11results about How to "Break through the limitations" patented technology

This utility model relates to the field of machining center technology, specifically a quick-change tool chuck for CNC machining centers. It includes a spindle motor and a cutting tool. The spindle motor is mounted on the top of the spindle housing, and a Z-axis motor is fixedly connected to the back of the spindle housing. A motor is mounted on the top of the Z-axis motor, and a guide rail is mounted on the back of the Z-axis motor. The guide rail is mounted on the front of the column. This utility model significantly reduces tool runout and improves radial runout accuracy. The tapered hole design around the spindle port simplifies the mechanical structure and achieves synchronous positioning of the end face and the tapered surface, avoiding the gap problem of traditional tapers and reducing manufacturing costs. The built-in spring and pull stud assembly of the chuck can be disassembled separately, reducing maintenance costs. It overcomes the limitations of traditional chucks in terms of quick tool change, accuracy maintenance, and cost control, providing a better solution for efficient and precise machining in CNC machining centers.

This application relates to a clock tree synthesis method and system for reducing the vertical coupling capacitance of the clock tree, belonging to the field of clock tree synthesis technology. The core of the method lies in the fact that, during the clock tree synthesis process in the physical design phase, by using a preset vertical design of the clock tree and a coupling-aware clock tree synthesis optimization cost function, the parasitic coupling capacitance between clock lines and adjacent signal lines in the vertical metal layer is systematically reduced, thereby improving the noise immunity of the clock network and reducing delay uncertainty and dynamic power consumption.

This invention discloses a device for simulating the Doppler nonlinear effect in low-Earth orbit (LEO) satellite communication, comprising: a user interaction unit for reconstructing the three-dimensional propagation environment between the LEO satellite and the ground terminal based on set communication scenario parameters and calculating the Doppler nonlinear factor; a baseband Doppler nonlinear simulation unit for performing non-uniform resampling of the digital baseband signal based on the Doppler nonlinear factor to obtain a time-domain scaled signal; a carrier Doppler compensation unit for compensating the time-domain scaled signal based on the Doppler nonlinear factor and the carrier frequency to obtain a compensation signal with applied Doppler nonlinear effect; a digital-to-analog converter unit for converting the compensation signal with applied Doppler nonlinear effect into a baseband analog signal with applied Doppler nonlinear effect; and an up-conversion converter unit for up-converting the baseband analog signal with applied Doppler nonlinear effect to a radio frequency (RF) frequency to obtain an LEO satellite RF signal with applied Doppler nonlinear effect.

The embodiment of the invention provides a model detection result matching method and device, equipment and a medium, and relates to the technical field of image detection. The method comprises the steps of obtaining a first detection result set output by a target detection model and a second detection result set output by a key point detection model based on a to-be-detected image; extracting position change information corresponding to a first detection result set and a second detection result set between adjacent frames in the to-be-detected image; based on the first motion vector set, constructing a membership function for evaluating the motion consistency of the detection result; and inputting the second motion vector set into a membership function, and matching the first detection result set with the second detection result set based on an evaluation result output by the membership function. The method provided by the invention effectively solves the problem that the detection results of different models are difficult to match with each other in the prior art, so that the production safety detection effectiveness is influenced.

The application discloses a method for epitaxially growing an alpha-Ga2O3 film based on a tert-butyl alcohol precursor under normal pressure by MOCVD, and comprises the following steps: cleaning a substrate, placing the cleaned substrate on a reaction chamber base of a metal organic chemical vapor deposition (MOCVD) device, introducing nitrogen into the reaction chamber, adjusting the air pressure of the reaction chamber to normal pressure, performing high-temperature pretreatment on the substrate in the reaction chamber, wherein the high-temperature pretreatment is performed at 1000-1200 DEG C for 15-30 min, cooling the substrate to 570-630 DEG C, taking triethyl gallium as a gallium source precursor and taking tert-butyl alcohol as an oxygen source precursor, and growing an alpha-Ga2O3 film sample on the substrate, and cooling the alpha-Ga2O3 film sample to room temperature while introducing nitrogen to obtain an alpha-Ga2O3 film. The method can be used to prepare a high-quality, high-speed-grown pure-phase metastable alpha-Ga2O3 film.

This invention relates to a compound microbial agent for promoting disease resistance and yield increase in chili peppers and its application. The strains in the compound microbial agent for promoting disease resistance and yield increase in chili peppers consist of Bacillus coagulans BC66, Lactobacillus plantarum LP194, and Bacillus polymyxa FangSG106. Studies have found that these three strains work synergistically to improve the resistance of chili peppers to root rot and increase chili pepper yield. This provides a new strategy for controlling chili pepper root rot and increasing chili pepper yield, solving the problems of poor efficacy and insignificant yield increase of commercially available products. As a microbial preparation, this agent has natural components, leaves no pesticide residue after use, and will not pollute the soil, water sources, or ecological environment. It also avoids the problem of pathogen resistance caused by chemical pesticides, conforming to the concepts of green agriculture and sustainable development, and is of great significance for ensuring the quality and safety of agricultural products.

This invention discloses a digital course generation method and system based on a large language model. By closely integrating the acquisition of course materials, chapter segmentation and semantic analysis based on the large language model, and the construction of a multimodal index, it automatically maps multi-source heterogeneous information in teaching materials into a clear chapter hierarchy structure, and rapidly generates a structured model on this basis, thereby improving the organization efficiency and processing consistency of course content. Subsequently, by extracting semantic features from the structured model and integrating chapter hierarchy information to construct a knowledge graph, it achieves efficient transformation from raw teaching materials to a knowledge network that can be intelligently retrieved and visualized. Finally, the generated digital human image and its expressions and teaching actions are seamlessly integrated with the 3D teaching scene, structured model, and knowledge graph to form a complete digital course, significantly shortening the overall process time from material preparation to course delivery.

The application discloses an adaptive intrusion detection method for an industrial internet, comprising the following steps: step S1: deploying an open set model on a global server and delivering parameters; step S2: training on a local data set by a client; step S3: uploading unknown features by the client, and performing cluster analysis on the unknown features by the global server to generate pseudo labels and corresponding initial class centers; step S4: performing rapid adaptive training based on a meta-learning mechanism by the client to obtain updated client local model parameters; step S5: aggregating group models by an edge server, and generating an updated model by the global server; step S6: iterating until convergence; and step S7: deploying the global model to perform real-time intrusion detection. The application can effectively perceive and adapt to learning new threats, protect data privacy in a distributed environment, break through the limitations of traditional models in a dynamic open environment, and improve the overall security and adaptability of the industrial internet system.

This invention discloses a method and system for epilepsy monitoring and early warning, relating to the field of medical signal processing. It solves the problems of high false alarms and false negatives, and low energy efficiency in existing monitoring technologies due to physiological artifact interference, individual differences, and continuous high power consumption. The key technical points are: first, achieving deep artifact removal of the signal through multi-angle collaborative filtering; second, constructing a personalized lightweight prediction model based on historical data similarity matching and transfer learning; and finally, employing a dynamic signal filtering and graded power adjustment mechanism. This achieves the technical effect of significantly improving the accuracy of early warning for patients with specific lesions while greatly reducing system redundancy and energy consumption.

The embodiment of the invention discloses a text retrieval method and device, and the method comprises the steps: carrying out the structural processing and semantic segmentation of a to-be-retrieved text, and obtaining a fragment set; wherein the fragment set meets structural integrity and semantic integrity; performing knowledge vectorization and meta-information vectorization on the fragments in the fragment set to obtain knowledge vectors and meta-information vectors; constructing a clustering function based on a pre-constructed cosine similarity function, and performing inter-cluster aggregation and hierarchical construction according to the clustering function and a preset clustering threshold to obtain a multi-hierarchical retrieval structure; wherein the clustering function is generated based on knowledge vectors and meta-information vectors; and performing text retrieval according to the multi-level retrieval structure and a query vector generated based on the large language model. According to the method, semantic modeling and hierarchical retrieval of the document are realized, the problems of insufficient semantic understanding and result planarization of traditional keyword matching retrieval are solved, and the limitation of existing semantic vector retrieval on multi-version knowledge organization is broken through.

This invention discloses a method, apparatus, equipment, and medium for collaborative scheduling of virtual power plants in isolated microgrids, which can resolve the contradiction between data privacy protection and scheduling optimization in isolated scenarios. The method includes: constructing a federated digital twin model through federated learning iterative training by a central node and multiple local nodes; expanding local training samples and simulating and verifying the local model using a local digital twin engine during the training process; simulating and verifying the aggregated global model using a central digital twin engine; generating source-load prediction results for each virtual power plant based on the federated digital twin model; obtaining a balanced strategy combination for collaborative scheduling of multiple virtual power plants through dynamic game optimization based on the source-load prediction results and the scheduling strategy space of each virtual power plant; and generating scheduling instructions for each virtual power plant according to the balanced strategy combination and issuing them to each virtual power plant to execute resource allocation.