658 results about "System deployment" patented technology

The invention relates to the technical field of data processing, and discloses a BIM-based building construction quality information intelligent supervision system, which is used for improving the efficiency and accuracy of BIM-based building construction quality information intelligent supervision. The method comprises the following steps: a modeling module performs BIM modeling processing on a building engineering design drawing and building specification data to obtain a building twinborn body; the deployment module carries out field data acquisition system deployment on the building twinborn body to obtain a real-time data acquisition system; the detection module performs anomaly detection processing on the data acquired by the system to obtain a quality anomaly alarm and a priority processing level; the processing module carries out multi-dimensional visualization processing on the quality abnormity alarm and the priority processing level to obtain a visual interface; the decision-making module performs intelligent decision-making analysis on the quality abnormal information in the visual interface to obtain a target processing scheme; and the analysis module performs time sequence analysis and multivariable correlation analysis on the target processing scheme to obtain a dynamic quality evaluation report.

The invention belongs to the field of power systems, and discloses a power distribution network fault autonomous diagnosis and self-healing control method and system based on deep reinforcement learning, and the method comprises the steps: carrying out the collection and preprocessing of the multi-source heterogeneous data of a power distribution network; key feature vectors are extracted from the multi-source heterogeneous data based on a graph convolutional network, and a state representation model is constructed; based on an asynchronous dominant actor-commentator algorithm, constructing a fault diagnosis agent capable of quickly diagnosing faults; a meta-reinforcement learning algorithm is adopted, a dynamic reconstruction strategy library is generated through pre-training, and a self-healing control agent capable of rapidly adapting to various different fault scenes to generate an optimal reconstruction strategy is constructed; constructing a self-healing control module based on virtual impedance matching, wherein the self-healing control module is used for intelligent reconstruction and self-healing control of the power distribution network; a risk-sensitive reward function and a game equilibrium strategy optimization method are introduced to improve performance and robustness; and finally carrying out system deployment and engineering verification.

The embodiment of the invention provides a BIM-based hydraulic engineering digital management method and system. The method comprises the following steps: performing multi-dimensional monitoring system deployment on a to-be-monitored area to obtain multi-dimensional hydrological data; constructing a first BIM based on the topographic data of the to-be-monitored area, the real-time work area image, the hydraulic engineering construction information of the design stage and the equipment deployment information; fusing the multi-dimensional hydrological data, the water area change data, the construction progress data and the operation and maintenance monitoring data into the first BIM, and constructing a second BIM including a full life cycle; and through the equipment characteristic curve and the water conservancy project physical model, in combination with the multi-dimensional hydrological data and the water area change data, predicting a water conservancy project structure change trend and potential risk factors in the second BIM, fusing the water conservancy project structure change trend and the potential risk factors into the second BIM, and displaying an implementation effect and improvement suggestions in real time in the second BIM. A user is assisted to realize hydraulic engineering digital management, and the engineering management efficiency is improved.

The invention discloses a collaborative scheduling method based on a security agent, and relates to the technical field of network security design. The specific operation of the security agent collaborative scheduling method comprises the steps of system deployment and initialization, security operation task execution process, agent self-learning and capability evolution implementation, cross-domain security agent collaborative adaptation implementation and security operation visualization and traceability implementation. Connection paths between the security agent and business data, a private knowledge base, a security tool and multiple models are broken through, the problem that all elements in a traditional mode lack efficient communication and collaboration is solved, and by means of agent routing dynamic scheduling, A2A protocol interaction, MCP protocol tool calling, RAG business interface calling and multi-model combination, the security of the security agent is improved. Integration and intellectualization of the safety operation process are achieved, the continuity and the response speed of the operation process are improved, safety operation is more efficient and collaborative, and complex and variable safety requirements are met.

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 belongs to the field of PCIe Switch interconnection, and relates to a GPU cross-host communication interconnection system based on PCIe NTB, which comprises two hosts, two GPUs and two PCIe Switch chips, the two GPUs are respectively connected with the PCIe Switch chips, the two PCIe Switch chips are connected through a Crosslink line, a connection port of each PCIe Switch chip is set to be in an NTB mode, and the two GPUs achieve interconnection communication through the NTB. By windowing in the NTB, the address of the remote equipment is mapped in the local address space, so that the purpose of accessing the remote equipment is achieved. The PCIe Switch is used for replacing high-end network equipment, so that the hardware cost can be remarkably reduced, and the complexity of system deployment is reduced. Communication between the devices can be directly accessed through a memory address, and complex network connection, IP addresses or special software protocols do not need to be set; and low-delay and high-bandwidth GPU cross-host interconnection communication is achieved. Through the GPU which carries out cross-host communication in a PCIe NTB mode, the effect of GPU Direct P2P can be achieved.

The invention relates to the technical field of crack detection, in particular to a building crack intelligent detection and prediction method based on multi-modal data fusion, which comprises the following steps: constructing a multi-source heterogeneous data set including an image data set, a thermal imaging data set and a vibration data set; simulating complex environment interference through a GAN (Generative Adversarial Network), and dynamically enhancing image training data; designing a double-branch multi-mode fusion network, and extracting the edge and texture features of the crack; designing a multi-modal fusion branch, and carrying out feature alignment and weighted fusion on vision, thermal imaging and vibration data; and based on a long short-term memory network LSTM and a structural mechanics model, a crack trend prediction module is developed, and early warning is provided for building structure safety. According to the method, intelligent monitoring and early warning of building structure safety are realized by constructing a multi-source heterogeneous data set, enhancing image training data through a GAN, extracting features by using a double-branch multi-mode fusion network, predicting a crack trend based on an LSTM and a structural mechanical model, and finally integrating system deployment.

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.

The embodiment of the invention provides a network attack research and judgment method and system, a program product, equipment and a medium, the system deploys a plurality of agents, and the method comprises the following steps: inputting an attack sample into an attack feature extraction agent, and constructing an attack feature library based on the extracted attack features; inputting the network security log into a field extraction agent to obtain an extracted attack related field; inputting the attack feature library and the attack related fields into an attack analysis module, and obtaining attack analysis data of the attack analysis module on the attack related fields based on the attack feature library; inputting the threat intelligence data, the asset data and the attack analysis data into a comprehensive analysis report agent to obtain an analysis report including an attack result, an attack severity degree, an influence range and an attack technology; and inputting the analysis report into an attack processing module to obtain an attack processing plan. Attack research and judgment process automation is realized by utilizing the intelligent agent, the analysis, research and judgment capability on known attacks can be improved, unknown attack behaviors can be identified, and closed-loop protection measures are formed.

The invention belongs to the technical field of speech translation, and particularly relates to a video speech automatic translation method based on a pre-training model, and the method comprises the following steps: 1, preprocessing video and audio data; step 2, voice recognition and language detection; step 3, machine translation and text post-processing; step 4, speech synthesis and audio mixing; step 5, synchronizing video processing and subtitles; step 6, quality control and multi-dimensional evaluation; 7, carrying out model iteration and data closed loop; and step 8, system deployment and engineering implementation. Through deep fusion of efficient transfer learning of the pre-training model and the multi-modal technology, a high-precision, low-cost and easy-to-expand video speech translation solution is constructed, the time and labor cost of globalized content production is greatly reduced, the cross-language communication efficiency is improved, immersive multi-language experience is provided, and the method is suitable for popularization and application. And a data-driven continuous optimization mechanism is established, so that the system performance is improved along with the increase of the use scale.

The invention discloses a BIM (Building Information Modeling) data security protection system based on encryption and role permission control. The BIM data security protection system comprises a multi-level data encryption module, a role permission control module, a real-time security monitoring and auditing module, a user identity authentication module and a system deployment and maintenance module, according to the BIM data security protection system based on encryption and role permission control, through mechanisms such as multi-level data encryption, fine permission control, real-time security monitoring and auditing and multi-factor identity authentication, the security and privacy of BIM data in the storage, transmission and use processes are effectively improved.

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.

Techniques for host fleet management in a cloud provider network are described. Forecast data including a forecasted demand for virtual machines in each capacity pool of a set of capacity pools is obtained. A mathematical optimizer application is executed to generate a first optimal fleet plan, the mathematical optimizer application having an objective function to minimize a number of new host computer systems to add to the set of host computer systems to satisfy the forecasted demand for each capacity pool, the first optimal fleet plan includes an identification of a set of hardware types and, for each hardware type in the set, a quantity of new host computer systems of the hardware type. A plurality of new host computer systems is deployed, based on the first optimal fleet plan, for a hardware type in the set of hardware types into the set of host computer systems.

The invention discloses a turnout switch machine fault diagnosis and prediction model method based on artificial intelligence. The method comprises the following steps: step 1, data acquisition; step 2, data preprocessing; step 3, feature extraction; step 4, model training; 5, verifying the model; 6, deploying the model; step 7, fault diagnosis and prediction; an artificial intelligence algorithm is introduced to automatically analyze data and identify faults, safe operation of equipment is ensured, instant fault response is realized through real-time monitoring and rapid data processing, the equipment safety is improved, an automatic modeling tool is adopted to simplify the construction process, non-professional personnel operation is facilitated, system deployment is accelerated, and the system reliability is improved. The method combines expert experience and data driving to form a hybrid model, improves the adaptability and accuracy of the model, integrates multi-sensor data to form a unified monitoring platform, enhances the comprehensiveness and accuracy of fault diagnosis, and provides powerful guarantee for the safety and efficiency of railway transportation.

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.

The invention provides a heterogeneous multi-core-based embedded numerical control system, which comprises a development system, an operation system and a bus servo driving unit, and is characterized in that the data output end of the development system is connected with the data input end of the operation system, and the data transmission end of the operation system is connected with the data transmission end of the bus servo driving unit; the development system is used for programming and monitoring tasks, and the operation system is used for executing control logic, controlling external equipment, receiving compiled control programs from the development system and controlling on-site input and output equipment according to instructions in the programs, so that industrial automatic control is realized. The embedded soft PLC is divided into the development subsystem and the operation subsystem to be deployed on different cores of the multi-core embedded processor, the embedded soft PLC independent of PC operation is achieved, a method for directly explaining and executing the ladder diagram is provided, the ladder diagram does not need to be converted into an instruction list program, and the operation efficiency is improved. The algorithm complexity of ladder diagram compiling and interpretive execution is reduced, and the execution efficiency of the numerical control PLC is improved.

A process automatically generates configuration information used to build a target computing environment based on an image that depicts an architecture of the target computing environment. First, the process generates an original graph data structure having nodes and edges that respectively represent services and connectors detected in the image. The system then determines attributes of the target computing environment based on the original graph data structure. At least in part, the attributes describe a context in which the target computing environment is used, such as the type of industry associated with the target computing environment. The process then modifies the original graph data structure based on the attributes that have been determined, to produce a modified graph data structure. Finally, the process provides the configuration information to a deployment system, which uses the configuration information to deploy the target computing environment on a computing platform.

A method, system, apparatus, and architecture are provided for monitoring, handling, and escalating faults from a plurality of SoC subsystems by deploying at least one FCU instance at each SoC subsystem, where each FCU instance is configured to monitor one or more fault input signals at one or more fault inputs, to generate a local control signal for one or more hardware resources controlled by the FCU instance, and to escalate any unresolved fault on a fault output, and where a first plurality of FCU instances deployed at a first plurality of SoC subsystems are each connected in a fault escalation tree with an escalation FCU instance deployed at a first management SoC subsystem by connecting the fault outputs from the first plurality of FCU instances to the one or more escalation fault inputs of the escalation FCU instance deployed at the first management SoC subsystem.

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 machine learning-based transformer substation main wiring diagram intelligent identification method and system, and the method comprises the steps: collecting and preprocessing a transformer substation drawing data set, employing a super-resolution network Real-ESRGAN to improve the image quality, and enhancing the model generalization capability through data amplification; an image recognition model based on YOLOv5x6 is trained, the model is combined with Slim-Neck to improve real-time detection efficiency and accuracy, and a wiring mode, an interval type and a switching device are recognized step by step; meanwhile, a character recognition model based on PaddleOCRv4 is trained, and the performance of the model is improved by adopting a collaborative mutual distillation method CML; and finally, integrating an image recognition model and a character recognition model, realizing a front-end framework and a rear-end framework through algorithm module programming, and deploying the system at a mobile terminal, thereby realizing rapid and accurate transformer substation wiring diagram digitalization, improving the speed and accuracy of transformer substation drawing digitalization, ensuring the operation safety of a power grid, and improving the working efficiency of field technicians.

Methods and systems for parsimoniously updating cyber-system models based on then-current conditions. A wide variety of cyber-physical system models are deployed for ensuring that a system operates within its constraints while nevertheless achieving an assigned mission. Updating models is resource intensive, and thus should be done only when a particular degree of accuracy of a model is needed. Modern cyber-physical systems comprise sensors, transducers, and actuators that interoperate to carry out specific cyber-physical system behaviors. A control invariant barrier function (CBF) implements safety constraints that relate environmental parameters to safe behaviors of the cyber-physical system. Responsive to detected changes in the environment, a model update activity corresponding detected changes in the environment is initiated, but only when the result of such a model update impacts safe and / or mission-critical operation of the cyber-physical system. Invocation of model updates that would not impact safe operation of the cyber-physical system are suppressed.

The embodiment of the invention discloses a light application interaction architecture method and device based on data ferry and a medium, and the method comprises the steps: deploying an extranet light application in an extranet server, deploying an ERP system in an intranet server, and physically isolating the extranet server from the intranet server; deploying the cache database in an extranet server, and storing data of the extranet light application in the cache database; and deploying the data ferry machine in an intranet server, querying the newly added data in the cache database through the data ferry machine, and sending the newly added data to the ERP system to complete the light application interaction architecture. According to the embodiment of the invention, intranet applications and services of clients are not directly exposed in an extranet environment, external users cannot directly penetrate through the intranet services no matter what modes the external users pass through, IT security risks are effectively reduced through the light application of the ferry machine, and the extranet applications and the intranet applications have emphasis, perform their own functions and do not influence each other.

Deployment of arrangements of physical computing components coupled over a communication fabric are presented herein. In one example, a method includes presenting, to a workload manager, a target machine capable of receiving execution jobs from the workload manager. The target machine has a network state and comprises a selection of computing components. The method also includes receiving a job issued by the workload manager that is directed to the target machine. Based on properties of the job, the method includes determining resource requirements for handling the job, forming a composed machine comprising physical computing components that support the resource requirements of the job, transferring the network state of the target machine to the composed machine and indicating the network state of the composed machine to the workload manager, and initiating execution of the job on the composed machine.

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 provides a small and medium-sized enterprise digital transformation evaluation method, which comprises the following steps of: S11, analyzing and identifying regularly acquired small and medium-sized enterprise digital transformation evaluation files to obtain quantifiable multi-dimensional evaluation indexes; s12, constructing an evaluation index matching model based on the multi-dimensional evaluation indexes, and further constructing a smart contract architecture; s13, regularly collecting and analyzing the successful cases of the digital transformation of the small and medium-sized enterprises, performing scoring guidance for the quantifiable indexes corresponding to each successful case, and constructing a grade evaluation model; s14, determining quantifiable indexes corresponding to the small and medium-sized enterprises in transformation, deploying corresponding smart contracts in internal business systems of the small and medium-sized enterprises, and collecting key transformation data; and S15, analyzing the key transformation data through the grade evaluation model, and outputting a visual evaluation report. According to the invention, comprehensive and accurate quantitative evaluation of the digital transformation degree of small and medium-sized enterprises is realized, the objectivity, efficiency and credibility of evaluation are improved, and a user is helped to know the current situation of enterprise transformation.

The invention provides a time slice configuration method and system for a secure real-time bus (SRB), which can be applied to the technical field of communication, and the system is composed of a management device and a plurality of SRB devices in ring topology connection. The management equipment sends a detection starting enabling message; and each SRB device sends the network address to two adjacent SRB devices. And the management equipment sends a detection output enabling message to the target SRB equipment, the target SRB equipment creates a link relation packet, and the logic address is stored in the link relation packet and transmitted to the next SRB equipment. And after the other SRB equipment receives the link relation packet of the previous equipment, adding the logic address and continuing to forward the link relation packet. And when the target SRB equipment receives the link relation packet containing the logic address of the target SRB equipment, the target SRB equipment sends the link relation packet to the management equipment, so that time slice distribution of all the SRB equipment is completed. And through automatic time slice configuration and management, the system deployment efficiency is remarkably improved. And high efficiency and real-time performance of network management are ensured.

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.

The embodiment of the invention provides an energy storage system deployment optimization method and device based on a starfish optimization algorithm. The method is applied to the energy storage system deployment field. The method comprises the steps of establishing an energy storage system multi-objective optimization function and a constraint condition according to an optimization objective; under a constraint condition, solving a multi-objective optimization function of the energy storage system by utilizing a starfish optimization algorithm, and obtaining the position of a starfish individual with the lowest fitness in all starfish individual fitness when a preset iteration termination condition is met by iterating the positions and fitness of starfish individuals; and taking the position of the starfish individual with the lowest fitness as a final deployment scheme of the energy storage system. In this way, the deployment performance and optimization efficiency of the energy storage system are remarkably improved, the service life of energy storage system equipment is prolonged, cost minimization, system reliability and energy utilization rate maximization are achieved, and the optimization process is more flexible, more practical and more applicable.

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.