10results about How to "Increase update frequency" patented technology

The application discloses a tunnel construction process automatic monitoring method, and belongs to the technical field of tunnel engineering construction monitoring. The method comprises the following steps: step 1, automatic monitoring equipment is arranged at key positions of a tunnel opening area, an advanced support section, an excavation face, an initial support structure, a waterproof layer construction area and a secondary lining structure; step 2, each automatic monitoring equipment is started, and monitoring data is collected at a preset sampling frequency; step 3, after receiving the monitoring data, a central monitoring platform uses a big data analysis algorithm to deeply process the monitoring data; and step 4, the central monitoring platform feeds back monitoring results and early warning information after analysis to a tunnel construction control system in real time. The application realizes real-time data acquisition and analysis through 5G technology, especially the UWB positioning system collects data once per second, realizes instant acquisition and analysis of monitoring data, and compared with traditional manual monitoring, the data update frequency is improved by tens of times, and abnormal conditions in the construction process can be found in time.

The invention belongs to the technical field of Internet of Things data security, and provides an Internet of Things data confidentiality reading method and system based on a block chain, traced key fragments in a plurality of key fragments on the block chain are analyzed, the overall leakage difficulty degree of the multi-key fragments is evaluated, and for a storage hard disk with a relatively low leakage difficulty evaluation value, the leakage difficulty of the storage hard disk is evaluated. For a hard disk with high risk, key management needs to be enhanced, when a multi-key fragment easy-to-divulge signal is generated, a reference time consumption interval is acquired, and dynamic delay optimization operation is performed on time consumption for reading the traced key in the whole multi-key fragment according to the reference time consumption interval, so that the time consumption of the traced key in the whole multi-key fragment is reduced, and the time consumption of the traced key in the whole multi-key fragment is reduced. According to the method, different traced key fragments are endowed with different delay adjustment amounts according to the traced reading delay adjustment interval, the reading time consumption difference is increased, and the analysis and prediction difficulty of an attacker is increased, so that attack behaviors are effectively resisted, and the confidentiality of Internet of Things data in a block chain environment is guaranteed.

This application provides a hydrophilic-phobic composite trench surface for enhancing droplet condensation heat transfer under high subcooling and its preparation method. The surface is formed by processing a metal substrate and includes an array of superhydrophilic micro-grooves and hydrophobic ridges protruding between the grooves. Hydrophilic stripes are provided on both sides of the top of the hydrophobic ridges and are connected to the liquid film of the superhydrophilic micro-grooves. The preparation method includes four steps: metal substrate pretreatment, laser marking of the superhydrophilic micro-groove array, preparation of the hydrophobic ridges, and secondary laser marking of the hydrophilic stripes. This invention achieves directional and rapid transport of droplets on the ridges through the liquid film communication effect between the hydrophilic stripes and the superhydrophilic micro-grooves, significantly increasing the droplet renewal frequency, maintaining droplet condensation for a long time and avoiding flooding, thus significantly enhancing heat transfer efficiency. The preparation process is simple, has high processing precision, low cost, and is easy to achieve industrial mass production.

The utility model provides a kind of compact electrochemical ozone water catalytic electrode module for household appliance and electrolytic device applied the electrode module, it is related to electrochemical water treatment technical field for household appliance. It aims at solving the problem that existing " sandwich " flat plate structure electrode group stores ozone bubble and is difficult to escape. The electrode module includes anode assembly and cathode assembly. Anode assembly is provided with titanium base support plate, and vertical fixed anode electrode sheet;Cathode assembly is provided with the metal support plate symmetrical with titanium base support plate, and vertical fixed cathode electrode sheet. Titanium base support plate and metal support plate are provided with mounting portion, for threading bolt. After anode electrode sheet and cathode electrode sheet are staggered nested, they are electrically connected by bolt, and catalytic electrolysis function is realized. The electrode module of the utility model effectively avoids that ozone gas is invalidly gathered on electrode surface, so that ozone bubble can smoothly escape, prevent bubble cover layer from forming, thereby improve electrolytic efficiency, slow down anode corrosion, prolong equipment life.

The application discloses an NB-IoT access signal quality prediction method, system and device and a storage medium. The method comprises the following steps: acquiring wireless signal measurement data of a plurality of different network entity objects in a preset area and performing feature extraction to obtain wireless signal features and geographical position information of the network entity objects; the preset area is divided into a plurality of grid areas, and the wireless signal features of the network entity objects in each grid area are counted to obtain NB-IoT signal grid features and 4G signal grid features of each grid area; a grid feature correlation model of the preset area is established; the 4G signal area features of a target area are acquired, the 4G signal area features are matched, target NB-IoT signal grid features are obtained, and then the NB-IoT access signal quality of the target area is predicted. The application improves the efficiency and accuracy of the NB-IoT access signal quality prediction and can be widely applied to the technical field of Internet of Things.

This invention discloses a rotary reaction apparatus and process suitable for high-temperature molten salt pyrolysis of biomass. The reaction apparatus includes a molten salt purging device, a molten salt inlet, a compartmentalized molten salt tank, an integrated stage, a nickel-based alloy mesh, a motor, a reaction apparatus shell, a gas detection system, a temperature detection and control system, baffles, and a heating layer. The apparatus is made of high-temperature and corrosion-resistant materials, making it suitable for high-temperature and highly corrosive environments. Based on the synergistic effect of the molten salt characteristics and the reaction apparatus, the utilization efficiency of the molten salt is effectively improved and the mass and heat transfer processes are enhanced through the significant thinning and renewal rate of the liquid film under hypergravity conditions. By adjusting the molten salt feed rate and the rotation speed of the rotary table, the pyrolysis process under different mass and heat transfer efficiencies can be explored. This invention can be extended to reaction systems such as liquid metals. The assembly of this invention is relatively efficient, with low investment, and it can explore the influence of mass and heat transfer during the pyrolysis process on the products, thereby obtaining relevant thermodynamic and kinetic parameters.

The invention belongs to the technical field of robot positioning and computer vision, and provides a non-intrusive positioning method, system, device and medium for a robot in a cockpit, the method is realized based on a 3D Gaussian splashing technology, and the method comprises the following steps: in an offline state, constructing a high-fidelity three-dimensional digital model capable of generating a virtual image; before a task is executed, calculating an initial six-degree-of-freedom pose of the visual sensor under a target cockpit coordinate system; in the execution process, the initial six-degree-of-freedom pose is used as the current estimation pose of the first iteration, and the pixel-level luminosity error between the virtual image and the real image is calculated in real time; and solving a six-degree-of-freedom pose increment through a luminosity error, superposing the six-degree-of-freedom pose increment to a current visual sensor pose, updating to obtain a current estimated pose, inputting the current estimated pose into next iteration, and carrying out drifting-free continuous estimation of the robot. According to the method, centimeter-level, drifting-free and marker-free high-precision closed-loop positioning can be realized, and the aviation airworthiness requirements are met.

This application discloses a battery maximum capacity update method, apparatus, electronic device, and product, belonging to the field of artificial intelligence. When a battery charging event is detected and the battery state meets a preset low-charge condition, a battery capacity update process is triggered. Based on the battery's resting state before the charging event, an initial charge reference value is determined. During charging, a first charge parameter representing the amount of charge received by the battery is accumulated, and a second charge parameter representing the amount of charge discharged by the battery is monitored. When the second charge parameter exceeds a preset first threshold, the capacity update process is terminated. When the battery reaches a fully charged state and the first charge parameter exceeds a preset second threshold, the maximum battery capacity is calculated and updated based on the initial charge reference value and the first charge parameter. The battery maximum capacity update method provided in this application can effectively improve the capacity update frequency while adapting to complex operating conditions.

The invention discloses an intelligent bag taking method and system based on target recognition analysis, and relates to the technical field of target recognition. The method comprises the following steps of bag taking interference analysis, bag taking identification analysis and bag taking decision feedback. According to the method, the bag taking interference analysis result is obtained based on the bag taking identification interference parameters so as to judge whether to carry out image dynamic acquisition adjustment or not, if yes, bag taking dynamic identification analysis is carried out after the image dynamic acquisition adjustment is carried out, and if not, bag taking dynamic identification analysis is directly carried out; recognition errors caused by ambient light changes or other factors are effectively avoided, recognition of the bag taking action is more accurate, whether a bag taking decision feedback mechanism is triggered or not is judged after bag taking dynamic recognition analysis is conducted, if yes, bag taking decision feedback is executed, and if not, image dynamic recognition optimization is executed, so that the bag taking action is more accurate. The reliability of the automatic bag taking machine in actual operation is effectively improved, and then recognition of the bag taking process of the automatic bag taking machine is more accurately carried out.

The application provides a vacuum induction melting endpoint element and tapping temperature prediction method and system based on a physical information network. It relates to the fields of metallurgical engineering and intelligent manufacturing. The method of the application first collects and pre-processes smelting multi-source heterogeneous data, then constructs four types of physical constraint equations based on metallurgical physical principles, designs a physical information neural network model with a shared feature extraction layer and a multi-task learning architecture, fuses data and physical constraint losses to construct a compound loss function and dynamically adjusts the weights, trains and optimizes the model for deployment, realizes online real-time prediction of endpoint elements and tapping temperature, and completes continuous learning and updating of the model based on new measured data. The application combines physical knowledge and data-driven to improve prediction accuracy and real-time performance, reduce smelting energy consumption and raw material waste, improve product qualification rate, and is suitable for intelligent control of special steel smelting.