78results about How to "Efficient collaboration" patented technology

The invention discloses a multi-bus decoupling distributed embedded hardware rendering architecture, system and method, and relates to the technical field of ultra-high-definition video hardware processing, and the key points of the technical scheme are that the architecture comprises a multi-bus decoupling module which comprises a plurality of hardware buses which are physically isolated from one another, each hardware bus is an exclusive hardware transmission link bearing a single-type manufacturing task; the modular processing unit is an independent hardware board card and is integrated with an external signal input port, an upstream bus signal input port and a downstream bus signal output port; the plurality of modular processing units are cascaded in sequence through a hardware bus in the multi-bus decoupling module to form a distributed assembly line rendering link; when the modular processing units are newly added, the signal processing capability and the rendering synthesis capability are linearly improved along with the increase of the number of the modular processing units. According to the invention, the problem of performance bottleneck of the traditional architecture in processing 4K / 8K ultra-high-definition and multichannel rendering is fundamentally solved.

The invention relates to a digital twin-driven distributed warehousing system and method, and belongs to the technical field of intelligent logistics. The system comprises a sensing execution layer, a network transmission layer, an edge computing layer, a cloud platform layer and an application service layer. The method comprises the following steps: acquiring storage physical entity data through a perception execution layer; the data is transmitted to the edge computing layer and the cloud platform layer through the network transmission layer; in the cloud platform layer, a high-fidelity virtual warehouse is constructed and synchronized through a digital twin engine; using a multi-agent reinforcement learning algorithm to perform centralized training in a digital twin environment to generate a distributed cooperative scheduling strategy; and issuing the strategy to an edge computing layer and a sensing execution layer, and driving an autonomous mobile robot cluster to execute a cooperative task. According to the invention, step-type improvement of the warehousing system in flexibility, intelligence and cooperative capability is realized, and the problems of rigid bottleneck, non-optimal decision and low cooperative efficiency of a traditional system are solved.

The invention relates to the technical field of medical instruments, and particularly discloses a multifunctional medical physiotherapy robot which comprises a cabinet, an operation screen and a six-axis robot, and a quick-change base is mounted on an output shaft of the six-axis robot. The core is that the quick-change base can be quickly detached and provided with four functional modules, namely a low-frequency pulse spray massage head, a radio frequency thermal therapy massage head, a shock wave massage head and a negative pressure massage head. Each massage head is connected with the execution end through a structure comprising a flexible connecting piece so as to adapt to the curved surface of the human body and compensate motion errors. Through the quick change mechanism and the central control system, integration and programmed collaborative application of multiple advanced physiotherapy technologies on one device are achieved, the problems that an existing device is single in function and poor in collaboration are solved, and the device has the advantages of being accurate in treatment, convenient and fast to operate and wide in adaptation disease range.

This utility model relates to the field of food processing equipment manufacturing technology, and in particular to a composite motion drive mechanism for a gluten roll winding device, which consists of a torque output unit and a drag force output unit. The winding assembly performs circumferential rotation under the drive of the torque output unit; the unloading cylinder, driven by the drag force output unit, completes axial reciprocating movement, causing the formed gluten to detach. The drag force output unit uses a transmission shaft as its power source, and through the cooperation of a cam mechanism, a multi-component transmission mechanism, a rocking component, and an elastic reset component, converts the power into the reciprocating rocking motion of the rocking component, thereby driving the unloading cylinder to move synchronously. Thus, on the one hand, the composite motion drive mechanism has a relatively simple design structure, and thanks to the operating characteristics of the cam mechanism, the unloading cylinder can achieve non-rigid unloading force application; on the other hand, by adjusting the contour curve of the cam mechanism and the parameters of the multi-component transmission mechanism, and with the assistance of the elastic reset component, the gluten roll winding device can adapt to various unloading requirements.

The application provides an edge device-oriented lightweight multi-modal early gastric cancer collaborative auxiliary diagnosis system, which comprises a lightweight multi-modal classification module, a decision-level fusion unit, a first feature extraction network and a second feature extraction network; the decision-level fusion unit is used for evidence theory fusion of first classification probability and second classification probability, and outputs a multi-modal classification result; a lightweight segmentation module is constructed based on an encoding-decoding structure, an encoder of the lightweight segmentation module comprises a plurality of stacked lightweight bottleneck modules, a feature enhancement module is arranged in a skip connection of the encoder, and the feature enhancement module is used for pixel-level lesion segmentation of a white light endoscopy image; a gating cooperation unit is connected with the lightweight multi-modal classification module and the lightweight segmentation module respectively, and is used for generating a gating signal according to the multi-modal classification result; when the multi-modal classification result is positive, the lightweight segmentation module is activated to perform a segmentation task; and when the multi-modal classification result is negative, a subsequent segmentation process is terminated.

The invention relates to a module cooperative control method and device for an intelligent charging pile and electronic equipment, and the method comprises the steps: obtaining a cable state signal which at least comprises a cable position signal and a wire reel rotation signal; receiving a charging process signal transmitted by the charging module in real time, wherein the charging process signal at least comprises charging power data and a fault state signal; generating and outputting a motor control instruction and a charging control instruction according to the cable state signal and the charging process signal; when it is judged that the cable reaches the limit position according to the cable position signal or the cable winding and unwinding length calculated according to the electric wire reel rotating signal is abnormal, a motor control instruction used for stopping the cable winding and unwinding action and a charging control instruction used for interrupting the charging process are synchronously generated. According to the invention, cable physical state monitoring and charging process safety control can be fused, and the problem of systematic cooperation failure caused by information barriers and response splitting between modules is solved.

The embodiment of the invention provides a cross-forward isolation data comparison system, method and device, a medium and a product, and relates to the field of data synchronization and verification. The system comprises a first agent which is deployed in an intranet and accesses a source end database through a database connection protocol; the second agent is deployed in an external network and establishes one-way communication connection with the first agent; the first agent is also used for transmitting the source end data of the source end database to the second agent through the forward isolation device through the one-way communication connection; and the comparison service is deployed in an external network, pulls the source end data from the interface of the second agent, and performs comparison operation on the source end data and the target end data. According to the method provided by the invention, the technical problem of data comparison in a cross-forward isolation scene is solved through the design of a double-agent architecture and a user-defined protocol, the security and reliability of data comparison are realized, and efficient and secure data comparison in a strict network isolation environment is realized.

High-performance P(VDF-TrFE) based composite film and preparation method thereof, and nanogenerator containing the composite film, the present application relates to piezoelectric composite material technical field, specifically relates to a kind of P(VDF-TrFE) / ZnO / CMWCNTs composite film and preparation method thereof, and piezoelectricity / friction electricity nanogenerator containing the composite film;The composite film is P(VDF-TrFE) / ZnO / CMWCNTs composite film, with P(VDF-TrFE) copolymer mass as benchmark, the addition amount of each component is as follows: P(VDF-TrFE) copolymer: TrFE molar content is 30%;ZnO nanoparticles: mass fraction is 0.36~1.80%;CMWCNTs: mass fraction is 0.01~0.03%;Overcome the technical defects, such as filler ratio out of control in existing P(VDF-TrFE) composite system, process parameter is not clear, piezoelectric property is low, and the output performance of nanogenerator based on it is poor, and stability is insufficient.

This invention provides a system for real-time dynamic adjustment of grouping across devices, including an identity authentication module, a distributed synchronization module, a rule engine module, a trigger engine module, and an algorithm engine module. These modules are coupled and interact through standardized data interfaces. By establishing a three-element association relationship between users, devices, and groups, unified management and authentication of user identities are achieved in a multi-device environment. A dynamic adjustment strategy is employed to achieve static allocation and dynamic adjustment of user permissions. Multi-dimensional grouping rules are formulated to filter users meeting certain conditions into the same group. A multi-dimensional trigger strategy is used to dynamically adjust groups. Intelligent calculation and optimization of dynamic grouping are performed based on the K-means clustering algorithm combined with a greedy strategy. Data synchronization between devices is achieved based on a distributed architecture, enabling real-time dynamic adjustment and efficient collaboration of grouping across devices.

The invention discloses a TEMPO-CNT composite membrane based on layer-by-layer assembly, a preparation method and application, and belongs to the technical field of preparation of electrochemical wastewater treatment materials. According to the composite membrane, a layer-by-layer assembly process is adopted, a carbon-based conductive adsorption layer and a TEMPO catalytic function layer are sequentially constructed on a substrate layer, and an ordered layered structure is formed. According to the structure, the high specific surface area and conductivity of the carbon material are fully reserved, TEMPO active sites are uniformly exposed, and efficient cooperation of pollutant adsorption and electrocatalytic degradation is achieved. The composite membrane prepared by the invention can be adapted to various electrochemical systems such as direct current and alternating current (pulse), trace organic pollutants in wastewater can be efficiently removed with low energy consumption by applying corresponding voltage, and the composite membrane has the advantages of flexible operation, wide application scene, good environmental compatibility and the like.

The invention is suitable for the technical field of vehicle dynamics, and provides a physical constraint fused amphibious vehicle dynamics parameter dynamic identification method, which comprises the following steps: carrying out working condition identification according to a key state quantity to obtain a working condition classification result; based on a working condition classification result, a neural network model is adopted to learn dynamic parameter related characteristics from the state data after working condition classification; based on the amphibious vehicle dynamics model, constructing a loss function fused with a physical mechanism, and combining boundary condition loss, initial condition loss and data interior point loss to obtain a weighted loss function fused with physical constraints; and back propagation is carried out based on a weighted loss function, parameters of the neural network model and vehicle kinetic parameters are optimized, and dynamic identification of the kinetic parameters is realized. According to the invention, the working condition identification precision of the vehicle in various complex operation scenes on land and on water can be improved, and the dynamic identification of the kinetic parameters of the vehicle in various complex operation scenes on land and on water can be realized.

The invention discloses an image segmentation method, device and equipment, a medium and a product. The method comprises the steps of obtaining image segmentation prompt information in response to an image segmentation prompt information input operation for a first image; the image segmentation prompt information and the first image are input into a pre-trained image segmentation model to obtain a first image segmentation result, the first image segmentation result is displayed, the image segmentation prompt information comprises at least one of point prompt information, smearing prompt information and geometric prompt information, and the smearing prompt information comprises at least one of the point prompt information, the smearing prompt information and the geometric prompt information. The pre-trained image segmentation model is obtained by training a sample image, sample image segmentation prompt information and a sample image segmentation result. According to the technical scheme, the problem that the accuracy and efficiency of current image segmentation need to be improved is solved, image segmentation can be carried out by combining the model with the manual operation prompt information, the efficiency and accuracy of image segmentation are improved, and efficient cooperation of the model and manual operation is achieved.

The application discloses a kind of robot post-disaster rescue collaboration methods based on deep learning and large language model, by introducing " reflection mechanism " in natural language processing, realize task semantic analysis, dynamic optimization and adaptive scheduling.Large language model generates task semantic graph and combines reinforcement learning to adjust priority in real time, form closed-loop task reflection and optimization process, greatly improve the flexibility and adaptability of robot in complex environment.Design " distributed perception bridge " module, through attention mechanism dynamic screening and sharing key perception data, realize the efficient cooperation of heterogeneous robot, even in the condition of unstable communication still can guarantee rescue efficiency.Based on the reinforcement learning model driven by environmental characteristics, real-time perception of physical properties such as fragment density and slope, optimize behavior strategy, improve the generalization ability and robustness of model.Through " force-semantic coupling " motion planning, dynamically adjust the operation path and force of manipulator, improve the success rate of complex task.

This disclosure relates to parallel inference methods, apparatuses, devices, and media for multiple LoRA large models, and pertains to the field of deep learning technology. By adding a dedicated process for the LoRA model, it achieves decoupling and separate management from the original large model process at the process level. At the system architecture level, it realizes isolation and parallel computing of the basic large model and multiple LoRA models in terms of computing and storage resources. Compared with traditional methods that deploy the large model and LoRA models on the same device, this disclosure can deploy more LoRA models and improve inference concurrency. Before each iteration of inference, the metadata data is synchronized within the LoRA process group, and the input data is controlled to be broadcast only within the large model process group, avoiding communication and storage redundancy caused by broadcasting input data to the LoRA process and optimizing preprocessing efficiency. By separating the LoRA process and the large model process for parallel operation, efficient separation and collaboration of inference are achieved.

The utility model discloses a kind of Dulong Chishao cultivation devices, it is related to Chishao cultivation technical field, support frame, two symmetrical distribution's watering direction adjusting parts are installed on the support frame, two watering direction adjusting parts are all rotationally connected with reagent spraying part, one end of two reagent spraying parts close to support frame is hinged with support frame, and another end of two reagent spraying parts is all installed with multiple atomizing nozzles.The Dulong Chishao cultivation device is synchronous with soil loosening shovel to complete soil loosening operation, and the contact pressure of linkage plate and ground is automatically triggered baffle displacement by mechanical transmission, so that the seed tank bottom seed hole is accurately opened and closed, and vibration during soil turning shovel operation is used to realize automatic seed sowing;Reset spring is immediately reset to close seed hole when stopping moving, to form the closed loop operation system of soil turning-sowing-stopping, which not only avoids seed waste, but also ensures the unity of sowing depth and soil turning effect, significantly improves the standardization degree of Chishao planting.

The invention relates to the technical field of unconventional oil gas and geothermal resource development, and particularly discloses a self-propelled jet drilling and instant gas fracturing integrated system and method.The system comprises a ground supply and control unit, a continuous pipe and a jet fracturing drill bit assembly connected to the tail end of the continuous pipe; the jet fracturing drill bit assembly comprises a high-pressure gas channel, an annular cavity, an axial nozzle and a radial nozzle, and the annular cavity is divided into a proppant cavity and an instant pulse fracturing cavity through an annular sliding block. The method comprises the steps of periodically circulating axial drilling, radial fracturing and propping agent injection. According to the method, fusion of drilling and fracturing in time and space is achieved, drilling energy is converted into fracturing energy in situ, an enhanced shaft wrapped by a continuous'fracturing ring 'is formed, and the method has the outstanding advantages of being simplified in procedure, short in operation period, high in energy utilization rate and continuous and uniform in reservoir transformation.

The invention discloses a convenient low-consumption tailings treatment system, and relates to the technical field of tailings comprehensive utilization, the convenient low-consumption tailings treatment system comprises a dressing plant, the dressing plant is connected with a tailings concentration device body through a self-flowing pipeline, and the lower end of the tailings concentration device body is connected with a first valve and a second valve through tailings pipelines; a stirring barrel is connected to the lower portion of the first valve, the tailing concentration device body is connected with an overflow pool through an overflow pipe, and a water return pipeline connected with a dressing plant is arranged on the left side of the overflow pool. The problems that in a traditional ore dressing plant tailing treatment and underground filling station, an independent or semi-independent system is usually adopted, tailings are firstly conveyed to a large ore dressing plant concentration well to be concentrated and precipitated, then sand is taken from the large ore dressing plant concentration well through a filling station, multiple times of pumping, concentration and stirring are needed, energy consumption is high, investment is large, operation cost is high, and management is complex are solved. Overflow water cannot be recycled nearby, and environmental protection risks exist.

The invention discloses a large-size carbon fiber prepreg sheet adsorbing and transferring tool and a using method. The large-size carbon fiber prepreg sheet adsorbing and transferring tool comprises a truss, and a plurality of sets of independent vacuum suction cup devices are arranged on the truss in the length direction at intervals; transfer trolleys are arranged at the two ends of the truss and drive the tool for adsorbing the material pieces to move. A lifting device is arranged between the truss and the transfer trolley, and the truss moves up and down relative to the transfer trolley under the action of the lifting device; a plurality of visual positioning assemblies are arranged on the truss in the length direction at intervals and used for adjusting the adsorption position between the tool and the material piece. The tool can replace manual material piece carrying, all assemblies are clear in labor division and efficient in cooperation, the vacuum suction cup device is independently controlled, guide rods of the lifting device are guided, real-time feedback of visual positioning is achieved, it is ensured that the tool runs stably, adsorption is firm, transferring is accurate, the tool can be stably matched with the prepreg transferring procedure in large carbon fiber piece production for a long time, and the production efficiency is improved. The practicability is high; the deformation of the material sheet is greatly reduced, and the production efficiency is improved.

This invention discloses a method and system for joint advanced prediction and detection of tunnel face and borehole ground-penetrating radar. It mainly includes: developing an integrated host for tunnel face and borehole ground-penetrating radar, achieving joint data acquisition from both; utilizing the tunnel face ground-penetrating radar to emit electromagnetic waves, with one antenna of the borehole radar emitting electromagnetic waves, and the other antenna of the borehole radar and the tunnel face ground-penetrating radar receiving the electromagnetic waves. This application designs a joint observation system for tunnel face ground-penetrating radar and borehole radar, achieving omnidirectional, multi-angle ray coverage and increasing the amount of observation data; deriving calculation formulas for tunnel ground-penetrating radar forward modeling, the adjoint state method, the objective function, and the inverse error function, achieving full waveform inversion of tunnel ground-penetrating radar; and enabling near-three-dimensional fine detection and imaging of adverse geological bodies such as karst caves and fractured bodies in front of the tunnel face.

The utility model relates to the technical field of equipment coordination, and discloses a multi-equipment coordination control system, which comprises user equipment and a server, and is characterized in that the user equipment comprises main control equipment and at least one coordination equipment, and the main control equipment is connected with the coordination equipment in a wired or wireless manner; the server establishes communication connection with the main control equipment; the main control equipment comprises a first communication interface, a first processor and a first storage module; the cooperative device comprises a second communication interface and an execution module. According to the utility model, through optimizing the communication interface design of the master control device and the cloud instance, the efficient and stable client device cluster physical networking topology is constructed, the hardware module layout is innovated, and the hardware-level security protection structure is strengthened; the problems of unstable equipment connection, poor module collaboration, weak safety protection and the like in the system structure level in the prior art are solved, dynamic permission adjustment, intelligent task allocation and automatic switching after main control equipment fails are realized, and the performance and reliability of multi-equipment cooperative control are improved.

The application provides an electric core lower surface protection film rolling mechanism, which comprises a rotating disc film pasting platform, a first protection film pressure rolling assembly, a first XYZ driving module and a second carrying manipulator. The rotating disc film pasting platform integrates an electric core adsorption platform, a protection film adsorption platform and a first lifting driving module for driving the electric core adsorption platform to lift. When rolling, the second carrying manipulator adsorbs and fixes the electric core, the first lifting driving module drives the electric core adsorption platform to lower to avoid, and the first XYZ driving module drives the first protection film pressure rolling assembly to execute rolling on the lower surface of the electric core in the free space. Through dynamic lowering of the electric core adsorption platform, the space interference between the bearing structure and the pressure rolling assembly is completely eliminated, the pressure rolling assembly completely covers the lower surface of the electric core (including the edge area), and the rolling blind area is avoided.

This application discloses an artificial intelligence-based dynamic scheduling method and system for logistics transportation, relating to the field of artificial intelligence technology. It addresses the technical problem that existing technologies often rely on fixed rules based on experience or simple optimization algorithms, which become rigid in complex and dynamic real-world environments, unable to make forward-looking and global trade-offs, leading to low efficiency in transportation scheduling methods. The method obtains a dynamic scheduling knowledge graph by processing and integrating multimodal transportation data; optimizes the dynamic scheduling knowledge graph to obtain an optimized scheduling instruction set, and constructs a dynamic scheduling knowledge graph that transforms fragmented static information into a semantically related global dynamic relationship network, providing a panoramic and structured situational awareness foundation for decision-making. Based on this knowledge graph, rolling optimization scheduling is performed using an artificial intelligence model, enabling the learning of complex relationships, prediction of dynamic changes, and global trade-offs and adaptive decision-making, thereby improving the efficiency of transportation scheduling methods.

The application discloses a kind of off-site computing power dynamic collaborative optimization methods based on multi-agent reinforcement learning, including the following steps: constructing resource topology diagram;Based on resource topology diagram, get node-level state feature vector and system-level state feature vector;Multi-agent environment is constructed;Local observation, global information and agent action set are input into improved CTDE model, output policy network parameters and value network parameters and construct training batch;Based on training batch, get converged policy network parameters and converged value network parameters;Get execution result;Obtain dynamically updated policy network parameters and dynamically updated value network parameters, realize the dynamic collaborative optimization of task acceptance, resource allocation, task migration, replica start-stop and bandwidth matching.

The invention discloses a wafer microscopic detection system, relates to the technical field of wafer detection, and aims to solve the problems of low efficiency, easy misjudgment and easy secondary damage of a wafer in traditional detection. The system comprises a workbench, a mechanical arm is arranged on the workbench, and a suction cup is arranged at the end of the mechanical arm; a wafer classification bin, a macro detection device, a micro detection device and a recognition device are further arranged on the workbench, and all the devices are located in the motion path range of the mechanical arm. Wherein the wafer classification cabin comprises a plurality of wafer cabins and is used for storing wafers of different types and states; the recognition device comprises an image acquisition fixing frame, image acquisition equipment and a light source; the macro detection device comprises a rotating device and an image acquisition device, the rotating device is provided with a drivable clamping plate with a wafer positioning groove, and the image acquisition device is arranged on a wafer rotating path; the micro-detection device comprises a three-dimensional moving platform and a microscope. The three-dimensional moving platform is used for moving the wafer between the rotating device and the microscope. The system realizes automatic and efficient wafer detection, improves the detection precision and efficiency, and reduces the wafer damage risk.

The application provides an industrial asset space-time trajectory tracking method and system based on multi-source heterogeneous positioning data fusion. Among them, the edge node on the industrial asset collects multi-source heterogeneous asset positioning data to infer signal propagation path, extracts the geometric characteristics of the terrain reflecting surface and selects the polarization direction of the LoRa and satellite communication link; the edge node is divided into a federal learning group according to the geographical area, the positioning data is transmitted in the group through the polarization direction, the space-time feature segment of the industrial asset trajectory is generated, and is broadcast to the adjacent federal learning group; according to the space-time feature segment broadcast by the adjacent group, combined with the signal coverage blind area information, the topological extension is carried out on the broken area of the cross-group trajectory, and a continuous trajectory prediction path is generated; based on the signal attenuation difference of different terrain areas, the continuous prediction path is integrated, and a space-time trajectory tracking strategy is generated. The technical scheme provided by the application improves the reliability of industrial asset trajectory tracking in complex terrain.

The application discloses a data communication method and device based on a core isolation architecture, equipment and a medium, and belongs to the technical field of multi-core heterogeneous data communication. The method comprises the following steps: acquiring uploaded data packets through a first data processing core, classifying each data frame according to an instruction type identifier and a file type identifier configured for each data frame, writing an instruction frame carrying the instruction type identifier into a high-priority queue, and writing a file frame carrying the file type identifier into a low-priority queue; reading the instruction frame in the high-priority queue through a second data processing core and sending the instruction frame to an embroidery machine; and when it is determined that the high-priority queue has been emptied, reading the file frame in the low-priority queue and sending the file frame to the embroidery machine. Through the core isolation architecture between the first and second data processing cores, the application not only meets the quick response requirement of the control instruction frame of the embroidery machine, but also meets the efficient transmission requirement of the file frame, and can adapt to the operation requirement of the high-precision and high-efficiency embroidery machine.

The invention provides a design method and device for an aviation airborne porous system complex flow channel shell part, and belongs to the field of aviation hydraulic pressure. The method comprises the following steps: generating an arrangement scheme of internal interfaces; on the basis of the arrangement scheme, a flow channel space path and corresponding geometric parameters are generated through a path planning algorithm; the runner space path is processed on the basis of a geometric processing rule corresponding to the manufacturing process type, and an initial hole system structure blank is formed through a feature modeling algorithm on the basis of the geometric parameters and the processed path; performing performance prediction, manufacturability rule examination and geometric envelope analysis on the initial hole structure blank to obtain evaluation data; based on the evaluation data, generating an adjustment suggestion for the arrangement scheme of the internal interface through a second artificial intelligence model; updating the arrangement scheme of the internal interfaces according to the adjustment suggestion to obtain a convergent hole system structure blank; and outputting a shell part design result. According to the method and device provided by the invention, intelligent optimization design of the aviation porous runner shell can be realized.

The invention discloses a self-adaptive segmental beam bridge girder erection machine compatible with multi-span combination and a construction method thereof, and the bridge girder erection machine comprises a main beam which comprises two truss beams and two end transverse bracings; the cross section of the truss girder is triangular, and the truss girder comprises connecting sections arranged at the two ends and a plurality of standard sections arranged between the two connecting sections. A longitudinal moving rail is fixedly arranged at the upper end of the truss girder in the length direction; the front supporting leg and the rear supporting leg are detachably arranged at the two ends of the bottom of the main beam respectively. The middle supporting leg is arranged at the bottom end of the main beam and is arranged between the front supporting leg and the rear supporting leg; the number of the middle supporting legs is at least four, and the middle supporting legs are used for supporting the main beam and / or driving the main beam to walk and move in the construction direction; the two lifting crown blocks and the two auxiliary crown blocks are arranged at the upper end of the main beam through longitudinal moving rails and can move front and back in the construction direction. And the two hoisting crown blocks are arranged between the two auxiliary crown blocks so as to cooperatively finish hoisting of a plurality of segmental beam blocks. According to the bridge girder erection machine, self-adaptive seamless switching of various complex hole span combinations can be achieved.

The application discloses a multi-unit cooperative action resource scheduling method and device, relates to the technical field of resource scheduling, and comprises the following steps: receiving an emergency rescue request containing an incident location and an event level, determining an initial task area and required resource types by matching with a scheduling case library; evaluating the health state and task load of available rescue units based on a resource state database, and then acquiring dynamic attributes and spatial position information of the rescue units; decomposing a rescue task in combination with the initial task area and unit information, generating a plurality of rescue sub-tasks which are functionally parallel or serial; assigning appropriate rescue units to each sub-task through a task allocation decision model and forming a task sequence; and finally, distributing the encrypted task sequence to corresponding units in a safe manner to execute rescue. Through the above method, the method realizes quick response, intelligent decomposition and efficient cooperation of the rescue task, and improves the timeliness, accuracy and overall rescue success rate of resource scheduling.

The application discloses a distributed energy storage regulation method and system based on edge computing and artificial intelligence, relates to the technical field of power system energy storage regulation and intelligent microgrid, and constructs a three-layer architecture of a sensing layer, a decision layer and a control layer: the sensing layer collects operation parameters of energy storage units, power grid state information and a clearness index; the decision layer is composed of an artificial intelligence prediction module and a global scheduling optimization engine, a random forest is used to select features and construct an RF-LSTM hybrid model to predict load power, a clearness index method is used to predict photovoltaic output power, a comprehensive objective function is constructed, and a global scheduling instruction is generated by solving through a particle swarm optimization algorithm; the control layer adopts an edge computing architecture, and energy storage unit collaborative regulation and an event triggering mechanism are realized through a local controller. The application realizes hierarchical scheduling of edge autonomy and global optimization, effectively improves prediction accuracy, voltage stability and economy, and reduces communication burden and network loss.