22results about How to "Targeted optimization" patented technology

The invention provides a power distribution network single-phase earth fault processing and fault rapid regional isolation system for solving the problems existing in power distribution network single-phase earth fault regional isolation at present. The system is composed of an improved compensation damping type active intervention arc extinguishing device installed on a transformer substation bus, primary and secondary fusion intelligent switches installed at all nodes of a distribution line, and a primary and secondary fusion intelligent switch intelligent control terminal. When a single-phase grounding fault occurs, a grounding switch of the compensation damping type active intervention arc extinguishing device is switched on, a primary and secondary fusion intelligent switch control terminal of each node of a power grid generates corresponding low-resistance, medium-resistance and high-resistance zero-sequence protection fixed values, and when the single-phase grounding fault occurs, zero-sequence current protection is started to realize rapid fault area isolation of the single-phase grounding fault.

The invention relates to an intelligent robot grabbing method and device, electronic equipment and a storage medium. The method can comprise the following steps: acquiring multi-modal sensing information corresponding to a target capture scene; based on a multi-modal semantic analysis model, performing semantic analysis processing on the multi-modal perception information, and outputting semantic association information corresponding to the to-be-grabbed object; according to the semantic association information, determining a target grabbed object, a recommended grabbed point corresponding to the target grabbed object and a recommended grabbed strategy; on the basis of a grabbing pose prediction network, pose prediction processing is conducted on the recommended grabbing points, and robot grabbing pose information is obtained; according to the recommended grabbing strategy and the robot grabbing pose information, the target grabbing object is grabbed, and grabbing state parameters are obtained; and on the basis of the grabbing state parameters, the grabbing pose information of the robot is adjusted. According to the technical scheme provided by the invention, objects can be effectively prevented from sliding off, being damaged or colliding, and the intelligent level and the grabbing efficiency of the robot are improved.

The utility model discloses a SF6 gas micro -water density monitoring devices contains micro -water detection module, inlet pipe, exhaust pipe, pump body, L type telescopic pipe and butt joint, drying cylinder, place cavity, step support surface, filter cartridge (infill drying agent), sliding sleeve, upper / lower limit convex ring, sliding groove and convex strip, boss, extruding block, fixed peg, spring, connecting rod, pressure gauge, wireless transmitting module, when working, the pump body draws gas and enters drying cylinder after micro -water detection, conical hole and extruding block - step support - sliding sleeve constitute forced flow structure, and make sample gas to pass through filter cartridge reflux equipment, and pressure gauge and wireless transmission realize pressure monitoring and data report, and the structure is convenient for installation maintenance, and inhibits bypass, and stable reflux moisture content, and improves detection result consistency.

The invention relates to the field of intelligent power grids and intelligent fusion terminals, in particular to a transformer health monitoring system based on an intelligent fusion terminal TTU, and the system comprises a waveform data collection module which is used for collecting the waveform data of a transformer; the environment data acquisition module is used for acquiring operation environment data of the transformer; the denoising and reconstruction module is used for carrying out denoising elimination and waveform reconstruction on the waveform data of the transformer; the feature extraction module is used for performing feature extraction, enhancement and fusion on the preprocessed waveform data and the operation environment data of the transformer to obtain a fusion feature vector; the state analysis module is used for inputting the fusion feature vector into a mixed regression model for health state prediction to obtain a transformer health index prediction value; and the TTU decision module is used for matching the control decision scheme and controlling the working state of the transformer. According to the invention, the accuracy and reliability of transformer health prediction and the reliability of overall operation of a power grid can be improved.

The invention discloses a remote sensing residential area extraction method and system based on multi-source data fusion semantic segmentation, and particularly relates to the field of remote sensing image processing and land utilization mapping. A multi-source fusion automatic labeling strategy is adopted, and a rural residential area pixel-level training label is automatically generated by using an impervious surface product, an open source map interest point and a night light learning area-brightness threshold value; the method comprises the following steps: constructing an SELPFormer lightweight Transform segmentation model, introducing Lite-PPM, SCSE and ELA feature enhancement modules and a lightweight decoder on the basis of SegFormer, and outputting a rural residential spot pixel level extraction result for regional scale rural residential spot mapping.

The application discloses a centrifugal pump volute flow channel parameter optimization method and system, and relates to the technical field of industrial equipment digital optimization; the method comprises the following steps: based on volute structure data and mechanical seal installation data, the inner wall of the volute is partitioned and identified to obtain a sealing front area, a pressure transmission area and a flow discharge area; based on the sealing front area, the pressure transmission area, the flow discharge area, mechanical seal contact requirement data and target working condition data, contact control analysis is carried out to obtain contact control data; based on the sealing front area, the pressure transmission area, the flow discharge area, the contact control data and the volute structure data, flow channel adjustment item extraction is carried out to obtain regional adjustment data; based on the regional adjustment data, impeller outlet structure data, the contact control data and the target working condition data, flow channel sequence correction is carried out to obtain target flow channel parameters; the application can take into account the sealing working state and the target working condition requirement, and improve the pertinence and adaptability of centrifugal pump volute flow channel parameter optimization.

This application provides a method and apparatus for linking supplier profiles with procurement activities. The method includes acquiring multi-source heterogeneous data related to a target supplier from multiple data sources. Upon detecting a change in any data point within this heterogeneous data set, the method triggers a real-time recalculation of the target supplier's health score to obtain a real-time health score. This real-time health score is then used to determine and execute the control strategy for the target supplier within the procurement transaction system, thereby achieving dynamic control over procurement activities involving the target supplier. This method enables real-time supplier status awareness, constructs a hierarchical and categorized differentiated control system, effectively solves the problems of limited control methods and delayed risk response, and significantly reduces compliance and financial risks.

The long-distance tear injection device loaded on the unmanned aerial vehicle comprises a base, the base is fixedly connected to the top end bearing face of the unmanned aerial vehicle, a pressurizing injector is installed on the plate face of the base, a fixing support is installed at the side end of the pressurizing injector, and the pressurizing injector is installed on the fixing support. The pressurizing ejector and the base are limited and fixed through the fixing support, a long gun ejector head is installed at the front end of the pressurizing ejector, the rear end of the pressurizing ejector is detachably connected with a material pot, a pump is installed at the top end of the pressurizing ejector, the input end of the pump is communicated with the material pot through a hose, and the pump is connected with the material pot. And the output end of the pump is communicated with the pressurizing ejector. The pressurizing ejector is installed on the unmanned aerial vehicle, and the unmanned aerial vehicle approaches target personnel by means of maneuverability of the unmanned aerial vehicle and conducts non-fatal strike on the target personnel or areas, so that the target personnel or the areas lose resistance temporarily, and safety of handling personnel is guaranteed.

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

The invention discloses an intelligent forest stand parameter extraction system based on laser radar point cloud data, which belongs to the technical field of laser radar point cloud data processing and forest resource investigation and comprises a multi-scale point cloud preprocessing module, a semantic guidance depth segmentation module, an intelligent parameter calculation module and a self-adaptive quality optimization module. High-precision and high-reliability intelligent extraction of forest stand parameters is realized through deep learning semantic segmentation of a Transform architecture, parameter calculation of confidence coefficient weighting, uncertainty quantification of Monte Carlo sampling and adaptive quality optimization of closed-loop feedback, a deep coupling relationship is formed among modules, the segmentation confidence coefficient directly affects the parameter weight, and the reliability of the forest stand parameters is improved. The uncertainty index triggers closed-loop adjustment, the adjustment parameter is fed back to the front module, a closed-loop optimization path of preprocessing, segmentation, parameter calculation, quality evaluation, adaptive adjustment and reprocessing is formed, and the precision and robustness of forest stand parameter extraction under a complex forest stand structure are remarkably improved.

This invention belongs to the technical field of large-scale model retrieval result optimization, specifically involving a search relevance scoring optimization method and system based on a large language model. It constructs continuous search behavior data by collecting user search logs and segmenting them into sessions at time intervals; it uses a large language model semantic encoder to vectorize search requests and candidate results, and constructs feature vectors by combining interaction information such as click location and dwell time; it calculates an initial relevance score based on this, and further introduces a cross-request continuity coefficient to model the changes in user intent during multiple search processes; it incrementally updates the ranking scoring header parameters by filtering and enhancing positive samples and difficult negative samples, and by combining popular words and long-tail words for gradient accumulation in different channels; finally, it re-ranks and outputs the candidate results. This scheme achieves continuous optimization of search relevance scoring by combining continuous search behavior and multi-user feedback information.

The application provides a planet rover transfer device and a transfer characteristic test evaluation method, and belongs to the technical field of planet rover transfer and test. The planet rover transfer release device comprises a slow-release rope, a hanger, a swing rod and an attitude control rope. One end of the swing rod is rotationally connected to a side wall of a lander. The other end of the swing rod is provided with an attitude control hinge. One end of the hanger is connected to the attitude control hinge, and the other end of the hanger is connected to a rover. One end of the attitude control rope is connected to the lander, and the other end of the attitude control rope passes through the attitude control hinge. The slow-release rope is wound on a slow-release rope wheel. The slow-release rope wheel is arranged on the side wall of the lander. The slow-release rope is connected to the hanger. The device is mainly used for planet rover transfer device and transfer characteristic test.

This invention discloses a VETO detection method and system for shielding cosmic ray muons, specifically relating to the field of cosmic ray muon background shielding. The method includes acquiring response data output by an outer VETO detector within the current observation period; aggregating the response data according to response time order and spatial adjacency; identifying response groups corresponding to the same muon crossing; and outputting muon events. Based on the muon events, the first and last response times, cross-regional propagation order, regional response density, and crossing depth corresponding to each response group are extracted. Corresponding aftereffect markers are generated according to the combination relationships of these parameters. By generating aftereffect markers for muon events and expanding the regional rules, a constrained spatiotemporal correlation is formed between the delayed background and candidate events. Based on this, shielding, observation, and alerting processes are performed in layers, thereby relatively suppressing delayed pseudo-signals and mitigating dead-time diffusion caused by fixed windowing.

The application relates to the technical field of intelligent packaging equipment and industrial automation control, in particular to a multi-station collaborative control system of a bag feeding and vacuum packaging machine applying edge computing; the system is in communication connection with a field sensing network and a multi-spindle servo driving bottom layer of the bag feeding and vacuum packaging machine, and comprises an edge gateway gathering module, an edge collection module, a time sequence feature evaluation module, a scheduling decision module and a collaborative execution module; multi-dimensional working condition disturbance data and state fine adjustment request data are pulled in parallel, absolute local time stamps are added, target working condition feature sequences are generated, system time sequence entropy is calculated, and the remaining time window of a time sequence synchronization collapse boundary is predicted, thereby generating a computing power unloading and flexible yielding instruction or a rigid collaborative maintenance instruction, realizing multi-spindle motion curve order reduction adaptation and non-key task interruption, and avoiding time sequence disorder spreading into mechanical collision.

The application provides a multi-stage sludge screening device and a sewage treatment system. The device is used for screening sludge of a sewage treatment unit, and comprises a first number of first cyclones, a second number of second cyclones and a third number of third cyclones. The specification parameters of the first cyclones, the second cyclones and the third cyclones gradually decrease. The feed inlet of each first cyclone is used to receive sludge of the sewage treatment unit. The overflow outlets of the first cyclones are in communication with the feed inlets of the second cyclones. The underflow outlets of the first cyclones are in communication with a first pipeline. The other end of the first pipeline is in communication with a main pipeline. The overflow outlets of each second cyclone are in communication with the feed inlets of the third cyclones. The underflow outlets of each second cyclone are in communication with a second pipeline. The underflow outlets of each third cyclone are in communication with a third pipeline. The overflow outlets of each third cyclone are in communication with the main pipeline through a fourth pipeline. The multi-stage sludge screening device and the sewage treatment system can improve the performance of sludge and effectively improve the sewage treatment efficiency.

The invention discloses a vertical speed reducer shaft system connection optimization method, which constructs a closed-loop optimization method of'fault statistics, modeling simulation, coupling design and experimental verification '. The defects of the existing rigid flange and the plum coupling are fundamentally positioned and overcome. The fault statistics in the step S1 provides actual data support for subsequent optimization, and blind design is avoided; the modeling simulation in the step S2 accurately determines a failure mechanism by comparing the states before and after improvement; coupling design in the step S3 is based on a failure mechanism, and optimization pertinence is ensured; and S4, verifying the effectiveness of the guarantee scheme through experiments. The overall method can remarkably reduce vibration transmission and stress concentration, improve the reliability of the vertical speed reducer and reduce the operation and maintenance cost.

The present application belongs to the technical field of inspection robots, and specifically discloses a track inspection explosion-proof robot monitoring system, which comprises a sliding groove, a support and a monitoring mechanism arranged on the support; the sliding groove is arranged on three sidewalls of a pipe gallery except the bottom; the support is in sliding connection with the sliding groove; the support comprises two vertical rods and a horizontal rod; the two ends of the horizontal rod are rotatably connected with the top of the two vertical rods; the vertical rods and the horizontal rod are telescopic; the bottom of the vertical rod is provided with a moving part for controlling the movement of the vertical rod along the sliding groove; the monitoring mechanism is connected with a track wheel; the vertical rods and the horizontal rod are provided with tracks which are in communication with each other on the sidewalls in the pipe gallery; the monitoring mechanism is connected with the tracks through the track wheel; and the track wheel is connected with a power source for controlling the movement of the track wheel along the tracks. By using the sliding groove and the support, the movement of the monitoring mechanism along the sliding groove is controlled, and the monitoring mechanism can move on each side rod of the support, so that the monitoring of each direction and different height positions in the pipe gallery is realized.

The invention discloses an intelligent question-answering and business guidance system for multi-modal interaction in the electric power field, relates to the technical field of electric power intelligent operation and maintenance, and aims to solve the problems that the oil sludge content, the oil temperature and the oil level of an existing mineral insulating oil transformer are lack of collaborative correlation diagnosis, multi-modal interaction and operation and maintenance guidance are disjointed, and the operation and maintenance efficiency is poor. The system comprises a multi-modal data acquisition module, a data preprocessing module, a coupling diagnosis module, an intelligent guide output module and a business linkage module. The multi-modal data acquisition module is used for acquiring multi-source data of the oil-immersed transformer, and the multi-source data comprises infrared thermal imaging data, oil level gauge image data, oil sampling image data and voice questioning data. The method has the advantages that fault multi-dimensional accurate diagnosis, multi-mode smooth interaction and customized operation and maintenance guidance are realized, and the operation and maintenance accuracy and efficiency of the transformer are improved.

The application discloses an online battery thermal runaway early warning method and system based on electrochemical impedance spectrum (EIS) parameter extraction. The method comprises: an experimental device and method for EIS key parameter extraction for battery thermal runaway early warning, the experimental device comprises: a battery, a chamber capable of providing an adiabatic environment, a battery testing device, an EIS online acquisition device and a host computer, the parameter extraction method comprises a feature importance analysis algorithm and a sensitivity analysis algorithm; the thermal runaway early warning system comprises: a battery, an EIS online acquisition device and a host computer; the thermal runaway early warning method issues a first-level thermal runaway early warning when the battery temperature exceeds the upper limit of a thermal management threshold, issues a second-level thermal runaway early warning in a battery self-heating temperature interval, and issues a third-level thermal runaway early warning when the battery voltage drops according to the extracted thermal runaway early warning key parameters.

The embodiment of the specification discloses an offline intelligent wearable device NFC service processing scheme. Including: controlling the NFC card reader on the offline intelligent wearable device to be in a closed state; receiving an NFC service trigger instruction; entering a designated service application, and automatically switching the NFC card reader from the closed state to the open state through the designated service application; reading target information from a target NFC device through the NFC card reader in the open state, and writing user information of the offline intelligent wearable device to the target NFC device, so that the target NFC device interacts with the service end of the designated service application according to the user information, and executes corresponding target service; according to the target information, a short-distance wireless communication connection is established with the target NFC device, and the execution result of the target service returned by the target NFC device is received, wherein the maximum communication distance corresponding to the short-distance wireless communication connection is greater than the NFC communication distance of the target NFC device.

The application discloses a kind of logistics exception work order processing method, device, equipment and storage medium, for the abnormal work order that appears in logistics distribution, so that the problem that logistics order cannot be normally completed distribution, by obtaining the trigger event of work order exception, the trigger event is classified and stored, and the exception work order dataset is obtained;According to the single rule of pre-configuration, the exception work order in exception work order dataset is distributed, so that exception work order is handled;And real-time update the processing state of exception work order, configure query interface, for user to obtain the relevant information of exception work order.It is convenient to analyze the reason of exception work order distribution failure, to carry out targeted improvement, improve the processing efficiency of exception work order.

The application discloses a new low-carbon city carbon emission collaborative prediction method and system based on digital twinning, relates to the technical field of low-carbon city carbon emission prediction, and comprises the following steps: constructing a city multi-source carbon emission data access channel, collecting dynamic streaming data and static benchmark data to form an original data lake, generating normalized carbon emission element data set through standardization cleaning and space-time alignment, and driving a city-level digital twinning basic model to generate a twinning body real-time state sequence. Through the improved attention fusion algorithm introducing a learnable collaborative adjustment factor, an adaptive bias term and a cross-head attention interaction layer, multi-dimensional collaborative features are extracted, a carbon emission collaborative prediction model is used to output multi-time point prediction results, the results are fed back to the digital twinning model to carry out prediction scenario virtual deduction, and a prediction verification closed loop is formed. The method optimizes carbon emission feature extraction and prediction verification process, and improves the accuracy and rationality of city carbon emission collaborative prediction.