13results about How to "Achieve leapfrogging" patented technology

This invention discloses a method for preparing and applying a sodium borohydride-modified self-supporting anode for AEM water electrolyzers. Firstly, an amorphous ternary metal hydroxyl oxide precursor is grown in situ on a nickel substrate via room temperature liquid phase deposition. The process involves the presence of Co in solution. 2+ Fe 3+ Ni ions are introduced through slight corrosion of the nickel foam matrix. 2+ The ions, the three, and the OH- produced by hydrolysis ⁻ Co-deposition occurs under the influence of dissolved oxygen, leading to the self-assembly of amorphous nanosheet structures on the substrate surface. Subsequently, a mild chemical reduction treatment with sodium borohydride solution is used to obtain a structurally stable and high-performance self-supporting electrode. The method described in this embodiment is mild, simple, low-cost, and has good versatility.

The invention discloses a winch traction system steering pulley stress detection device, which belongs to the technical field of electric power circuit construction, and comprises a main body, a connecting shaft rotatably mounted on the main body, and a movable arm connected with the main body and provided with a roller, and further comprises a pressure sensor arranged on a stress path of the connecting shaft, the traction force sensor is used for detecting traction force borne by the steering tackle; the control panel is arranged in the main body, is electrically connected with the pressure sensor and is used for processing the traction force data; the positioning module is integrated on the control panel and is used for acquiring the position information of the steering pulley; the original invisible mechanical state is converted into real-time and accurate digital information with a position label, it is guaranteed that the signals collected by the sensor truly reflect the axial traction force borne by the tackle, the processes such as downhole pre-preparation and real-time detection in operation are omitted, the time consumption of single-time operation is shortened, and the operation and maintenance efficiency is greatly improved.

This invention discloses a method and apparatus for detecting delamination defects in ceramic matrix composites using a flexible microwave resonator. The apparatus includes a flexible microwave resonator, a vector network analyzer, a two-dimensional scanning platform, and a data processing unit. The flexible microwave resonator consists of a polyimide substrate, a top-opening resonant ring, and a bottom coplanar waveguide feeding structure, conformally attached to the surface to be tested due to its flexibility. The method acquires S11 curves at various points by scanning, extracts the resonant frequency as a feature value, and finds that the resonant frequency offset has a monotonically changing relationship with the depth of the delamination defect. By constructing a resonant frequency distribution image, high-sensitivity localization, imaging, and quantitative depth inversion of delamination defects in ceramic matrix composites are achieved. This invention solves the problems of rigid sensors being unable to adapt to curved surface detection and low sensitivity for small defects, and is suitable for non-destructive testing of complex components such as aero-engine blades.

The invention discloses an electric digital data driven VR industrial interactive design system, and the system comprises a semantic security field construction module which is used for generating a virtual space with a logic constraint attribute based on a physical equipment security boundary; the digital twin mapping module is used for constructing an asset hierarchy and electrical topology model and laying semantic anchor points dynamically associated with real-time parameters; the interaction intention analysis module is used for analyzing a user intention instruction and an operation trend track in real time through action track coupling analysis; the logic pre-verification processor is used for performing physical simulation by taking the intention trajectory as a drive, deducing an equipment evolution trajectory, performing rule alignment with a safety field, and identifying logic conflicts; and the dynamic interception and interlocking engine is used for calculating a safety margin and executing VR feedback limitation and physical control system instruction interlocking. According to the method, through synchronous blocking of the virtual interaction side and the physical execution side, the problem that the interaction action is disjointed from the actual production logic in the industrial VR environment is solved, and the misoperation risk is effectively prevented.

This invention relates to the field of intelligent medical devices and precision drug delivery technology, and discloses a biofluid-assisted intelligent drug release triggering and control method that responds to the wound microenvironment. The method includes: collecting multi-parameter sensor signals such as pH, temperature, and biomarker concentration from the wound microenvironment, and performing preprocessing and feature extraction; calculating a fusion trigger index based on a dynamic weighted fusion algorithm to generate graded release level signals; employing a nested outer and inner loop dual-mode adaptive control structure to dynamically adjust control parameters according to the release level and real-time deviation, generating precise drive control quantity setpoints; further, predicting wound trends based on short-term historical data, and prospectively optimizing the control target based on a clinical rule knowledge base. This invention solves the problems of rigidity, lag, and inaccuracy of traditional local drug delivery methods, achieving intelligent closed-loop, adaptive, and prospective drug release regulation for complex dynamic wound microenvironments, significantly improving treatment efficacy and safety.

The invention discloses a bridge report generation method and system based on multi-modal causal and reinforcement learning. The method comprises the following steps: acquiring a disease image and text description, extracting structured disease information from the text description, generating multi-modal feature data, and performing image-text consistency verification; retrieving standard articles and historical cases based on the verified disease information, and positioning disease nodes in the causal knowledge graph and reversely tracing root cause nodes to generate a reasoning chain; fusing the multi-modal feature data, the retrieval result and the reasoning chain, generating an evaluation report draft through a large language model, and performing logic verification; and obtaining an expert correction text, inputting the expert correction text into the reward model, calculating a feedback score, and optimizing a knowledge graph edge weight and a report generation strategy. The invention also provides a system for realizing the method. According to the method, through image-text consistency verification, causal reasoning and reinforcement learning, the report accuracy, interpretability and compliance are effectively improved.

This invention discloses a method for dynamic control of reservoir operating water level during the flood season based on forecast availability. It includes analysis of basic hydrological and meteorological laws, analysis of water level-discharge relationship, analysis of meteorological and hydrological forecast levels, interval flow analysis, calculation of the reservoir's operating water level float limit during the flood season, and calculation combining simulation and actual inflow results. For each combination of forecast period and pre-discharge flow, the lowest allowable float value is taken as the reservoir's operating water level fluctuation result under that forecast period and pre-discharge scenario. This invention significantly improves the scientific rigor, safety, and practicality of dynamic control of reservoir operating water level during the flood season by constructing a closed-loop control system from basic hydrological and meteorological law analysis to actual inflow verification.

The present application relates to the technical field of abnormal data detection, in particular to a layered time series deep anomaly detection method and system for concept drift data stream. The method comprises: collecting traffic data in parallel through multi-scale time windows; constructing a layered heterogeneous deep network to extract short-term local features and long-term trend features; dynamically fusing multi-dimensional deviation features based on environmental state; evaluating the abnormal detection result of the target traffic data based on the comprehensive evaluation value; and adaptively adjusting the forgetting factor of each level through an error feedback mechanism to realize the dynamic evolution of the model when concept drift occurs. The present application also discloses a corresponding detection system. The present application effectively enhances the collaborative representation ability of the model for sudden anomalies and hidden attacks, significantly shortens the performance convergence time in a drifting environment, reduces the false positive rate, and greatly improves the sensitivity and global robustness of heterogeneous network traffic detection.

This invention belongs to the field of power system customer service automation and artificial intelligence application technology. It discloses an intelligent reporting system for important power supply service matters based on automatic capture and intelligent matching of meteorological early warnings. The system is characterized by comprising: 1) a real-time meteorological early warning capture module; 2) an early warning compliance judgment module; 3) an automatic generation module for reporting time periods; 4) an intelligent matching module for reporting scope, with a built-in scope rule engine constructed based on the "Notes on the Review of Reporting of Category III Severe Weather"; 5) an automatic filling module for reporting materials; 6) an automatic uploading module for multiple attachments; 7) a human-computer interaction and reverse verification module; and 8) a data closed-loop and rule optimization module. This system can solve the problems of poor timeliness, error-proneness, and lack of automated closed-loop management caused by the reliance on manual operation for reporting Category III severe weather in existing technologies.

The application discloses a battery combustion detection and automatic fire extinguishing method based on image recognition, and relates to the technical fields of fire safety and image processing. The method comprises the following steps: S1, outputting a battery combustion panoramic monitoring image sequence; S2, outputting a fire source two-dimensional pixel coordinate by improving a BiSeNet model; S3, outputting a fire source space positioning coordinate; S4, outputting an obstacle avoidance planning path of a fire extinguishing device; S5, selecting an optimal injection pressure, and outputting a directional fire extinguishing jet along the obstacle avoidance planning path of the fire extinguishing device; S6, outputting real-time evaluation data of fire extinguishing efficiency, and feeding back and correcting the optimal injection pressure; and S7, calculating a permutation entropy degree to measure system dynamics complexity, and if it is determined that the fire source is relighting, the obstacle avoidance planning path of the fire extinguishing device and the optimal injection pressure are recalculated. The application overcomes the defects of visual perception limitations, single control strategy and lack of feedback optimization of traditional methods, and provides an efficient solution for intelligent prevention and control of battery fires.

The present application relates to the technical field of power equipment detection, and discloses a micro offset early warning method and system for an electric energy meter detection device, a medium and a product. The early warning method comprises the following steps: randomly decomposing an error value of a detection unit into three errors subject to a normal distribution; obtaining prior and posterior distributions of the three errors according to a Bayesian method, and calculating a system offset mean value and a 95% confidence interval of the offset; calculating a fusion early warning score of the detection unit based on the system offset mean value; and triggering a micro offset early warning according to a judgment result of the system offset mean value, the confidence interval and the fusion early warning score. The present application can effectively identify a micro systematic offset far below a maximum allowable error, scientifically distinguish between equipment failure and individual dispersion of an electric meter, solve the problem that a traditional method cannot find a gradual drift, realize a leap from "threshold management" to "trend management", and provide reliable technical support for predictive maintenance of an electric energy meter calibration device and high-precision metering guarantee.

This invention discloses a method and system for early warning of abnormal behavior of dormitory personnel based on millimeter-wave radar. It combines three-dimensional spatial semantic modeling to divide the area into beds, desktops, and floors, and introduces a time gating mechanism to filter normal sleep and accurately determine abnormal prolonged lying-down states. By extracting the trajectory curvature probability distribution entropy value and round-trip repetition degree within specific semantic regions, it effectively overcomes the limitations of existing technologies in objectively quantifying and accurately identifying latent behavioral patterns such as student anxiety in real-life scenarios. A multi-source evidence fusion framework is constructed, which dynamically weights radar motion intensity evidence and acoustic energy evidence by calculating the spatial consistency between the radar target and the audio source location. Furthermore, by utilizing synthesis rules that include conflict handling, it effectively suppresses false alarms, greatly improving the accuracy and reliability of fall detection and violent conflict identification in complex practical applications.

This invention relates to the field of medical and nursing device technology, and discloses a hammock-type assisted turning bed and a turning method, including a bed frame body. The bed frame body includes multiple functional segments arranged sequentially along its length. Each functional segment is equipped with a bed surface driving mechanism and a support adjustment mechanism. The bed surface driving mechanism includes a roller winding device and a bed surface. Two roller winding devices are symmetrically arranged on both sides of the bed frame body of the functional segment. The two ends of the bed surface are wound around the rollers of the corresponding roller winding devices. The support adjustment mechanism is located below the bed surface and includes multiple electric cylinders arranged along the width direction of the bed frame body. The hammock-type assisted turning bed and turning method provided by this invention solve the problems of high risk of shear friction injury, high risk of pressure sores, poor comfort, and insufficient safety and adaptability in the practical application of existing technologies.