8results about How to "Reasonable diversion" patented technology

The invention discloses a capacity expansion management and control method for predictable easily-congested road sections, and relates to the technical field of traffic management and control, historical data of each ETC portal in a near period of time on an expressway are collected, and historical traffic operation states of each road section in the monitoring range of each ETC portal are calculated; according to the historical traffic operation state of each road section, easily-congested road sections are screened, easily-congested routes are formed, and the daily average traffic volume of the easily-congested routes is calculated; and formulating a capacity expansion control strategy according to the daily average traffic volume of the easily-congested route. The method is used for solving the problems of large traffic flow and low traffic efficiency of predictable easily-congested road sections, capacity expansion can be carried out in a way of adding lanes and the like for regular and long-term easily-congested road sections so as to improve the traffic capacity, the method is a mesoscopic periodic strategy, conventional microcosmic management and control are improved to mesoscopic management and control, and the traffic efficiency is improved. Optimized configuration and efficient utilization of traffic resources can be realized, and the operation efficiency and the service level of the whole traffic system can be improved.

The invention belongs to the technical field of solid waste material preparation, and particularly relates to a device for preparing a multi-element solid waste-based cementing material, the device comprises a preparation box, a grinding and crushing assembly is mounted in the preparation box, and the grinding and crushing assembly comprises a rotary mounting disc arranged in the preparation box; the differential requirements of multiple applications on the granularity of the solid waste-based cementing material can be accurately met, accurate-granularity products adaptive to different scenes are produced by conveniently switching the grinding discs, and compared with the traditional technology that if the granularity needs to be changed, shutdown, equipment disassembly and whole set of grinding parts need to be frequently carried out, the working procedures are tedious, consumed time is long, equipment idling is caused, and production is interrupted, the production efficiency is greatly improved. According to the device, complex disassembly is not needed, the switching process is started instantly when the servo motor rotates reversely, under the cooperation of the wedge-shaped limiting piece, the wedge-shaped groove and other assemblies, grinding disc switching is rapidly completed, follow-up production is rapidly connected, the downtime is shortened, the overall production efficiency is remarkably improved, and the continuous industrial production rhythm and the unit time yield can be improved.

The invention discloses a data analysis and display system based on a large model, and the system comprises a data collection module which is used for carrying out the matching with a business database according to a current business stage, obtaining a matching result, starting a data burying point according to the matching result, and carrying out the data collection, and obtaining initial data; the data processing module is used for deploying a plurality of edge computing nodes on an edge server and performing multi-thread preprocessing on the initial data by utilizing the edge computing nodes; the data analysis module is used for transmitting the preprocessed initial data into an analysis model of the current service stage to obtain an analysis result; and the result display module is used for carrying out classified statistics on the preprocessed initial data and the analysis result to obtain a plurality of data reports and displaying the data reports in a monitoring center. The invention relates to the technical field of e-commerce data analysis, and solves the technical problems of low data processing efficiency and insufficient accuracy and breadth of data analysis in an existing e-commerce data analysis system.

The invention discloses a vertical axis wind driven generator with a wind power flow guide plate device, and belongs to the technical field of wind driven generators, the vertical axis wind driven generator comprises a tower, a rotary body, a flow guide module, a first impeller assembly and a second impeller assembly, the top of the tower is connected with a vertical shaft, and the end, away from the tower, of the vertical shaft is connected with the rotary body through a bearing; a sliding ring is arranged at the upper end of the rotary body, the flow guide module is arranged at the front end of the rotary body, a stand column is connected to one side of the rotary body, an upper cross beam and a lower cross beam are arranged on the stand column, and the two ends of the upper cross beam and the two ends of the lower cross beam are connected with the first impeller assembly and the second impeller assembly respectively. A directional rudder is arranged at the top end of the stand column and located on the side, away from the rotary body, of the stand column. The wind power generation device has the advantages of uniform wind power distribution, effective reverse force prevention, reasonable structural design, high wind energy utilization rate and convenience in use.

The utility model relates to the field of engine bench test equipment, and discloses an oil inlet and return pressure control device for an engine bench test, which ensures the performance test accuracy of an engine under different working conditions through a system formed by an oil tank, an oil inlet and return control unit and an oil pipe. The key component comprises a pressure reducing valve used for actively controlling oil inlet pressure and preventing oil return resistance increase and engine power abnormity caused by too high pressure. The one-way valve enables return oil to be directly guided into the engine, oil return resistance is reduced, and oil supply circulation and combustion stability are guaranteed; reasonable diversion and convergence of an oil inlet and return system are achieved through the three-way design, the operation efficiency and flexibility of an oil supply system are improved, the oil inlet and return proportion can be conveniently adjusted according to test requirements, and therefore accurate and real engine performance data are obtained.

The invention provides a cooling device, a battery pack and electric equipment, and relates to the technical field of batteries. The cooling device comprises a first cold plate, a second cold plate, a flow dividing block and a flow dividing assembly, a first flow channel extending in the first direction and a second flow channel extending in the second direction are formed in the flow dividing block and communicate with each other, the first flow channel communicates with an inner flow channel of the first cold plate, and the second flow channel communicates with an inner flow channel of the second cold plate; the flow dividing block is provided with a liquid inlet pipe corresponding to the first flow channel, the flow dividing assembly is movably arranged on the flow dividing block corresponding to the second flow channel, in the moving process of the flow dividing assembly, cooling liquid in the liquid inlet pipe can flow to at least one of the first flow channel and the second flow channel, the cooling liquid can be reasonably divided, and efficiency and reasonable utilization are achieved.

This invention discloses a dynamic load balancing adjustment method for big data processing that integrates deep learning. The method comprises the following steps: Step S1: Collecting basic parameters of edge nodes and calculating communication and collaboration metrics between edge nodes; Step S2: Constructing an initial polyhedron structure based on the basic parameters, communication metrics, and collaboration metrics of the edge nodes; Step S3: Obtaining real-time load data of the edge nodes and predicting future load data of the edge nodes based on the real-time load data using an LSTM model; Step S4: Optimizing the initial polyhedron structure based on the future load data using the Transformer deep learning algorithm to obtain an optimized polyhedron structure; Step S5: When an edge node experiences overload, formulating an adjustment strategy based on the structural parameters of the optimized polyhedron structure and performing load balancing adjustments based on the adjustment strategy. By constructing a dynamically changing polyhedron structure, the method reflects changes in edge node load and inter-node relationships, enabling timely and accurate dynamic load balancing adjustments.