475results about How to "Reduce duplication" patented technology

The invention discloses a logistics park vehicle path planning method and system, and the method comprises the steps: obtaining the real-time position and task state information of a vehicle in a park, dynamically constructing a vehicle path planning network model, dividing a road into nodes and edges, and forming a directed weighted graph; according to the directed weighted graph, an improved multi-lane algorithm is adopted, the path length, the congestion degree and the vehicle characteristic factors are comprehensively considered, and the optimal path of each vehicle is calculated; for the optimal path, introducing a virtual lane and a time dimension, pre-judging occupation conditions of multiple vehicles on the virtual lane for each time slice, and constructing a conflict constraint matrix; obtaining park high-precision map data, extracting road network topology, lane lines and traffic sign marking elements, performing lane-level refinement on the optimal path, and generating a driving track; and through a multi-sensor fusion positioning technology, obtaining high-precision position and attitude information of the vehicle, matching the high-precision position and attitude information with the driving track, and calculating a track tracking error.

The invention provides an unmanned aerial vehicle route layout method and device for complex terrains, equipment and a medium, and relates to the technical field of unmanned aerial vehicle aerial photogrammetry. The method comprises the following steps: carrying out preliminary region division on a terrain region to be surveyed, and determining a plurality of region units; clustering the area units according to topographic observation data to obtain survey sub-areas; determining a survey priority corresponding to each survey sub-region, and matching a basic flight route corresponding to the unmanned aerial vehicle according to the survey priority; and splicing the different types of basic flight routes corresponding to the survey sub-regions, and performing optimization adjustment on the spliced basic flight routes to obtain a flight route of the target unmanned aerial vehicle so as to perform topographic survey on the topographic region to be surveyed. According to the technical scheme, the route planning of the unmanned aerial vehicle can adapt to various types of landform features, and the safety and aerial survey efficiency of the unmanned aerial vehicle are ensured while the integrity and accuracy of aerial survey data are improved.

The invention relates to the technical field of path planning, and discloses a laser fuse additive manufacturing thermal management path planning closed-loop regulation and control system, which comprises a data acquisition module, a data processing module, a temperature distribution prediction module and a path planning regulation and control module, acquiring temperature distribution characteristic data and first characteristic data; the data processing module is used for preprocessing the temperature distribution feature data and the first feature data to obtain a regional feature sequence; the temperature distribution prediction module is used for constructing a temperature distribution prediction model according to the regional feature sequence; and the path planning regulation and control module is used for generating a regulation and control scheme in combination with the improved parrot optimization algorithm and the temperature distribution prediction model. Through combination of temperature prediction, path optimization, multi-dimensional feature extraction and an improved optimization algorithm, global optimization and dynamic regulation and control of the processing process are realized.

The invention discloses a network security alarm automatic research and judgment method, device and equipment and a medium, and relates to the technical field of artificial intelligence, original alarm data of various network security equipment and systems are acquired, and the original alarm data are processed; the processing comprises data preprocessing, feature extraction and classification aggregation; performing deep packet analysis on the processed original alarm data to obtain an analysis structure and content, and performing abnormal behavior identification and attack purpose derivation on the analysis structure and content to obtain an abnormal behavior attack purpose; the method comprises the following steps: performing threat level evaluation on an abnormal behavior attack purpose based on a threat intelligence source in a preset third-party knowledge base to obtain a network security alarm threat level, performing dynamic research and judgment evaluation on the network security alarm threat level to obtain a dynamic research and judgment evaluation result of network security equipment and system, and sending the dynamic research and judgment evaluation result to the network security equipment and system. According to the invention, deep interpretation and analysis of network security alarms can be realized, real attack events are automatically screened out, and the accuracy and efficiency of alarm research and judgment are improved.

The invention relates to a path planning method of a photovoltaic robot, the photovoltaic robot, equipment and a medium, and the method comprises the steps: setting a distance between adjacent paths according to a machine cleaning performance index, generating an internal cleaning path based on a photovoltaic plate map and the distance between the adjacent paths, and discretizing the internal cleaning path into a plurality of path points with expected poses; an acceptance path point is arranged on each sub-cleaning path of the internal cleaning path, and parameters of the acceptance path points comprise an expected cleaning area; executing an internal cleaning path, monitoring a pose error between an actual pose and an expected pose in real time, and determining a cleaning performance error according to an actual cleaning area and an expected cleaning area; when the pose error is greater than the pose tolerance threshold or the cleaning performance error is less than the cleaning tolerance threshold, a target internal cleaning path is generated and executed based on the pose error and / or the cleaning performance error. The execution speed and the cleaning efficiency of the photovoltaic robot on the cleaning path are improved, and meanwhile it is ensured that the cleaning quality reaches the expected standard.

The invention relates to the technical field of digital printing machines, in particular to an intelligent ink droplet control method and system of a digital printing machine and the digital printing machine. The method comprises the steps of real-time data acquisition, multi-dimensional parameter modeling, real-time ink droplet behavior prediction, self-adaptive ink jet parameter adjustment, closed-loop feedback control, medium characteristic self-adaptive matching, intelligent multi-region optimization and environmental factor compensation. Ink droplet behaviors and environmental data are collected in real time through a high-speed camera and various sensors, a nonlinear model is constructed by using a deep learning technology, and a dynamic parameter optimization curve is generated. According to the method, the printing quality and efficiency are remarkably improved, and the method is suitable for various media and complex scenes.

The invention discloses a private domain user management method and system for multiple touch channels, a medium and a program product, and the method comprises the steps: obtaining the historical behavior data of a user in each touch channel; identifying the behavior relevance of the user among the arriving channels; constructing an inter-channel behavior mapping relation of migration paths of the user among the touch channels based on behavior relevance; according to the behavior mapping relation between the channels, the overlapping ratio of user behaviors between the reaching channels, the difference of conversion effects and the overlapping ratio of time sequences are calculated; based on the overlapping rate, the difference and the coincidence degree, determining the reaching channel complementation degree; grouping and clustering the reaching channels according to the reaching channel complementation degree to obtain a plurality of channel collaboration units; and the optimal time difference of the arriving users in each channel cooperation unit is calculated, and the marketing resources are allocated among the arriving channels based on the optimal time difference, so that the accuracy of private domain operation management is improved.

The invention relates to a double-flexible-support pendulum type all-quartz resonant accelerometer and an assembly method thereof, the accelerometer comprises a sensitive mass block structure composed of a mass block, mass block flexible supports and stress isolation areas, an upper resonant beam is connected above the mass block, and a lower resonant beam is connected below the mass block; a lower limiting plate is connected below the sensitive mass block structure, and the lower part of the lower limiting plate is connected to the mounting base; an upper limiting plate and a lower limiting plate are connected above the sensitive mass block structure, and the sensitive mass block structure and the upper limiting plate penetrate through the positioning binding post; the outer sides of the lower limiting plate, the sensitive mass block structure and the upper limiting plate are provided with a shell, and the shell is connected to the mounting base; the upper resonant beam and the lower resonant beam are electrically connected with a resonant circuit in the mounting base through positioning binding posts, and signals are transmitted to the resonant circuit; according to the invention, the environmental adaptability of the accelerometer is improved, the temperature characteristic of the accelerometer is reduced, the volume of the accelerometer is reduced, and the accelerometer adapts to the miniaturization and high-precision development trend of an inertial navigation system.

The invention discloses a visual detection optimization method and system based on data set classification. The method comprises the steps of introducing a scene classification label and carrying out standardization processing on scene features in a data set labeling and preprocessing stage, and carrying out scene classification multi-task learning in a model selection and training stage, so that a model dynamically adjusts feature learning in different scenes, and the multi-scene adaptive capacity is improved. And in the model evaluation and verification stage, scene-based hierarchical evaluation is introduced and corresponding optimization is carried out. In the model deployment and reasoning stage, a dynamic scene is introduced to adapt to reasoning, and the reasoning path of the model is dynamically adjusted to adapt to the characteristics of the scene, so that the reasoning accuracy is improved. In the later optimization, scene feature clustering and transfer learning are used, and the multi-scene performance of the model is optimized. According to the method, under the condition that the model is not jointly trained through multiple data sets, the multi-scene adaptive capacity of the visual detection model is improved through data set classification.

The invention relates to an early warning event processing system of an oil and gas pipeline optical fiber early warning system, and the system comprises a preprocessing module which is used for receiving and preprocessing the real-time early warning data of a plurality of early warning events, and obtaining the preprocessed real-time early warning data; the initial merging module is used for determining a first similar early warning event in the plurality of early warning events according to the preprocessed real-time early warning data, and performing initial merging on the real-time early warning data of the first similar early warning event to obtain a merged early warning event; the dynamic upgrading and downgrading processing module is used for acquiring a multi-dimensional feature vector of the combined early warning event; using a deep learning model to adjust the initial early warning level of the combined early warning event according to the multi-dimensional feature vector to obtain an adjusted early warning level; and the output module is used for outputting the combined early warning event and the adjusted early warning level thereof. According to the system, repeated and redundant information can be reduced, and the early warning event processing efficiency, response speed and dynamic flexibility are improved.

The invention belongs to the technical field of edible oil preparation, particularly relates to a camellia oil preparation system and a preparation method, and aims to solve the problems that when an existing camellia oil preparation system prepares a pressed blank before squeezing, the amount of added crushed camellia materials cannot be accurately mastered, so that the pressed blank needs to be repeatedly squeezed for multiple times after being formed, and the production cost is reduced. In order to solve the problems that in the prior art, the number of times of completely squeezing a pressed blank cannot be effectively confirmed, and the squeezing efficiency and effect are reduced, according to the scheme, the device comprises a barrel, a cover plate is fixedly connected to the inner wall of the barrel, a stirring module is arranged on the cover plate, a round hole is formed in the cover plate, and a feeding hopper is fixedly connected into the round hole. According to the camellia oil preparation system and the preparation method disclosed by the invention, the quantity of crushed camellia particles in the pressed blanks for squeezing the camellia oil can be accurately controlled, so that the forming quality of the pressed blanks is effectively controlled, the camellia oil can be completely squeezed by repeatedly squeezing each pressed blank for the same times, the repeated operation is greatly reduced, and the production efficiency is improved. And the oil pressing efficiency is improved.

The invention relates to a critical disease inter-hospital referral patient scoring and resource allocation method, system and device, and a medium. The method comprises the following steps: determining referral demands of patients; constructing a resource matching model in combination with the illness state and the geographic position of the patient and the medical specialist information of the hospital to generate a recommended hospital list, and determining a transfer-in hospital and a referral time window; calculating an optimal referral path and the shortest time required by referral in the referral time window according to the transfer-in hospital and the referral time window in combination with the geographic information and the real-time road condition data; and allocating the ambulances to the patients within the available range of the ambulances based on the globally optimized resource allocation model. The advanced scoring rule and the resource allocation algorithm are introduced, the treatment efficiency of critical patients is improved, more scientific and objective decision support is provided, and unnecessary referral treatment and repeated examination are reduced, so that the medical cost is effectively reduced, medical errors are reduced, and the satisfaction degree of the patients is greatly improved.

The invention discloses a network security attack and defense confrontation scene generation system for a novel power system. The scene editor module receives user interaction and constructs or modifies an attack and defense scene; the network simulation module generates real network environment data based on a network space surveying and mapping technology, constructs a simulation network environment and manages simulation data through a simulation database; the AI automatic control module integrates an AI algorithm to simulate an attack behavior, intelligently generates and adjusts a defense strategy, and manages an attack and defense rule through a rule engine; the security isolation module deploys security equipment to realize sensitive data isolation; the data flow direction is controlled through strategy configuration, and information leakage is prevented; the evaluation and feedback module is used for collecting data in the drilling process, carrying out multi-evaluation on the drilling effect and generating reports and suggestions; and the business module adopts a plug-in architecture, dynamically loads or unloads each functional module, constructs a multi-layer defense system, and realizes generation, evaluation and feedback of an intelligent confrontation strategy. According to the invention, the authenticity and effectiveness of attack and defense drilling are improved.

The invention relates to the technical field of ecological environment monitoring, and discloses intelligent eagle equipment and an ecological environment monitoring method, and the intelligent eagle equipment comprises a data obtaining module which is used for obtaining ecological environment images, temperature data and point cloud data of a target area at different distances through employing a multi-focal-segment fusion algorithm; the data processing module is used for performing parallel processing on the acquired data by adopting a quantum circuit algorithm; the remote transmission module is used for transmitting the collected data and the processed data to a ground control station in real time so as to make decisions and determine monitoring task requirements through the ground control station; the monitoring path planning module is used for receiving monitoring task requirements, selecting a path planning algorithm according to terrain complexity, performing path planning on a target area in combination with the collected data, and converting a path planning result into a control instruction through a ground control station; and the unmanned aerial vehicle platform comprises a composite wing unmanned aerial vehicle and a multi-rotor unmanned aerial vehicle, and is used for carrying other modules and receiving the control instruction of the ground control station to carry out flight monitoring.

The invention discloses an industrial park net load prediction method and system based on a multilayer perceptron, and the method comprises the following steps: dividing historical industrial park operation data according to an audio frequency collection region, and obtaining region historical operation data corresponding to the audio frequency collection region; performing clustering analysis on the historical operation data of each region based on the audio frequency fluctuation, and obtaining audio frequency-aging correlation according to a clustering result; training by using historical industrial park operation data, historical distributed energy operation data and audio frequency-aging correlation to obtain an industrial park net load prediction model; and obtaining industrial park net load prediction data according to the current industrial park operation data, the current distributed energy operation data, the industrial park load net prediction model and the audio frequency-aging correlation. The method has the beneficial effects that an aging model does not need to be constructed for each industrial device, the overall model structure is simplified, and meanwhile, the prediction efficiency and prediction accuracy of the load of the industrial park are improved.

The invention belongs to the technical field of integrated circuits, and particularly relates to a chip-level integrated circuit fault diagnosis method based on improved wavelet entropy, which comprises the following steps: S1, acquiring an original signal of a chip-level integrated circuit, and reconstructing the original signal by using a VMD signal reconstruction technology; s2, performing deep processing on the reconstructed signal by adopting an improved wavelet entropy method, and extracting key features of a fault signal; s3, monitoring the voltage change of each node through the key characteristics of the fault signal, and effectively positioning the fault position; and S4, setting a fault factor which can comprehensively consider the fault position, the attenuation degree and the fault length, comparing the fault factor with a set threshold value, and judging the severity of the fault, thereby realizing the online diagnosis of the fault of the chip-level integrated circuit. According to the invention, by introducing the adaptive wavelet basis selection and multi-scale wavelet entropy fusion technology, the accuracy and efficiency of diagnosis are significantly improved, the repeatability of fault signal feature extraction is reduced, and the real-time performance and stability of a diagnosis system are improved.

The invention discloses a three-dimensional reconstruction method based on an unmanned aerial vehicle and edge calculation, and relates to the field of unmanned aerial vehicle technology, edge calculation and three-dimensional scene reconstruction. The method comprises the following steps: an unmanned aerial vehicle carries a monocular camera to collect a standard-definition video stream from a target scene; the edge computing device receives and processes the standard-definition video stream in real time to generate preliminary low-precision three-dimensional reconstruction; the edge computing device identifies a defect area by analyzing a low-precision reconstruction result, and optimizes the flight path of the unmanned aerial vehicle; the unmanned aerial vehicle collects a high-definition video stream from the target scene according to the optimized path; and the edge computing device performs off-line high-precision three-dimensional reconstruction on the high-definition video stream so as to improve the accuracy and detail expression capability of a reconstructed scene. Through cooperative work of the unmanned aerial vehicle and the edge calculation end, real-time data processing, feedback and decision making in the collection process and high-precision three-dimensional reconstruction result storage in the off-line stage are achieved, and the real-time performance and accuracy of three-dimensional reconstruction are effectively improved.

The invention discloses an automatic verification device and method for a weighing coal feeder device. The automatic verification device comprises a weight calibration system, a weight verification control system, a sensor calibration system and a weighing coal feeder. According to the invention, the weight of the standard weight most suitable for the current calibration requirement is dynamically calculated and selected through the weight calibration system based on historical data, environmental parameters and the like of the weighing sensor, so that the calibration precision and flexibility are greatly improved, and variable working condition requirements can be met; according to the invention, an automatic weight verification control system is designed, horizontal displacement, lifting adjustment and state switching of the weight are realized, and the calibration process is fully automatic; the output data of the sensor are collected in real time through the sensor calibration system, dynamic correction is carried out in combination with multiple times of weighing error calculation and historical data, drift and error trends of the weighing sensor are analyzed in real time in combination with parameters such as temperature, humidity and vibration, and error correction values are generated, so that the accuracy of weighing data is ensured.

The invention discloses a key value storage system indexing method oriented to an NVM-NVMe SSD (Non-Volatile Memory-Non-Volatile Memory Express Solid State Disk) hybrid architecture, which comprises the following steps of: constructing a heterogeneous storage architecture taking cold and hot data perception as a core driving mechanism, coordinating and managing two types of storage media, namely a non-volatile memory NVM and a solid state disk NVMe SSD, and realizing efficient identification, layered writing and dynamic migration of cold and hot data. According to the method, the characteristics of low delay, durability and byte addressing of the NVM are utilized, the frequency and I / O overhead of Flush and Compaction operations are reduced in a data write-in path, meanwhile, the problem of mixed storage of cold and hot data is avoided, and therefore the overall performance and storage efficiency of a system are remarkably improved. In addition, by introducing an asynchronous migration module, the method can dynamically adapt to the change of data popularity along with time evolution, and effectively support high performance and high availability of the key value system in long-term operation.

The invention discloses a wall-climbing robot cylindrical tank space surface welding seam path planning method. The method comprises the steps that 1, a 2D map of a three-dimensional cylindrical tank welding seam is constructed; step 2, constructing an undirected connected graph; 3, judging whether any cross point meets the requirements of an Euler loop or not; 4, constructing a shortest path Euler loop by using a virtual edge adding method; and 5, an improved Fluery algorithm is utilized to plan a path through which the robot can traverse the welding seam at a time. According to the method, the three-dimensional cylindrical tank welding seam is mapped to the 2D plane, the 2D map of the welding seam path is accurately constructed, path planning is optimized through the undirected connected graph and the virtual edge method, and it is ensured that the cylindrical tank wall-climbing robot can traverse all welding seams on the shortest path. According to the method, an improved Fluery algorithm is combined, shortest path planning of an Euler loop is achieved, the efficiency and accuracy of robot weld traversal are optimized, an efficient path control scheme is provided for a robot, and the working capacity and the autonomous navigation level of the robot in a complex environment are improved.

The invention discloses a construction method and device of a query page, a storage medium and electronic equipment, and relates to the technical field of man-machine interaction interface design. The method comprises the steps that a user request is received, and the user request is used for changing a plurality of query conditions currently displayed in a display page or newly adding query conditions in the display page; a query condition configuration list is displayed in the runtime page, the query condition configuration list comprises N preset query conditions, and N is an integer larger than 1; according to the user request, multiple target query conditions meeting the user request are determined from a query condition configuration list, and the multiple target query conditions represent query conditions needing to be displayed to the user after responding to the user request; and rendering the runtime page according to the plurality of target query conditions to obtain a target query page. The technical problems of high repeatability and low efficiency of the creation process of the query page in the prior art are solved.

The invention relates to the field of big data processing, and particularly discloses a message pushing processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: if a push message type of a to-be-executed message push task exists at current time, taking the current time as query ending time; for each message pushing task, if a historical task execution record of a pushing message type of the message pushing task is queried, determining the last execution end time and the message processing duration of the last execution process from the historical task execution record; determining query start time based on the last execution end time and the message processing duration to construct a message query interval which is continuous and not overlapped with a historical query interval of a last push task in the historical task execution record; and querying according to the message query interval to obtain message content and pushing the message content. By adopting the method, decoupling of the service interface and the message processing interface can be realized, and complete message content can be efficiently pushed.

The invention discloses a coated titanium anode and an embedding preparation method thereof, and belongs to the technical field of coated titanium anodes, metal salt powder, an organic additive and inert filler are fully mixed to form embedding agent powder, the mass fraction of metal salt is 45-59%, the mass fraction of the organic additive is 1-5%, and the mass fraction of the inert filler is 40-50%; the sintering treatment is as follows: the pretreated titanium substrate is completely immersed in the embedding agent powder, the sintering temperature is 400-600 DEG C, the sintering time is 1-3 hours, and the heating rate is 5-10 DEG C / min. According to the method, low-temperature sintering is realized by precisely regulating and controlling the components and the proportion of the embedding medium and combining process parameters such as low-temperature sintering, and the damage to a titanium substrate is avoided; and meanwhile, the coating binding force of the titanium anode is improved, the service life of the titanium anode is prolonged, and technical innovation and industrial value are achieved.

The invention discloses a database AI question answering system and method based on a large language model and retrieval enhancement, and relates to the technical field of database retrieval. The system comprises a front-end interaction module, a distributed cache management module, a task scheduling center, a large language model processing sub-module, a retrieval enhancement sub-module, an answer optimization sub-module and a database management sub-module. All the sub-modules are mutually independent and work cooperatively, through an efficient task scheduling mechanism, the system can monitor the load and resource states of all the sub-modules in real time, accurate allocation of tasks is conducted according to an intelligent algorithm, in a large-scale concurrent request scene, single-point faults and resource waste are effectively avoided, stable operation of the system is ensured, and meanwhile, the system can be widely applied to large-scale concurrent requests. The distributed cache management module further optimizes the storage and access of the data, reduces repeated data query and transmission, and improves the overall performance.

The invention discloses an intelligent information collecting and summarizing system, and relates to the technical field of information management. The problems of high cost, potential safety hazards and low working efficiency in a traditional information collection mode are solved. The system comprises a user interface module, a data verification module, a data encryption module, a data storage module, an API interface module, a summary processing module, a data analysis and visualization module, an authority management module and an adaptive learning module. A user inputs data through an interface, the data are stored in a database after being verified and encrypted, then the data are transmitted to a summarizing processing module through an API interface to be processed, and an analysis result is displayed. The authority management module ensures that the system is safe and controllable, and the adaptive learning module optimizes the system according to user feedback. The method has a good application prospect in the field of information management.

The invention discloses a preparation method of a three-dimensional flower-cluster-shaped CdS QDs (at) ZnS / ZnO composite photocatalyst, belongs to the field of preparation of photocatalytic materials, and aims to solve the problem of relatively low photocatalytic efficiency. The preparation method comprises the following steps: 1, preparing zinc oxide: dissolving Zn (CH3COO) 2.2 H2O in deionized water, stirring until Zn (CH3COO) 2.2 H2O is completely dissolved, adding NaOH, stirring to form an emulsion, transferring the mixed emulsion into a polytetrafluoroethylene reaction kettle, and treating at 160 DEG C for 10 hours; 2, preparation of cadmium sulfide quantum dots (CdS QDs): dropwise adding thioacetamide (TAA) into a Cd (NO3) 2.4 H2O aqueous solution, continuously stirring and dropwise adding a NaOH solution, adjusting the pH value of the solution to 10.5, then adding a Na2S solution, stirring at 65 DEG C for 1 h, cooling to room temperature, and aging for 24 h; and 3, dissolving Zn (CH3COO) 2.2 H2O and TAA in deionized water, adding ZnO powder, adding CdS QDs, and carrying out rapid stirring. Putting into a microwave reaction instrument, reacting at 160 DEG C for 45 minutes, washing and drying. The three-dimensional flower-cluster-shaped CdS QDs (at) ZnS / ZnO composite photocatalyst is prepared through a microwave-assisted hydrothermal method, and the photocatalytic oxidation performance is effectively improved.

The invention provides a method, system and device for collecting MODBUS device data based on an Internet of Things platform and a medium, and belongs to the technical field of data conversion, and the method comprises the following steps: obtaining point table information of a target MODBUS device, MODBUS channel information for data collection of the target MODBUS device, and point position information configuration; creating a product model, a device model and an object model for the target MODBUS device on the Internet of Things platform, and carrying out mapping relation binding with point location information of data acquisition of the target MODBUS device; reading data from the target MODBUS equipment according to the bound mapping relation, and storing the data according to a preset storage strategy; and converting the read target MODBUS equipment data into standard data which can be identified by the Internet of Things platform. The MODBUS equipment data is efficiently converted into the Internet of Things standard data, the cost period is shortened, and the method is compatible with a multi-equipment platform.

The invention relates to a 2GPa-grade ultrahigh-strength steel plate and a manufacturing method thereof. The 2GPa-grade ultrahigh-strength steel plate comprises the following chemical components in percentage by weight: 0.35%-0.45% of C, 0.10%-0.40% of Si, 0.30%-0.60% of Mn, 0.80%-1.20% of Cr, 1.20%-1.80% of Ni, 0.30%-0.60% of Mo, 0.05%-0.15% of V, 0.01%-0.04% of Ti, less than or equal to 0.006% of P, less than or equal to 0.003% of S, less than or equal to 0.00015% of H, less than or equal to 0.006% of N and the balance of Fe and inevitable impurities. The tensile strength of the 2GPa-grade ultrahigh-strength steel plate is larger than or equal to 2000MPa, the yield strength is larger than or equal to 1500MPa, the plasticity is good, the percentage elongation after fracture is larger than or equal to 10%, and the 2GPa-grade ultrahigh-strength steel plate can be bent by 70 degrees without cracks or breaking and is suitable for being used as protective steel.

The invention discloses a method, system and equipment for improving ammeter data acquisition efficiency and a medium, and relates to the field of power systems. In the method, in response to an electric meter file and a network configuration parameter received from an acquisition terminal, networking is carried out according to the network configuration parameter to establish a communication connection with an electric meter; sending networking topology information to the acquisition terminal, and receiving a periodic acquisition task generated by the acquisition terminal according to the networking topology information; performing a first round of acquisition according to the periodic acquisition task and the ammeter file, constructing a trunk branch according to the physical phase of each ammeter and the hierarchical relationship in the communication network, and generating branch groups at the trunk tip of the trunk branch according to the phase relationship of the ammeter and the data acquisition condition of the first round of acquisition; and executing the periodic acquisition task according to the trunk branches and the branch groups. By implementing the technical scheme provided by the invention, the electricity meter data acquisition efficiency is improved.

The invention relates to the technical field of image data processing, in particular to an unmanned aerial vehicle inspection method for road slope engineering, which comprises the following steps: acquiring a video frame sequence of a road slope by using an unmanned aerial vehicle; obtaining two fitting curved surfaces of pixel points in each frame in the video frame sequence; determining the noise interference degree of the pixel points; calculating the optimization degree of the window radius of the pixel point and determining the final window radius; and according to the final window radius, obtaining an aligned video frame sequence by using an LK algorithm, and further obtaining a panorama of the road slope project so as to realize routing inspection of the road slope project. According to the method, the window radius is adaptively determined for each pixel point through curved surface fitting and structural similarity analysis in combination with iterative computation, so that the algorithm can accurately capture pixel motion information, and the accuracy of video frame alignment is remarkably improved; according to the method, the splicing problem caused by frame dislocation and fuzziness is effectively avoided, the produced road slope panorama is clearer and more accurate, and a high-quality image is provided for subsequent inspection.