319 results about "System deployment" patented technology

The invention relates to the field of electronic communication, and provides a multi-protocol dynamic switching method and system based on an FPGA. The method comprises the following steps: carrying out regional division on an FPGA chip through a layout planning tool to obtain a static logic region and a plurality of reconfigurable logic partitions; performing hanging processing on the current protocol module based on the protocol switching trigger signal, and writing running state data of the current protocol module into a state cache unit to obtain protocol context snapshot data; according to the target protocol type, bit stream loading is carried out on the corresponding reconfigurable logic partition through configuration of an access port, and a reconfiguration protocol module is obtained; and reading protocol context snapshot data, and performing state recovery on the reconstruction protocol module to obtain a target protocol data path. According to the invention, rapid protocol switching is realized, the utilization rate of hardware resources is improved, and the system deployment cost is reduced.

The invention relates to the technical field of cables, and particularly discloses a cable terminal simulation and state evaluation method and system in a humid environment, multiple types of sensor arrays are deployed, distributed temperature and humidity sensors are installed at key parts of a cable terminal, and aiming at the technical problems of one-sided single-dimensional monitoring, simulation model solidification and insufficient static weight adaptation, the cable terminal simulation and state evaluation method and system are provided. Cooperative acquisition of multiple parameters such as temperature and humidity, partial discharge and corrosion current is achieved through deployment of multiple types of sensor arrays, the nonlinear interaction relation between humidity permeation and electric field distortion is dynamically reflected in combination with a multi-physics field coupling simulation model, the one-sidedness of single parameter monitoring is solved, and the risk misjudgment rate is reduced by 40% or above; a dynamic water film thickness model is adopted to update interface parameters of the sealing ring in real time, a simulation result is updated per hour in combination with a finite element-boundary element hybrid algorithm, an electric field distortion simulation error is controlled within 12%, and the simulation precision is improved by more than one time compared with a fixed boundary condition.

A robotic fleet resource provisioning system includes a computer-readable storage system storing a fleet resources data store and resource provisioning rules. The fleet resources data store maintains a fleet resource inventory indicating fleet resources, each with features, configuration requirements, and a status. The resource provisioning rules are accessible to an intelligence layer to ensure that provisioned resources comply with the resource provisioning rules. The system receives a request for a robotic fleet to perform a job and determine a job definition data structure. The definition data structure defines a set of tasks that are to be performed in performance of the job. The system determines a robotic fleet configuration data structure corresponding to the job based on the set of tasks and the fleet resource inventory. The system determines a respective provisioning configuration for each respective fleet resource. The system deploys the robotic fleet to perform the job.

The invention discloses a heterogeneous computing power resource dynamic scheduling system and method based on multi-objective optimization, and the system is deployed in a digital ecological platform complex based on multivariate consensus and embedded intelligent management. Comprising a platform access module, a data acquisition and perception module, a multi-target modeling and optimization module, a dynamic scheduling and execution module and a fault-tolerant mechanism module. The system registers as a computing power scheduling service node through an intelligent contract interface, obtains and verifies the compliance of a computing task, collects heterogeneous computing power resource node state data, and generates a scheduling decision by dynamically adjusting the weight of a target function; evaluating task suitability by using an AMCU suitability scoring model, and executing a scheduling AMCU strategy; according to the method, the technical problems of low resource scheduling efficiency and poor fault-tolerant capability in a heterogeneous computing power environment are solved, and the system throughput and the resource utilization rate are improved.

In the implementation of techniques for deploying machine learning models with automated resource management, a system receives logic corresponding to a machine learning model and computing resource data corresponding to a plurality of computing resources available. Based on the logic and the computing resource data, the system generates the machine learning model and an allocation of one or more computing resources of the plurality of computing resources available for the machine learning model, in which the machine learning model conforms to the logic. Upon generation of the machine learning model and the allocation of the one or more computing resources, the system deploys the machine learning model and the allocation of the one or more computing resources of the plurality of computing resources available for the machine learning model.

The invention discloses a system and a method for automatically measuring pipe network parameters based on three-dimensional scanning of a wellhead of an inspection well, and belongs to the technical field of municipal engineering measurement. The system comprises a wellhead fixing assembly, a three-dimensional laser scanning assembly, a posture sensing assembly, a distance measuring assembly, a coordinate input assembly, a control processing assembly and a telescopic rod assembly. According to the method, through system deployment leveling, coordinate reference establishment, working condition judgment, point cloud acquisition, data processing and result output, automatic measurement of inspection well depth, pipe network pipe diameter, pipeline trend and pipe orifice center coordinates is realized. The system is fixed at a wellhead, does not need to descend, and adapts to scenes such as shallow wells / deep wells and good / weak signal areas; based on a high-density point cloud and an automatic algorithm, the measurement precision is high, the efficiency is improved, and output data can be directly used for pipe network modeling. The method solves the problems of low efficiency, strong manual dependence and poor safety of traditional measurement, and is suitable for parameter measurement of various inspection wells and pipe networks.

The invention discloses an anti-countercurrent system based on V2G equipment and a control method, and the system comprises at least two charging and discharging modules which are connected to one side of a power line, and the other side of the power line is connected to a power grid; the charging and discharging module comprises a first bidirectional electric meter and a V2G charging pile. One end of the V2G charging pile is connected with the power line through the first bidirectional ammeter, and the other end is connected with the charging terminal. The bidirectional main electricity meter is connected between the power line and the power grid; the contactor is connected between the bidirectional main ammeter and the power line. The anti-countercurrent control module is in communication connection with the bidirectional main electric meter, the contactor, the first bidirectional electric meter and the V2G charging pile; according to the invention, a virtualized anti-countercurrent control architecture is adopted, any V2G charging pile or cloud server is used as an anti-countercurrent control module, a traditional hardware controller is replaced by existing equipment computing power, global power regulation and control are realized based on data provided by the bidirectional main ammeter and the first bidirectional ammeter, and the system deployment cost and complexity are significantly reduced.

The invention discloses an architecture system and method for large-scale task allocation, and belongs to the field of spaceflight measurement and control, and the system comprises a large-scale hardware device which is used for deploying processing units with different performances and various heterogeneous physical communication link resources; the hardware resource dynamic modeling and visualization framework is used for realizing a dynamic modeling system based on multi-source heterogeneous hardware topology perception; the resource topology awareness database captures and synchronizes system deployment changes by maintaining the dynamic topological relation of hardware resources, presents the life cycle state of the hardware resources, and supports system-level resource situation visualization and decision making; a versioning management engine of component arrangement is applied, a multi-version executable unit is packaged based on an atomization component, and an application instance is completed through a combined modeling component; and deploying a scheduling decision system for deploying a scheduling decision. The method can adapt to task deployment requirements of a current large-scale spaceflight measurement and control system.

Linear unretimed interfaces lack clock and data recovery and retiming circuits implemented on a sophisticated digital signal processor. When the interface is not a retimed interface, it can be especially useful to extract some information about the link to allow for debugging and optimization of system deployment. An efficient solution can be implemented in unretimed interfaces to compute metrics such as the impulse response and signal histogram. Having the metrics allows for the solution to check and monitor the quality and the status of the link. Based on the link quality and status information, it is possible to address non-idealities and optimize performance of the unretimed interfaces and the link.

The invention discloses a subway transport capacity matching and passenger flow collaborative management and control method based on multi-agent reinforcement learning, and relates to the technical field of urban rail transit operation management. The method comprises the following components: S1, a subway system digital twin model construction step, S2, a multi-agent reinforcement learning training environment construction step, S3, an extreme scene simulation and agent training step, S4, a virtual-real data interaction and model iteration step and S5, an actual system deployment and decision execution step. According to the method, a high-fidelity digital twin model of a subway system is constructed, extreme scenes including passenger flow retention caused by rainstorm and instantaneous large passenger flow of a large competition field are simulated in the model, and a multi-stage sampling method based on scene clustering is combined to perform training for ten millions of times; and the decision-making capability and the cooperation efficiency of the multiple agents in the face of complex and extreme conditions are obviously improved.

The invention discloses a relay unmanned aerial vehicle track optimization method, which comprises the following steps of: firstly, constructing a lossy relay unmanned aerial vehicle communication system model under finite length coding, and covering communication time slot division, unmanned aerial vehicle flight constraint and a channel model; deducing outage probability expressions of two communication strategies under finite length coding, wherein the outage probability expressions are an independent decoding strategy and a joint decoding strategy respectively; then, a trajectory optimization problem is converted into a Markov decision process (MDP), and a state space, an action space, a reward function and a state transition mechanism are clarified; solving by adopting a joint optimization algorithm based on depth deterministic strategy gradient (DDPG) to realize joint optimization of the unmanned aerial vehicle track and the communication strategy; and finally, outputting an optimal unmanned aerial vehicle track and strategy configuration to provide reference for actual system deployment. The method can effectively reduce the outage probability of the system and improve the communication reliability under the condition of limited length coding, and is suitable for various scenes in 6G and future air-ground cooperative communication networks.

The invention relates to the technical field of engineering structure health monitoring and artificial intelligence, and discloses an offshore wind turbine tower drum base three-dimensional stress distribution prediction and visualization method, which comprises the following steps: generating batch working conditions by presetting a bending moment range and an interval, and calling a finite element software automation script to execute static analysis; node stress values are extracted and integrated into a structured training data set; customizing neural network training: constructing a full-connection network, and training a model by adopting a standardized preprocessing and early stop mechanism; generating an interactive cloud picture: generating a 3D stress cloud picture HTML (Hypertext Markup Language) file supporting rotation / zooming / data query based on a spatial interpolation algorithm and a Plotly tool, and automatically marking the coordinate and the numerical value of a maximum stress point; and end-to-end system deployment: packaging as a Flask Web application, and inputting a bending moment value by a user to generate an interactive cloud picture in real time. The stress analysis period is greatly shortened, the engineering application threshold is reduced, and rapid evaluation and remote cooperation of the offshore wind turbine tower drum base can be efficiently supported.

The invention provides a robot operating system and method based on hardware isolation and a dynamic task engine, belongs to the technical field of artificial intelligence, and aims to solve the problem that the real-time performance and the intelligence are bidirectionally opposite for a long time in an architecture level in the field of robots. The system comprises a heterogeneous multi-core SoC, a universal operating system deployed in a non-real-time domain, a kernel real-time operating system deployed in a real-time domain, an inter-core communication bus based on shared physical memory configuration and an integrated development tool chain based on a VSCode plug-in. The method comprises the steps that a robot operating system based on hardware isolation and a dynamic task engine is built; task generation, routing and deployment are carried out; and when the real-time domain executes the task, the high-frequency state data is reported to the non-real-time domain through the inter-core communication bus to form closed-loop cooperative control.

The invention discloses a park large-screen centralized management and control method and system of an intelligent large-screen management platform, and relates to the technical field of intelligent large-screen management, and the method comprises the steps: building the network connection between a platform and a large screen through the configuration of communication parameters and the input of large-screen equipment identification information, and completing the equipment access authentication through the network connection relation; collecting parameter information and an equipment operation state of the accessed equipment; based on the parameter information of the accessed device, setting a content distribution strategy of a display area, and executing format adaptation and split screen template configuration on the multi-format content; and receiving a voice instruction, completing user identity recognition, and executing alarm grading and display content adjustment according to the collected equipment operation state. According to the method, an access mechanism based on automatic matching of communication parameter configuration and equipment identification information is constructed, so that the access efficiency of heterogeneous large-screen equipment and the automation level of system deployment are effectively improved.

The invention discloses a chirp interval modulation backscatter communication method and a chirp interval modulation backscatter communication system based on variable-length scrambling codes, which mainly solve the problems of high power consumption of backscatter labels and high system deployment cost in the prior art. According to the scheme, a sending end sends an environment LoRa signal; the backscattering label modulates information to be sent to an environment LoRa signal in a time interval modulation mode, and modulates a variable-length scrambling code to an anchor symbol; a receiving end performs frequency shift compensation on the backscattering signal by adopting a frequency shift compensation method, demodulates the backscattering signal by combining a sliding window with a variable-length scrambling code, intercepts a backscattering signal sample through the sliding window, and performs de-spreading and fast Fourier transform (FFT) on the signal in the window; the position of an anchor symbol is determined by detecting the maximum value of an FFT peak value, information sent by the backscattering label is recovered from the position of the anchor symbol, and data demodulation is completed. On the premise of keeping demodulation reliability, the power consumption of the tag is effectively reduced, the deployment cost of a backscatter communication system is reduced, and the method can be used for ultra-low power consumption Internet of Things communication.

The invention relates to the technical field of non-electrical variable control or adjustment systems, in particular to an unmanned aerial vehicle (UAV) positioning method and system, which comprises an airborne positioning module integrated with an ultra wide band (UWB) transceiver, an inertial measurement unit, a visual sensor module and a global navigation satellite system receiving module, and cooperates with an external UWB positioning beacon. High-precision, continuous and reliable positioning of the unmanned aerial vehicle is realized through core function modules such as multi-modal data real-time quality evaluation, dynamic weight fusion positioning, environment perception and situation recognition, robustness and integrity monitoring and the like. According to the method, the positioning precision and the system robustness can be remarkably improved, the complex environment adaptability and the anti-interference capability are enhanced, and the system deployment and maintenance cost is effectively reduced.

The invention discloses a generator set defect detection method based on deep learning, and belongs to the technical field of generator sets, and the method comprises the following steps: S1, collecting and marking multi-source heterogeneous data; s2, data preprocessing and feature engineering; s3, constructing a deep neural network model: designing and constructing a composite deep learning model architecture fused with multi-modal data processing capability; s4, performing model training and verification; s5, optimizing and lightening the model; s6, edge computing system deployment and real-time detection; s7, carrying out online feedback and model iteration; and S8, generating a visual diagnosis interface and a report. By integrating various heterogeneous data sources such as the vibration sensor, the acoustic sensor and the thermal infrared imager, multi-angle real-time monitoring of the running state of the generator set is realized, and in the acquisition stage, the synchronous acquisition card is utilized to ensure the time precision.

The invention discloses an industry knowledge graph query and retrieval interface system capable of being quickly customized, and relates to the field of computer software, and the system comprises a data and representation unit which is used for generating a semantic vector and storing the semantic vector into an open source vector database; the mixed retrieval engine is used for carrying out word segmentation processing on a query statement input by a user and obtaining a search result by combining an extended search mechanism in the knowledge graph and utilizing a fusion sorting algorithm; the reasoning and optimizing unit is used for reasoning the retrieval result and realizing adaptation of different industries in combination with a meta-learning-based field adaptive engine; and the interaction and service unit is used for optimizing user interaction experience through a dynamic hot word recommendation mechanism and realizing system deployment and customized configuration according to the micro-service architecture. According to the method, the structured element indexes are extracted from the corresponding industry files by constructing the industry standard knowledge graph, so that the accuracy and the specialty of data sources are ensured.

In order to solve the problem that under the condition that a PMON program is not changed, the PMON program cannot provide inter-core memory isolation through two addresses of 0 * 8000000000000000 and 0 * 9000000000000000 configured by a direct mapping configuration window, the AMP architecture multi-core real-time operating system deployment method capable of meeting the inter-core memory isolation is designed on a Loongson platform. According to the multi-core deployment method for the AMP architecture operating system based on the Loongson platform disclosed by the invention, by designing a secondary bootstrap program, the mode that a PMON program directly loads an operating system mirror image is changed into the mode that the secondary bootstrap program is firstly loaded, and the operating system is started by the secondary bootstrap program. The secondary bootstrap program configures the MMU through a page table mapping address translation mode, so that operating systems between different cores can run in different address spaces, and an isolated running environment is provided. Once a certain operating system accesses the address space of other core operating systems, the system will report TLB refilling exceptions to prevent other core memories from being damaged, and therefore the inter-core memory isolation is achieved.

The invention discloses an intelligent mowing robot system based on multi-sensor fusion and a mowing method, and relates to the technical field of mowing robots, and the intelligent mowing robot system based on multi-sensor fusion mainly comprises a system control module, an environment sensing module, a motion module, a mowing module, a software system module and a power supply module. By implementing the intelligent mowing robot system based on multi-sensor fusion and the mowing method provided by the invention, the deployment flexibility and the operation efficiency of the mowing robot system can be improved.

The invention discloses an on-line quality judgment method based on indentation mechanics in an injection molding process. The method comprises the following steps: (1) system configuration: constructing an on-line quality judgment system; (2) benchmark establishment: pre-establishing a qualified sample mechanical feature library and storing the qualified sample mechanical feature library in a qualified sample feature library unit as a quality judgment benchmark; (3) system deployment: completing linkage debugging verification of the quality online judgment system and the injection molding machine, and ensuring synchronization of the detection action and the injection molding period; (4) injection molding, synchronous indentation test and original data acquisition; (5) data preprocessing and mechanical feature extraction; (6) quality judgment; and (7) closed-loop feedback and dynamic optimization of the feature library. According to the invention, the synchronization of indentation detection and injection molding periods, anti-interference signal acquisition and full-inspection judgment of internal quality can be realized, a production line closed loop of'detection-judgment-feedback-optimization 'is formed, and the method is adaptive to the rhythm of injection molding large-batch continuous production.

The application discloses a live broadcast marketing recommendation system and method based on user portrait, relates to the technical field of data processing, and aims to solve the problems of lack of intelligent identification of user interest and consumption behavior, serious homogenization of recommendation and low conversion efficiency in the existing live broadcast marketing mode. The system is deployed in the live broadcast platform background service cluster, and the overall architecture includes a user portrait collection module, a behavior analysis engine, a marketing recommendation module, a real-time push component, an interest label visualization module and an automatic optimization mechanism. Each module realizes data interaction through a high-speed internal network and a message queue, and establishes a real-time connection with the front end and the platform transaction database. The system realizes the precision, personalization and intelligent upgrading of live broadcast marketing, effectively improves the recommendation conversion efficiency, reduces the loss of high-value users, enables the precise operation of anchors, optimizes the user experience and the platform competitiveness, and has significant technical value and commercial value.

The application discloses a network card management system and method and electronic equipment, and relates to the technical field of network card management. The system comprises a mainboard, a network card and a preset cable. The mainboard is provided with a mainboard power supply circuit, a logic controller and a connector. The connector comprises a power supply pin connected to the mainboard power supply circuit and at least one bandwidth identification pin. The inside of the mainboard side plug of the preset cable is provided with a target circuit connection structure, and the power supply pin and the bandwidth identification pin are directly electrically connected when the cable is connected. The logic controller automatically determines the network card bandwidth allocation mode by collecting the level signal of the bandwidth identification pin and generates a configuration signal to control the network card work. The technical problem that the network card bandwidth configuration in the related art depends on software setting is solved. The automatic identification and configuration of the network card bandwidth are realized through the hardware connection topology, and the system deployment efficiency and reliability are significantly improved.

The invention provides an automatic deployment method and device of a Ceph cluster, electronic equipment and a storage medium, the automatic deployment method of the Ceph cluster, provided by the invention, realizes adaptive deployment of different operating systems by determining system deployment strategies and deployment dependency data matched with the different operating systems respectively, and greatly improves compatibility of Ceph cluster deployment; according to the automatic deployment method for the Ceph cluster, automatic deployment can be achieved, manual operation is not needed, and the deployment efficiency of the Ceph cluster is improved.

The invention discloses a Fast DDS-based QNX system soft diagnosis method and system and electronic equipment, and relates to the field of system diagnos.The method comprises the steps that S1, a Fast DDS-based global data space is constructed and serves as a real-time communication bus between a QNX system and an Android system, and decentralized interaction of dual-system diagnosis data is achieved; s2, deploying a soft diagnosis service in the QNX system; the soft diagnosis service comprises four core function modules: a black screen detection and self-healing module, a resource dynamic monitoring module, a virtual machine monitoring module and a burying point analysis module; s3, a diagnosis agent service is deployed in the Android system; the diagnosis agency service receives the alarm and data issued by the QNX system through the Fast DDS client; the method comprises the following steps: reading a log packaging file and a tcpdump file stored in a QNX system through a shared directory; and summarizing the data and uploading the summarized data to a cloud platform to realize visual display of the diagnostic data.

The application discloses a large language model fast reasoning method and system based on an Android system deployment, and comprises the following steps: constructing an OpenGL environment in a PC terminal, cloning a large language model reasoning framework in the OpenGL environment, selecting GPU hardware acceleration in the OpenGL environment, and obtaining an so file after compiling and converting the large language model reasoning framework and the hardware acceleration; acquiring a large language model resource file, and converting and quantifying the large language model resource file into a GGUF format file; preparing an Android NDK environment by using an Android development component, converting the GGUF format file of the large language model into an LLM.so file in the Android NDK environment, and configuring dynamic library linkage in the Android NDK environment; creating an Android NDK project, configuring GPU calling instructions of the large language model reasoning in the Android NDK project, starting the large language model reasoning, and running in a CPU of the corresponding PC terminal.

The invention belongs to the technical field of intelligent monitoring, and provides a self-adaptive node addressing method and system suitable for a multi-node intelligent equipment system.The technical scheme includes the steps that an addressing instruction is received, and a search initial address range is obtained; taking the search initial address range and the maximum effective device number as input, and under the constraint of the size of an available stack memory, performing adaptive calculation to obtain a fuzzy dividing and conquering factor for dividing the search range and fine scanning granularity for fine search; the method comprises the following steps: initializing an address stack, pressing a search initial address range into the address stack, and circularly executing the following steps: sending a popped query instruction of a stack top address range, dynamically matching a corresponding branch processing mode according to a received response condition until the address stack is empty, and obtaining an addressing result of each node. The system deployment speed is improved, the communication overhead is reduced, and the stability in a complex environment is enhanced.

The invention relates to an intelligent concrete spraying construction method and system for a large-span arc-shaped roof. The method comprises the steps of system deployment, path planning, intelligent spraying, axial displacement and multi-layer spraying and quality monitoring. The system comprises a mobile platform, a track system, an execution mechanism, a sensing system, a concrete proportion regulation and control module, a pipeline collaborative management system and a central control system. Through cooperation of special equipment and intelligent control, the problems of flow falling, rebound and thickness control are systematically solved, and finally high-quality and high-efficiency automatic construction on the large-span arc-shaped roof is achieved.

The system obtains an issue associated with a network and resolves the issue by suggesting a solution and receiving an approval from an AR / VR device. Based on the issue, the system creates a ticket describing the issue and obtains diagnostic information associated with the issue. Based on the diagnostic information, the system determines a fix for the issue and sends a first notification to the AR / VR device. The first notification includes a description of the issue, the fix for the issue, and a request to test the fix. Upon receiving an approval to test the fix, the system performs regression testing using the fix and determines whether the fix passed the regression testing. Upon determining that the fix passed the regression testing, the system sends a second notification to the AR / VR device requesting an approval to deploy the fix, and upon receiving the approval, the system deploys the fix.

The embodiment of the invention provides a virtual machine application program upgrading system, a system deployment method and an upgrading method. The system comprises an upgrading server, a virtualization management platform and a virtual machine, the upgrading server is independently deployed by the virtualization management platform in a cluster deployment or non-cluster deployment manner according to the scale of the virtual machine to be upgraded, and is used for providing an upgrading service for the virtual machine under at least one virtualization management platform; the virtualization management platform is used for managing the upgrade server through network communication; a client program for upgrading is installed in the virtual machine, and the client program and the upgrading server realize upgrading of the application program of the virtual machine through network communication. According to the scheme of the embodiment, the upgrading server can adapt to scenes of different virtual machine scales, virtual machine application program upgrading across virtualization platforms is achieved, more resources are saved, equipment maintenance is facilitated, and a virtual machine application program upgrading solution can be provided under the scene that a virtual machine CD driver cannot be used.