13results about How to "Balanced Utilization" patented technology

The utility model provides a modularized fluorine ion exchange column, which adopts a column body structure formed by connecting a plurality of sections of flanges to realize height adjustability and adapt to different fluorine concentration and flow requirements. Spiral flow guide ribs are arranged in the column to guide wastewater to spirally flow, fluid distribution is optimized through centrifugal force, and the fringe effect is reduced; the assembling precision between the columns is ensured through a concave-convex positioning mechanism, and the corrosion resistance is enhanced by matching with a polytetrafluoroethylene lining. The system integrates a water distribution plate and funnel combined structure, realizes flow equalization through groove water distribution holes, eliminates a bias flow phenomenon, and improves the resin utilization rate. And the saturation of the resin can be observed at any time through fluorine ion color-changing exchange resin and an observation window. The resin bracket is of a pull ring type quick release structure, and quick maintenance is achieved through a tap bolt and a sealing ring annular groove. According to the device, through modular combination, flow field optimization and visual monitoring, the fluorine ion deep purification efficiency and the operation convenience are remarkably improved.

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.

This invention discloses a visualized intelligent scheduling system for SMT production lines, relating to the field of precision electronics. It solves the problem of poor scheduling performance in existing intelligent scheduling systems for production lines. The system includes a data acquisition module: analyzing production demand for target orders to be executed, obtaining the quantity of products in the target order, performing historical production quantitative analysis on the production line executing the order based on the quantity of products in the target order, and acquiring production line scheduling data based on the analysis results; a production line matching module: matching production lines for target orders to be executed, obtaining target-suitable production lines; a production analysis module: monitoring the production of sample production units included in the target-suitable production line, obtaining the overall efficiency of the unit equipment based on the monitoring results, and obtaining production scheduling analysis data; and a production scheduling module: performing real-time production scheduling for the product production units on the target-suitable production line. This invention can improve the scheduling efficiency of intelligent scheduling systems for production lines.

The invention provides a main node election method of a multi-node network, the multi-node network and electronic equipment, and relates to the technical field of wireless communication. The method comprises the following steps: if a current main node judges that a preset election triggering condition is met, broadcasting an election instruction containing a score calculation rule to the whole network; scoring response data including node identifiers and energy consumption scoring values returned by the nodes are received, the energy consumption scoring values are scoring values calculated by the nodes according to energy consumption parameter sets of the nodes on the basis of scoring calculation rules, and the energy consumption parameter sets include the remaining battery capacity, the historical energy consumption rate and the data load; sorting all the nodes according to all the energy consumption score values so as to determine a new main node; and generating and broadcasting election result data containing the node identifier of the new master node so as to trigger the network to perform master-slave role switching and network synchronization according to the data. The scheme can solve the problems of unbalanced energy consumption and insufficient adaptability, so as to effectively prolong the service life of the network and improve the reliability of the network.

The application is suitable for the field of heparin sodium crude product production, and provides a continuous drying and smashing integrated machine for heparin sodium crude product production, which comprises a secondary drying and smashing box, a drying and smashing cylinder assembly is arranged in the secondary drying and smashing box, the drying and smashing cylinder assembly is used for receiving heparin sodium wet solid introduced by a primary drying and smashing box; the drying and smashing cylinder assembly comprises a feeding pipe, a power shaft and a drying and smashing cylinder structure; the drying and smashing cylinder structure comprises a drying and smashing outer cylinder and at least two drying and smashing inner cylinders which are sequentially sleeved; the feeding pipe is communicated to the innermost drying and smashing inner cylinder of the at least two drying and smashing inner cylinders through a hose; the power shaft is used for synchronously driving the drying and smashing outer cylinder and the drying and smashing inner cylinders to rotate; the heparin sodium wet solid can be fully guaranteed to be in full contact with the heating body of the cylinder mesh in the sequentially graded smashing process, which is beneficial to linkage and cooperation of the two processes of drying and smashing, and reduces equipment investment cost and maintenance cost.

The application discloses a multi-strategy unmanned aerial vehicle rapid obstacle avoidance path planning method based on dynamic ellipsoid sampling, which comprises the following steps: constructing an ellipsoid according to the starting point and the ending point of the unmanned aerial vehicle path planning, mapping a sampling point to the ellipsoid space to obtain a sampling point in the ellipsoid, and dynamically adjusting ellipsoid parameters through cyclic sampling to obtain an initial planning path and path nodes, which can focus on an effective area and improve sampling efficiency; a multi-strategy expansion mechanism is used to optimize the initial planning path nodes, and the convergence speed and obstacle avoidance ability are improved; potential parent nodes meeting the feasibility condition are searched in the neighborhood of the optimized path nodes, and the node with the minimum path cost is selected as a new parent node, and the new parent node is used to update the optimized planning path; a three-stage path smoothing strategy is used to smooth the updated optimized planning path, and an unmanned aerial vehicle planning path is obtained, so that the path feasibility and safety are ensured, and the path smoothness is improved.

The invention relates to a convolutional neural network acceleration technology, and provides a convolutional neural network accelerator designed on an ARM + FPGA heterogeneous platform. The ARM end generates a task descriptor containing Deadline, Cbudget and Bbudget, and predicts a budget; dynamic scheduling based on slack is adopted at the FPGA end, preemptive execution is implemented with tile as granularity, and context such as paraalsum and output buffer is stored / recovered at the boundary of the tile; and meanwhile, bandwidth shaping is carried out on DMA access by using a token bucket and a time slice, so that the bandwidth of each task does not exceed Bbudget. According to the scheme, DDR contention and delay jitter are reduced in a multi-task scene, and the real-time deadline satisfaction rate and the array utilization rate are improved.

The application discloses a method for layer scheduling of mixed deep neural network tasks in an embedded real-time system. The method considers the limited CPU and GPU resources of the embedded real-time system, the basic conditions of task scheduling, the time limit of task scheduling and other factors, and designs a scheduling mechanism for layer distribution of mixed deep neural network tasks for the embedded real-time system. The method builds a deep neural network task model and a layer task model, mathematically calculates the task scheduling overhead, the worst response time, the utilization sum of the task under the minimum layer task mapping scheduling, sets an optimization function and a constraint condition solving method, and realizes more balanced utilization of the heterogeneous CPU and GPU computing resources in the real-time system under the condition of shorter worst response time, and improves the real-time performance and schedulability of deep neural network tasks in the embedded real-time system.

This invention provides a time slot planning method and system for a navigation constellation time division multiplexing network, comprising an initialization module, a preprocessing module, a fully autonomous navigation time slot planning module, a non-fully autonomous navigation time slot planning module, and an output module. It sets a navigation constellation time slot table composed of MEO dynamic and static link time slot tables, IGSO dynamic link time slot tables, and GEO dynamic link time slot tables, and determines the total number of time slots to be selected for each time slot table. After initializing the time slot table, according to the prescribed principles of uniqueness within the same column, mutual reference within the same column, rolling filling, uniqueness in the same row, and priority for smaller PDOP values, it generates time slot tables adapted for measurement-centric and communication-secondary functions for two typical scenarios: fully autonomous navigation supported only by inter-satellite links and non-fully autonomous navigation supported by inter-satellite and satellite-to-ground links. This invention generates time slot tables that meet the requirements of measurement-centric and communication-secondary functions under different navigation scenarios through a unified method, possessing good completeness, system compatibility, and task flexibility.

The application discloses a natural gas hydrate reservoir layering balanced exploitation regulation and control method based on simulation optimization, S1: constructing a three-dimensional geological model according to well logging, seismic and core data of a target area; S2: establishing a heat-flow-force-chemical multi-field coupling numerical model and initializing; S3: defining a multi-dimensional engineering decision parameter space; S4: establishing a comprehensive objective function; S5: obtaining an optimal engineering decision parameter combination X_optimal through iterative search; S6: implementing drilling and well completion operations according to X_optimal, and dynamically verifying and feedback adjusting the model and exploitation system based on real-time monitoring data in the production process. The heat-flow-force-chemical multi-field coupling numerical model is established based on the three-dimensional geological model, a proxy model and multi-objective optimization are introduced, and dynamic verification and feedback adjustment are conducted in combination with monitoring data in the production period, so that interlayer contradictions are effectively inhibited, balanced utilization of reservoir energy is realized, and the overall recovery rate and development economy of the multi-layer hydrate reservoir are improved.

The application discloses a convolution operation method and device. The specific implementation scheme is as follows: the method comprises the following steps: configuring a split parameter; inputting the split parameter, the parameter of the convolution operation and the parameter of the convolution acceleration device into a cost function to obtain the optimal value of the split parameter under the condition of meeting the constraint condition; adopting the optimal value of the split parameter to split input image data and weight data used for inputting the convolution acceleration device into a plurality of input data blocks and a plurality of weight data blocks; and controlling the plurality of input data blocks and the plurality of weight data blocks to be input into an internal local buffer, so that an operation device obtains the input data blocks and the weight data blocks required by the convolution operation from the internal local buffer, and performs the convolution operation on the input data blocks and the weight data blocks to obtain a plurality of output data blocks. The average utilization rate of the convolution acceleration device is improved, the time of the convolution operation is effectively reduced, and the balance between the utilization rate and the bandwidth demand of the convolution acceleration device is realized.

This invention provides a method, system, medium, and device for resilient traffic scheduling protection against network communication failures, belonging to the field of vehicle network communication and safety management technology. The method acquires traffic monitoring data in real time and extracts traffic characteristics from the data. Based on these characteristics, it determines whether sudden traffic surges exist. If a sudden surge exists and its duration exceeds a duration threshold, a dynamic buffer allocation strategy is employed; otherwise, a default queue allocation strategy is used. The dynamic buffer allocation strategy, compared to the default queue allocation strategy, increases the allocation ratio of the security control data queue within the buffer. This method intelligently identifies sudden traffic surge characteristics and triggers buffer resource reallocation, ensuring the transmission of critical security control data streams when network congestion occurs due to sudden traffic surges. It maintains the low-latency characteristics of critical security control data, achieving an optimal balance between network load and resource utilization.

The invention discloses a welding robot task scheduling control method based on an end-cloud collaborative architecture, and relates to the technical field of welding robot intelligent scheduling, and the method comprises the steps: receiving a real-time state and a production order of a welding robot, decomposing the order into welding sub-tasks, and generating an initial instruction; constructing a dynamic robot capability model according to the real-time state, and reflecting the availability, the load and the position of each robot; and the tasks and the models are uploaded to a cloud scheduling center, cross-robot space-time conflict detection and resource balance analysis are performed through a global optimization scheduler, a task sequence is dynamically adjusted, an optimization scheduling scheme is generated, and execution robots, time windows and welding parameters are allocated to each sub-task. According to the method, collaborative operation and dynamic optimization among the multiple welding robots are achieved, equipment conflicts are avoided, and the overall production efficiency and the resource utilization rate are improved.