13results about How to "Avoid processing delays" patented technology

The invention discloses an LLC resonant converter fault diagnosis method, device and equipment, a medium and a program product, and the method comprises the steps: carrying out the open-circuit fault analysis of an LLC resonant converter, generating a fault diagnosis strategy of the LLC resonant converter based on an open-circuit fault analysis result, and responding to the open-circuit fault of the LLC resonant converter, and collecting switch tube drain-source voltage parameters of each bridge arm in the LLC resonant converter, determining a target drain-source voltage value of each switch tube based on the switch tube drain-source voltage parameters, and performing fault diagnosis on the LLC resonant converter based on the fault diagnosis strategy and the target drain-source voltage value. According to the method, the accurate fault diagnosis strategy is constructed through open-circuit fault analysis, and the drain-source voltage parameters of the switch tube during the open-circuit fault are analyzed in combination with the fault diagnosis strategy, so that high-efficiency fault diagnosis is realized, the fault is found and positioned in time, and the reliability and the stability of the LLC resonant converter are effectively improved.

The present disclosure provides an agent-based data flow real-time scheduling method, which comprises: according to the factory production environment, building an intelligent scheduling framework driven by reinforcement learning, which comprises an environment, an agent and a reward function; converting data flow characteristics and system state into feature vectors to construct a multi-dimensional feature reinforcement learning state space; the agent perceives the reinforcement learning state space and calls a prediction model to predict the data flow characteristic change trend and the system state change trend in the future preset time period, and generates a resource pre-allocation scheme based on the prediction result; the agent generates at least one scheduling action based on a multi-objective scheduling optimization algorithm to form a scheduling strategy according to the current production target, the resource pre-allocation scheme and the reinforcement learning state space. The present disclosure effectively avoids resource waste and data processing delay, significantly improves resource utilization, and ensures stable and efficient production of the intelligent factory production environment.

The invention provides a direction-angle-variable airspace management Web grid generation and drawing assembly and method, and aims to adapt to complex terrains and optimize the coverage of grids on geographic information by dynamically adjusting the grid direction and angle. The assembly comprises a user interface and visualization module, a self-adaptive terrain grid construction module and a coverage detection module. The user interface module integrates data and provides a graphical operation interface, the adaptive module dynamically adjusts the grid according to the terrain and user parameters, and the coverage detection module ensures that the grid meets the coverage requirement. According to the method, through real-time feedback, accurate rotation calculation, flexible adjustment of the size and the shape of the grid and accurate coverage detection, the efficiency and the precision of airspace management are remarkably improved.

The present invention belongs to the field of intelligent control technology, and specifically relates to a control system for a tubular textile yarn packaging and detection integrated machine. The system detects tension, winding speed and ambient temperature in real time during the production of tubular textile yarn, thereby identifying winding control objects and implementing winding control based on the detection results. The system is not limited to winding speed control, and on the one hand, it realizes the refined and reasonable control of yarn winding. On the other hand, since it is not limited to winding speed control, it can greatly avoid the control fluctuation of winding speed. At the same time, winding stage setting is performed during yarn winding, and the tension and winding speed control of adjacent winding stages are used to control the associated winding stages, and then feedback control is performed based on the winding effect deviation of the associated winding stage. The system can not only provide a supplement to the positive control effect, but also timely identify the detection control error, avoid processing delay, and help reduce production costs.

The invention discloses a plane touch measurement obstacle avoidance path planning method and device on a measuring machine, and belongs to the technical field of three-coordinate detection. According to the method, the data volume is optimized, only the point cloud data of the geometric element to be measured is used instead of the whole model information, the data volume is remarkably reduced, and the calculation and storage requirements are reduced; the path planning efficiency is improved, the point cloud data enables the path planning algorithm to generate an effective path more quickly, and processing delay caused by model complexity is avoided; accurate obstacle avoidance is realized, when a standard path is generated, obstacle avoidance processing and path point correction are carried out to adapt to geometrical characteristics of an actual workpiece, interference with a groove and a boss is avoided, and measurement accuracy is ensured; the effectiveness of the path is greatly improved, and the effectiveness and the measurement precision of the planned path are improved by setting the ROI and screening invalid path points.

This invention discloses a distributed message processing system based on dynamic sliding windows and intelligent scheduling, aiming to solve the problems of processing latency, resource waste, and insufficient scalability caused by fixed grouping and polling strategies in traditional message processing technologies. It is suitable for dynamic message scheduling and load balancing in high-concurrency, high-throughput scenarios. A four-layer collaborative architecture is adopted, with a distributed message queue layer, a sliding grouping module, an intelligent scheduling module, and a cluster of processing units working together to form a closed-loop control through a state feedback mechanism. The system designs a hybrid sliding window and dynamic triggering grouping mechanism, a two-way feedback intelligent scheduling system, and a multi-dimensional elastic control strategy, which can dynamically optimize resource allocation based on message traffic fluctuations and processing unit load status, balancing processing timeliness and transaction consistency. It can be widely applied to scenarios such as financial transaction clearing, e-commerce flash sale traffic smoothing, and IoT data processing, achieving adaptive throughput improvement and efficient resource utilization, and possesses strong practicality and promotional value.

The invention relates to a multi-screen playing method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring video source data of a target video, and demultiplexing the video source data to obtain video coding data; determining a video timestamp of each video frame in the target video according to the playing speed in the video coding data; packaging the video coding data to obtain a real-time transmission data packet, the real-time transmission data packet at least comprising the video coding data and each video timestamp; and sending the real-time transmission data packet to a receiving end device, so that the receiving end device decodes the video coding data to obtain video decoding data, and performs picture rendering on the video decoding data based on the video timestamps to synchronously play video pictures of the target video with the sending end device based on the video timestamps. By adopting the method, the playing time delay of picture synchronous playing on different screen interfaces can be reduced.

The application discloses an end-edge collaborative adaptive enhancement and coding method for low-light video analysis, comprising: a terminal device collects a low-light video stream in real time and synchronously monitors environmental light intensity, edge computing power and network bandwidth; an edge side generates a collaborative enhancement strategy based on multi-modal perception data, dynamically selects an enhancement level and a coding resolution, and delivers them to the terminal; the terminal executes brightness correction and contrast stretching through a lightweight spatial enhancement network, then encodes and transmits to the edge side according to the strategy resolution; after decoding the video stream, the edge side optimizes cross-frame motion compensation and noise suppression through a timing enhancement network; finally, a target detection model is input for inference, and the result is fed back to optimize the strategy. Through dynamic resource scheduling, division of labor and cooperation of neural enhancement networks and closed-loop feedback mechanism, the performance of low-light video analysis is significantly improved; through deep reinforcement learning, the enhancement level and resolution are optimized in real time, and the accuracy, delay and resource efficiency are balanced.

This disclosure relates to transposing a neural network matrix in hardware. The disclosure relates to methods, systems, and apparatus for transposing a neural network matrix in hardware, including computer programs encoded on a computer storage medium. In one aspect, a method includes the actions of: receiving a request on a hardware circuit having a matrix computation unit to perform computation on a neural network, the request specifying a transpose operation to be performed on a first neural network matrix; and generating instructions, when executed by the hardware circuit, to transpose the first neural network matrix by performing a first operation, wherein the first operation includes repeatedly performing the following second operations: updating the first neural network matrix by swapping the upper right quadrant and lower left quadrant of each current submatrix for a current subdivision of the first neural network matrix that divides it into one or more current submatrixes; and updating the current subdivision by subdividing each current submatrix into a corresponding new submatrix.

The present invention provides a multi-tenant task scheduling method, device, equipment and storage medium, and relates to the technical field of SAAS online car-hailing task scheduling. The present invention can play a decentralized role by deploying multiple platform nodes to form a platform network, which can not only reduce the risk of single point failure and data tampering, but also be more conducive to processing the data of multiple tenants at the same time, avoiding processing delays, and using platform nodes to analyze and process the scheduling information of each task scheduling of the tenant, so as to identify bad tenants with long-term and multiple timeouts, facilitate the processing of bad tenants, and avoid damaging the overall image of the company.

The application discloses a kind of task processing systems based on intelligent internet of things equipment.The system includes system initialization and task table dynamic construction unit, hardware, protocol stack initialization, create event table etc.and predefine core task;Hierarchical event polling and priority processing unit, event is handled according to priority;Adaptive low-power management unit, adjust system power consumption;Dynamic task extension and hot plug support unit, identify new equipment and allocate task resources.Wherein, hierarchical event polling unit can distinguish key and ordinary event processing.The application realizes the efficient processing of internet of things equipment task by the cooperation of each unit, with dynamic expansion capacity, can also adaptively adjust power consumption, improve system performance and energy utilization efficiency.

A high-speed synchronous transmission device and a video playing system for multichannel digital videos, the device comprising: a plurality of high-speed synchronous transmission modules, each high-speed synchronous transmission module comprising a video input interface, a laser transmitting module, a laser receiving module, and a video output interface; the video input interface receives a high-bandwidth digital video signal from a video source; the laser transmitting module comprises a laser driver and a laser transmitter, the laser driver is connected with the video input interface so as to convert the video input interface into a laser driving signal, and the laser transmitter is connected with the laser driver so as to generate a laser signal corresponding to the high-bandwidth digital video signal under the driving of the laser driving signal; the laser receiving module comprises a laser receiver and a signal restoration circuit, the laser receiver is used for receiving the laser signal generated by the laser transmitter and converting the laser signal into a light current signal, and the signal restoration circuit is connected with the laser receiver so as to process the light current signal and restore a high-bandwidth digital video signal for playing.

The application discloses a power supply energy efficiency intelligent scheduling power distribution system for a large computing power data center, relates to the field of power supply energy efficiency scheduling of the large computing power data center, and comprises a data acquisition layer, an edge cooperative pre-scheduling layer, a global energy efficiency scheduling layer and a power distribution execution layer. The data acquisition layer synchronously acquires full-amount operating parameters of the power side and the computing power side of the data center, the edge cooperative pre-scheduling layer is arranged in each cabinet column head cabinet, pre-scheduling response is conducted on local sudden computing power load fluctuation, and local emergency power distribution regulation instructions are generated. The global energy efficiency scheduling layer is arranged in a data center management and control platform, generates global power distribution configuration data based on preset preset digital twin power distribution models and in combination with acquisition data of the whole data center and power supply peak-valley period parameters. The application adopts a two-stage cooperative scheduling architecture, rapidly responds to load mutation through the edge side, avoids service interruption caused by overload triggering protection, and improves power supply reliability.