26results about How to "Reduce overdependence" patented technology

The invention relates to the technical field of power grid operation, and provides a power grid operation safety distance accurate sensing device and method in a non-fixed scene, and the device comprises a hardware device and terminal software which is in communication connection with the hardware device. The hardware device is integrated and deployed on a movable support or a holder, and comprises a laser radar sensor which is used for rapidly scanning a power grid operation scene and obtaining three-dimensional point cloud data including three-dimensional coordinates, laser intensity and echo information; the high-definition visible light camera is approximately parallel to the optical axis of the laser radar sensor and is used for collecting real-time video images of the operation scene; an AI visual analysis module and a point cloud processing unit are arranged in the embedded processor; and the terminal software is deployed on the edge computing equipment or the background server and is used for receiving and processing the data from the hardware device. According to the invention, the safe distance can be accurately sensed.

The invention belongs to the technical field of wind power generation, and particularly relates to a wind turbine generator state evaluation method and a related device, and the method comprises the steps: obtaining an electromagnetic transient response signal of a to-be-evaluated wind turbine generator; performing empirical mode decomposition on the electromagnetic transient response signal of the wind turbine generator to be evaluated to obtain a plurality of image forming model components; performing feature extraction on each image forming model component, and performing normalization processing to obtain a feature vector; classifying the feature vectors by using a pre-constructed state classification model to obtain a state evaluation result of the to-be-evaluated wind turbine generator; wherein the pre-constructed state classification model is a pre-trained support vector machine; according to the method, the fault features in the electromagnetic transient response signals of the wind turbine generator can be effectively extracted, and the accuracy and robustness of state evaluation are improved; meanwhile, non-linear and non-stationary signals can be decomposed in a self-adaptive mode, the time domain features of the signals are reserved, and the information amount and accuracy of state evaluation are improved.

The invention discloses a distributed computing fault snapshot generation system and method and a storage medium, and relates to the technical field of distributed computing, and the distributed computing fault snapshot generation system comprises a master control node and computing nodes; the master control node is used for capturing a calculation task exception event and adding context information for the calculation task exception event; reporting the calculation task exception event added with the context information to the calculation node with the calculation task exception; the context information at least comprises abnormal information; the computing node is used for analyzing the type of abnormal information and executing a diagnosis strategy according to the type of the abnormal information when the computing task abnormal event is received; and collecting snapshot data, packaging the collected snapshot data, and uploading the packaged snapshot data to a distributed storage. The system can actively capture a complete state snapshot at the moment of a fault, and can effectively support deep root cause analysis. In addition, the system automatically executes a proper diagnosis strategy and persistently stores snapshot data, and has accurate triggering and intelligent decision-making capabilities.

The application provides a strain of Arthrobacter sp. ZJUHUYJH1 and application thereof in prevention and treatment of paratyphaceae root-knot nematodes, and belongs to the technical field of prevention and treatment of plant root-knot nematodes. The Arthrobacter sp. ZJUHUYJH1 provided by the application has a preservation number of CCTCC NO: M 2025922, is isolated from rice rhizosphere soil infected by paratyphaceae root-knot nematodes, has a good prevention and treatment effect on paratyphaceae root-knot nematodes, a rectification mortality of 91.4% on second instar larvae of root-knot nematodes, can reduce the number of root-knots and the ratio of the number of root-knots to dry weight of rice infected by paratyphaceae root-knot nematodes, and has potential and practical application value in the research of paratyphaceae root-knot nematodes.

The invention discloses a pod propulsor structure optimization design method based on data driving. Comprising the steps of defining a design variable and an optimization target, constructing a parameterized geometric model, building a full-process automatic simulation analysis framework, generating a sample space through experimental design, obtaining a complete sample data set, constructing a high-precision agent model, carrying out algorithm optimization based on the agent model, verifying optimal design and calculating a data closed loop. And continuously updating the model. According to the method, the trained data driving agent model is utilized, in a huge design space, performance evaluation can be completed only in an extremely short time, the calculation period is greatly shortened, and a global optimal solution set can be rapidly obtained in combination with a global optimization algorithm; according to the method, various factors such as design requirements, test design, an agent model construction method and an optimization algorithm are comprehensively considered, the method can be suitable for structural design of other pod propellers with different production models or different design requirements, and effective guidance is provided for subsequent design of the pod propellers.

This invention provides an aortic pre-fenestration branch guidewire guidance system, comprising a central catheter, a capture ring, and a sliding cannula. The capture ring is connected to the outer wall of the central catheter. The sliding cannula is coaxially sleeved on the outside of the central catheter and can slide along the axial direction of the central catheter. When the sliding cannula moves proximally, the capture ring is released from the constraint of the sliding cannula and unfolds radially outward of the central catheter, thereby forming a capture opening that can accommodate the target guidewire. When the sliding cannula moves distally, the sliding cannula radially compresses the capture ring in its unfolded state, forcing the capture ring to undergo radial compression deformation. The radial compression deformation of the capture ring reduces the cross-sectional area of ​​the portion surrounding the target guidewire, thereby clamping the target guidewire and improving the success rate.

The invention belongs to the technical field of electrochemical in-situ characterization, and particularly relates to a packaging layer processing method for near-normal-pressure photoelectron spectroscopy analysis. The method comprises the following steps: constructing an initial packaging layer covering liquid electrolyte on the surface of a working electrode; integrating the samples on a sample carrying table and transferring the samples to an analysis equipment chamber; the thinning system of the equipment is used for carrying out in-situ thinning on a target area, the analysis beam of the equipment is synchronously or alternately used for monitoring the signal change of the thinned area in real time, and the thickness of the packaging layer is precisely regulated and controlled to the target nanoscale based on signal feedback. According to the method, through a strategy of first packaging and then in-situ optimization, the contradiction that effective sealing and high signal transmittance are difficult to consider in a traditional method is solved, high-quality in-situ and dynamic characterization of an electrode-electrolyte interface in a volatile liquid electrolyte environment is realized, and the accuracy and reliability of test data are remarkably improved.

The invention relates to a fine-adjustable side window mounting structure and method for a passenger train, and belongs to the manufacturing technology of rail transit vehicles. According to the technical scheme, the extending direction of an installation block long round hole in an installation block and the extending direction of a window frame long round hole in a window frame installation inclined face are in a crossed state, adjustment freedom degrees are provided in the vehicle width direction and the vehicle length direction, and fine adjustment in the vehicle width direction and the vehicle length direction is conducted respectively; adjusting freedom is provided by adjusting the matching position of the mounting block and the window frame mounting slope in the vertical direction of the vehicle, and the vehicle is adjusted in the vertical direction. The method has the beneficial effects that high precision and controllability are achieved, and the installation comprehensive error is controlled within the range of + / -4 mm through a unique three-way fine adjustment mechanism; 25-degree inclined plane matching is combined with tooth-shaped meshing, and the anti-micro-motion performance is excellent in a vibration environment. Adjustment is convenient and fast, and the adjustment direction is clear due to the design of the crossed oblong holes. Due to the design of the split type mounting blocks, stress concentration is avoided, the rigidity of the whole structure is good, and the service life is long.

The invention relates to the technical field of image segmentation, in particular to a tongue coating segmentation image and digestive disease classification method. According to the method, the position of a particle center point is determined by introducing multi-scale LoG filtering, and tongue particles and tongue coating particles are distinguished according to the law of spatial distribution and density change characteristics; according to the method, local adaptive threshold adjustment is carried out on other pixel points through the change of uneven particle density of different parts, more accurate tongue coating areas and tongue quality areas are obtained through division, and subsequent classification is carried out based on the tongue coating areas and the tongue quality areas. According to the method, the tongue coating area is divided more accurately through multi-scale LoG filtering and spatial statistical characteristics, a reliable data basis is provided for subsequent auxiliary classification of digestive diseases, and the classification accuracy is improved.

This invention belongs to the field of tunnel engineering, specifically relating to a data-mechanism-model-driven intelligent analysis method and system for rock mass strength parameters. It includes: generating a simulation dataset adapted to the current engineering rock mass strength and geological conditions through high-fidelity drilling numerical simulation, and training a multilayer perceptron as a physical information proxy model to achieve physical mapping of the rock drilling process. Secondly, the three-dimensional parameters are processed by three-dimensional spatial aggregation and segmentation. Combining graph neural network analysis and transformer model information extraction, a hybrid loss function for multi-dimensional data is defined. This hybrid loss function, together with the physical loss function, forms an optimized loss function with physical information and drilling data. An automatic optimization process for the loss function is then performed to achieve rock mass strength prediction. This invention can effectively analyze rock mass strength parameters.

The invention relates to the technical field of shield tunneling machine automatic control, in particular to an automatic control system and method for a shield tunneling machine muddy water conveying system, and the method comprises the following steps: when a shield tunneling machine starts tunneling or stops tunneling, executing a bypass mode, and transiting from the bypass mode to a tunneling mode or transiting from the bypass mode to a stop mode. According to the automatic control system and method, the tunneling mode, the stop mode and the bypass mode are set, the muddy water conveying system is automatically controlled to enter the bypass mode according to whether the shield tunneling machine conducts tunneling or not, then the muddy water conveying system enters the tunneling mode or the stop mode from the bypass mode, and through transition of the bypass mode, the muddy water conveying system is automatically controlled to enter the tunneling mode or the stop mode. And the stability of muddy water circulation and pressure adjustment can be ensured.

The invention provides an intelligent positioning and protocol recommendation method, device and system for magnetic resonance scanning and a medium, and the method comprises the steps: obtaining a positioning image of a patient, and recognizing the anatomical structure information in the positioning image through a pre-trained deep learning model; based on the identified anatomical structure information, according to a preset clinical rule base, generating at least one suggested scanning range frame on the positioning image; and displaying the generated scanning range frame in an interactive interface, and adjusting the scanning range frame by responding to a user operation instruction. According to the invention, the traditional manual operation is converted into a one-key confirmation mode or a fine adjustment mode, so that the scanning preparation time is greatly shortened, and the equipment turnover rate is improved. Based on an AI algorithm and a preset rule, man-made differences are eliminated, and consistency and normalization of scanning results in different scenes are guaranteed. Dependence on personal experience is reduced, new user training cost is reduced, low-level errors are avoided, and user experience is optimized through an intuitive and intelligent interaction interface.

The application relates to the technical field of drainage devices, and a multifunctional negative pressure drainage ball, which comprises a negative pressure ball body, liquid inlet and liquid outlet arranged at two ends of the negative pressure ball body, a liquid inlet pipeline and a pressure adjusting device, one end of the liquid inlet pipeline is connected with the liquid inlet through a three-way pipe, a pressure gauge is connected to the three-way pipe, the pressure adjusting device is connected to the liquid inlet pipeline, the pressure adjusting device comprises a scale cylinder and a piston rod, the piston rod is slidably connected with the scale cylinder, one end of the scale cylinder away from the piston rod is connected with the liquid inlet pipeline and a cleaning liquid container through a connecting pipe and a cleaning pipe, first and second valves are respectively arranged on the connecting pipe and the cleaning pipe, and third and fourth valves are respectively arranged at two ends of the connecting position of the liquid inlet pipeline and the connecting pipe. The application can effectively improve the stability and smoothness of the drainage operation.

The application discloses a gyrotron integrated test analysis method, and belongs to the field of high-power microwave device testing. The method designs a steady-state working condition debugging starting point according to a starting current curve; and combines experimental power measurement data to correct a simulated power characteristic surface. The method provided by the application combines theoretical simulation with experimental data, realizes rapid identification and optimization of gyrotron working characteristics, improves debugging efficiency and precision, and is suitable for engineering debugging and operation optimization of an electron cyclotron resonance heating system. The method has the advantages of process standardization, high safety and strong migration, and can improve debugging efficiency, enhance calibration precision and reliability.

The embodiment of the invention relates to the field of rehabilitation training, and discloses a rehabilitation training device based on multi-split muscle activation feedback and electronic equipment, and the device comprises a signal collection module which is arranged in a body surface projection area of multi-split muscle and is used for obtaining a multi-split muscle signal in a process of performing rehabilitation training for a target training action; and the processor is connected with the signal acquisition module and is used for calculating an activation level in real time according to the multi-split muscle signal and outputting a feedback signal for reflecting a relationship between the activation level and a target training interval. According to the rehabilitation training device based on the multifidus muscle activation feedback, the problems of accurately monitoring the multifidus muscle activation condition and providing instant feedback and action guidance in dynamic waist rehabilitation training are solved, so that the multifidus muscle activation condition can be accurately monitored in the dynamic waist rehabilitation training, and the rehabilitation training efficiency is improved. Immediate feedback and action guidance are provided, and real-time and understandable biological feedback is formed in daily rehabilitation training.

The invention is suitable for the field of hydraulic structure design of water conservancy and hydropower engineering, and provides a gravity dam economic section automatic design method and system based on an intelligent optimization algorithm, and the method comprises the steps: inputting design parameters, and initializing an algorithm population; performing stability calculation and constraint verification on each candidate section in the population; the candidate sections are evaluated through a preset fitness function, the function applies a great penalty value to the sections which do not meet the stability constraint, and the volumes of the sections which meet the constraint are directly used as fitness values; the population is iteratively evolved by using an intelligent optimization algorithm, and individuals with better fitness values are continuously screened out; and finally outputting an economic section which meets all safety constraints and has the minimum concrete volume. According to the method, a complex constrained engineering optimization problem is converted into an unconstrained optimization problem, automation and intellectualization of gravity dam section design are achieved, the design efficiency is greatly improved, and the engineering amount of a dam body can be remarkably reduced on the premise that safety is guaranteed.

The present application relates to the technical field of intelligent transportation and vehicle behavior prediction, in particular to a real-time trajectory prediction method for over-limit and over-load vehicles based on collaborative filtering, especially to a trajectory prediction method for over-limit and over-load vehicles, combining multi-dimensional behavior clustering and BiLSTM-Transformer hybrid model, introducing a DBSCAN clustering step based on multi-dimensional comprehensive similarity, which can automatically and accurately classify over-limit and over-load vehicles with similar behavior patterns into the same group. The most similar group is matched for the target vehicle for model training, effectively solving the problem of fuzzy model learning target caused by data heterogeneity. At the same time, the hybrid model architecture layer is good at capturing local time series dynamics and short-term driving rules, while the self-attention mechanism of the encoder can effectively model global long-distance dependence and complex trajectory patterns, and the two complement each other, thus achieving a leap in prediction accuracy as a whole. The algorithm can automatically identify noise points, further enhancing the robustness of the method to data noise.

The invention relates to a suspension type tube plate welding machine head which comprises a machine head body, a welding torch, a welding torch adjusting mechanism, a wire feeding mechanism and a center positioning shaft are arranged at one end of the machine head body, and at least two supporting rod assemblies capable of being expanded in the radial direction are arranged around the machine head body. One end of the integrated box body is connected with the other end of the machine head main body, a lifting appliance is fixed to the top of the integrated box body, and a central pipe is arranged in the integrated box body in the axial direction in a penetrating mode; the center positioning shaft is connected with one end of the center pipe through an expansion sleeve assembly. A sliding ring assembly is arranged in the integrated box body and coaxially arranged on the periphery of the center pipe in a sleeving mode. And a water-gas sharing flow channel surrounding the slip ring assembly is also arranged in the integrated box body. By means of the modular design and the highly-integrated box body, the whole machine is compact in structure, the weight is obviously reduced, rapid hanging, flexible moving and accurate positioning can be achieved through the top lifting tool, and the adaptability to large workpiece multi-position welding and narrow space operation is greatly improved.

The invention relates to the technical field of artificial intelligence, and provides a scene text recognition method and device, equipment and a medium. The method comprises the steps of obtaining a to-be-recognized scene text image; inputting the scene text image to be recognized into a scene text recognition model, wherein the scene text recognition model comprises a visual converter encoder and a decoder based on a Mama model; extracting a visual feature sequence of the to-be-recognized scene text image through a visual converter encoder; and decoding the visual feature sequence through a decoder based on a Mama model to generate a text sequence corresponding to the scene text image to be recognized. According to the method, the visual converter encoder is combined with the decoder based on the Mama model, the scene text recognition precision is guaranteed, meanwhile, efficient sequence decoding is achieved through the linear calculation complexity of the Mama decoder, reasoning delay is remarkably reduced, and the method is particularly suitable for the edge deployment environment with limited calculation resources.

The invention discloses an intelligent decision algorithm model design and development auxiliary system, and relates to the technical field of computer software, and the system comprises a data flow and feature engineering pipeline which is used for automatic data processing and feature construction; the model factory and hyper-parameter autonomous optimization engine is used for automatically generating and optimizing a model based on Bayesian optimization; the multi-dimensional evaluation and decision-making cockpit is used for carrying out comprehensive performance evaluation and visual comparison on the candidate models; and the full-life-cycle tracing and knowledge graph module is used for systematically recording and managing experimental knowledge. The invention aims to solve the problems of fragmentization of a model development process, low hyper-parameter tuning efficiency and weak experiment management, realizes full-process automation and intelligent coordination from data to model deployment, improves development efficiency and model performance, and promotes precipitation and reuse of knowledge.

The invention discloses a tool and method for controlling the depth of a contaminated layer on the surface of titanium alloy, and the tool comprises a box body which is provided with an opening in the top and is used for accommodating a titanium alloy part to be treated; the top cover assembly is connected with the opening of the box body, the top cover assembly comprises a ceramic matrix composite one-way cover and a one-way exhaust valve, a plurality of vent holes are formed in the ceramic matrix composite one-way cover, and the one-way exhaust valve is installed at the vent holes; the sealing piece is arranged at the joint of the box body and the sealing cover assembly, and the sealing piece is an annular aerogel gasket; the internal bearing mechanism comprises a plurality of internal bearing assemblies, and the plurality of internal bearing assemblies are arranged in the box body; and the pre-vacuumizing valve is arranged on the box body. According to the method, the depth of the surface pollution layer of the titanium alloy subjected to heat treatment can be stably controlled within 0.05 mm and is obviously superior to the upper limit of 0.08 mm required by the existing industrial standard.

The invention relates to the technical field of power system safety monitoring, and provides an intelligent power fire early warning system with a self-learning capability, which comprises a field sensing layer, a gateway layer, a server layer and an interaction layer, the field sensing layer comprises an electrical parameter acquisition module, a thermal parameter acquisition module and a fault feature acquisition module; the gateway layer comprises a data acquisition module which is responsible for collecting, converting, synchronizing and uploading data of each sensor of the field sensing layer; the server layer comprises a data processing module, a feature extraction module, a historical database, a self-learning analysis module, a disposal suggestion generation module and a man-machine interaction interface; the interaction layer comprises a linkage control interface and a user terminal. According to the invention, through two key technologies of multi-parameter fusion and closed-loop self-learning, two core defects of single monitoring dimension and static stiffness of an early warning model of a traditional power fire early warning system are fundamentally solved.

This utility model discloses a deformation detection device for large wind turbine hoisting, belonging to the field of wind power equipment installation technology. It includes: multiple sensor units for detachable installation on the surface of the wind turbine component to be hoisted, with each sensor unit consisting of a housing and a strain gauge, a triaxial accelerometer, and a wireless data transmission module housed within the housing; a central processing and control hub for receiving and processing deformation data from the multiple sensor units, and communicating with the wireless data transmission module; and a monitoring and alarm terminal for displaying deformation data in real time and issuing alarm signals when a risk is detected, electrically connected to the central processing and control hub. This device, by arranging multiple sensor units on the wind turbine component, achieves full-process, real-time, and quantitative monitoring of structural deformation and vibration status of key parts during hoisting, solving the technical problem that traditional methods cannot dynamically grasp the actual stress condition of the component.

The invention discloses a high-strength film greenhouse installation method based on standardized precise control, and belongs to the technical field of film greenhouse installation, and the method comprises the steps: S1, executing a set of standardized installation processes, including foundation positioning and construction, steel structure installation, environmental control system integration, electrical system installation and overall debugging operation; s2, in the step S1, quantitative precision control is carried out on key construction links, and the key construction links at least comprise foundation engineering, steel structure assembling and positioning and installation and calibration of environment control equipment; and S3, in the process of the step S1, building materials of standard specifications and a standardized mechanical connection mode are adopted in a unified mode, and the overall strength and design durability of the greenhouse structure are guaranteed. The combined load of 0.55 kN / m wind pressure and 0.20 kN / m snow pressure can be borne, the designed service life is larger than or equal to 15 years, the drainage capacity is larger than or equal to 140 mm / h, and the thin film greenhouse is particularly suitable for a thin film greenhouse with the span being 6-8 m and the shoulder height being 3.0-4.0 m and has the advantages of being high in structural strength, good in installation precision, long in service life and excellent in environment control.