3248results about How to "Ensure consistency" patented technology

The invention discloses an agent task scheduling planning method, and relates to the technical field of agent scheduling. The method comprises the steps of analyzing a task instruction to generate atomic tasks capable of being independently executed, constructing a subtask dependency graph, and defining association constraints between the tasks; determining the real-time resource occupancy state of the intelligent agent to obtain a resource state tensor, completing resource-task association anchoring and dependency priority ranking in combination with the sub-task dependency graph, and generating a task priority sequence with resource constraint; performing dynamic capability matching and predictive load balancing calculation on the sequence through a task-agent adaptation model, and determining a target execution agent of each atomic task; and based on the target execution agent and the subtask dependency graph, performing time sequence scheduling arrangement and conflict resolution, and generating a collaborative execution scheme. The method improves the reasonability and efficiency of agent task scheduling, reduces resource conflicts and execution timeout risks, and is suitable for agent cluster collaborative scheduling in a complex scene.

The invention relates to the technical field of industrial vision and artificial intelligence, and discloses an aluminum coating formula prediction method and system based on industrial vision and double-model fusion. The method comprises the following steps: acquiring visible light and near-infrared band images of the surface of an aluminum material coating through multispectral image acquisition, identifying a defect area to generate a binary mask, extracting three types of features of color, texture and spectral reflection, and respectively inputting feature vectors into a random forest regression model and a convolutional neural network model to obtain a target image; and dynamically calculating a fusion weight according to the verification set error, and carrying out weighted fusion on the prediction results of the two models to generate a formula component content prediction value. According to the method, the technical problems of low precision, low efficiency and insufficient generalization ability of a traditional aluminum coating formula determination method are solved, and rapid and accurate prediction of the formula is realized.

The invention relates to a road infrastructure full-automatic inspection method, device and equipment based on an unmanned aerial vehicle group, and a medium thereof. The method aims at the problem that disease characteristics collected by unmanned aerial vehicles in traffic flow and vegetation shielding scenes are broken, and the method comprises the following steps of: decoupling texture and motion characteristics of a dynamic shielding area; feature maps of the effective area and the shielding area are separated; performing cross-frame splicing and continuous repair on the fracture features by using an optical flow constraint generation network, and reconstructing the geometric integrity of a shielded region; infrared data are fused to correct thermal deformation errors, and a high-precision continuous curved surface model is generated; and finally, based on a disease quantitative feature vector matching maintenance strategy, realizing full-process automation from data acquisition to decision output. According to the method, the continuous modeling precision and the maintenance decision reliability of pavement disease detection in the shielded environment are remarkably improved.

The invention discloses a heat supply network pipeline hydraulic and thermal working condition abnormal fluctuation intelligent identification and fault early warning method, and relates to the technical field of computer processing, and the method comprises the following steps: S01, collecting hydraulic and thermal parameters of a heat supply network pipeline in real time; s02, acquiring abnormal data of the time sequence sample set based on the thermodynamic mechanism model, detecting and repairing the abnormal data; s03, extracting characteristic parameters capable of reflecting abnormal fluctuation of the hydraulic and thermal working conditions of the heat supply network pipeline from the repaired time sequence sample set; s04, establishing an abnormal fluctuation identification model by utilizing an intelligent algorithm, and judging whether the hydraulic and thermal working conditions of the heat supply network pipeline have abnormal fluctuation or not; and S05, when the abnormal fluctuation is identified, giving a grading early warning mechanism and risk prevention and control suggestions of the damage degree grade of the associated pipeline. According to the invention, by fusing multi-source data and an intelligent algorithm, full-chain intelligent management of the hydraulic and thermal working conditions of the heat supply network pipeline from abnormal accurate sensing, fault intelligent diagnosis to risk active early warning is realized.

The invention belongs to the technical field of enterprise informatization management and big data integration, and particularly relates to an enterprise informatization management integration platform based on big data. Comprising an auditing element unified structured acquisition module, a main body unique identifier analysis and failure closed loop module, a caliber version and field mapping version joint locking module and an evidence index binding and consistency verification packaging module. The platform reads interface and field mapping from a service system log according to a configuration table, normalizes the interface and field mapping and writes the interface and field mapping into an event account book collocation state; executing main body gating on the original entry record to generate a main body identifier and writing back the main body identifier; when failure occurs, the reason code is written and blocked, and the failure evidence index is returned; performing node analysis on the aperture script and generating an aperture chain fingerprint; and serializing the event segments, calculating abstracts, constructing batch abstract roots, positioning first inconsistent serial numbers when recalculation is inconsistent, and scheduling and supplementary collection, so as to output a recheckable audit evidence packet. According to the invention, aperture consistency and evidence traceability can be realized.

The invention relates to the technical field of automobile part machining, and discloses an automobile part multi-station synchronous clamping and positioning device which comprises a support, a vertical plate is fixedly arranged in the middle of the support, the vertical plate is slidably connected with a plurality of sliding plates, a sliding seat is fixedly arranged on one side of each sliding plate, a baffle is arranged on one side of each sliding seat, and the baffle is fixedly connected with the support. Two sliding rods in sliding connection with the sliding seat are fixedly arranged on one side of the baffle, the surfaces of the sliding rods are sleeved with springs, and a first clamping plate is fixedly arranged at one end of each sliding rod; the single air cylinder drives the cross beam to synchronously push all the sliding plates, synchronous clamping of workpieces at multiple stations is achieved, the auxiliary clamping time is greatly shortened, the production efficiency is improved, the consistency of clamping actions of all the stations is guaranteed, and the problem of workpiece deformation or displacement caused by uneven clamping force is solved.

The invention discloses a preparation method of a high-stability photoresponse covalent organic framework membrane and application of the high-stability photoresponse covalent organic framework membrane in selective separation of multiple components. 4-azido azobenzene is prepared by carrying out azido reaction on 4-aminoazobenzene in an acidic aqueous solution, and then a BPTA-TAPB-COF membrane is used as a matrix to prepare the high-stability photoresponse covalent organic framework membrane. 4-azido azobenzene is efficiently grafted to the pore wall of the BPTA-TAPB-COF membrane through a click chemical reaction, the photoresponse covalent organic framework membrane is constructed, and the covalent organic framework membrane can be used for multi-component selective separation and is suitable for multi-component systems with different sizes. The azobenzene group in the pore channel of the prepared Azo-COF membrane is subjected to reversible cis-trans isomerization under the irradiation of ultraviolet / visible light, the response speed is high, and the cycle performance is good; the Azo-COF membrane has good application in the light-operated nanofiltration process, the performance of the Azo-COF membrane is not reduced after the Azo-COF membrane is continuously recycled for 12 days, and the structure of the Azo-COF membrane is kept stable.

The embodiment of the invention provides a client verification method and device and electronic equipment, and relates to the technical field of clients, and the method comprises the steps: obtaining a hardware fingerprint of a user terminal in real time under the condition that a verification probe is utilized to monitor a verification trigger event in the operation process of a client; under the condition that the verification trigger event is the first verification trigger event, obtaining a client identifier of the client; sending the hardware fingerprint of the user terminal and the client identifier of the client to a server, so that the server queries a historical binding fingerprint corresponding to the client based on the client identifier of the client, and verifies the hardware fingerprint of the user terminal based on the historical binding fingerprint of the client to obtain a first verification result; and receiving a first verification result fed back by the server. Therefore, the credibility requirements of various scenes on the client can be effectively met.

The invention relates to a credit distribution method in multi-agent cooperation, and the method comprises the following steps: obtaining joint data of a multi-agent system, the joint data comprising observation information and execution actions of each agent; the joint data are input into a discriminator model, and the discriminator model carries out modeling on an interaction dependency relationship among multiple agents based on an interaction dependency relationship modeling module of an attention mechanism; generating an auxiliary reward signal corresponding to each agent through a discriminator model; generating a fused reward signal based on the auxiliary reward signal and a global reward signal from the environment; and training and updating the multi-agent strategy model by using the fused reward signal so as to optimize the cooperation strategy of the multi-agent system. By introducing a credit distribution mechanism based on a discriminator model, automatic decomposition and optimization generation of individual reward signals are realized, so that the learning efficiency and stability of a multi-agent system in a complex cooperative task are remarkably improved.

The application provides a double-station worktable for CNC, and particularly relates to the technical field of CNC machine tool auxiliary equipment, and comprises a CNC main body, an inner platform and a tool head unit, and further comprises a double-shaft switching mechanism arranged between the outer side of the CNC main body and the inner platform, wherein the double-station worktable for CNC; the double-shaft switching mechanism composed of an X-axis displacement component, a Y-axis displacement component and a sinking fastening component is arranged, so as to solve the defects of the existing technology, such as the jamming misplacement caused by the single guide rail alignment of the multi-station switching, the lack of special connection structure, the non-separation of the carrier and the guide rail during the processing, the vibration transmission affecting the precision, and the like, to realize the cooperative action of the X-direction bearing movement of the jig table, the Y-direction smooth connection and the locking of the processing position sinking, and the double-station switching does not need complex debugging, so that the equipment downtime is greatly reduced, and the processing precision and stability are ensured.

The invention discloses a load-oriented self-adaption double-source waste heat mode switching control method, particularly relates to the technical field of industrial process control and waste heat comprehensive utilization, and aims to solve the problems that heat supply mode switching in an existing double-source waste heat system depends on artificial experience, waste heat supply cannot be matched in a self-adaption mode along with load change, and the working efficiency is low. The waste heat utilization rate is low, the heated load temperature fluctuation is large, and the operation stability is poor. A heat exchange topology model is established in a double-source waste heat system, a load heat demand track and a waste heat capacity fingerprint are synchronously constructed in a rolling time window, and a heat supply mode sequence is optimally selected by taking a load heat demand satisfaction degree, a waste heat utilization degree and a mode switching cost as indexes under an equipment operation constraint and a mode switching constraint. Therefore, the effects of automatically matching the heat load and the waste heat supply under the condition of dynamic change of the working condition and the load, giving consideration to temperature stability and efficient utilization of the waste heat, reducing manual adjustment and improving the system energy efficiency and the operation stability are achieved.

The invention discloses an image fusion method based on a double-branch feature decoupling auto-encoder, and belongs to the field of computer vision and image processing. According to the method, for the problems of modal pollution and structural distortion in infrared and visible light image fusion, structural semantic information and high-frequency texture details of a source image are extracted respectively by constructing a content feature coding module and a detail feature coding module, and feature decoupling is achieved. And performing deep fusion on the decoupled features by using an adaptive feature weighting mechanism, and reconstructing a fused image with infrared target saliency and visible light detail definition through a shared decoder. According to the method, an end-to-end two-stage training strategy is adopted for optimization, complex prior or post-processing is not needed, the effects of improving the fused image contrast, edge preservation and target recognition performance are remarkable, and the method is suitable for the fields of weak light monitoring, intelligent perception, unmanned system navigation and the like.

The invention provides a multi-band composite high-integration TR assembly. The multi-band composite high-integration TR assembly comprises a shell, a front multi-layer board, a back multi-layer board, a C / X / Ku band receiving and transmitting circuit, a C / X / Ku band single receiving circuit and a Ka band receiving and transmitting circuit, wherein the front multi-layer board and the back multi-layer board are connected in the shell, the C / X / Ku band receiving and transmitting circuit is connected with the front multi-layer board, and the Ka band receiving and transmitting circuit is connected with the back multi-layer board. The low-cost scheme design of an all-solid-state microwave multilayer board suitable for batch production and testing is adopted, ports and transmission line layout are reasonably designed, multi-band composite mode transmission is achieved in the form of the front face and the back face, a C / X / Ku-band transmitting circuit and an H-polarization receiving circuit are integrated on the front face, and the transmission efficiency is improved. A C / X / Ku frequency band V polarization receiving circuit and a Ka frequency band receiving and transmitting circuit are integrated on the reverse side, different functional circuits are respectively transmitted through a microstrip line and a strip line through an interface circuit structure covering 1-40 GHz and an in-board vertical transition structure, the isolation degree of different circuits is improved, mutual crosstalk between different signals is avoided, and the transmission efficiency is improved. And the functions of high integration, high consistency, ultra wide band, numerical control phase shift, numerical control attenuation and the like of the assembly are realized.

The present application relates to the technical field of laser processing, especially to a lock processing and cutting device, which comprises a machine table and a transfer module installed on the machine table; a laser head is fixedly installed at the end of the execution component of the transfer module; a conveying assembly for conveying a sheet is fixedly installed above the machine table; wherein a positioning assembly for side positioning of the sheet and a stop assembly for stopping the end of the sheet are installed above the machine table; through the synergistic effect of the positioning assembly and the stop assembly, the present application realizes accurate positioning of the sheet, effectively guarantees the cutting accuracy and consistency of the lock panel; secondly, the traditional bench type single piece processing is replaced by a pipeline type continuous operation; the conveying, positioning and cutting processes of the sheet can be seamlessly connected, the auxiliary time of equipment waiting and manual intervention is reduced, the production efficiency is greatly improved, the finished product and waste after cutting can be automatically separated along the pipeline, and the post-processing process is greatly simplified.

The invention relates to the technical field of antenna detection, in particular to a laser cutting antenna line type defective product detection method and system, and the method comprises the steps: obtaining processing batch information, building a coiled material motion coordinate system, and storing target antenna parameters and reference information of a dispensing region; acquiring image data of the antenna, and aligning the image data with the reference information in the coiled material motion coordinate system; extracting an antenna boundary according to the image data, and calculating a geometric deviation based on the antenna boundary and the reference information; obtaining a defect coordinate position according to the geometric deviation, and comparing the dispensing area with the geometric deviation to judge the severity of the defect; mapping the coordinate position to a coiled material motion coordinate system to obtain bad position data, and executing differentiation processing according to the severity; and storing the bad position data and the processing batch information corresponding to the differentiation processing, and generating a detection result. According to the invention, the antenna boundary and geometric deviation are analyzed through the image data and the reference information, defects in the antenna cutting process are identified, and the detection accuracy is improved.

The invention discloses a sedimentary facies model construction method and device, equipment and a storage medium. The method comprises the following steps: acquiring regional geological parameters of a target construction region; and determining structure interpretation data according to the regional geological parameters, and constructing a three-dimensional structure model according to the structure interpretation data. And analyzing distribution information of each lithofacies in the three-dimensional structure model according to regional logging data, and constructing a lithofacies framework model. A target sedimentary facies model corresponding to the target construction area is constructed according to the three-dimensional sedimentary point cloud and the lithofacies framework model based on a multi-point geostatistics algorithm, and the three-dimensional sedimentary point cloud is obtained by performing actual sedimentary simulation on the target sedimentary construction model obtained through pre-training based on the area geological parameters of the target construction area. According to the technical scheme, the three-dimensional sedimentary point cloud of the research area can be accurately extracted, high geological objectivity and physical authenticity are achieved, and therefore the objectivity and geological reliability of the sedimentary facies model are remarkably improved.

The invention discloses a multi-source geographic vector data matching method based on topological relevance, which comprises the following steps: collecting multi-source basic geographic vector data to form a preprocessed data set; constructing multi-index data quality evaluation based on local topological features; extracting and classifying spatial topological relation edges; constructing a weighted adjacent matrix of the target map; a neighborhood topology consistency measurement index is calculated, and neighborhood topology consistency quantization and adaptive weight fusion are carried out; establishing a global optimization objective function by taking the confidence coefficient matrix as input, solving a maximum weight bipartite graph matching problem with topology constraints by taking the topology retention rate as a hard constraint condition, and outputting a global optimal matching scheme; and constructing a quantitative evaluation index topology deviation measure based on topology invariant difference, judging whether a matching scheme has a significant topology conflict, and performing hierarchical repair according to the conflict condition. According to the method, the reliability and logic self-consistency of multi-source vector data fusion are improved, and the key problem of topological contradiction in the prior art is solved.

The invention provides a trajectory tracking control method and system for a high-load omni-directional AGV, the omni-directional AGV is driven by a plurality of steering wheel mechanisms which are independently steered and driven, and the trajectory tracking control method is characterized by comprising the following steps: acquiring vehicle state information and expected trajectory information of the omni-directional AGV in real time; on the basis of the vehicle state information and the expected track information, core parameters of a model prediction controller are optimized online through a chaos simulated annealing algorithm, and the core parameters comprise a state weight matrix, a control increment weight matrix, a prediction time domain and a control time domain; wherein the model prediction controller performs state prediction based on a longitudinal-transverse decoupling dynamic model adaptive to a high-load working condition; performing rolling horizon optimization through the model prediction controller by utilizing the optimized core parameters, and solving to obtain an optimal control increment; and converting the optimal control increment into a driving instruction for a multi-steering-wheel mechanism, and controlling the omnidirectional AGV to track an expected trajectory.

The invention relates to the field of numerical control machining and computer-aided manufacturing software, and particularly discloses a honeycomb core six-axis ultrasonic cutting track digital control and interpolation optimization system which comprises a track preprocessing module, a parameterized spline interpolation module, a six-axis linkage inverse solution module, a dynamic feed-forward compensation module, an ultrasonic energy adaptive control module and a multi-source information fusion and decision module. By the adoption of the technical scheme, smooth and efficient interpolation of a track, dynamic feed-forward compensation of motion errors and self-adaptive adjustment of cutting energy can be achieved, and therefore the machining precision, the surface quality and the system stability are improved. According to the invention, ultrasonic energy control is originally incorporated into an overall trajectory control closed loop, and real-time accurate regulation and control of cutting energy are realized through the ultrasonic energy adaptive control module. The module is based on force, amplitude, temperature and other multi-sensor information, adopts fuzzy reasoning to intelligently decide output power, and ensures that cutting energy is constant and optimal under different processing conditions.

The invention discloses a cross-temperature health state assessment method and system for an underwater robot battery, and relates to the technical field of battery health state assessment, and the method comprises the steps: S1, collecting data in the operation process of an underwater robot; s2, an environment temperature profile is constructed, and working condition types are identified; s3, constructing a multi-dimensional health feature vector; s4, constructing an LSSVM and SVR regression model, and optimizing model hyper-parameters; s5, calculating characteristic stability and comprehensive complexity indexes, and adaptively selecting a model; s6, identifying the working condition category of the charge-discharge cycle, extracting and standardizing the features, calling the adaptive model, iteratively outputting SOH estimated values, and splicing to form an SOH evolution curve; according to the cross-temperature health state evaluation method and system for the underwater robot battery provided by the invention, the problems of unstable cross-temperature performance and insufficient generalization ability in the prior art are solved.

The invention discloses an intelligent demand analysis and man-hour evaluation method and system, and belongs to the technical field of computer vision and artificial intelligence. Analyzing the multi-modal demand document containing the text, the picture and the table to generate structured demand data; based on the structured demand data and the system module description, performing module-level splitting on the demand to generate a module task set; retrieving an associated system implementation context for each task in the module task set based on a multi-dimensional knowledge base; fusing the structured demand data, the module task set and the system implementation context to generate a fine-grained technical task; based on a historical case index, calculating reference working hours for the fine-grained technical task; and cross-module cooperative correction and personalized correction based on the ability of the task executor are sequentially performed on the reference working hours to obtain final evaluation working hours, so that automatic deep analysis and accurate and personalized working hour evaluation of software requirements can be realized.

The invention provides a clothing pattern intelligent generation method and system based on multi-modal visual identification, and relates to the technical field of visual identification. The method comprises the following steps: firstly, acquiring clothing image data and text description data, performing unified preprocessing, obtaining a style category label, an appearance attribute label and a local contour key point set through multi-modal visual identification, generating structure semantic elements and geometric anchor points by utilizing a semantic-to-structure mapping knowledge base, and constructing a plate type structure diagram; further analyzing the structural constraint and executing constraint solution to generate a candidate pattern; and in combination with manufacturability verification and constraint correction, closed-loop optimization is formed, a target plate type file meeting the structure and manufacturing requirements is output, and effective connection from semantic recognition to plate type structure generation is realized.

The invention relates to the technical field of underground building foundation reinforcement and leakage prevention, in particular to an underground building foundation reinforcement and leakage prevention integrated device and method.The device comprises a movable rack, and a jolt ramming mechanism and an air drying mechanism are installed on the movable rack; the primarily-coated coating is impacted and compacted through the first compaction block and the second compaction block, the waterproof coating is powerfully pressed into holes in the inner wall of the foundation pit, a deeply-fused tight bonding layer is formed, and the interface bonding force and adhesive force between the waterproof coating and the inner wall of the foundation pit are greatly enhanced in the process; and the defect of insufficient bonding strength in the prior art is effectively overcome, so that the phenomena of peeling, cracking and overall falling of the waterproof coating in the later period are fundamentally prevented.

The invention discloses a multi-camera live broadcast stream pushing realization method and system, and relates to the technical field of artificial intelligence, and the method comprises the steps: calling a plurality of cameras to carry out the video collection of a current live broadcast scene, obtaining a plurality of video data, and distributing an independent thread for each camera; collecting audio data of the current live broadcast scene; encoding the audio data and the plurality of video data, and synchronizing the audio data and the plurality of video data based on a timestamp to obtain a plurality of audio and video data; and pushing the audio and video data to a live broadcast platform based on the independent thread. The problem that multi-camera live broadcast stream pushing cannot be realized in the prior art is solved.

The invention relates to the technical field of waste resource recycling and automatic processing, and discloses a waste household appliance disassembling process parameter adaptive control method and system, and the method comprises the steps: carrying out the registration fusion of multi-view surface data, and obtaining a complete point cloud model; identifying a high-deformation area based on curvature features and fitting cutting reference surface parameters; performing smooth adjustment on the reference plane parameters according to the pose difference of the adjacent areas to obtain a coordinated reference plane set; generating an initial compensation vector in combination with the discrete points of the cutting path, and correcting direction mutation to obtain a preliminary compensation instruction; and real-time cutting feedback data are collected in the disassembling process, if the machining state is abnormal, the compensation vector of the follow-up path is corrected, and a target self-adaptive control instruction is obtained. According to the invention, self-adaptive precise cutting of waste household appliance parts with complex deformation and uneven material characteristics can be realized.

The invention discloses a causal knowledge graph construction and question-answering system based on retrieval enhancement generation and a large language model. The system comprises a multi-source heterogeneous knowledge base construction module, a retrieval enhancement generation module, a named entity recognition and causal triple extraction module and a knowledge fusion reasoning module, according to the method, a high-quality named entity annotation data set and a causal data set are constructed, and normalization and integrity of input knowledge are guaranteed; a mixed retrieval strategy (keyword + vector + sparse embedding) is provided, and the evidence coverage rate and recall precision are improved. Under RAG driving, LLM is combined, two rounds of causal triple extraction are achieved, and the causal relationship coverage degree and the direction judgment confidence degree are improved; a conflict detection and atlas fusion mechanism is designed to ensure the unity and consistency of new and old causal knowledge; a question answering system based on a causal atlas is also established, multi-hop causal reasoning is supported, and answers with controllable credibility and explainable are output.

The application relates to the technical field of data analysis, and discloses a karst fissure identification-based open-pit mine blasting parameter optimization method and system. The method comprises the following steps: obtaining karst fissure distribution characteristic data through multi-source detection, establishing a three-dimensional fissure network topology structure, analyzing static breaking agent inflation stress propagation rules, performing multi-objective optimization solving based on stress propagation direction and intensity distribution to obtain an initial blasting parameter combination, and obtaining dynamic adjustment blasting parameters through real-time tracking and regulation according to fissure dynamic evolution in the blasting process. The application solves the problem that static blasting parameters cannot be real-time regulated according to the dynamic evolution state of the fissure network in the blasting process, resulting in deviation between the blasting effect and the expected target.

The application discloses a tunnel or mine gushing water space-time prediction method and system coupled with a water power numerical model, and the method comprises the following steps: based on the identified and verified underground water numerical model, outputting multi-source data, complementing the missing measured data, quantifying the difference between fault and normal stratum permeability characteristics and coupling to the data system, and incorporating the tunnel or mine excavation space data. An LSTM-isolation forest-K nearest neighbor regression coupled model is constructed, and a multifunctional module is configured to realize common training of multi-scene data. The pretreated multivariate time series data is divided into a training set and a test set, hidden features are extracted through the coupled model, abnormal detection results are fused, a residual correction model is trained synchronously, and the hyperparameters and weights are adaptively optimized according to the multi-project prediction error feedback. Based on the trained coupled model, a window rolling strategy is adopted to carry out synchronous gushing water space-time prediction, residual correction is combined, and prediction data meeting the engineering precision is output. Reliable technical support is provided for engineering construction safety control.

The application discloses a semiconductor flat-plate warehouse inserting and taking structure, which comprises an inserting and taking connecting frame, an inserting and taking arm and a self-adapting locking mechanism arranged on the inserting and taking arm. The self-adapting locking mechanism mainly comprises a straight-line transmission rod, a scissor type lifting amplification mechanism, a limiting pressing plate and a guiding reset unit. The core of the application is that the self-weight load generated during the inserting and taking of the flat-plate warehouse is used as a driving force. When the inserting and taking arm supports the flat-plate warehouse, the weight presses the straight-line transmission rod, forces the scissor type lifting mechanism to expand and drives the limiting pressing plate to stably move downwards, so that the positioning pin on the limiting pressing plate is inserted into the pin hole of the flat-plate warehouse, automatic locking and positioning are realized. After unloading, the mechanism is automatically reset under the action of the reset spring. The application does not need external power, realizes "inserting and taking to locking", can effectively inhibit the inertial swing and vibration during the carrying process, prevents the wafers in the warehouse from being damaged due to knocking and has the advantages of simple structure, reliability, safety and high positioning precision.

Embodiments of the application disclose a screw-based gesture recognition method and device, electronic equipment and a storage medium. A first key point position corresponding to a hand key point in a continuous frame image is detected. A three-dimensional coordinate of each hand key point in a corresponding first coordinate system is calculated. The first coordinate system is a three-dimensional coordinate system determined by adjacent key points away from the fingertips of the hand key point. The three-dimensional coordinates are input into a preset screw-based forward kinematics model to obtain a pose transformation set of the hand key point corresponding to each frame of image. According to the pose transformation set, a Jacobian matrix corresponding to each frame of image and a predicted three-dimensional coordinate corresponding to each hand key point are calculated, and a corresponding second key point position is calculated according to the predicted three-dimensional coordinate. The pose transformation set is optimized based on the positions of the key points and the Jacobian matrix. Parameters are output based on the optimized pose transformation set. The application ensures the consistency of the processing of the shapes of the front and back hands, thereby improving the accuracy of the processing results.