and the historical operational data corresponding to each level, generating a power grid fault state transition diagram; and obtaining a power grid digital twin based on the power grid fault state transition diagram. This invention solves the technical problem of being unable to achieve high-fidelity digital reproduction and panoramic simulation of the dynamic evolution process of complex power grids due to the limitations of static modeling in the main, distribution, and utilization links of existing power grids and the difficulty in coordinating multi-source heterogeneous data.

The invention relates to the technical field of distributed computing, in particular to an intelligent iterative knowledge base management system and method for on-site technical services, and the system comprises an edge layer which is used for collecting multi-modal data of on-site equipment in the operation process; the data acquisition layer is used for collecting multi-modal data and preprocessing the multi-modal data to obtain preprocessed multi-modal data; the distributed storage layer is used for carrying out distributed storage and deduplication storage on the preprocessed multi-modal data; the intelligent analysis layer is used for processing the preprocessed multi-modal data and constructing a technical service iteration knowledge graph; performing causal reasoning on the technical service iteration knowledge graph, and updating a pre-constructed technical iteration tree; the application service layer is used for providing field technical services for technicians according to the technical service iteration knowledge graph and the technical iteration tree, and the problems that multi-modal data fusion is low in efficiency, technical iteration manual dependence is high, knowledge and operation collaboration is poor and the like can be solved.

This invention provides a method, apparatus, device, and storage medium for recommending technologies that link supply and demand. The method includes: obtaining technical information from technology suppliers through a patent trading platform; constructing a technology library based on the technical information, which includes patent application texts, application dates, and IPC classification numbers; obtaining demand information from technology demanders through the patent trading platform and classifying the demands, with each demand classification associated with the IPC classification number; filtering technical information in the technology library according to set conversion criteria to obtain technologies to be converted; classifying the technologies to be converted based on the IPC classification number to generate a list of technologies to be converted, and pushing this list to the technology demanders corresponding to the demand categories associated with the IPC classification numbers. This invention can break down information barriers between patent technology suppliers and demanders, enabling targeted recommendations of patent technologies, improving patent transfer efficiency, and meeting the needs of both parties.

This application discloses a process time prediction method and related apparatus, relating to the field of iron and steel smelting. This application obtains the steelmaking parameter set, refining parameter set, and continuous casting parameter set corresponding to the three processes of steelmaking, refining, and continuous casting for the target steel grade. The semantic vector of the target steel grade is obtained collaboratively based on the gradients of the steelmaking model, refining model, and continuous casting model, which can integrate the process semantic information of the three processes. The steelmaking parameter set, refining parameter set, and continuous casting parameter set, along with the semantic vector of the target steel grade, are respectively input into pre-constructed steelmaking, refining, and continuous casting time prediction models. This achieves accurate matching between the model corresponding to each process and its own process characteristics, allowing each model to focus on capturing the unique and most critical process features of the corresponding process without needing to learn complex hybrid mapping functions. This effectively avoids the internal logic confusion caused by a single model predicting the time of multiple processes, significantly improving the accuracy of time prediction for each process in steelmaking, refining, and continuous casting.

The invention belongs to the technical field of industrial process control, and particularly relates to an intelligent management and control method for a gas film coal yard, which comprises the following steps: dividing a control object into an equipment layer and a functional layer, and setting an equipment layer control mode according to the real-time response demand and communication condition of equipment; a function layer control mode is set according to the cooperation complexity of functions and global optimization requirements, and a principle of selecting centralized control or distributed control for a device layer and a function layer in various scenes is designed; according to the method, hierarchical processing of data and hierarchical issuing of instructions are realized, and a distributed autonomous architecture and an intelligent decision algorithm are combined, so that the global intelligent level of coal yard management and control is improved while the on-site quick response capability is guaranteed, and the coal yard management and control efficiency is improved. The invention also provides a non-transitory readable recording medium storing the program of the method and a system comprising the medium, and the program can be called through a processing circuit to execute the method.

The application discloses a driving coordination protection method and a vehicle, and applies to the technical field of vehicle safety control. The driving coordination protection method comprises the following steps: generating first state information representing the interaction risk of pedestrians outside the vehicle based on the sensing features outside the vehicle; generating second state information representing the injury risk of passengers in the vehicle based on the sensing features in the vehicle; generating third state information representing the motion control capability of the vehicle based on the state of the vehicle; generating fourth state information representing the adjustment capability of the passenger restraint system based on the injury risk of the passengers in the vehicle and the state of the vehicle; and generating a coordination control instruction for coordinating and controlling the motion of the vehicle and the passenger restraint system based on the first, second, third and fourth state information. The method integrates the sensing of the environment outside the vehicle, the state of the passengers in the vehicle, the control capability of the vehicle and the adjustment capability of the restraint, so that the protection effect on the passengers in the vehicle can be simultaneously optimized when the control action such as emergency braking is performed to avoid danger outside the vehicle, and the driving safety is improved.

This invention relates to the field of automation technology for lightweight steel components, and discloses an automated production line for lightweight steel components in prefabricated steel structure residential buildings. The production line includes a central control system, an automatic conveying system, and raw material processing units, laser cutting units, robotic welding units, and shot blasting units arranged sequentially along the material conveying direction. By constructing an integrated production line under the central control system, encompassing raw material processing, laser cutting, robotic welding, and shot blasting, this invention achieves fully automated and collaborative control of lightweight steel components from raw materials to finished products. Compared to existing technologies that focus only on partial improvements to single processes or logistics optimization, this solution enables seamless connection and intelligent scheduling of all processes, effectively breaking down information barriers and connection bottlenecks between processes, and improving material flow efficiency and overall production cycle time.